GENETIC CHARACTERIZATION OF THE ST. KITTS-ORIGIN ......WFU Wake Forest University WFUPC Wake Forest...
Transcript of GENETIC CHARACTERIZATION OF THE ST. KITTS-ORIGIN ......WFU Wake Forest University WFUPC Wake Forest...
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GENETIC CHARACTERIZATION OF THE ST. KITTS-ORIGIN VERVET MONKEY (CHLOROCEBUS AETHIOPS SSP.) AS A MODEL OF POLYGENIC OBESITY
BY
STANTON BRADLEY GRAY, D.V.M.
A Dissertation Submitted to the Graduate Faculty of WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES
In Partial Fulfillment of the Requirements
For the Degree of
DOCTOR OF PHILOSOPHY
Molecular Pathology
August 2009
Winston Salem, North Carolina
Approved By:
Janice D. Wagner, D.V.M., Ph.D., Advisor _________________________________
Examining Committee:
Carl D. Langefeld, Ph.D., Chairman _________________________________
Timothy D. Howard, Ph.D. _________________________________
Jay R. Kaplan, Ph.D. _________________________________
Lawrence L. Rudel, Ph.D. _________________________________
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ACKNOWLEDGEMENTS
I wish to thank my advisor, Dr. Jan Wagner, as well as Dr. Tim Howard, who
acted as my unofficial co-advisor. Their contribution, both together and individually, to
my Ph.D. program and overall academic experience at Wake Forest University has been
invaluable. I also thank Dr. Carl Langefeld, Chairman of my Final Examining Committee,
Dr. Larry Rudel, and Dr. Jay Kaplan for their service on my committee. I greatly
appreciate all committee members for their support, tremendous expertise in their
respective fields, and engaging scientific discussions and inquiries during our meetings.
Technical support and expertise with association analyses was provided by Ms.
Julie Ziegler from Public Health Genomics. Technical assistance and expertise with DNA
sequencing and other protocols was provided by Mr. Abdoulaye Diallo from the Center
for Human Genomics. I am grateful for their essential contributions and for the
invariably positive interactions I had with them.
Collaboration with Drs. Rich Broughton and Jim Thompson at the University of
Oklahoma, Department of Zoology is very much appreciated. Dr. Thompson was
responsible for fostering my early intellectual development and curiosity in genetics
research over 15 years ago. I am honored and fortunate to count him among my friends
and colleagues.
My gratitude is also extended for other more “behind-the-scenes”
collaborations, without which this work would not have been possible, with Drs. Kylie
Kavanagh, Lynn Fairbanks, Nelson Friemer, and Matthew Jorgensen.
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This work was funded, in part, by the Wake Forest University School of Medicine
Venture Fund, the Skorich Diabetes Research Fund, the Monty Blackmon Diabetes
Research Fund (Dr. Wagner), T32 RR07009 from NIH/NCRR (Dr. Gray), and an Animal
and Biological Materials Resources grant from the National Center for Research
Resources (P40 RR 019963 to Dr. Lynn Fairbanks at UCLA). Support of this project also
came from the Center for Public Health Genomics (Dr. Langefeld) at WFUSM.
Finally, I want to thank Dr. Shauna Gray for her love, friendship, and support. I
also want to thank my family for their unwavering love and belief in me. My daughter
and “Sunshine”, Ms. Hannah Stafford, deserves special mention; watching and helping
her grow up over the past thirteen and a half years has always reminded me what was
most important in life, and therefore helped me find proper perspective when aspects
of my academic program were difficult. I would also like to specifically thank my father,
Mr. Gordon Gray, for his particularly vocal and persistent encouragement of my
endeavor for a Ph.D. and research career.
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TABLE OF CONTENTS
Page LIST OF TABLES AND FIGURES…………………………………………………………………………… iv LIST OF ABBREVIATIONS…………………………………………………………………………………… vii ABSTRACT………………………………………………………………………………………………………… ix Chapter I. INTRODUCTION………………………………………………………………………………….. 1
II. COMPARATIVE ANALYSES OF SINGLE NUCLEOTIDE
POLYMORPHISMS IN THE TNF PROMOTER REGION
PROVIDE FURTHER VALIDATION FOR THE VERVET
MONKEY MODEL OF OBESITY……………………………………………………………… 32
III. PHYLOGENETIC AND TAXONOMIC IMPLICATIONS OF
TNF PROMOTER SEQUENCE COMPARISONS BETWEEN
ST. KITTS- AND AFRICAN-ORIGIN CHLOROCEBUS SUBSPECIES…………….. 61
IV. TNF SINGLE NUCLEOTIDE POLYMORPHISMS ARE
ASSOCIATED WITH BMI, WAIST CIRCUMFERENCE, AND
SERUM CHOLESTEROL LEVELS IN A PEDIGREED NONHUMAN
PRIMATE MODEL (CHLOROCEBUS AETHIOPS SSP.)……………………………… 79
V. CLINICOPATHOLOGIC CHARACTERIZATION OF
NATURALLY OCCURRING DIABETES MELLITUS IN
VERVET MONKEYS………………………………………………………………………………. 105
VI. OVERALL DISCUSSION AND CONCLUSIONS……………………………............... 126
BIBLIOGRAPHY……………………………………………………………………………………………….. 138 SCHOLASTIC VITA……………………………………………………………………………………………. 157
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LIST OF TABLES AND FIGURES
TABLES Page CHAPTER I Table 1. Selected inflammatory and metabolic regulators within adipose tissue and their putative interactions………………………………………. 6 Table 2. Summary of associations between TNF gene SNPs and various obesity-related phenotypic traits in humans………………………………… 23 CHAPTER II Table 1. Polymorphisms in the human ortholog St. Kitts-origin vervet TNF gene and flanking sequence…………………………………………………………… 41 Table 2. Haplotypes and frequencies of the human ortholog St. Kitts-origin vervet TNF gene and flanking sequence……………………………………. 43 Table 3. Distance matrices and percentage of DNA sequence identity between humans, chimps, vervets, and rhesus…………………………………… 44 Table 4. Results of Kolmogorov-Smirnov tests for non-uniform distribution………………………………………………………………………………….. 46 CHAPTER III Table 1. Presumed fixed nucleotide differences between Chlorocebus subspecies……………………………………………………………………………………. 70 CHAPTER IV Table 1. Heritability estimates (h2) for obesity-related phenotypes of VRC vervets………………………………………………………………………………. 85 Table 2. Polymorphisms in the human ortholog St. Kitts-origin vervet TNF gene and flanking sequence…………………………………………………………… 88 Table 3. Haplotypes and frequencies of the human ortholog St. Kitts-origin vervet TNF gene and flanking sequence……………………………………. 91
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TABLES Page CHAPTER V Table 1. Clinical Characteristics……………………………………………………………………….. 133 FIGURES CHAPTER II Figure 1. LD structure of the St. Kitts-origin vervet TNF locus…………………………… 42 Figure 2. Multi-species sequence comparison of TNF 5’ promoter region………………………………………………………………………………………………. 48 Figure 3. Phylogenetic shadowing and clustering of SNPs in the TNF promoter region in five primate species……………………………………………… 50 CHAPTER III Figure 1. Map of Africa showing approximate ranges for Chlorocebus subspecies……………………………………………………………………………………. 64 Figure 2. Multi-species and -subspecies sequence comparison of the TNF promoter region………………………………………………………….. 69 Figure 3. TNF promoter-based phylogentic trees…………………………………………….. 71 CHAPTER IV Figure 1. LD structure of the St. Kitts-origin vervet TNF locus………………………….. 89 Figure 2. Association of SNPs in the TNF gene in the St. Kitts-origin vervet monkey of the VRC…………………………………………………………. 92 Figure 3. Sequence comparison of TNF 5’ promoter region between humans and St. Kitts-origin vervet…………………………………………………….. 94
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FIGURES Page CHAPTER V Figure 1. Glucose and insulin responses during intravenous glucose tolerance tests in diabetic and nondiabetic monkeys………………………….. 114 Figure 2. Pancreatic Histology and Immunohistochemistry………………………………. 118 Figure 3. Comparison of amylin amino acid sequences…………………………………….. 119 Figure 4. Pedigree Analysis………………………………………………………………………………. 121
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LIST OF ABBREVIATIONS
AIDS Acquired Immunodeficiency Syndrome BMI body mass index BUN blood urea nitrogen C/EBP CCAAT-enhancer-binding proteins cDNA complimentary deoxyribonucleic acid CRE cyclic-AMP response element CRP C-reactive protein CVD cardiovascular disease D.M. distance matrix dbSNP Single Nucleotide Polymorphism database dNTP deoxynucleotide triphosphate ELISA ennzyme-linked immunosorbent assay ER endoplasmic reticulum ERK extracellular signal-regulated kinase FA fatty acid FABP fatty acid binding protein FAO fatty acid oxidation FAT fatty acid translocase FATP fatty acid transport protein FFA free fatty acid FG fasting glucose GLUT glucose transporter H&E hematoxylin and eosin HbA1c hemoglobin A1c HCT hematocrit HDL-C high density lipoprotein-cholesterol HOMA homeostasis model assessment HPLC high performance liquid chromatography IAPP islet amyloid polypeptide ICAM inter-cellular adhesion molecule IFN interferon IL interleukin IR insulin resistance IRS insulin receptor substrate JNK c-Jun N-terminal kinase KDa kiloDalton KO knockout LD linkage disequilibrium LDL-C low density lipoprotein-cholesterol LPL lipoprotein lipase MAF minor allele frequency
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MAPK mitogen-activated protein kinase MCP monocyte chemoattractant protein MHC major histocompatibility complex MODY maturity-onset diabetes of the young mRNA messenger ribonucleic acid mTNF membrane-bound tumor necrosis factor mTNFR membrane-bound tumor necrosis factor receptor
NF- B nuclear factor kappa-light-chain-enhancer of activated B cells NFAT nuclear factor of activated T-cells NHP non-human primate OWM Old World monkey PAI plasminogen activator inhibitor PCR polymer chain reaction PPAR peroxisome proliferator-activated receptor Ra receptor antagonist SIV simian immunodeficiency virus SK St. Kitts SNP single nucleotide polymorphism SOC suppresor of cytokine signalling sTNF soluble tumor necrosis factor sTNFR soluble tumor necrosis factor receptor SVF stromovascular fraction T2D type-2 diabetes TACE tumor necrosis factor-alpha converting enzyme TF transcription factor TG triglyceride TNF tumor necrosis factor TNF tumor necrosis factor gene symbol TNFR tumor necrosis factor receptor TNFR-DD tumor necrosis factor receptor-death domain TPC total plasma cholesterol TSS transcription start site UCLA University of California – Los Angeles UCSC University of California – Santa Cruz VCAM vascular cell adhesion molecule VRC Vervet Research Colony VTR variable tandem repeat W:H waist-to-hip ratio WAT white adipose tissue WBCC white blood cell count WC waist circumference WFU Wake Forest University WFUPC Wake Forest University Primate Center
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ABSTRACT
Tumor necrosis factor (TNF) is a cytokine with critical roles in inflammation, and
in mediating an intersection of chronic, low-grade inflammation and concurrent
metabolic dysregulation associated with obesity and its comorbidities. As part of an
ongoing initiative to further characterize the St. Kitts-origin vervet monkey as a
nonhuman primate (NHP) of polygenic obesity, the human ortholog vervet TNF gene
and flanking regions were sequenced and genotyped from 265 monkeys in a closed,
pedigreed colony. This revealed a total of 11 single nucleotide polymorphisms (SNPs),
and one 4 base pair insertion/deletion polymorphism. Many of these polymorphisms
were in strong linkage disequilibrium, and were contained within one haplotype block,
comprising five haplotypes.
Using sequences from humans, chimpanzees, vervets, baboons, and rhesus
macaques, phylogenetic shadowing of the TNF promoter region revealed that vervet
and other NHP SNPs were clustered non-randomly and non-uniformly (p<0.0001)
around conserved transcription factor binding sites. Thus, the distribution of SNPs in
vervets and other NHPs is shown to be analogous to that of humans.
The taxonomy of the St. Kitts vervet and the African Green monkey is identical
and designated Chlorocebus aethiops sabaeus, although it has long been regarded as
tentative. Phylogenetic analyses were perfomed using TNF putative promoter region
nucleotide sequence, among the St. Kitts-origin vervet, and four other African-origin
subspecies. Results show the St. Kitts vervet has significant sequence differences from
the African Green monkey. This is the strongest evidence to date challenging the
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current taxonomic classification, and suggests the sabaeus subspecies designation for
the St. Kitts vervet should be reconsidered.
Association analyses were performed between polymorphisms of the vervet
TNF orthologous gene and previously defined obesity-related phenotypes. Positive,
significant associations were observed between a subset of SNPs (all within a single
haplotype) and body mass index, waist circumference (p < 0.05), total plasma
cholesterol, and HDL-cholestrerol (p < 0.01). The former three associations have been
reported in humans and provide further model validation, whereas the latter has been
reported as an inverse association in humans. The novel association with HDL-
cholesterol warrants further study, but may provide insight into the newly emerging
dual inflammatory and anti-inflammatory role of HDL-cholesterol.
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CHAPTER I
INTRODUCTION
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Obesity and overweight epidemic
Currently, more than 30% of U.S. adults are obese, with another 35%
overweight; in addition, incidence of overweight children and adolescents is now over
15% (NHANES 2007). Compared to 30 years ago, these figures have approximately
doubled in adults and quadrupled in children and adolescents (NHANES 2007). The
simplest and most generally utilized surrogate measure for adiposity is body mass index
or BMI (weight / height2). The number of people classified as obese or overweight,
defined by BMI over 30 or 25 kg/m2 respectively, has reached epidemic proportions in
the U.S. and around the world (IOTF 2007), with commensurate social, medical, and
public health costs (Wyatt, Winters et al. 2006). Obesity, and overweight to a lesser
degree, have consistently been associated with increased morbidity and mortality linked
to cardiovascular disease (CVD), hypertension, type 2 diabetes (T2D), dyslipidemia,
metabolic syndrome (a set of CVD risk factors including hypertension, dyslipidemia,
central obesity and insulin resistance), airway inflammation, fatty liver disease,
gallstones, osteoarthritis, sleep apnea, and certain forms of cancer (NHLBI 2000; Eckel,
Barouch et al. 2002; Klein, Burke et al. 2004; Wellen and Hotamisligil 2005), with relative
risk of these comorbidities being positively correlated with BMI (Wyatt, Winters et al.
2006). In addition, visceral fat, or central adiposity as defined by waist circumference
over 40 inches in males and over 35 inches in females, is a risk factor for these diseases
even independent of a BMI over 30 or 25 kg/m2 (NHANES 2007).
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Genetics and phenotypic expression of obesity
The genetic and molecular mechanisms underlying adipose tissue distribution,
maintenance, excess and possible pathologic sequelae are complex and far from
completely understood. Adding to this complexity are important non-genetic
components permitting and modulating phenotypic expression of obesity, obesity-
related traits, overweight, and comorbidities such as: age, developmental programming
(in utero and post-natal), sex, hormonal status, lifestyles, nutrition, physical activity
level, risk behavior, socioeconomic status, and stress (Shively and Clarkson 1988;
Roseboom, van der Meulen et al. 2001; Hill, Wyatt et al. 2003; Roche, Phillips et al.
2005; Mutch and Clement 2006; Pasquali, Vicennati et al. 2006; Schneider, Tompkins et
al. 2006; Taylor and Poston 2007). Thus, obesity, overweight, and the possible resulting
comorbidities, have very heterogeneous phenotypic expression resulting from an
interaction between a wide array of non-genetic components and genetic susceptibility
factors. This is supported by numerous epidemiological studies in large, diverse human
populations [reviewed in (Sorensen 1995)]. According to several studies, 30 to 80% of
variation in body weight may be determined by genetic factors in humans [reviewed in
(Mutch and Clement 2006)] and similar heritability values have been shown in obesity-
related parameters in vervets (Kavanagh, Fairbanks et al. 2007) (Table 1, Chapter 4) and
other NHPs (Comuzzie, Cole et al. 2003). In discussing the genetic contributions to the
development of obesity, it is important to contrast monogenic and polygenic forms.
Monogenic forms of obesity involve single mutations, are very rare, very severe, and
usually involve early (childhood) onset. Polygenic forms of obesity are the more
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common manifestation and involve the previously described interaction of numerous
genetic variants with various age, sex, and environmental risk factors. In polygenic
obesity, a key conceptual point is that each susceptibility gene variant alone is thought
to have a minor, modulating effect on the obesity phenotype or disease risk.
Inflammatory cascade of obesity
Until relatively recently, adipose tissue was regarded only as a reservoir for
triglycerides. That perspective began to change when mRNA expression of the
inflammatory cytokine TNF- was discovered in adipose tissue of rodent models of
obesity (Hotamisligil, Shargill et al. 1993). Adipose tissue was then established as an
endocrine organ with the subsequent discovery of leptin (Zhang, Proenca et al. 1994),
which is a hormone-like cytokine secreted mostly by adipocytes (thus termed
‘adipokine’) acting on neurons in the hypothalamus regulating food intake and energy
homeostasis, but also upregulating phagocytosis and pro-inflammatory cytokines via
other cell targets (Loffreda, Yang et al. 1998; Wellen and Hotamisligil 2005). The role of
adipose tissue has expanded as additional secretory products with various physiologic
roles continue to be discovered such that it is now recognized to be an integral
endocrine organ. Fatty acids (FAs) are released during times of negative energy balance
and are the most abundant secretory product of adipocytes. The set of more recently
discovered secretory products of adipocytes, which includes leptin, TNF- , adiponectin,
and numerous other adipokines and cytokines, act in an autocrine, paracrine, or
endocrine manner to control various, often overlapping or integrated, metabolic
functions such as: angiogenesis, appetite, blood pressure, hemostasis, immunity,
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inflammation and acute-phase response, insulin sensitivity, lipid metabolism, and
overall systemic energy homeostasis [reviewed in (Trayhurn and Wood 2004; Esteve,
Ricart et al. 2005; Wellen and Hotamisligil 2005; Hotamisligil 2006; Cawthorn and Sethi
2008)]. Over 50 adipokines and cytokines produced by WAT have currently been
identified. Adipokines act in concert with traditional cytokines produced by other cells
of adipose tissue, called the stromovascular fraction (SVF). The SVF comprises
preadipocytes, endothelial cells, smooth muscle cells, fibroblasts, leukocytes, and
resident and infiltrated macrophages (Ross, Erickson et al. 2002; Weisberg, McCann et
al. 2003; Xu, Barnes et al. 2003; Curat, Miranville et al. 2004; Fain, Madan et al. 2004).
Coincident, and overlapping, with the expanding metabolic role of adipose tissue
is the notion that obesity is characterized by a state of chronic low-grade inflammation
(Yudkin, Stehouwer et al. 1999; Das 2001; Festa, D'Agostino et al. 2001; Engstrom,
Hedblad et al. 2003; Trayhurn 2005; Wellen and Hotamisligil 2005; Cawthorn and Sethi
2008), which seems to originate in, and be mediated by the cytokines, adipokines and
other factors secreted from adipose tissue. This view originated with observations that
increased circulating levels of several inflammatory markers are elevated in obesity
(Hotamisligil, Shargill et al. 1993; Hu, Liang et al. 1996; Visser, Bouter et al. 1999; Das
2001; Bullo, Garcia-Lorda et al. 2003; Trayhurn and Wood 2004)(Table 1). Subsequent
elucidation of the cellular sources and interactions of these factors and, most recently,
the finding that macrophages infiltrate adipose tissue in obesity (Weisberg, McCann et
al. 2003; Xu, Barnes et al. 2003) further support this idea.
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Table 1. Selected inflammatory and metabolic regulators within adipose tissue and their putative interactions. CRP, C-reactive protein; FAO, fatty acid oxidation; IL, interleukin; MCP, monocyte chemotactic protein; PAI, plasminogen activator inhibitor; TNF, tumor necrosis factor; GLUT, glucose transporter; Ra, receptor antagonist; ICAM, intracellular adhesion molecule; VCAM, vascular cell adhesion molecule; PPAR, peroxisome
proliferators ctivated receptor; IFN, interferon; WBCC, white blood cell (leukocyte) count [leptin (Maffei, Fei et al. 1995; Siegrist-Kaiser, Pauli et al. 1997; Bullo, Garcia-Lorda et al. 2003; Seufert 2004); CRP (Yudkin, Stehouwer et al. 1999; Pannacciulli, Cantatore et al. 2001) *CRP elevated in both overweight and obese states (Visser, Bouter et al. 1999); TNF-α (Hotamisligil, Shargill et al. 1993; Friedman and Halaas 1998; Moller 2000; Minokoshi, Kim et al. 2002; La Cava and Matarese 2004); adiponectin (Berg, Combs et al. 2001; Chandran, Phillips et al. 2003; Engeli, Feldpausch et al. 2003; Yamauchi, Kamon et al. 2003; Kumada, Kihara et al. 2004); review (Trayhurn and Wood 2004; Fantuzzi 2005; Juge-Aubry, Henrichot et al. 2005; Wellen and Hotamisligil 2005)]
Factors involved in the initiating event have not yet been definitively established,
although local adipose tissue hypoxia in obesity, due to adipocyte hyperplasia and/or
hypertrophism, is the most widely cited hypothesis (Neels and Olefsky 2006), and
convincing evidence has been put forth [e.g. (Hosogai, Fukuhara et al. 2007)]. Further,
whether the inflammatory cascade occurs early or later in obesity has not been clarified;
Factors Association Metabolic effects or
associations Putative interactions
Adiponectin in obesity inflammation, insulin
resistance, atherogenesis; FAO
TNF- , IL-6, ICAM-1, VCAM-1, resistin
IL-10, IL-1 Ra
TNF- in obesity inflammation, IR; FAO
adiponectin, GLUT4,
PPAR
CRP, IL-6, leptin, resistin, MCP-1, PAI-1
Leptin in obesity satiety, FAO, immune function,
inflammation, phagocytosis, TH1
response; T-cell apoptosis
WBCC, CRP, IL-6,
leptin, TNF , IFN- ,
IFN- , IL-2; insulin
CRP in obesity* inflammation, insulin
resistance, atherogenesis
TNF- , IL-6, leptin, PAI-1, ICAM-1, VCAM-
1, E-selectin
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this is particularly true for humans as little to no data are available from obese or
overweight children. Regardless of the uncertainties that remain, there is ample
evidence that inflammation may be causal in the development of insulin resistance,
hyperlipidemia and other components of the metabolic syndrome (Trayhurn and Wood
2004), thus suggesting a pathogenic link between obesity and T2D and CVD.
Table I summarizes three key adipokines (adiponectin, leptin, and TNF ) in
adipose tisse which coordinate, mediate, and perhaps initiate its integrated metabolic,
immune, and inflammatory functions (Hotamisligil 2006). C-reactive protein is also
listed as it is the most commonly used surrogate marker for systemic inflammation.
More detailed descriptions of each of these follow. Since TNF- , and specifically genetic
variation which potentially modulates its effect, is the focus of this thesis project, its role
is described in much greater detail.
Leptin is a hormone-like adipokine produced mainly by adipocytes in amounts
proportional to total body adiposity (Friedman and Halaas 1998). Its primary function is
regulation of long-term satiety and energy expenditure through receptors in several
hypothalamic nuclei (Fei, Okano et al. 1997) such that genetic defects in either the
leptin or leptin receptor gene result in morbid obesity, as shown in mouse models and
humans [reviewed in (Friedman and Halaas 1998)]. Leptin receptors are distributed
throughout multiple peripheral tissues and organs as well, modulating diverse
physiological functions such as reproduction (Chehab, Mounzih et al. 1997),
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angiogenesis (Sierra-Honigmann, Nath et al. 1998), hematopoiesis (Cioffi, Shafer et al.
1996), regulation of bone mass (Takeda, Elefteriou et al. 2002), stimulation of lipolysis in
WAT (Siegrist-Kaiser, Pauli et al. 1997), and regulation of cytokine (Maedler, Sergeev et
al. 2004) and insulin (Seufert 2004) gene expression in the pancreas. A large body of
evidence has accumulated pertaining to the latter effects of leptin on pancreatic -cells
[reviewed in (Seufert 2004)]. Taken together, all known effects of leptin on pancreatic
-cells act to exert long-term (i.e. not generally interfering with short-term stimulatory
actions of nutrients, such as glucose, and hormones) inhibition of insulin secretion and
expression, which adapts the amount of insulin secretion to the amount of adiposity.
Conversely, insulin stimulates both leptin biosynthesis and secretion from WAT, thus
establishing a classic endocrine negative feedback loop, or sometimes termed the
“adipo-insular axis” (Seufert 2004). Evidence to support this concept comes mainly
from animal model and in vitro studies, but is also supported in human studies [e.g.
(Guldstrand, Ahren et al. 2003)]. Table 1 summarizes the metabolic effects and
correlations of leptin with other serum factors.
Adiponectin is an adipokine discovered almost simultaneously by four groups
and therefore has various designations: adipocyte complement-related protein of 30
kDa (Acrp30) (Scherer, Williams et al. 1995), the most abundant gene transcript 1
(apM1) (Maeda, Okubo et al. 1996), gelatin-binding protein of 28kDa (GBP28) (Nakano,
Tobe et al. 1996), or ADIPOQ (Hu, Liang et al. 1996). It is produced exclusively by the
adipocyte fraction of WAT, and circulates at relatively high serum levels (e.g. in mg/ml
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range versus ng/ml for leptin) in lean animals and humans (Fain, Madan et al. 2004;
Fantuzzi 2005). Plasma levels are inversely correlated with BMI and body fat, as well as
fasting proinsulin, TNF- expression, and the insulin response, even after correction for
adiposity (Kern, Di Gregorio et al. 2003; Pellme, Smith et al. 2003). The relevance of
adiponectin was initially recognized by decreased glucose levels after administration to
obese and non-obese diabetic rodent models (Berg, Combs et al. 2001), as well as by
improved insulin resistance of diabetic rodents fed a high fat diet (Yamauchi, Kamon et
al. 2001). Direct evidence of its role in mediating insulin sensitivity was shown through
adiponectin gene knockout (Chandran, Phillips et al. 2003) and overexpression
(Yamauchi, Kamon et al. 2003) mouse studies. In addition to its pivotal role as an insulin
sensitizing factor, it also appears to have significant anti-inflammatory properties, which
are mediated through reduced secretion and expression of TNF- (Masaki, Chiba et al.
2004), reduced secretion of IL-6, and induction of anti-inflammatory cytokines IL-10 and
IL-1Ra (Kumada, Kihara et al. 2004; Wolf, Wolf et al. 2004; Wulster-Radcliffe, Ajuwon et
al. 2004) (Table 1). Inhibition of nuclear factor B (NF- B) by adiponectin may be the
more central molecular mechanism explaining some or all of these effects (Wulster-
Radcliffe, Ajuwon et al. 2004). Further, adiponectin reduces induction of the endothelial
adhesion molecules ICAM-1 and VCAM-1 (Table 1) via either TNF- or resistin (Ouchi,
Kihara et al. 1999; Kawanami, Maemura et al. 2004), thus having anti-atherogenic
properties (Engeli, Feldpausch et al. 2003), and possibly curtailing WAT inflammation by
interfering with local macrophage infiltration.
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C-reactive protein (CRP) was initially discovered as a substance in the serum of
patients with pneumococcal pneumonia, and named for its precipitation when
combined with polysaccaride C of Streptococcus pneumoniae (Tillett and Francis 1930).
It was subsequently shown to be synthesized in the liver, and went on to be
characterized as one of many proteins, termed “acute phase proteins”, induced in
response to a variety of acute infections and inflammatory states (Clyne and Olshaker
1999). Its utility as a biomarker of inflammation stems from the fact that it is normally
present in trace amounts in serum, but increases rapidly and significantly in response to
inflammatory conditions, as it is stimulated by various cytokines, particularly IL-6, IL-1,
and TNF- (Table 1). Further, CRP levels stay elevated until the inflammation has been
resolved, at which time levels rapidly decline with an elimination half-life estimated at
4-9 hours (Clyne and Olshaker 1999). The functional properties of CRP include: binding
of plasma lipoproteins (Pepys, Rowe et al. 1985), complement activation (Volanakis
1982), modulation of phagocytic activity (Kolb-Bachofen 1991), and induction of tissue
factor (Cermak, Key et al. 1993), although exact in vivo function is not known and how
much CRP plays a causative role in inflammation is subject to debate (Yudkin,
Stehouwer et al. 1999; Pannacciulli, Cantatore et al. 2001). Elevated CRP levels have
been shown to be associated with excess adiposity (Visser, Bouter et al. 1999; Yudkin,
Stehouwer et al. 1999; Pannacciulli, Cantatore et al. 2001), insulin resistance (Yudkin,
Stehouwer et al. 1999; Pannacciulli, Cantatore et al. 2001), risk of T2D (Pradhan,
Manson et al. 2001; Nakanishi, Yamane et al. 2003), and CVD and severity of
atherosclerosis and CVD (Berk, Weintraub et al. 1990; Thompson, Kienast et al. 1995; de
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Maat, Pietersma et al. 1996; Paul, Ko et al. 2004), as well as being predictive for
cardiovascular events or CVD-related mortality (Kuller, Tracy et al. 1996; Mendall, Patel
et al. 1996; Ridker, Cushman et al. 1997).
Role of TNF-α in adipocyte biology, and obesity-related inflammation
Testament to the importance of this area of research, there have been
numerous excellent reviews of this subject [e.g. (Esteve, Ricart et al. 2005; Juge-Aubry,
Henrichot et al. 2005; Wellen and Hotamisligil 2005; Hotamisligil 2006; Cawthorn and
Sethi 2008)]. One review in particular by Cawthorn and Sethi (2008), who were involved
in much of the primary research reported therein, is exceptionally useful for its specific
review of TNF- and its role in adipocyte biology and merits special mention as it greatly
facilitated writing this particular thesis section.
TNF- is a cytokine originally named for its ability to cause necrosis of tumors
when induced with bacterial endotoxin. It has subsequently been shown to be not only
the principal mediator of the acute inflammatory and febrile response, but also a multi-
functional cytokine that can regulate many cellular and biological processes such as
immune function, cell differentiation, proliferation, apoptosis, and energy metabolism
and homeostasis (Juge-Aubry, Henrichot et al. 2005; Cawthorn and Sethi 2008). More
recently, it has been recognized as a key initiator and regulator of several cytokines,
adipokines, and acute-phase proteins involved in adiposity-related inflammation
(Coppack 2001; Trayhurn and Wood 2004; Cawthorn and Sethi 2008) (Table 1). TNF-
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expression in WAT was initially demonstrated in obese rodent models, and found to be
markedly increased while downregulating glucose transporter-4 (GLUT4) in adipose
tissue (Hotamisligil, Shargill et al. 1993). Since then, it has been extensively examined in
relation to insulin action, and multiple effects have been described (Moller 2000;
Coppack 2001; Hotamisligil 2003; Juge-Aubry, Henrichot et al. 2005; Wellen and
Hotamisligil 2005), including attenuated insulin receptor signaling via decreased tyrosine
kinase activity (Hotamisligil, Peraldi et al. 1996), and general promotion of insulin
resistance through TNF- gene knockout (Uysal, Wiesbrock et al. 1997) and
overexpression (Xu, Hirosumi et al. 2002) mouse studies.
As previously mentioned, the factors involved in the initiation of obesity-related
inflammation have not been established. Likewise, the initial factor(s) responsible for
inducing TNF- is not clear. This is complicated by the fact that regulation of TNF gene
transcription is cell type-specific (Cawthorn and Sethi 2008). However, questions of
timing of TNF- and the inflammatory cascade of obesity in general, have focused on
identifying the intial trigger(s) that stimulate recruitment and activation of macrophages
into WAT since macrophages are thought to be largely responsible for obesity-related
TNF- secretion (Cawthorn and Sethi 2008). One previously mentioned hypothesis that
has some support is that expanding adipose tissue associated with obesity leads to
adipocyte cell death, and this may induce chemoattractant signals that recruit
monocytes (Neels and Olefsky 2006). Both rodent and human studies support this
hypthesis, which demonstrate increased numbers of apoptotic and necrotic adipocytes
13
in both WAT and brown adipose tissue, respectively (Nisoli, Briscini et al. 1997; Cinti,
Mitchell et al. 2005; Hosogai, Fukuhara et al. 2007; Strissel, Stancheva et al. 2007). One
study in particular shows that the majority of macrophages in WAT of obese mice and
humans are localized to dead adipocytes (Cinti, Mitchell et al. 2005). An alternative
hypothesis, which is not mutually exclusive with the former, relates to immune function
and nutritional status being closely linked (Hotamisligil 2006). It has been suggested
that dietary FAs can alter cytokine production (Kelley 2001) and may play a major role in
initiating obesity-related inflammation, specifically, the ratio of pro-inflammatory n-6 or
anti-inflammatory marine-derived n-3 FAs (Cawthorn and Sethi 2008). Like many other
cytokines, levels of TNF-α are nutritionally regulated but, can be enhanced by
hyperinsulinemia alone (McTernan, Harte et al. 2002). But, again, which of these
conditions comes first is currently unclear. As a final note on timing of obesity-related
inflammation, it is important to keep in mind that in vivo cytokine actions result from a
complex interplay of both anti- and pro-inflammatory cytokines. The cellular milieu of
coordinate anti-inflammatory cytokines, such as adiponectin and IL-10, is likely to play a
role in modulating the intial inciting factors or events triggering TNF- , and obesity-
related inflammation in general.
TNF- is synthesized as a 26-kDa transmembrane monomer (mTNF- ) (Kriegler,
Perez et al. 1988). Subsequent proteolytic cleavage by TNF- converting enzyme (TACE)
yields an additional 17-kDa circulating soluble TNF- molecule (sTNF- ) (Black, Rauch et
al. 1997). Both sTNF- and mTNF- mediate metabolic and inflammatory processes
14
(Perez, Albert et al. 1990; Xu, Sethi et al. 1999). Levels of both have been shown to be
increased in the WAT of obese, diabetic rodent models (Hotamisligil, Shargill et al. 1993;
Xu, Uysal et al. 2002). However, due to the fact that circulating levels of sTNF- are
much lower than in the catabolic diseases, this initially caused debate as to whether
sTNF-α played a significant role inducing states of insulin resistance (Cawthorn and Sethi
2008). Subsequent improvement in assays have helped to show that circulating sTNF-
are well correlated to BMI (Zahorska-Markiewicz, Janowska et al. 2000), and systemic
insulin resistance in mice and rat studies (Togashi, Ura et al. 2002; Weisberg, McCann et
al. 2003; Serino, Menghini et al. 2007).
The molecular mechanisms of TNF- action in adipocytes are mediated through
two distinct cell surface receptors: tumor necrosis factor alpha receptor 1 (TNFR1) and
TNFR2 (Cawthorn and Sethi 2008). TNFR1 is a 55-kDa peptide in humans and 60-kDa in
rodents; TNFR2 is 75-kDa in humans and 80-kDa in rodents. TNFR structure has not
been defined in any NHP at the time of this writing. Both TNFR1 and TNFR2 are
ubiquitously expressed transmembrane glycoproteins that trimerize upon ligand
binding, and like TNF- , both can be proteolytically cleaved to release soluble forms
(sTNFR) (Cawthorn and Sethi 2008), which may be involved in neutralization and
excretion of TNF- thereby modulating TNF- activity (Gatanaga, Hwang et al. 1990).
Both TNFRs are nutritionally regulated as well (Zahorska-Markiewicz, Janowska et al.
2000), and have been reported to increase in both obese and non-obese adults with
pro atherogenic lipid profiles (Hotamisligil, Arner et al. 1997; Mohamed-Ali, Goodrick et
15
al. 1999). TNFR1 and TNFR2 contain highly homologous extracellular domains, but their
intracellular domains have no sequence homology and thus activate separate and
distinct signalling pathways (MacEwan 2002). The vast majority of the obesity-related
and adipocyte biology TNF- effects have been shown to be mediated through the
trimeric TNFR1 death domain (TNFR1-DD) (Csehi, Mathieu et al. 2005; Cawthorn, Heyd
et al. 2007). Specifically, TNFR1-DD can activate cell survival and pro-inflammatory
signalling pathways that lead to the activation of nuclear factor-kappa B (NF- B) and of
mitogen-activated protein kinase (MAPK) cascades, such as those involving extracellular
signal-related protein kinase (ERK), p38 MAPK, and c-Jun N-terminal kinase (JNK) (Jain,
Phelps et al. 1999; Ryden, Dicker et al. 2002; Chae and Kwak 2003; Suzawa, Takada et al.
2003; Kim, Kim et al. 2005).
A major role for TNF- in cellular metabolism was evident upon its discovery as
the agent responsible for cancer cachexia (Kriegler, Perez et al. 1988). Its metabolic role
was further defined by in vitro studies showing it affected glucose homeostasis in
adipocytes (Stephens and Pekala 1991), promoted lipoloysis in cultured adipocytes
(Kawakami, Murase et al. 1987), and inhibited adipocyte differentiation and lipogenesis
(Beutler, Milsark et al. 1985; Torti, Dieckmann et al. 1985). The landmark discovery
implicating TNF-α in T2D was made by Hotamisligil et al (1993) who showed that TNF-
is elevated in adipose tissue from obese diabetic rodents, and is, in fact, a mediator of
obesity-related insulin resistance and T2D. This role was verified with TNF KO mice
(Uysal, Wiesbrock et al. 1997) which had insulin sensitivity restored. Thus, TNF-
16
production appears to contribute to the pathogenesis of rodent obesity-induced insulin
resistance. Evidence that this is true for humans had been less well established before
the aforementioned assay difficulties correlating circulating sTNF- with obesity were
resolved. These issues made it specifically difficult to ascertain whether TNF- activity,
from both mTNF- and sTNF- , was completely neutralized by various anti-TNF
treatments (Cawthorn and Sethi 2008). More recent reports utilizing improved
technologies demonstrate that more chronic administration of anti-TNF- antibodies
improves insulin sensitivity in both lean (Kiortsis, Mavridis et al. 2005; Huvers, Popa et
al. 2007; Tam, Tomlinson et al. 2007) and obese patients (Hermann, Hebert et al. 2004).
Adipocytes of WAT secrete a significant portion of sTNF- . However, the
stromovascular fraction (SVF), which contains preadipocytes, endothelial cells, smooth
muscle cells, fibroblasts, leukocytes, and macrophages, has been shown to produce
substantially more TNF- than adipocytes (Ross, Erickson et al. 2002; Weisberg, McCann
et al. 2003; Xu, Barnes et al. 2003; Fain, Madan et al. 2004). In particular, adipose tissue
macrophages (ATMs) infiltrating into WAT in obese states are thought to be responsible
for a large proportion of the TNF- elevations in obesity (Weisberg, McCann et al. 2003;
Xu, Barnes et al. 2003; Coenen, Gruen et al. 2007; Lumeng, Bodzin et al. 2007) although
their relative contribution has not been precisely established. A recent rodent model
study illustrates this uncertainty by showing that, although macrophage-derived TNF-
can impair insulin sensitivity in TNF KO mice, the absence of TNF- in macrophages
17
alone does not protect otherwise wild-type mice from obesity-related insulin resistance
(De Taeye, Novitskaya et al. 2007).
Role of TNFα in insulin resistance and dyslipidemia. Adipose tissue is a key regulator of
systemic carbohydrate metabolism. As a prime example, mice with tissue-specific
GLUT4 KO in adipose tissue develop systemic glucose intolerance and hyperinsulinemia
(Abel, Peroni et al. 2001). Subsequent studies have clearly established the ability of
TNF- specifically to induce insulin resistance in adipocytes (Ruan and Lodish 2003)
through both transcriptional, and more direct cellular signalling mechanisms via TNFR1-
DD (Csehi, Mathieu et al. 2005). Several of these interrelated effectors, mechanisms,
and cellular pathways are summarized below:
1) Insulin receptor, insulin receptor substrate-1 (IRS-1), and GLUT4, which are all
required for insulin-stimulated glucose uptake in adipocytes, have been shown to be
suppressed at the transcriptional level by TNF-α (Stephens, Lee et al. 1997; Ruan,
Hacohen et al. 2002; Ruan, Miles et al. 2002).
2) Peroxisome proliferator-activated receptor gamma (PPAR ), a transcription factor
(TF) of central importance, is targeted by TNF- in adipocytes (Miles, Romeo et al.
1997; Peraldi, Xu et al. 1997). TNF- suppresses transcriptional activity of PPAR via
serine phosphorylation of its N-terminal domain, mediated by JNK and extracellular
signal-regulated kinase (ERK1/2) (Hu, Kim et al. 1996; Adams, Reginato et al. 1997).
Post-transcriptional regulation is also thought to occur by suppression of PPAR
18
mRNA by TNF- , although this may simply occur due to the fact that PPAR
expression is upregulated by its own activity (Cawthorn and Sethi 2008).
3) NF- B, which is thought of as the classic TNF- -induced TF, also mediates inhibition
of PPAR transcription (Suzawa, Takada et al. 2003).
4) CCAAT/enhancer binding protein (C/EBPα), another adipogenic TF and PPAR target
gene, is also suppressed by TNF- at the mRNA level (Jain, Phelps et al. 1999).
5) The promoter region of the GLUT4 gene contains response elements for both PPAR
and C/EBPα (Jain, Phelps et al. 1999), which are two of the likely mechanisms by
which TNF- downregulates GLUT4. But, whether this is true for all genes
downregulated in insulin resistant states is not currently clear (Cawthorn and Sethi
2008).
6) Another MAPK which may contribute to PPAR and GLUT4 suppression by TNF- is
mitogen activated protein kinase kinase kinase kinase 4 (MAPK4) which activates the
JNK signalling pathway in adipocytes (Tang, Guilherme et al. 2006). However, its
specific role and mechanism are currently not known (Cawthorn and Sethi 2008).
7) The transcriptional events required for TNF- -induced insulin resistance may also
involve the transcriptional activity of NF- B itself, and hence NF- B target gene
expression. But, this has yet to be fully demonstrated in adipocytes. Despite this,
there is ample evidence to support the requirement for the upstream signals that
lead to NF- B activation in TNF- -induced insulin resistance in vitro and in vivo
(Yuan, Konstantopoulos et al. 2001; Ruan, Hacohen et al. 2002; Arkan, Hevener et al.
2005; Cai, Yuan et al. 2005). Several potential NF- B target genes that are
19
upregulated by TNF- in adipocytes have been implicated in adipocyte insulin
resistance. Suppressor of cytokine signalling-3 (SOC-3) is one particularly relevant
NF- B target gene which inhibits insulin receptor-dependent IRS-1 tyrosine
phosphorylation and thereby suppresses insulin-stimulated glucose uptake
(Emanuelli, Peraldi et al. 2001; Peraldi, Filloux et al. 2001; Ueki, Kondo et al. 2004).
8) Serine phosphorylation of IRS-1 (Hotamisligil, Peraldi et al. 1996; Peraldi, Hotamisligil
et al. 1996; Zick 2005) is one of the most well studied non-transcriptional
mechanisms of compromising insulin receptor/IRS-1 signalling. TNF-α is thought to
effect this outcome via direct signalling events that mediate shared signal
transduction between TNFR1-induced pathways and proximal insulin signals
(Engelman, Berg et al. 2000).
9) Alterations in membrane lipid composition can be caused by TNF-α action. These
can lead to insulin resistance through several means, including activating serine
kinase signalling cascades, and altered membrane fluidity which impairs receptor
internalization, cyling and function [reviewed in (Cawthorn and Sethi 2008)].
10) Endoplasmic reticulum (ER) stress (Ozcan, Cao et al. 2004; Nakatani, Kaneto et al.
2005; Ozawa, Miyazaki et al. 2005; Ozcan, Yilmaz et al. 2006), oxidative stress and
mitochondrial dysfunction (Furukawa, Fujita et al. 2004; Lin, Berg et al. 2005; Lowell
and Shulman 2005; Houstis, Rosen et al. 2006) have been linked to obesity-related
inflammation, insulin resistance, and T2D [reviewed in (Hotamisligil 2006)]. All of
these pathways can be induced by TNF- , and have been linked to activation of the
JNK [e.g. (Urano, Wang et al. 2000)] or NF- B [e.g. (Hu, Han et al. 2006)] pathways.
20
It has been reported that production of reactive oxygen species (ROS) contributes to
both TNF- -induced NF- B activation (Gloire, Legrand-Poels et al. 2006) and TNF- -
induced insulin resistance (Houstis, Rosen et al. 2006). In addition, oxidative stress is
suggested to promote increased TNF- production under adverse metabolic
conditions such as hyperglycemia (Esposito, Nappo et al. 2002). TNF- in adipose
tissue upregulates expression of many genes that encode proteins involved in
responses to ER stress or oxidative stress (Ruan, Hacohen et al. 2002), and
downregulates components of the electron transport chain (Dahlman, Forsgren et
al. 2006) likely inducing mitochondrial dysfunction. This idea is further supported by
evidence showing TNF- inhibiting fatty acid oxidation (FAO) in differentiated
human adipocytes (Dahlman, Forsgren et al. 2006).
11) The principal insulin-sensitizing adipokines are adiponectin and leptin (Sethi and
Vidal-Puig 2007). Adiponectin promotes insulin sensitivity and favorable serum lipid
profiles through AMPK activation and increased FAO (Yamauchi, Kamon et al. 2002;
Yamauchi, Kamon et al. 2003). TNF- suppresses adiponectin, which is one of
several overlapping mechanisms by which TNF- effects systemic insulin resistance
and dyslipidemia (Kappes and Loffler 2000; Fasshauer, Klein et al. 2002; Ruan,
Hacohen et al. 2002). This mechanism of adiponectin suppression is thought to be
mediated, at least in part, by suppression of PPAR (Matsuzawa 2005), C/EBPb (Kita,
Yamasaki et al. 2005), and/or through activation of JNK (Hirosumi, Tuncman et al.
2002; Kim, Kim et al. 2005). How TNF- regulates leptin is not as well understood.
TNF- actually promotes leptin release from adipocytes (Kirchgessner, Uysal et al.
21
1997; Finck and Johnson 2000). In the absence of TNF- , obesity-related
hyperleptinemia is significantly reduced; however, the mechanism is unclear as the
transcriptional upregulation is context-dependent (Grunfeld, Zhao et al. 1996;
Kirchgessner, Uysal et al. 1997; Trujillo, Lee et al. 2006).
12) Despite the realization over the past 15 years that adipocytes play larger metabolic
and endocrine roles, their major functions continue to be the ability to store and
release surplus energy through lipogenesis and lipolysis/thermogenesis respectively.
These processes are regulated by numerous extracellular stimuli, such as insulin,
cortisol, catecholamines, growth hormone, testosterone, free fatty acids (FFA), and
cytokines [reviewed in (Ramsay 1996)]. Lipid metabolism in adipocytes can be
directly affected by TNF- via inhibition of FFA uptake and lipogenesis, as well as
stimulation of FFA release via lipolysis thereby contributing to the development of
dyslipidemia and the metabolic complications thereof (Cawthorn and Sethi 2008).
Conversion of lipids into triacylglycerol is dependent on the availability of substrates,
namely glucose, and the regulation of key enzymatic pathways. This conversion is
affected by TNF-α by the induction of adipocyte insulin resistance and resultant
impaired glucose uptake into adipocytes. In addition, TNF- downregulates
expression of FA transport protein (FATP) and translocase (FAT) in adipose tissue
(Memon, Feingold et al. 1998), as well as the FA binding protein FABP4/aP2
(Cawthorn and Sethi 2008), although the exact mechanisms have not been
definitively established. FFA uptake into adipocytes is also affected by lipoprotein
lipase (LPL) (Ramsay 1996), and TNF- downregulates LPL expression in both murine
22
adipose tissue and in 3T3-L1 adipocytes (Ruan, Miles et al. 2002; Ruan, Pownall et al.
2003), likely via TNFR1 (Lopez-Soriano, Llovera et al. 1997). However, the effects of
TNF- on LPL in human adipose are not clear at this time (Kern 1988; Fried and
Zechner 1989). TNF- also suppresses transcription (likely through PPAR ) and
mRNA expression of many proteins involved in gluconeogenesis, and de novo FA
synthesis and esterification (Cawthorn and Sethi 2008), which leads to impaired TG
storage in adipose tissue. This can contribute to hyperlipidemia, along with the
potential ability of TNF- to stimulate lipolysis which can occur in the absence of
insulin (Cawthorn and Sethi 2008). Thus, it would appear that TNF-α does not simply
antagonize insulin’s anti-lipolytic actions. In addition, extracellular glucose is
required for TNF- -mediated adipocyte lipolysis (Green, Rumberger et al. 2004),
which suggests that ATP is required. These mechanisms have yet to be fully
elucidated.
Association studies in humans
Numerous polymorphisms have been identified in cytokine, adipokine, and
inflammatory biomarker candidate genes for the putative inflammatory cascade of
obesity. Those shown to be statistically associated with obesity-related phenotypic
traits or disease risk in various human populations are mostly single nucleotide
polymorphisms (SNPs), primarily located in the enhancer/promoter regions, although a
significant number can also be found within the intronic and 3’/5’ untranslated (UTR)
regions. Very few genetic polymorphisms in the coding (exon) regions resulting in non-
23
synonymous amino acid changes have been observed. Of all such association studies,
those examining the TNF- (TNF) gene variants are among the most abundant in the
literature and are the focus of this dissertation. Table 2 summarizes selected studies
which have demonstrated significant phenotypic associations with certain genotypes or
haplotypes (sets of statistically associated alleles within a gene or on a single
chromatid). In addition, whole genome scans have shown linkage of the region near the
adiponectin gene with T2D in French and Japanese populations (Vionnet, Hani et al.
2000; Mori, Otabe et al. 2002) and with fasting insulin levels in European Americans
(Kissebah, Sonnenberg et al. 2000).
Table 2. Summary of associations between TNF gene SNPs and various obesity-related phenotypic traits in humans.
BP, blood pressure; FFA, free fatty acids; FG, fasting glucose; HDL, high density lipoprotein; LDL, low density lipoprotein; TG, triglycerides; WC, waist circumference; W:H, waist-to-hip ratio; (Fernandez-Real, Gutierrez et al. 1997; Wilson, Symons et al. 1997; Hoffstedt, Eriksson et al. 2000; Skoog, Eriksson et al. 2001; Fernandez-Real and Ricart 2003; Wybranska, Malczewska-Malec et al. 2003; Corbalan, Marti et al. 2004; Markovic, O'Reilly et al. 2004; Um, Kang et al. 2004); review (Fernandez-Real 2006)]
As previously discussed, obesity is paradigmatic of phenotypes that are the
resolution of complex gene-gene interactions, as well as interactions of genotype with
environment, developmental age, and sex (Scriver 2001). Association studies attempt
to further elucidate genetic bases for susceptibility to such complex disease phenotypes.
To best interpret such studies and put them in the proper context, it is important to
Gene symbol
Gene name
Traits or disease risk associated with certain genotypes or haplotypes
Size (kb)
TNF TNF-alpha
obesity, BMI, FG, FFA, insulin resistance, TG, WC, W:H, CRP
leptin, TNF- 2.8
24
recognize the way these traits likely evolved. Such phenotypes almost certainly
conferred significant selective advantage throughout a very large span of evolutionary
history, but have now become detrimental with the vastly different environments and
selective pressures, or lack thereof, humans now experience compared to the hunter-
gatherer, or even pre-industrial, lifestyle. As a prime example, genetic predisposition to
obesity is presumably the result of evolution in environments in which food was not
easily attainable, thus favoring selection for metabolically efficient phenotypes
involving, among other things, the ability to store transient caloric excess as triglycerides
within adipocytes (Neel 1962). In environments of caloric abundance and much less
need for caloric expenditure, such as those experienced in industrialized countries,
chronic metabolic overload and thus obesity may ensue. Local and systemic
inflammatory responses to obesity are characteristic to mammalian species from
rodents and felines to primates (Miller, Bartges et al. 1998; Dandona, Aljada et al. 2004;
Pickup 2004). Why obesity elicits an inflammatory response, which can clearly be
detrimental to health, is an open question but related to: 1) chronically overweight or
obese states and their associated disorders were likely to have been rare throughout
most of the evolutionary history of animals in their reproductive years, and therefore
rarely subject to negative selective pressures and; 2) metabolic and immune pathways
have evolved to be closely linked and interdependent such that many hormones,
cytokines, adipokines, transcription factors, and bioactive lipids can function in both
metabolic and immune roles (Wellen and Hotamisligil 2005) (Table 1). A model of
overlapping metabolic and inflammatory signaling and sensing pathways in adipocytes
25
or macrophages has been put forth by Wellen and Hotamisligil (2005). This model
describes cellular homeostasis as striking a balance between metabolism and
inflammation, which becomes challenging in conditions of chronic overnutrition since
the processes required for response to nutrients and nutrient utilization, such as
mitochondrial oxidative metabolism and increasing protein synthesis in the endoplasmic
reticulum, can also induce the inflammatory response. To what degree this model is
supported by subsequent mechanistic studies is of secondary importance to the
rationale put forth here. The relevant points to the present study are: 1) the molecular
and genetic mechanisms of adipose-related inflammation also involve metabolic and
immune systems, which are among the most basic requirements across the animal
kingdom and therefore highly conserved (Wellen and Hotamisligil 2005), and likely
entail numerous genes which each have small permissive or modulatory effects on
phenotype and; 2) in any effort to investigate the genetic bases for susceptibility to
obesity, the environment (including age and sex) is a critical determinant of phenotypic
expression, and subsequently, of what genes will be identified as contributing to
phenotype (Scriver 2001).
Limitations of human studies
Controlling for the multitude of environmental risk factors has been a major
confounder of efforts to elucidate the role and relative contribution of variation in
candidate genes in human studies. Although there is little to no debate regarding the
essential role gene-gene and gene-environment interactions play in the development of
26
obesity, these aspects are rarely addressed in association studies due to the complex
experimental designs and data processing they would entail (Mutch and Clement 2006).
In addition, converging lines of evidence from epidemiological and animal model studies
indicate that interactions between genes and embryonic, fetal, and early postnatal
environments (termed ‘epigenetics’ or ‘developmental programming’) also contribute
[reviewed in (Taylor and Poston 2007)], adding another dimension of complexity and
difficulty in environmental control for human studies. Further, longitudinal studies in
humans, particularly those starting in childhood and/or spanning a significant portion of
lifetime, are logistically impossible or highly improbable. Other shortfalls often include
lack of statistical power to detect modest effect, lack of control over type-1 error rate,
population stratification and overinterpretation of marginal data (Mutch and Clement
2006).
Limitations of existing obesity and diabetic models
Research directed at further elucidating the genetic and molecular mechanisms
of obesity and disentangling the age- and environment-related factors through more
relevant animal models has been assigned as one of the highest priorities in the U.S.
(Eckel, Barouch et al. 2002; USHHS 2007). Rodents currently represent the most
common animal model of obesity and its comorbidities, and have greatly advanced
knowledge in the field. However, there are major physiological and developmental
differences between rodents and humans that are reflective of their evolutionary
divergence approximately 80 million years ago (Eizirik, Murphy et al. 2001). In contrast,
27
the separation of humans and other great apes from Old World Monkeys (OWM)
occurred about 25 million years ago (Page and Goodman 2001), making them a much
more genetically appropriate model for studying human obesity (West and York 1998;
Wagner, Kavanagh et al. 2006). One important example of this is the similarity of
reproductive physiology (e.g. menstruation, cycling, and menopause) between OWM
and humans, which is starkly different in rodents. Sex hormones and estrogen in
particular, have been shown to affect obesity and insulin resistance as well as risk of T2D
and CVD in humans and OWM (Salpeter, Walsh et al. 2006; Schneider, Tompkins et al.
2006; Wagner, Kavanagh et al. 2006). Furthermore, estrogen and/or progestin
(synthetic progesterone) levels and/or administration have been positively correlated
with leptin (Hong, Yoo et al. 2007), negatively correlated with TNF- (Hong, Yoo et al.
2007) and negatively associated with adiponectin (Im, Lee et al. 2006) in humans. The
development of obesity in OWM is similar to humans in that it can develop without
experimental manipulation and while on a standard diet (Kemnitz 1984; Comuzzie, Cole
et al. 2003; Wagner, Kavanagh et al. 2006), and obesity is a risk factor for the
development of diabetes in those species as it is in humans (Wagner, Kavanagh et al.
2006). T2D develops naturally in several species of OWM, and they exhibit similar
clinical and pathological changes in the pancreas as those observed in humans (Wagner,
Kavanagh et al. 2006). The Wagner lab has extensive experience with the
characterization of obesity, diabetes and CVD in OWM [e.g. (Wagner, Bagdade et al.
1996; Wagner, Carlson et al. 1996; Wagner, Cline et al. 2001; Wagner, Kavanagh et al.
2006)]. However, one limitation has been insufficient numbers of spontaneously obese
28
or diabetic monkeys, thus necessitating the use of diet-induced obesity or chemically-
induced diabetes to study interactions and various aspects of these diseases. Another
limitation has been lack of pedigree information, which limits analysis of genetic and age
components of disease, and does not allow prospective assessment of pre-diabetic
conditions.
The Vervet Research Colony (VRC)
The Wake Forest University Primate Center VRC was founded in 1975 at UCLA
with 57 founders (29 females, 28 males) wild-caught from St. Kitts, West Indies. The
current population includes approximately 450 descendants with 24 of the original
matrilines now in their 5th to 8th generation. Animals are currently housed in 8
indoor/outdoor corrals and, prior to 2009, fed a commercial primate chow daily,
supplemented by fresh fruits and vegetables. All animals have ad libitum access to food
and opportunities to exercise. Current colony management practices have been
designed to reflect the natural social composition of vervet monkeys in the wild. All
animals are reared by their mothers in indoor/outdoor enclosures. Infants and juveniles
remain in the natal group with their mothers and female kin. Males are removed at
adolescence and transferred to other groups, and adult males are rotated between
groups at 3-4 year intervals to mimic the natural processes of emigration and
immigration. These policies were originally intended to promote normal development
and provide opportunities for animals to express age and sex-appropriate species-
typical behavior. They have produced a population of animals that is particularly
29
valuable in two respects: 1) matrilineal grouping of females and movement of males
between groups has produced a large, complex, inter-related pedigree that is ideal for
behavioral and medical genetics research and; 2) maintaining animals in stable
matrilineal groups allows the study of naturally occurring individual differences in
physiology, behavior, reproduction, and disease in a developmental and social context
that is within the normal range for this species. Paternity has been verified for the
entire pedigree using microsatellite markers (Newman, Fairbanks et al. 2002). The
multigenerational pedigree of animals with known mothers and fathers at the VRC
allows use of variance components techniques to estimate the genetic contributions to
different traits and to identify animals at risk for specific disorders.
Working in collaboration with Lynn Fairbanks at UCLA, a high prevalence of
spontaneous obesity, gestational diabetes and T2D in the VRC population has been
observed over the years. Also, maternal BMI can predict the BMI of offspring at 4-5
years of age (Fairbanks & Wagner, unpublished data). Thus, given that Old World
nonhuman primates (NHP) are particularly important animal models for the study of
obesity and related inflammation given their close phylogenetic relationship to humans,
similar reproductive and endocrine physiology to humans, and their potential to exhibit
spontaneous obesity, insulin resistance, T2D and CVD, the practical and more proximate
rationale of this study was to further characterize the St. Kitts-origin vervet monkey
(Chlorocebus aethiops ssp.), both phenotypically and genetically, to refine it as a model
of obesity and its comorbidities. The longer term goal of this thesis project was to more
30
fully elucidate the cellular, molecular and genetic mechanisms involved in the initiation
and regulation of adipose-related inflammation. A better understanding of the role of
adipose-induced inflammation will likely be a crucial step in developing effective
preventative and therapeutic strategies to address obesity and its inflammation-related
comorbidities.
The overarching hypothesis of this project is that defining genetic associations
between genetic polymorphisms in the orthologous vervet monkey TNF gene and
previously defined obesity related phenotypes will yield valuable insight into the
pathophysiologic mechanisms and genetic contributions underlying obesity and its
inflammatory-related comorbidities in humans. Specific aims are:
1) Identify and characterize the common genetic variation (SNPs +/-
microsatellites) in the orthologous TNF vervet gene using DNA sequencing and
linkage disequilibrium structure.
A. Inherent in this aim is comparing vervet TNF gene sequences to that of
humans and other relevant NHPs using bioinformatics. Such comparisons are
used to assess percentage of sequence identity, regions of conservation,
ancestral alleles, and phylogeny.
2) Assess any genetic associations between TNF genetic polymorphisms and the
following, previously characterized obesity-related phenotypic traits by
Kavanagh et. al (2007): body mass index (BMI), waist circumference (WC), total
31
plasma cholesterol (TPC), triglycerides (TG), and high density lipoprotein
cholesterol (HDL-C).
3) Provide a basis for future studies involving longitudinal measures of obesity-
related traits and cytokine levels, as well as other potential phenotypic
measures including gene expression, metabolomic, and proteomic profiles, in
order to further dissect genotypic and age-related contributions to disease
using the vervet monkey model.
32
CHAPTER II
COMPARATIVE ANALYSES OF SINGLE NUCLEOTIDE POLYMORPHISMS IN THE TNF
PROMOTER REGION PROVIDE FURTHER VALIDATION FOR THE VERVET MONKEY
MODEL OF OBESITY
Stanton B. Gray, Timothy D. Howard, Carl D. Langefeld, Gregory A. Hawkins,
Abdoulaye F. Diallo, Janice D. Wagner
The following manuscript has been conditionally accepted for publication in the journal
Comparative Medicine. Stylistic variations are due to the requirements of the journal.
Dr. S.B. Gray prepared the manuscript and was primarily responsible for performing and
directing the experiments, as well as data analysis and interpretation. Technical
assistance was provided by Mr. A.F. Diallo. Analytical assistance was provided by Drs.
T.D. Howard and G.A. Hawkins. Statistical analysis assistance was provided by Dr. C.D.
Langefeld. Drs. T.D. Howard and J.D. Wagner acted in an advisory capacity. All co-
authors provided editorial input.
33
Abstract
Tumor necrosis factor (TNF) is a cytokine which plays critical roles in inflammation, the
innate immune response, and a variety of other physiological and pathophysiological
processes. It has also recently been shown to mediate an intersection of chronic, low-
grade inflammation and concurrent metabolic dysregulation associated with obesity and
its comorbidities. As part of an ongoing initiative to further characterize the St. Kitts-
origin vervet monkey as an animal model of obesity and inflammation, we sequenced
and genotyped the human ortholog vervet TNF gene and ~1 kb of the flanking 3’ and 5’
regions from 265 monkeys in a closed, pedigreed colony. This revealed a total of 10
single nucleotide polymorphisms (SNPs), and one 4 bp insertion/deletion, with minor
allele frequencies of 0.08-0.39. Many of these polymorphisms were in strong or
complete linkage disequilibrium with one another, and were contained within one
haplotype block, comprising five haplotypes with frequencies of 0.075-0.298. Using
sequences from humans, chimpanzees, vervets, baboons, and rhesus macaques,
phylogenetic shadowing of the TNF promoter region revealed that vervet SNPs, like the
SNPs in related species, were clustered non-randomly and non-uniformly (p<0.0001)
around conserved TF binding sites. These data, combined with previously defined
heritable phenotypes, permit future association analyses in this nonhuman primate
model which have great potential to help dissect the genetic and non-genetic
contributions to complex diseases like obesity. More broadly, the sequence data and
comparative analyses reported herein facilitates study of the evolution of regulatory
sequences of inflammatory and immune-related genes.
34
Introduction
Obesity is a worldwide epidemic, and a major risk factor for several chronic diseases
including type 2 diabetes (T2D) and cardiovascular disease (CVD) (Wyatt, Winters et al.
2006). Chronic, low-grade, systemic inflammation is associated with obesity and also
plays a major role in the pathogenesis of T2D and CVD (Trayhurn and Wood 2004).
Excessive adipose tissue, as seen in overweight and obese states, is a significant source
of circulating inflammatory cytokines which represents a potential pathogenic
mechanism linking obesity to these comorbidities. Many cytokine regulators of the
putative inflammatory cascade of obesity have been identified. Of these, TNF is among
the most well studied. TNF is a cytokine secreted by adipocytes and other tissues which
plays critical roles in lymphocyte biology, immune responses, and promoting
inflammation (Juge-Aubry, Henrichot et al. 2005); it also increases insulin resistance (IR)
by downregulating glucose transporter 4 (GLUT4) in adipocytes (Hotamisligil, Shargill et
al. 1993), serine phosphorylation of IRS-1 (Hotamisligil, Peraldi et al. 1996), as well as
several other mechanisms. Serum TNF levels are correlated with obesity and serum
levels of C-reactive protein (CRP), leptin and other inflammatory cytokines (Coppack
2001; Trayhurn and Wood 2004).
Exempting some rare monogenic forms, obesity, T2D, and CVD are classic examples of
complex, polygenic diseases. As such, expression of these disease phenotypes requires
a combination of genetic susceptibility at multiple gene loci and certain environmental
risk factors such as lifestyle habits, socio-economic status, and diet (Shively and Clarkson
1988; Roseboom, van der Meulen et al. 2001; Hill, Wyatt et al. 2003; Mutch and
35
Clement 2006; Pasquali, Vicennati et al. 2006; Taylor and Poston 2007). In addition,
there are significant gender- (Salpeter, Walsh et al. 2006; Schneider, Tompkins et al.
2006) and age-related components to progression and severity of disease expression.
Fully delineating these components and their relative contributions has been
problematic in human studies (Mutch and Clement 2006). Animal models, of course,
provide essential research avenues to control or specifically manipulate environmental
factors, thereby yielding more powerful studies through increased homogeneity of
conditions, as well as enable the study of disease progression throughout the lifetime of
the animal. Old world nonhuman primates (NHPs) are particularly important animal
models for the study of obesity and inflammation given their close phylogenetic
relationship to humans, comparable fat distribution (Bergman, Kim et al. 2007), similar
reproductive and endocrine physiology to humans, and their potential to exhibit
spontaneous obesity, IR, T2D and CVD (Wagner, Bagdade et al. 1996; Wagner, Carlson et
al. 1996; West and York 1998; Wagner, Cline et al. 2001; Wagner, Kavanagh et al. 2006;
Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones et al. 2007).
Despite obesity and its comorbidities being polygenic diseases, detailed analysis of each
gene implicated is needed to better understand its role in the disease cascade, including
gene-gene and gene-environment interactions, and to ultimately expand the range of
diagnostic and therapeutic targets. As a prime example, certain risk alleles in humans at
single nucleotide polymorphisms (SNPs), primarily within the regulatory
promoter/enhancer regions, of the TNF gene have various significant associations with
obesity and related traits in humans including: CVD or T2D disease risk, IR, lipid profiles,
36
and serum and/or expression levels of adiponectin, CRP, leptin and TNF levels
(Fernandez-Real 2006). Despite the multitude of genetic association studies, those
demonstrating functional SNPs affecting TNF secretion [e.g. (Skoog, Eriksson et al.
2001)], or in vitro transcription factor (TF) binding (Kroeger, Carville et al. 1997; Wilson,
Symons et al. 1997; Knight, Udalova et al. 1999; Udalova, Richardson et al. 2000) are
fewer. A major reason for the difficulty in identifying functional SNPs in TNF, or
anywhere within the major histocompatibility complex (MHC), is the strong degree of
linkage disequilibrium (LD), or non-random association of two or more alleles, within
this region (Shiina, Ota et al. 2006), yielding extended haplotypes (Ceppellini, Siniscalco
et al. 1955).
As part of an ongoing initiative to further genetically and phenotypically characterize the
St. Kitts-origin vervet monkey (Chlorocebus aethiops sabaeus) as a model of obesity,
insulin resistance, and type 2 diabetes (Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones
et al. 2007), we sequenced and genotyped the TNF gene and its promoter region in 265
monkeys from the pedigreed Vervet Research Colony (VRC), and performed
comparative analyses with human and other NHPs commonly used in biomedical
research. In addition, we tested our prediction that SNPs in the human ortholog vervet
TNF promoter region would be distributed non-randomly around conserved TF binding
sites, as shown in humans and other NHPs (Leung, McKenzie et al. 2000; Baena,
Mootnick et al. 2007).
Materials and Methods
37
Animals. All methods for the care and use of nonhuman primates conformed to U.S.
Department of Agriculture and Public Health Service standards, and all experimental
protocols were approved by the Chancellor’s Animal Research Committee at UCLA and
the Institutional Animal Care and Use Committee for the Department of Veterans Affairs
Greater Los Angeles Healthcare System. Two hundred and sixty five vervets
(Chlorocebus aethiops sabaeus) from the VRC were used in this study. The VRC was
founded in 1975 at UCLA from 57 vervets (28 males, 29 females) wild caught from 1975-
1983 in St. Kitts, West Indies, as described in Fairbanks et al. (2004). The current
population includes approximately 450 descendants with 24 of the original matrilines in
their 5th to 8th generation, and now resides at the Wake Forest University Primate
Center (WFUPC). All vervets were fed a commercial primate laboratory chow which is
relatively low fat and high fiber (Laboratory Diet 5038; Purina, St. Louis, MO) ad libitum
supplemented with fresh fruits and vegetables.
PCR and Sequencing. Genomic DNA was isolated from peripheral blood samples using
standard protocols previously described (Jasinska, Service et al. 2007). For sequencing,
PCR primers were generated with the PrimerSelect software (Laser Gene software,
DNASTAR, Madison, WI.) using a consensus TNF gene sequence created from human,
chimpanzee (Pan troglodytes) and rhesus monkey (Macaca mulatta) found in the NCBI
gene database (www.ncbi.nlm.nih.gov; uc003nui.1, NM_001045511, NM_001047149
respectively). Primer consensus sequences were created using the editing feature in
Sequencher v4.6 (Gene Codes Corp., Ann Arbor, MI), and were designed to amplify the
entire TNF gene plus ~1 kb 3’ and ~1 kb 5’ flanking regions. PCR conditions were as
38
follows: initial denaturation at 95oC for 10 min, followed by 30 cycles of 96oC for 1 min,
58-60oC for 1 min and 72oC for 60-90 sec with final elongation for 10 min at 72oC in a 20-
µl reaction mixture. PCR products were purified (QuickStep, Edge Biosystems Inc.,
Gaithersburg, MD) to remove dNTPs and excess primers that interfere with sequencing
reactions. Purified PCR products were sequenced using dye-terminator chemistry
(BigDye, ABI, Foster City, CA). Dye-terminator reactions were performed in 5-10 µl
reactions in 96-well plates. The dye-terminator kit was diluted fourfold using a 2.5X
dilution buffer (50 mM Tris, 10 mM MgCl2 pH 9.0). Sequencing reactions were purified
by ethanol precipitation prior to loading on an ABI3730XL DNA Analyzer using the POP7
sequencing polymer.
Sequence Analyses. Sequences from the 265 VRC vervets were aligned and genotyped
using Sequencher v4.6 (Gene Codes Corp., Ann Arbor, MI). LD structure and
allele/haplotype frequencies were determined with Haploview, version 4.0 (Barrett, Fry
et al. 2005). Sequence alignment scores were generated using ClustalW, version 1.7
(Thompson, Higgins et al. 1994). This vervet sequence (EU626004), and all other
sequences, except baboon, reported herein are in the NCBI gene database (accession
numbers noted above); baboon TNF promoter sequence has been published elsewhere
(Haudek, Natmessnig et al. 1998; Leung, McKenzie et al. 2000; Baena, Mootnick et al.
2007). Transcription factor binding sites for NFAT, ETS, 3, CRE, and SP1 (Goldfeld,
Doyle et al. 1990; Tsai, Jain et al. 1996; Tsai, Yie et al. 1996; Falvo, Uglialoro et al. 2000;
Tsai, Falvo et al. 2000; Tsytsykova and Goldfeld 2002; Barthel, Tsytsykova et al. 2003),
and 1 and 2 (Goldfeld, Doyle et al. 1990) were crosschecked with ORegAnno
39
(Montgomery, Griffith et al. 2006) as implemented in the UCSC genome browser
(www.genome.ucsc.edu/). Conserved regions were identified and illustrated by
phylogenetic shadowing (Boffelli et al. 2003), using the web-based program eShadow
[http://eshadow.dcode.org/; (Ovcharenko, Boffelli et al. 2004)]. Only validated (i.e.
demonstrated experimentally) human SNPs (dbSNP build 128) are reported in the
promoter sequence comparison; of those, only those with 5% minor allele frequency
(MAF) or greater were used to compare to the eShadow output. SNP locations were
compiled from dbSNP (Build 128, www.ncbi.nlm.nih.gov) for humans, and reports in the
literature for chimpanzee (Baena, Mootnick et al. 2007), and rhesus macaque (Singh and
Schmidtke 2005); TNF SNPs for the baboon were not available at the time of this writing.
Statistical Analyses. Komolgorov-Smirnov tests whether the empirical distribution of a
sample statistically deviates from a specified theoretic distribution. Here the
Komolgorov-Smirnov test was computed using Analyse-It® for Microsoft Excel version
2.12 (Analyse-it Software, Ltd. http://www.analyse-it.com/; 2008) to test whether the
distribution of the p-values deviated from a uniform distribution; under the null
hypothesis the p-values of our test follow a uniform distribution. Thus, the distribution
of SNPs p-values along a 50-base pair sliding window for each species (human, chimp,
vervet, and rhesus) plus the consensus distribution of all four was tested for non-
uniformity.
40
Results
Analysis of ~1 kb 5’ upstream, ~0.9 kb 3’ downstream, all four exons, and all intronic
regions of the human ortholog vervet TNF gene in 265 vervet monkeys revealed a total
of 12 polymorphisms: 11 SNPs and one 4 bp insertion/deletion, with MAF ranging from
0.08 to 0.39 (Table 1). None of the loci corresponding to the SNPs found in vervets have
been reported to be polymorphic in human populations (dbSNP build 128). The +611
(TGAA)4/5 insertion/deletion, located in intron 1, is a (TGAA)6 in humans and is
apparently fixed; chimpanzees also contain (TGAA)6. The rhesus monkey sequence is
reported as (TGAA)5, but it is unknown if this sequence is polymorphic in rhesus or any
other NHP species. The entire human ortholog vervet TNF gene was contained within a
single haplotype block (Figure 1), as determined by the confidence interval algorithm
(Gabriel, Schaffner et al. 2002) implemented within Haploview 4.0 (Barrett, Fry et al.
2005). The C/T+2681 SNP located at the farthest 3’ UTR was the only SNP not included
with this block (Figure 1). Many of the polymorphisms were found to be in strong or
complete LD with one another (Figure 1), as is common within and between genes and
intergenic regions of the human MHC (Ceppellini, Siniscalco et al. 1955; Shiina, Ota et al.
2006). Five haplotypes were contained in this block, with frequencies ranging from
0.075 to 0.298 (Table 2). No similarities were detected upon comparing TNF LD
structures of vervet and human (www.hapmap.org).
Table 3 compares sequence identities for the 1176 bp TNF promoter region between
human and chimpanzee, St. Kitts-origin vervet, Hamadrayas baboon, and rhesus
macaque, which are 99.7%, 94.4%, 94.6%, and 94.5%, respectively. Identities for the
41
Table 1. Polymorphisms in the human ortholog St. Kitts-origin vervet TNF gene and
flanking sequence
*Polymorphism names denote nucleotide variants flanking gene position relative to
human transcription start site. Repeat polymorphisms denoted by repeated sequence
in parentheses and repeat number variants subscripted and separated by a slash (e.g.
(tgaa)4/5).
Polymorphism* MAF Minor allele
A-809G 0.309 G
A-756G 0.311 A
G-602T 0.210 G
C-352T 0.393 C
A-322G 0.312 A
C+426G 0.209 C
+611(tgaa) 4 / 5
0.078 (tgaa) 4
G+1285T 0.387 T
C+2133T 0.309 T
A+2362G 0.316 A
A+2405G 0.318 A
C+2681T 0.077 C
42
Figure 1.
Figure 1. LD structure of the St. Kitts-origin vervet TNF locus. The single haplotype block
(outlined triangle) was determined with the confidence interval algorithm (Gabriel et al.
2002) of HaploView. Numbers indicate pairwise r2 values X100. Darker blocks denote
higher correlation and black squares with no numbers represent complete LD (r2 = 1).
Relative positions of polymorphisms are indicated on diagram of the human ortholog St.
Kitts-origin vervet TNF gene and flanking sequence. Colored regions denote
promoter/enhancer region (green), untranslated regions (blue), exons (red blocks), and
introns (red lines).
5’
3’
43
Table 2. Haplotypes and frequencies of the human ortholog St. Kitts-origin vervet TNF
gene and flanking sequence
Haplotype Freq
G A T C A G (tgaa)5 T T A A 0.298
A G G T G G (tgaa)5 G C G G 0.208
A G T T G C (tgaa)5 G C G G 0.205
A G T T G G (tgaa)5 G C G G 0.183
A G T C G G (tgaa)4 T C G G 0.075
44
1000Macaca mulatta
98.51.891000Chlorocebus aethiops
94.07.5594.207.131000Pan troglodytes
94.07.5594.207.131000.001000Homo sapien
% IDtr
D.M.% IDtr
D.M.% IDtr
D.M.% IDtr
D.M.
Macaca mulattaChlorocebus aethiopsPan troglodytesHomo sapienA
1000Macaca mulatta
98.51.891000Chlorocebus aethiops
94.07.5594.207.131000Pan troglodytes
94.07.5594.207.131000.001000Homo sapien
% IDtr
D.M.% IDtr
D.M.% IDtr
D.M.% IDtr
D.M.
Macaca mulattaChlorocebus aethiopsPan troglodytesHomo sapienA
100
97.7
92.3
%IDpr
100
98.4
93.1
% IDtot
0
2.12
7.97
D.M.
Macaca mulatta
100
92.9
%IDpr
100
%IDpr
Macaca mulatta
1000Chlorocebus aethiops
93.37.711000Homo sapien
%IDtot
D.M.%IDtot
D.M.
Chlorocebus aethiopsHomo sapienB
100
97.7
92.3
%IDpr
100
98.4
93.1
% IDtot
0
2.12
7.97
D.M.
Macaca mulatta
100
92.9
%IDpr
100
%IDpr
Macaca mulatta
1000Chlorocebus aethiops
93.37.711000Homo sapien
%IDtot
D.M.%IDtot
D.M.
Chlorocebus aethiopsHomo sapienB
Table 3. Distance matrices (D.M.) and percentage of DNA sequence identity (% ID)
between humans, chimps, vervets, and rhesus (A), or between humans, vervets and
rhesus (B). Subscripts for % ID refer to cDNA transcript only (tr), total TNFA gene (tot),
or only the enhancer/promoter region (pr).
45
entire ~4 kb TNF gene including 5’ and 3’ flanking regions are >99%, 93.3%, and 93.1%,
respectively. The entire TNF sequence was not available for baboon at the time of this
writing.
Figure 2 illustrates a sequence comparison of the TNF promoter region in the five
primate species. The transcription binding sites NFAT, ETS, 3, CRE, and SP1,
confirmed to be essential for TNF gene regulation (Goldfeld, McCaffrey et al. 1993; Tsai,
Jain et al. 1996; Tsai, Yie et al. 1996; Falvo, Uglialoro et al. 2000; Tsai, Falvo et al. 2000;
Tsytsykova and Goldfeld 2002; Barthel, Tsytsykova et al. 2003)are noted, as well as 1
and 2, which bind NF- B proteins, but are not essential to TNF gene regulation
(Goldfeld, Doyle et al. 1990). There is complete conservation of those sites essential for
gene regulation among the species examined here. The vervet, rhesus, and baboon
contain an A instead of a G in 2 (position -206), but 1 is completely conserved in all
species examined. SNP locations for human, chimpanzee, rhesus, and the St. Kitts-origin
vervet relative to the human transcription start site are noted (Figure 2). All fall outside
major blocks of conserved regions known to be critical for TNF gene regulation (Figure
3A), In addition, there is non-random clustering of SNPs among the four species
examined at sites shown to contain alleles in humans significantly associated with risk
for a variety of inflammatory- or innate immunity-related diseases (Figure 3B) (i.e. -308,
-857, -863) (Fernandez-Real 2006).
The statistical significance of these SNP clusters was assessed with the Kolomogorov-
Smirnov test. The null hypothesis, that the distribution of SNPs in the 1176 nucleotide
46
Table 4. Results of Kolmogorov-Smirnov tests for non-uniform distribution.
sequence source D p
H. sapien 0.31 < 0.0001
P. troglodytes 0.47 < 0.0001
C. aethiops sabaeus 0.46 < 0.0001
M. mulatta 0.41 < 0.0001
Consensus 0.19 < 0.0001
47
Figure 2. Sequence comparison of TNF 5’ promoter region between humans (H sapien),
chimpanzee (P troglodytes), St. Kitts-origin vervet (C a sabaeus), rhesus monkey (M
mulatta), and baboon (P hamadrayas) with SNPs underlined and bolded with adjacent
nucleotide position for the species in which they have been reported. Nucleotide
positions are relative to the human TSS. The single letter code is used to identify SNPs :
M=A/C, R=A/G, W=A/T, S=C/G, Y=C/T, K=G/T. TF binding sites are underlined with
names above the sequence. NFAT (nuclear factor of activated T cells), Ets, 3, CRE
(cyclic AMP response element), and SP-1 are critical for TNF gene regulation (Goldfeld et
al. 1993; Tsai et al. 1996a; Tsai et al. 1996b; Falvo et al. 2000; Tsai et al. 2000;
Tsytsykova and Goldfeld 2002; Barthel et al. 2003); 1 and 2 are reported to bind NF-
B proteins and are not essential for gene regulation (Goldfeld et al. 1990; Leung et al.
2000).
48
Figure 2.
-1153 -1072 -1055
H sapien GGGAGCAAGAGCTGTGGGGAGAACAAAAGGATAA-GGGCTCAGAGAGCTTCAGGGATATGTGATGGACTCACCAGGTGAGGCYGCCAGACTGCTGCAGGG
P troglodytes ..................................-...............................................C.................
C a sabaeus ..................................A.....................C.........................C.................
M mulatta ..................................G.....................C.......A.......T.........C.................
P hamadrayas ..................................G........G............C.........................C.................
-1054 -1030 -955
H sapien GAAGCAAAGGAGAAGCTGAGAAGAYGAAGGAAAAGTCAGGGTCTGGAGGGGCGGGGGTCAGGGAGCTCCTGGGAGATATGGCCACATGTAGCGGCTCTGA
P troglodytes ........................AΔΔΔ........................................................................
C a sabaeus ........................CA...................A........................................A....T........
M mulatta ........................CA...................A........................................A....T........
P hamadrayas ...................T....CA...................A........................................A....T........
-954 -862 -856
H sapien GGAATGGGTTACAGGAGACCTCTGGGGAGATGTGACCACAGCAATGGGTAGGAGAATGTCCAGGGCTATGGAAGTCGAGTATGGGGACCCCCMCTTAAYG
P troglodytes ............................................................................................C.....C.
C a sabaeus ............................................A...........A..............GG..T................C.---GCC
M mulatta ............................................A..........................GG..T................C..--GCC
P hamadrayas ............................................AA.........................GG..T................CT---GCC
-854 -805 -781 -758
H sapien AAGACAGGGCCATGTAGAGGGCCCCAGGGAGTGAAAGAGCCTCCAGGACYTCCAGGTATGGAATACAGGGGACRTTTAAGAAGATATGGCCACACAMTGG
P troglodytes .................................................C....R..................G......................C...
C a sabaeus ........................T....................R...C..T....................G......................T.R.
M mulatta ........................T......Y.................C..T................K...G......................T...
P hamadrayas ........................T........................C..T....................G......................T...
-754 -655
H sapien GGCCCTGAGAAGTGAGAGCTTCATGAAAAAAATCAGGGACCCCAGAGTTCCTTGGAAGCCAAGACTGAAACCAGCATTATGAGTCTCCGGGTCAGAATGA
P troglodytes .......................................................................................T............
C a sabaeus ..................T...........................................................G......C..........G...
M mulatta ..................T...........................................................G......C..R.......G...
P hamadrayas ..................T...........................................................G......C..........G...
-654 -645 1 -571-569 -556
H sapien AAGAAGAAGRCCTGCCCCAGTGGGGTCTGTGAATTCCCGGGGGTGATTTCACTCCCC-GGGGCTGTCCCAGGCTTGTCCCTGCTMCMCCCACCCAGCCTT
P troglodytes .........G...............................................-..........................A.C.............
C a sabaeus .........G..............................T...........K....-..........................A.C.............
M mulatta .........G..........G...................T................G..........................A.C....T.M......
P hamadrayas .........G..............................T................-..........................A.C.............
-555 -510 -458
H sapien TCCTGAGGCCTCAAGCCTGCCACCAAGCCCCCAGCTCCTTCTCCCSGCAGGGACCCAAACACAGGCCTCAGGACTCAACACAGCTTTTC-CC-TCCAACC
P troglodytes .............................................C..................................Y........-..-.......
C a sabaeus C.........CTG........C.......................CCA...A.....................................T..C.......
M mulatta C.........CTG........C.......................CCA...A.....R.YG............................T..C.......
P hamadrayas C.........CTG........C.......................CCA...A........G..A.........................T..C.......
-457 -375 -358
H sapien CCGTTTTCTCTCCCTCAAGGACTCAGCTTTCTGAAGCCCCTCCCAGTTCTAGTTCTATCTTTTTCCTGCATCCTGTCTGGAARTTAGAAGGAAACAGACC
P troglodytes ..................................................................................G.................
C a sabaeus ..A........A...................................................................A..A.C...G...........
M mulatta ..A........AY.....................................................................A.C...G...........
P hamadrayas ..A........A......................................................................A.C...G...........
-357 -307 -258
H sapien ACAGACCTGGTCCCCAAAAGAAATGGAGGCAATAGGTTTTGAGGGGCATGRGGACGGGGTTCAGCCTCCAGGGTCCTACACACAAATCAGTCAGTGGCCC
P troglodytes ..........................R.......................G.................................................
C a sabaeus .....Y..........G..................RC...........G.A.C.....A....A.......A....C.......................
M mulatta ................G......Y............C...........G.A.......A....A.......A....C...............R.W.....
P hamadrayas ................G...................C...........G.A.......A....A.......A....C.......................
-257 -243 -237 2 -158
H sapien AGAAGACCCCCCTCRGAATCRGAGCAGGGAGGATGGGGAGTGTGAGGGGTATCCTTGATGCTTGTGTGTCCCCAACTTTCCAAATCCCCGCCCCCGCGAT
P troglodytes ..............G.....G...............................................................................
C a sabaeus ..............G.....G.........T.G.......A......A................G...................................
M mulatta ..............G.....G.........T.G.......A......A................G...................................
P hamadrayas ..............G.....G.........T.G.......A......A................G...................................
-157 NFAT/Ets CRE NFAT5/ 3 ETS NFAT/5 -58
H sapien GGAGAAGAAACCGAGACAGAAGGTGCAGGGCCCACTACCGCTTCCTCCAGATGAGCTCATGGGTTTCTCCACCAAGGAAGTTTTCCGCTGGTTGAATGAT
P troglodytes ....................................................................................................
C a sabaeus ...........A...G....................................................................................
M mulatta ...........A........................................................................................
P hamadrayas ...........A........................................................................................
-57 SP1 +1 +11 +24
H sapien TCTTTCCCCGCCCTCCTCTCGCCCCAGGGACATATAAAGGCAGTTGTTGGCACACCCAGCCAGCAGAYGCTCCCTCAGCAA
P troglodytes ................................................T..................C.............
C a sabaeus ..............---....................C..........T..................C.............
M mulatta ..A...........---....................C..........T..................C.............
P hamadrayas ..A...........---....................C..........T..................C.............
49
Figure 3. (A) Phylogenetic shadowing of the TNF promoter region in five primate
species. Multiple sequence alignment of TNF, including the promoter region, for
humans, chimpanzees, St. Kitts-origin vervet, rhesus monkey, and baboon was analyzed
with eShadow (Ovcharenko et al. 2004). Top x-axis is nucleotide position relative to
human TSS. The relative positions of polymorphisms in 4 of the 5 species studied here
are indicated along the bottom of the x-axis (H=human, C=chimpanzee, G=SK vervet,
R=rhesus monkey); no SNP information for the baboon was available. Percentage of
nucleotide variation (inverse of conservation) along a 50-nucleotide (nt) sliding window
is on the y-axis, and darker shading of peaks represents regions of higher conservation.
(B) Clustering of SNPs in NHPs. Plot of the number of SNPs in each of 4 primate species
(human, chimpanzee, vervet monkey, rhesus macaque) which cluster along a sliding 50-
nt window of the TNF promoter/enhancer region (Y-axis). SNPs in each of the 4 species
is designated by color (human=blue; chimp=red; vervet=green; rhesus=purple). X-axis is
nucleotide position relative to human TSS.
50
Figure 3.
A
B
51
sequence 5’ to the TSS does not differ from uniformity, was rejected (p < 0.0001) in each
species as well as the consensus sequence (Table 4).
Discussion
We report a total of five SNPs within the 5’ UTR, promoter/enhancer, and flanking
regions, with another six SNPs plus one insertion/deletion polymorphism in the intronic
and 3’ UTR and flanking regions of the human ortholog St. Kitts-origin vervet TNF gene
(Table 1, Figure 1). All polymorphisms except one (C/T+2681) form a single haplotype
block (Figure 1), which contains five haplotypes (Table 2) within the VRC population. To
our knowledge, this represents the most extensive report of SNPs, haplotypes, and LD
for any NHP of the TNF gene and flanking regions, as well as the first report of complete
TNF gene sequence data for the vervet monkey, or any other Chlorocebus species.
Old World nonhuman primates (NHP) are extremely valuable animal models for the
study of complex, polygenic diseases like obesity and its comorbidities (Comuzzie, Cole
et al. 2003; VandeBerg and Williams-Blangero 2003; Wagner, Kavanagh et al. 2006).
Particularly when pedigree and genomic structure is known, they offer great power to
dissect genetic from non-genetic components of disease through increased
homogeneity of conditions [e.g. (Freimer, Service et al. 2007; Vinson, Mahaney et al.
2008)], as well as enable study of disease progression throughout the lifetime of the
animal, thereby also controlling for age and some epigenetic effects [e.g. (de Vries,
Holmes et al. 2007)]. In addition, comparative sequence analyses utilizing NHPs are an
essential component of research directed at identifying functional regions within the
52
human genome (Villinger, Brar et al. 1995; Haudek, Natmessnig et al. 1998; Leung,
McKenzie et al. 2000; Boffelli, McAuliffe et al. 2003; Cooper and Sidow 2003) as well as
providing insight into the evolutionary history of transcriptional regulation (Goldfeld,
Leung et al. 2000; Shiina, Ota et al. 2006; Baena, Mootnick et al. 2007).
We have demonstrated that vervet TNF promoter SNPs are non-randomly and non-
uniformly distributed outside TF binding sites and other conserved regions. This is
consistent with differential rates of accumulation of mutations along the TNF promoter
region, also shown in previous published reports (Leung, McKenzie et al. 2000; Baena,
Leung et al. 2002; Higasa and Hayashi 2006; Baena, Mootnick et al. 2007). Those
regions not affecting TNF transcription will presumably be under neutral selection, while
there will be high selective pressure to preserve those regions that are essential to TF
binding. An unresolved question is whether SNPs around TF binding sites can modulate
transcription (or are in LD with other MHC alleles causing such effects), and if certain
alleles could impart greater survivability for an individual according to the specific
immunologic and/or metabolic challenges of that individual’s environment. The
concept that SNPs have accumulated independently in NHPs, and confer analogous
disease phenotypes and risk, has been proposed by others working with NHPs as models
of neuropsychiatric disorders (Lesch, Meyer et al. 1997; Bennett, Lesch et al. 2002;
Miller, Bendor et al. 2004; Bailey, Breidenthal et al. 2007). Here we provide the first
suggestion to our knowledge that SNPs in the promoter/enhancer region of TNF could
have accumulated in NHPs and humans experiencing similar selective pressures over
evolutionary time for modulating immune and/or inflammatory responses. The
53
demonstration that SNPs in humans, chimpanzees, vervets, and rhesus monkeys all
cluster together in two regions on the TNF promoter/enhancer region is particularly
interesting (Figure 3B). What makes this finding even more curious is that these regions
are within 50 nucleotides of three important human SNPs ( -308 and -857/-863) which
have been significantly associated with numerous obesity- and diabetes-related
phenotypes (Fernandez-Real 2006). It is possible that SNPs in these particular regions
modulate transcription in important but subtle ways and have thus accumulated in
these regions through convergent evolution in these 4 primate species (human,
chimpanzee, vervet, rhesus).
Research directed at further elucidating the genetic and molecular mechanisms of
obesity and disentangling the age- and environment-related factors through more
relevant animal models has been assigned as one of the highest priorities in the U.S.
(Eckel, Barouch et al. 2002). The information presented here represents the second
phase of our effort to further genetically characterize the St. Kitts-origin vervet as a
model of obesity and type 2 diabetes, both of which involve chronic, low-grade
inflammation and concurrent metabolic dysregulation mediated by TNF (Esteve, Ricart
et al. 2005; Hotamisligil 2006; Cawthorn and Sethi 2008). This adds to prior
characterization of obesity-related phenotypic measures, as well as demonstration of
these traits being heritable (Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones et al.
2007). The vervet monkey has long been one of the most important NHP models of
biomedical research, with a PubMed citation record over the past 10 years close to that
of rhesus macaque and greater than any other NHP (Freimer, Dewar et al. 2007).
54
However, gene sequence and genome information for the vervet has only recently
begun to emerge (Jasinska, Service et al. 2007). This report involves one of the largest
numbers of NHPs sequenced for TNF or any other individual candidate gene, which has
provided power to uncover both common and relatively rare SNPs/haplotypes, as well
as show that the distribution of these polymorphisms is consistent with the regions of
conservation or neutral selection shown in humans and other NHPs. Baena et al (2007)
demonstrated differential Sp1 TF binding and TNF transcription between certain species
of Asian apes and all other Old World apes and monkeys, based on nucleotide
differences within that TF binding site. However, no such intraspecies comparisons of
TNF TF binding in NHPs have been attempted to our knowledge. If significant genetic
associations exist between obesity-related phenotypes in the vervet and the SNPs and
/or haplotpyes presented here, then an important next step would be to evaluate those
variable nucleotide sequences for differential TF binding.
The broader value of these analyses addresses the intersection of metabolism and
innate immunity/inflammation, which are among the most fundamental requirements
for an organism’s survival. As such, these two processes show a high degree of
evolutionary conservation, are highly integrated, and are essentially one central
homeostatic mechanism (Hotamisligil 2006) , a greater understanding of which is
paramount given the current worldwide epidemic of obesity and its comorbidities
(Wyatt, Winters et al. 2006).
In summary, our report on sequence for the human ortholog St. Kitts-origin vervet TNF
gene, as well as polymorphisms and haplotype/LD structure, provides both proximate
55
and long-term value into research directed at further elucidating the pathogenic
mechanisms of obesity-related inflammation and metabolic dysregulation. Association
studies are currently underway using these SNP and haplotype data, as well as
previously defined obesity-related traits. Once any such associations have been
identified, this will allow targeted efforts towards understanding the functional
relevance of associated polymorphisms through TF binding assays, for example. This
approach, in a pedigreed NHP model, offers great potential to dissect genetic from
environmental components of polygenic, complex diseases such as obesity and its
comorbidities. In addition, the sequence data facilitates future comparative analyses,
and research into the evolution of regulatory gene sequences of complex disease.
Acknowledgements This work was funded, in part, by the Wake Forest University
School of Medicine Venture Fund, the Skorich Diabetes Research Fund, the Monty
Blackmon Diabetes Research Fund (JDW), T32 RR07009 from NIH/NCRR (SBG), and an
Animal and Biological Materials Resources grant from the National Center for Research
Resources (P40 RR 019963 to Dr. Lynn Fairbanks at UCLA). Support of this project from
the Center for Public Health Genomics (CDL) at WFUSM is greatly appreciated. The
authors would also like to thank Drs. Lynn Fairbanks (UCLA), Nelson Friemer (UCLA),
Matthew Jorgensen (WFUSM), Kylie Kavanagh (WFUSM), and Larry Rudel (WFUSM) for
their input and collaboration. This work constitutes partial fulfillment of Ph.D.
requirements for Dr. Gray.
56
References
1. Baena A, Leung JY, Sullivan AD, Landires I, Vasquez-Luna N, Quinones-Berrocal J, Fraser PA, Uko GP, Delgado JC, Clavijo OP, Thim S, Meshnick SR, Nyirenda T, Yunis EJ, Goldfeld AE. 2002. TNF-alpha promoter single nucleotide polymorphisms are markers of human ancestry. Genes Immun 3:482-487.
2. Baena A, Mootnick AR, Falvo JV, Tsytskova AV, Ligeiro F, Diop OM, Brieva C, Gagneux P, O'Brien SJ, Ryder OA, Goldfeld AE. 2007. Primate TNF promoters reveal markers of phylogeny and evolution of innate immunity. PLoS ONE 2:e621.
3. Bailey JN, Breidenthal SE, Jorgensen MJ, McCracken JT, Fairbanks LA. 2007. The association of DRD4 and novelty seeking is found in a nonhuman primate model. Psychiatr Genet 17:23-27.
4. Barrett JC, Fry B, Maller J, Daly MJ. 2005. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21:263-265.
5. Barthel R, Tsytsykova AV, Barczak AK, Tsai EY, Dascher CC, Brenner MB, Goldfeld AE. 2003. Regulation of tumor necrosis factor alpha gene expression by mycobacteria involves the assembly of a unique enhanceosome dependent on the coactivator proteins CBP/p300. Mol Cell Biol 23:526-533.
6. Bennett AJ, Lesch KP, Heils A, Long JC, Lorenz JG, Shoaf SE, Champoux M, Suomi SJ, Linnoila MV, Higley JD. 2002. Early experience and serotonin transporter gene variation interact to influence primate CNS function. Mol Psychiatry 7:118-122.
7. Bergman RN, Kim SP, Hsu IR, Catalano KJ, Chiu JD, Kabir M, Richey JM, Ader M. 2007. Abdominal obesity: role in the pathophysiology of metabolic disease and cardiovascular risk. Am J Med 120:S3-8; discussion S29-32.
8. Boffelli D, McAuliffe J, Ovcharenko D, Lewis KD, Ovcharenko I, Pachter L, Rubin EM. 2003. Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science 299:1391-1394.
9. Cawthorn WP, Sethi JK. 2008. TNF-alpha and adipocyte biology. FEBS Lett 582:117-131.
10. Ceppellini R, Siniscalco M, Smith CA. 1955. The estimation of gene frequencies in a random-mating population. Ann Hum Genet 20:97-115.
11. Comuzzie AG, Cole SA, Martin L, Carey KD, Mahaney MC, Blangero J, VandeBerg JL. 2003. The baboon as a nonhuman primate model for the study of the genetics of obesity. Obes Res 11:75-80.
12. Cooper GM, Sidow A. 2003. Genomic regulatory regions: insights from comparative sequence analysis. Curr Opin Genet Dev 13:604-610.
13. Coppack SW. 2001. Pro-inflammatory cytokines and adipose tissue. Proc Nutr Soc 60:349-356.
14. de Vries A, Holmes MC, Heijnis A, Seier JV, Heerden J, Louw J, Wolfe-Coote S, Meaney MJ, Levitt NS, Seckl JR. 2007. Prenatal dexamethasone exposure induces changes in nonhuman primate offspring cardiometabolic and hypothalamic-pituitary-adrenal axis function. J Clin Invest 117:1058-1067.
57
15. Eckel RH, Barouch WW, Ershow AG. 2002. Report of the National Heart, Lung, and Blood Institute-National Institute of Diabetes and Digestive and Kidney Diseases Working Group on the pathophysiology of obesity-associated cardiovascular disease. Circulation 105:2923-2928.
16. Esteve E, Ricart W, Fernandez-Real JM. 2005. Dyslipidemia and inflammation: an evolutionary conserved mechanism. Clin Nutr 24:16-31.
17. Fairbanks LA, Newman TK, Bailey JN, Jorgensen MJ, Breidenthal SE, Ophoff RA, Comuzzie AG, Martin LJ, Rogers J. 2004. Genetic contributions to social impulsivity and aggressiveness in vervet monkeys. Biol Psychiatry 55:642-647.
18. Falvo JV, Uglialoro AM, Brinkman BM, Merika M, Parekh BS, Tsai EY, King HC, Morielli AD, Peralta EG, Maniatis T, Thanos D, Goldfeld AE. 2000. Stimulus-specific assembly of enhancer complexes on the tumor necrosis factor alpha gene promoter. Mol Cell Biol 20:2239-2247.
19. Fernandez-Real JM. 2006. Genetic predispositions to low-grade inflammation and type 2 diabetes. Diabetes Technol Ther 8:55-66.
20. Freimer NB, Dewar K, Kaplan JR, Fairbanks LA. The Importance of the Vervet (African Green Monkey) as a Biomedical Model.
21. Freimer NB, Service SK, Ophoff RA, Jasinska AJ, McKee K, Villeneuve A, Belisle A, Bailey JN, Breidenthal SE, Jorgensen MJ, Mann JJ, Cantor RM, Dewar K, Fairbanks LA. 2007. A quantitative trait locus for variation in dopamine metabolism mapped in a primate model using reference sequences from related species. Proc Natl Acad Sci U S A 104:15811-15816.
22. Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, Higgins J, DeFelice M, Lochner A, Faggart M, Liu-Cordero SN, Rotimi C, Adeyemo A, Cooper R, Ward R, Lander ES, Daly MJ, Altshuler D. 2002. The structure of haplotype blocks in the human genome. Science 296:2225-2229.
23. Goldfeld AE, Doyle C, Maniatis T. 1990. Human tumor necrosis factor alpha gene regulation by virus and lipopolysaccharide. Proc Natl Acad Sci U S A 87:9769-9773.
24. Goldfeld AE, Leung JY, Sawyer SA, Hartl DL. 2000. Post-genomics and the neutral theory: variation and conservation in the tumor necrosis factor-alpha promoter. Gene 261:19-25.
25. Goldfeld AE, McCaffrey PG, Strominger JL, Rao A. 1993. Identification of a novel cyclosporin-sensitive element in the human tumor necrosis factor alpha gene promoter. J Exp Med 178:1365-1379.
26. Haudek SB, Natmessnig BE, Redl H, Schlag G, Giroir BP. 1998. Genetic sequences and transcriptional regulation of the TNFA promoter: comparison of human and baboon. Immunogenetics 48:202-207.
27. Higasa K, Hayashi K. 2006. Periodicity of SNP distribution around transcription start sites. BMC Genomics 7:66.
28. Hill JO, Wyatt HR, Reed GW, Peters JC. 2003. Obesity and the environment: where do we go from here? Science 299:853-855.
29. Hotamisligil GS. 2006. Inflammation and metabolic disorders. Nature 444:860-867.
58
30. Hotamisligil GS, Shargill NS, Spiegelman BM. 1993. Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance. Science 259:87-91.
31. Jasinska AJ, Service S, Levinson M, Slaten E, Lee O, Sobel E, Fairbanks LA, Bailey JN, Jorgensen MJ, Breidenthal SE, Dewar K, Hudson TJ, Palmour R, Freimer NB, Ophoff RA. 2007. A genetic linkage map of the vervet monkey (Chlorocebus aethiops sabaeus). Mamm Genome 18:347-360.
32. Juge-Aubry CE, Henrichot E, Meier CA. 2005. Adipose tissue: a regulator of inflammation. Best Pract Res Clin Endocrinol Metab 19:547-566.
33. Kavanagh K, Fairbanks LA, Bailey JN, Jorgensen MJ, Wilson M, Zhang L, Rudel LL, Wagner JD. 2007. Characterization and heritability of obesity and associated risk factors in vervet monkeys. Obesity (Silver Spring) 15:1666-1674.
34. Kavanagh K, Jones KL, Sawyer J, Kelley K, Carr JJ, Wagner JD, Rudel LL. 2007. Trans fat diet induces abdominal obesity and changes in insulin sensitivity in monkeys. Obesity (Silver Spring) 15:1675-1684.
35. Knight JC, Udalova I, Hill AV, Greenwood BM, Peshu N, Marsh K, Kwiatkowski D. 1999. A polymorphism that affects OCT-1 binding to the TNF promoter region is associated with severe malaria. Nat Genet 22:145-150.
36. Kroeger KM, Carville KS, Abraham LJ. 1997. The -308 tumor necrosis factor-alpha promoter polymorphism effects transcription. Mol Immunol 34:391-399.
37. Lesch KP, Meyer J, Glatz K, Flugge G, Hinney A, Hebebrand J, Klauck SM, Poustka A, Poustka F, Bengel D, Mossner R, Riederer P, Heils A. 1997. The 5-HT transporter gene-linked polymorphic region (5-HTTLPR) in evolutionary perspective: alternative biallelic variation in rhesus monkeys. Rapid communication. J Neural Transm 104:1259-1266.
38. Leung JY, McKenzie FE, Uglialoro AM, Flores-Villanueva PO, Sorkin BC, Yunis EJ, Hartl DL, Goldfeld AE. 2000. Identification of phylogenetic footprints in primate tumor necrosis factor-alpha promoters. Proc Natl Acad Sci U S A 97:6614-6618.
39. Miller GM, Bendor J, Tiefenbacher S, Yang H, Novak MA, Madras BK. 2004. A mu-opioid receptor single nucleotide polymorphism in rhesus monkey: association with stress response and aggression. Mol Psychiatry 9:99-108.
40. Montgomery SB, Griffith OL, Sleumer MC, Bergman CM, Bilenky M, Pleasance ED, Prychyna Y, Zhang X, Jones SJ. 2006. ORegAnno: an open access database and curation system for literature-derived promoters, transcription factor binding sites and regulatory variation. Bioinformatics 22:637-640.
41. Mutch DM, Clement K. 2006. Unraveling the genetics of human obesity. PLoS Genet 2:e188.
42. Ovcharenko I, Boffelli D, Loots GG. 2004. eShadow: a tool for comparing closely related sequences. Genome Res 14:1191-1198.
43. Pasquali R, Vicennati V, Cacciari M, Pagotto U. 2006. The hypothalamic-pituitary-adrenal axis activity in obesity and the metabolic syndrome. Ann N Y Acad Sci 1083:111-128.
59
44. Roseboom TJ, van der Meulen JH, Ravelli AC, Osmond C, Barker DJ, Bleker OP. 2001. Effects of prenatal exposure to the Dutch famine on adult disease in later life: an overview. Mol Cell Endocrinol 185:93-98.
45. Salpeter SR, Walsh JM, Ormiston TM, Greyber E, Buckley NS, Salpeter EE. 2006. Meta-analysis: effect of hormone-replacement therapy on components of the metabolic syndrome in postmenopausal women. Diabetes Obes Metab 8:538-554.
46. Schneider JG, Tompkins C, Blumenthal RS, Mora S. 2006. The metabolic syndrome in women. Cardiol Rev 14:286-291.
47. Shiina T, Ota M, Shimizu S, Katsuyama Y, Hashimoto N, Takasu M, Anzai T, Kulski JK, Kikkawa E, Naruse T, Kimura N, Yanagiya K, Watanabe A, Hosomichi K, Kohara S, Iwamoto C, Umehara Y, Meyer A, Wanner V, Sano K, Macquin C, Ikeo K, Tokunaga K, Gojobori T, Inoko H, Bahram S. 2006. Rapid evolution of major histocompatibility complex class I genes in primates generates new disease alleles in humans via hitchhiking diversity. Genetics 173:1555-1570.
48. Shively CA, Clarkson TB. 1988. Regional obesity and coronary artery atherosclerosis in females: a non-human primate model. Acta Med Scand Suppl 723:71-78.
49. Singh KK, Schmidtke J. 2005. Single nucleotide polymorphisms within the promoter region of the rhesus monkey tumor necrosis factor-alpha gene. Immunogenetics 57:289-292.
50. Skoog T, Eriksson P, Hoffstedt J, Ryden M, Hamsten A, Armer P. 2001. Tumour necrosis factor-alpha (TNF-alpha) polymorphisms-857C/A and -863C/A are associated with TNF-alpha secretion from human adipose tissue. Diabetologia 44:654-655.
51. Taylor PD, Poston L. 2007. Developmental programming of obesity in mammals. Exp Physiol 92:287-298.
52. Thompson JD, Higgins DG, Gibson TJ. 1994. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673-4680.
53. Trayhurn P, Wood IS. 2004. Adipokines: inflammation and the pleiotropic role of white adipose tissue. Br J Nutr 92:347-355.
54. Tsai EY, Falvo JV, Tsytsykova AV, Barczak AK, Reimold AM, Glimcher LH, Fenton MJ, Gordon DC, Dunn IF, Goldfeld AE. 2000. A lipopolysaccharide-specific enhancer complex involving Ets, Elk-1, Sp1, and CREB binding protein and p300 is recruited to the tumor necrosis factor alpha promoter in vivo. Mol Cell Biol 20:6084-6094.
55. Tsai EY, Jain J, Pesavento PA, Rao A, Goldfeld AE. 1996. Tumor necrosis factor alpha gene regulation in activated T cells involves ATF-2/Jun and NFATp. Mol Cell Biol 16:459-467.
56. Tsai EY, Yie J, Thanos D, Goldfeld AE. 1996. Cell-type-specific regulation of the human tumor necrosis factor alpha gene in B cells and T cells by NFATp and ATF-2/JUN. Mol Cell Biol 16:5232-5244.
60
57. Tsytsykova AV, Goldfeld AE. 2002. Inducer-specific enhanceosome formation controls tumor necrosis factor alpha gene expression in T lymphocytes. Mol Cell Biol 22:2620-2631.
58. Udalova IA, Richardson A, Denys A, Smith C, Ackerman H, Foxwell B, Kwiatkowski D. 2000. Functional consequences of a polymorphism affecting NF-kappaB p50-p50 binding to the TNF promoter region. Mol Cell Biol 20:9113-9119.
59. VandeBerg JL, Williams-Blangero S. 2003. International perspectives : the future of nonhuman primate resources : proceedings of the workshop held April 17-19, 2002. Washington, D.C.: National Academies Press.
60. Villinger F, Brar SS, Mayne A, Chikkala N, Ansari AA. 1995. Comparative sequence analysis of cytokine genes from human and nonhuman primates. J Immunol 155:3946-3954.
61. Vinson A, Mahaney MC, Cox LA, Rogers J, VandeBerg JL, Rainwater DL. 2008. A pleiotropic QTL on 2p influences serum Lp-PLA2 activity and LDL cholesterol concentration in a baboon model for the genetics of atherosclerosis risk factors. Atherosclerosis 196:667-673.
62. Wagner JD, Bagdade JD, Litwak KN, Zhang L, Bell-Farrow AD, Wang ZQ, Cefalu WT. 1996. Increased glycation of plasma lipoproteins in diabetic cynomolgus monkeys. Lab Anim Sci 46:31-35.
63. Wagner JD, Carlson CS, O'Brien TD, Anthony MS, Bullock BC, Cefalu WT. 1996. Diabetes mellitus and islet amyloidosis in cynomolgus monkeys. Lab Anim Sci 46:36-41.
64. Wagner JD, Cline JM, Shadoan MK, Bullock BC, Rankin SE, Cefalu WT. 2001. Naturally occurring and experimental diabetes in cynomolgus monkeys: a comparison of carbohydrate and lipid metabolism and islet pathology. Toxicol Pathol 29:142-148.
65. Wagner JE, Kavanagh K, Ward GM, Auerbach BJ, Harwood HJ, Jr., Kaplan JR. 2006. Old world nonhuman primate models of type 2 diabetes mellitus. ILAR J 47:259-271.
66. West DB, York B. 1998. Dietary fat, genetic predisposition, and obesity: lessons from animal models. Am J Clin Nutr 67:505S-512S.
67. Wilson AG, Symons JA, McDowell TL, McDevitt HO, Duff GW. 1997. Effects of a polymorphism in the human tumor necrosis factor alpha promoter on transcriptional activation. Proc Natl Acad Sci U S A 94:3195-3199.
68. Wyatt SB, Winters KP, Dubbert PM. 2006. Overweight and obesity: prevalence, consequences, and causes of a growing public health problem. Am J Med Sci 331:166-174.
61
CHAPTER III
PHYLOGENETIC AND TAXONOMIC IMPLICATIONS OF TNF PROMOTER SEQUENCE COMPARISONS BETWEEN ST. KITTS- AND AFRICAN-ORIGIN CHLOROCEBUS SUBSPECIES Stanton B Gray, Richard E Broughton, Carl D Langefeld, , James N Thompson jr, Gregory
A Hawkins, Abdoulaye F Diallo, Janice D Wagner, Timothy D Howard
The following manuscript will be submitted for publication to the American Journal of
Primatology. Stylistic variations are due to the requirements of the journal. Dr. S.B.
Gray prepared the manuscript and was primarily responsible for performing and
directing the experiments, as well as data analysis and interpretation. Technical
assistance was provided by Mr. A.F. Diallo and Dr. R.E. Broughton. Analytical assistance
was provided by Dr. R.E. Broughton. Drs. T.D. Howard and J.D. Wagner acted in an
advisory capacity. All co-authors provided editorial input.
62
Introduction
The vervet monkey (also called the green monkey) is an Old World Monkey (OWM)
model for a variety of complex human diseases and behaviors such as diabetes,
cardiovascular disease, AIDS, substance abuse, attention deficit disorder, alcoholism,
reproduction, and tissue regeneration. European ships brought small numbers of
African vervets to the Caribbean islands of Barbados, St. Kitts, and Nevis as early as the
16th century and continued through the 18th century (McGuire 1974; Denham 1987).
Since then, vervet population numbers on these islands have increased quickly and
sustainably, with vervets now considered a pest species in some areas. Subsequently,
vervets from the Caribbean islands, and St. Kitts (SK) in particular, have become the
main source of vervet monkeys used in biomedical research.
Characteristics of the SK vervet which contribute to its being a biomedical model of
increasing importance are: 1) abundance; 2) free from the zoonotic Cercopithecene
Herpes Virus-1 (Herpes B; 3) relatively small and temperamentally tractable compared
to macaques; 4) no evidence of other confounding pathogens such as filovirus, SIV,
STLV, yellow fever, malaria, or schistomiasis; 5) evolutionarily as close, or closer, to
humans as the baboon and macaque species and; 6) relatively easily bred in captivity
(National Research Council (U.S.) and Institute for Laboratory Animal Research (U.S.)
2003). Further, the first draft of a linkage map for the vervet has recently been
completed (Jasinska, Service et al. 2007), which will enable genetic mapping of complex
63
traits, and it is as an approved target OWM species for genome sequencing
(www.genome.gov).
The current taxonomic classification of the SK vervet is Chlorocebus aethiops sabaeus,
which is based on sequence comparisons of a 389 nucleotide fragment of the
mitochondrial 12S rRNA gene between SK vervet (isolated from the feces of a single
monkey) and four other African Chlorocebus subspecies: C. a. aethiops, C. a.
pygerythrus, C. a. sabaeus and, C. a. tantalus (van der Kuyl and Dekker 1996) (Figure 1).
However, this taxonomic classification has long been regarded as tentative (Denham
1987; Wang 2006) stemming from: 1) historical evidence indicating that the most likely
sources of SK vervets along the west coast of Africa contained other subspecies in
addition to sabaeus (Handler, Lange et al. 1978; Denham 1987; Wang 2006) (Figure 1)
and, 2) the documentation of all four of the Chlorocebus subspecies producing viable
hybrid offspring along the edges of their geographic ranges (Groves 2001). More
recently, in his doctoral dissertation, Wang (2006) repeated the comparison made by
van der Kuyl and Dekker (1996), but used multiple vervets of SK-origin instead of a
single monkey and found that a purportedly fixed nucleotide difference is actually a
single nucleotide polymorphism (SNP). While not conclusive, this finding diminishes the
strength of van der Kuyl and Dekker’s data that originally led them to suggest that SK
vervets are solely descendants from Chlorocebus aethiops sabaeus.
64
C. a. sabaeus C. a. tantalus
C. a.aethiops
C. a. pygerythrus
Figure 1. Map of Africa showing approximate ranges for Chlorocebus subspecies. Adapted from van der Kuyl and Dekker (1996).
65
As part of our ongoing initiative to further characterize the vervet monkey as a model of
obesity and its comorbidities (Kavanagh et al. 2007a; Kavanagh et al. 2007b), we
sequenced and genotyped the tumor necrosis factor (TNF) promoter region in 265
monkeys of SK-origin from the pedigreed Vervet Research Colony (VRC) at the Wake
Forest University Primate Center (WFUPC) in Winston-Salem, NC. Previous comparative
analyses have shown that fixed nucleotide differences and polymorphisms in the TNF
promoter region have great value as markers of primate phylogeny and speciation
(Goldfeld, Leung et al. 2000; Baena, Leung et al. 2002; Baena, Mootnick et al. 2007). We
have used this region to perform phylogenetic analyses on the SK-origin vervet, the
African-origin vervet, and three other Chlorocebus subspecies of African origin. Here we
report the implications these analyses have for the uncertain taxonomic and
phylogenetic classification of the SK vervet.
Methods
Animals. Two hundred and sixty five vervets from the VRC were used in this study. The
VRC was founded in 1975 at UCLA from 57 vervets (28 males, 29 females) wild caught
from 1975-1983 in St. Kitts, West Indies, as described in Fairbanks et al (2004). There
have been no introductions or outbreeding since that time, and matings have been
carefully controlled to avoid inbreeding. The current population includes approximately
450 descendants with 24 of the original matrilines now in their 5th-8th generation, and
now resides at the Wake Forest University Primate Center (WFUPC).
66
Animal tissues. DNA was isolated from stored frozen aorta from four different
individual Chlorocebus aethiops pygerythrus monkeys and four different individual C. a.
aethiops monkeys. All of these monkeys were of African origin. DNA from SK vervets
was isolated from peripheral blood.
PCR and Sequencing. Genomic DNA was isolated from peripheral blood samples or
frozen aorta using standard protocols previously described (Jasinska, Service et al.
2007). For sequencing, PCR primers were generated with the PrimerSelect software
(Laser Gene software, DNASTAR, Madison, WI.) using a consensus TNF gene sequence
created from human, chimpanzee (Pan troglodytes) and rhesus monkey (Macaca
mulatta) found in the NCBI gene database (www.ncbi.nlm.nih.gov; uc003nui.1,
NM_001045511, NM_001047149 respectively). Sequences were obtained in both the
forward and reverese directions from -1152 to +24 with the ABI3730XL DNA Analyzer
using the POP7 sequencing polymer. The sequences of the primers used are described
in Supplementary Table 1.
Sequence Analyses. Sequences from the 265 VRC vervets were aligned and genotyped
using Sequencher v4.7 (Gene Codes Corp., Ann Arbor, MI). Sequence alignment scores
were generated using ClustalW, version 1.7 (Thompson, Higgins et al. 1994). This vervet
sequence (EU626004), human, chimpanzee, and rhesus macaque reported herein are in
the NCBI gene database (accession numbers noted above); baboon (Haudek,
Natmessnig et al. 1998; Leung, McKenzie et al. 2000; Baena, Mootnick et al. 2007) and
African Chlorocebus subspecies (Baena, Mootnick et al. 2007) TNF promoter sequences
have been reported elsewhere. Phylogenetic analyses employed maximum parsimony
67
using PAUP (version 4.10b) (Swofford 2002). One hundred heuristic searches were
performed with tree bisection-reconnection (TBR) branch swapping and all characters
weighted equally. The human sequence was designated as the outgroup. SNPs were
converted to the allele with dominant population frequency for purposes of
phylogenetic analysis. Phylogenetic trees were formatted for publication using MrEnt
(version 2.0) (Zuccon and Zuccon 2008).
Results
Multiple sequence alignment illustrates that the SK-origin vervet shares two SNPs with
C. a. tantalus, and one with the remaining three subspecies (Figure 2). The number of
presumed fixed nucleotide differences is shown in Table 1. Of particular relevance is the
observation that there are nine presumed fixed differences between the SK vervet and
the African subspecies of the same taxonomic classification (C. a. sabaeus), compared to
seven between the SK vervet and C. a. tantalus, and only one between the SK vervet
and both C. a. aethiops and C. a. pygerythrus.
Phylogenetic relationships between the SK-origin vervet and the three African-origin
Chlorocebus spp are illustrated in Figure 3. African C. a. sabaeus and C. a. tantalus form
one clade, while C. a. pygerythrus and the SK-origin vervet form another clade. C. a
aethiops forms the third clade within the Chlorocebus subspecies examined. There are
68
Table 1. Presumed fixed nucleotide differences between Chlorocebus subspecies.
AFR C a sabaeus
C a aethiops
C a pygerythrus
C a tantalus
SK C a sabaeus 9 1 1 7 AFR C a sabaeus 8 9 11 C a aethiops 2 6 C a pygerythrus 8
69
Figure 2. Multiple sequence comparison of the TNF promoter region. Nucleotides are
numbered from -1152 to +24 relative to human transcription start site. Periods (.)
denote identical nucleotide to the human reference sequence. SNP codes are: R = A/G;
Y = C/T; M = A/C; W = A/T; S = C/G; K = G/T. SK denotes St. Kitts-origin. AFR denotes
African-origin.
70
-1153 Homo sapien GGGAGCAAGAGCTGTGGGGAGAACAAAAGGATAA-GGGCTCAGAGAGCTTCAGGGATATGTGATGGACTCACCAGGTGAGGCCGCCAGACTGCTGCAGGG
C sabaeus SK ..................................A.....................C...........................................
C sabaeus AFR ..............................G...A.....................C...........................................
C aethiops ..................................A.....................C...........................................
C pygerythrus ..................................A.....................C...........................................
C tantalus ..................................A.....................C...........................................
Homo sapien GAAGCAAAGGAGAAGCTGAGAAGATGAAGGAAAAGTCAGGGTCTGGAGGGGCGGGGGTCAGGGAGCTCCTGGGAGATATGGCCACATGTAGCGGCTCTGA
C sabaeus SK ........................CA...................A........................................A....T........
C sabaeus AFR ........................CA........A..........A........................................A....T........
C aethiops ........................CA...................A........................................A....T........
C pygerythrus ........................CA...................A........................................A....T........
C tantalus ........................CA...................A........................................A....T........
Homo sapien GGAATGGGTTACAGGAGACCTCTGGGGAGATGTGACCACAGCAATGGGTAGGAGAATGTCCAGGGCTATGGAAGTCGAGTATGGGGACCCCCCCTTAACG
C sabaeus SK ............................................A...........A..............GG..T..................---G.C
C sabaeus AFR ................C...........................A...........A..............GG..T..................---G.C
C aethiops ...................................M........A...........A..............GG..T..................---G.C
C pygerythrus ............................................A...........A..........W...GG..T.................Y---G.C
C tantalus ............................................A...........A..............GG..Y..................---G.C
Homo sapien AAGACAGGGCCATGTAGAGGGCCCCAGGGAGTGAAAGAGCCTCCAGGACCTCCAGGTATGGAATACAGGGGACGTTTAAGAAGATATGGCCACACACTGG
C sabaeus SK ........................T....................R......T...........................................T.R.
C sabaeus AFR ........................T....................A......T....................C......................T...
C aethiops ........................T....................M......T...........................................T.R.
C pygerythrus ........................T....................A......T....................A......................T...
C tantalus R.......................T....................A......T...........................................T.R.
Homo sapien GGCCCTGAGAAGTGAGAGCTTCATGAAAAAAATCAGGGACCCCAGAGTTCCTTGGAAGCCAAGACTGAAACCAGCATTATGAGTCTCCGGGTCAGAATGA
C sabaeus SK ..................T...........................................................G......C..........G...
C sabaeus AFR ..................T.........................C.................................G......C..C.......G...
C aethiops ..................T...........................................................G......C..........G...
C pygerythrus ..................T...........................................................G......C..........G...
C tantalus ..................T.........................A.................................G......C..C.....A.G...
Homo sapien AAGAAGAAGGCCTGCCCCAGTGGGGTCTGTGAATTCCCGGGGGTGATTTCACTCCCCGGGGCTGTCCCAGGCTTGTCCCTGCTACCCCCACCCAGCCTTT
C sabaeus SK ........................................T...........K..............................................C
C sabaeus AFR ........................................K..........................................................C
C aethiops ........................................T..........................................................C
C pygerythrus ........................................T..........................................................C
C tantalus ..A..A.G................................T..........................................................C
Homo sapien CCTGAGGCCTCAAGCCTGCCACCAAGCCCCCAGCTCCTTCTCCCCGCAGGGA-CCCAAACACAGGCCTCAGGACTCAACACAGCTTTTC--CCTCCAACC
C sabaeus SK .........CTG........C........................-..A...A....................................TC.........
C sabaeus AFR .........CTG........C........................-..A...A....................................TC.........
C aethiops .........CTG........C........................-..A...A....................................TC.........
C pygerythrus .........CTG........C........................-..A...A.............................R......TC.........
C tantalus .........CTG........C........................-..A...A....................................TC.........
Homo sapien CCGTTTTCTCTCCCTCAAGGACTCAGCTTTCTGAAGCCCCTCCCAGTTCTAGTTCTATCTTTTTCCTGCATCCTGTCTGGAAGTTAGAAGGAAACAGACC
C sabaeus SK ..A........A...................................................................A..A.C...G...........
C sabaeus AFR ..A........A...................................................................A..A.C...G...........
C aethiops ..A........R...................................................................A..A.C...G...........
C pygerythrus ..A........A...................................................................A..A.C...G...........
C tantalus ..A........A...................................................................A..A.C...G...........
Homo sapien ACAGACCTGGTCCCCAAAAGAAATGGAGGCAATAGGTTTTGAGGGGCATGAGGACGGGGTTCAGCCTCCAGGGTCCTACACACAAATCAGTCAGTGGCCC
C sabaeus SK .....Y..........G..................RC...........G...C.....A....A.......A....C.......................
C sabaeus AFR ................G..................RC...........G...C.....A....A.......A....CG......................
C aethiops ................G...................C...........G...C.Y...A....A.......A....C.......................
C pygerythrus .....Y..........G...........K.......C...........G...C.....A....A.......A....C.......................
C tantalus .....Y..........G...................C...........G...C.....A....A.......A....C.......................
Homo sapien AGAAGACCCCCCTCGGAATCGGAGCAGGGAGGATGGGGAGTGTGAGGGGTATCCTTGATGCTTGTGTGTCCCCAACTTTCCAAATCCCCGCCCCCGCGAT
C sabaeus SK ..............................T.G.......A......A................G...................................
C sabaeus AFR ..........T...................T.G.......A......A................G...................................
C aethiops ..............................T.G.......A......A................G...................................
C pygerythrus ..............................T.G.......A......A................G...................................
C tantalus ..............................T.G.......A......A................G...................................
Homo sapien GGAGAAGAAACCGAGACAGAAGGTGCAGGGCCCACTACCGCTTCCTCCAGATGAGCTCATGGGTTTCTCCACCAAGGAAGTTTTCCGCTGGTTGAATGAT
C sabaeus SK ............A...G...................................................................................
C sabaeus AFR ............A...G...................................................................................
C aethiops ............A...G...................................................................................
C pygerythrus ............A...G...................................................................................
C tantalus ............A...G...................................................................................
+24
Homo sapien TCTTTCCCCGCCCTCCTCTCGCCCCAGGGACATATAAAGGCAGTTGTTGGCACACCCAGCCAGCAGACGCTCCCTCAGCAA
C sabaeus SK ..........--.-........................C.........T................................
C sabaeus AFR ..........--.-........................C.........T................................
C aethiops ..........--.-........................C.........T................................
C pygerythrus ..........--.-........................C.........T................................
C tantalus ..........--.-........................C.........T................................
Figure 2. Multiple sequence comparison of the TNF promoter region.
71
Pan
tro
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dyte
s
C. aeth
iop
s s
ab
aeu
s (
St.
Kit
ts o
rig
in)
C. aeth
iop
s p
yg
ery
thru
s
C. aeth
iop
s s
ab
aeu
s (
Afr
ican
ori
gin
)
C. aeth
iop
s t
an
talu
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C. aeth
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eth
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Macaca m
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Pap
io h
am
ad
rayas
Ho
mo
sap
ien
©MrEnt
Figure 3. TNF promoter-based phylogentic trees.
72
insufficient numbers of informative nucleotide differences to resolve the relationships
between the African sabaeus-tantalus clade, the St. Kitts sabaeus-African pygerythrus
clade, and the African aethiops clade. However, the placement of African C. a. sabaeus
with C. a. tantalus instead of the SK-origin vervet in one clade is striking, and counter to
expectation given the identical taxonomic classification.
Discussion
The vervet monkey has been one of the most important non-human primate (NHP)
models for biomedical research, with a PubMed citation record over the past 10 years
close to that of rhesus macaque and much greater than any other NHP
(www.genome.gov). The utility as a replacement to the rhesus macaque is being
increasingly recognized and is a major contributor to the dramatic recent increases in
the use of vervets.
The extensive use of rhesus macaques in biomedical research has highlighted very
important differences related to disease phenotypes between Chinese- and Indian-
origin populations of rhesus monkeys (Macaca fascicularis). These differences relate to
immunological phenotypes of the T-cells in response to infection with
immunodeficiency virus, which can severely confound research data if such regions of
origin are not considered. Simple genetic screening tests now exist to differentiate
73
between Chinese- and Indian-origin rhesus (Smith and McDonough 2005). Similarly,
there is evidence that significant differences exist in disease phenotypes between SK-
origin and African-origin vervets. Examples are serum lipid profiles and propensity for
atherosclerotic lesions in response to a high fat diet (Rudel, Reynolds et al. 1981). Thus,
as it pertains to potential impact on research outcomes, investigation into phylogenetic
relationships within and between Chlorocebus subspecies has relevant biomedical
importance.
The sequence comparisons reported here indicate that there is an urgent need for more
extensive phylogenetic analyses of the SK, SK-origin, African, and African-origin vervets,
particularly those used in biomedical research. We have shown that African
Chlorocebus aethiops sabaeus is more closely related to Chlorocebus aethiops tantalus
than it is to St. Kitts Chlorocebus aethiops sabaeus, which is most closely related to
Chlorocebus aethiops pygerythrus. These results provide strong evidence that the
current taxonomic classification of the Chlorocebus subspecies needs to be revised.
In summary, prior to this report there have been multiple lines of evidence to question
the current taxonomy, which calls the vervets of St. Kitts and the vervets of Africa
identical subspecies: 1) the orginal European ships carrying the vervet monkeys from
Africa ported in various locations within different subspecies’ ranges (Figure 1), 2) the
74
ability and propensity for subspecies to viably hybridize and, 3) the molecular data from
Wang (2006). Our phylogenetic analyses strongly suggest that the SK vervet and the
African vervet are not the same subspecies, but do not provide sufficient resolution of
nucleotide differences to assign a new taxonomic classification to the SK vervet. Only
one fixed nucleotide difference was seen between the SK vervet and both C. a.
pygerythrus and C. a. aethiops, while the latter two subspecies only had two (Table 1).
Thus, there is only minimal resolution for separating the SK sabaeus-African pygerythrus
clade from the aethiops clade. However, we report the strongest data thus far
challenging the validity of the current taxonomic classification. We suggest that the
data reported herein, together with the aforementioned lines of evidence, provides
ample evidence to question whether or not the sabaeus subspecies designation for the
St. Kitts vervet should continue to be used. Our sequence data shows the SK vervet
sharing one or two SNPs with each of the African subspecies examined, and that it is
most closely related to C. a. pygerythrus, with C. a. aethiops being a close second.
Potential limitations of this study include the fact that the VRC was founded from 57
wild-caught SK vervets. However, we have compared the entire orthologous TNF gene
plus 5’ and 3’ flanking regions in 24 presumably unrelated vervets taken directly from SK
to those of the VRC and found complete sequence identity; in addition, SK-origin VRC
vervets shared all SNPs found in vervets taken directly from the island of SK
(unpublished data). This suggests that the VRC experienced no significant loss of genetic
75
variability subsequent to the founding event. Another factor to be considered is that
the analyses reported herein rely on sequence data for African-origin C. a. sabaeus (n=4)
and C. a. tantalus (n=6) from a report by Baena et al. (2007), although there is no
perceived reason to believe this is a significant limitation to this study. It is also possible
that TNF could be subject to selective pressures given its role in metabolism and innate
immunity. Future phylogenetic analyses to further address the questions posed here
should likely include nucleotide sequence that is under neutral selective pressure, which
should allow greater amounts of genetic variation to accumulate over time and thus
presumably provide greater resolution of phylogenetic differences.
It is important to note that, regardless of any eventual revisions to the taxonomy of the
SK vervet, or whether further gene sequence or genome-wide SNP data support the
phylogenetic relationships reported here, the SK vervet appears to be a distinct
subspecies with distinct and reproducible phenotypes. These phenotypes, both normal
and associated with modeled disease states, have been observed to be markedly
different from vervet monkeys of African origin. Thus, we believe that further genetic
and phenotypic characterization of Chlorocebus monkeys used in biomedical research is
urgently needed, and that reporting the origin of all Chlorocebus monkeys in scientific
publications will greatly facilitate that process.
76
Acknowledgements: This work was funded, in part, by the Wake Forest University
School of Medicine Venture Fund, the Skorich Diabetes Research Fund, the Monty
Blackmon Diabetes Research Fund (JDW), T32 RR07009 from NIH/NCRR (SBG), an
Animal and Biological Materials Resources grant from the National Center for Research
Resources (P40 RR 019963 to Dr. Lynn Fairbanks at UCLA), and the Center for Public
Health Genomics (CDL). The authors would also like to thank Drs. Lynn Fairbanks
(UCLA), Nelson Friemer (UCLA), Matthew Jorgensen (WFUSM), Kylie Kavanagh
(WFUSM), and Larry Rudel (WFUSM) for their input and collaboration. This work
constitutes partial fulfillment of Ph.D. requirements for Dr. Gray.
77
References
Baena A, Leung JY, Sullivan AD, Landires I, Vasquez-Luna N, Quinones-Berrocal J, Fraser PA, Uko GP, Delgado JC, Clavijo OP et al. 2002. TNF-alpha promoter single nucleotide polymorphisms are markers of human ancestry. Genes Immun 3(8):482-7.
Baena A, Mootnick AR, Falvo JV, Tsytskova AV, Ligeiro F, Diop OM, Brieva C, Gagneux P, O'Brien SJ, Ryder OA et al. 2007. Primate TNF promoters reveal markers of phylogeny and evolution of innate immunity. PLoS ONE 2(7):e621.
Denham WW. 1987. West Indian green monkeys : problems in historical biogeography. Basel ; New York: Karger. 78 p. p.
Fairbanks LA, Newman TK, Bailey JN, Jorgensen MJ, Breidenthal SE, Ophoff RA, Comuzzie AG, Martin LJ, Rogers J. 2004. Genetic contributions to social impulsivity and aggressiveness in vervet monkeys. Biol Psychiatry 55(6):642-7.
Goldfeld AE, Leung JY, Sawyer SA, Hartl DL. 2000. Post-genomics and the neutral theory: variation and conservation in the tumor necrosis factor-alpha promoter. Gene 261(1):19-25.
Groves CP. 2001. Primate taxonomy. Washington, DC: Smithsonian Institution Press. viii, 350 p. p.
Handler JS, Lange FW, Riordan RV. 1978. Plantation slavery in Barbados : an archaeological and historical investigation. Cambridge: Harvard University Press. xiii, 368 p. p.
Haudek SB, Natmessnig BE, Redl H, Schlag G, Giroir BP. 1998. Genetic sequences and transcriptional regulation of the TNFA promoter: comparison of human and baboon. Immunogenetics 48(3):202-7.
Jasinska AJ, Service S, Levinson M, Slaten E, Lee O, Sobel E, Fairbanks LA, Bailey JN, Jorgensen MJ, Breidenthal SE et al. 2007. A genetic linkage map of the vervet monkey (Chlorocebus aethiops sabaeus). Mamm Genome 18(5):347-60.
Leung JY, McKenzie FE, Uglialoro AM, Flores-Villanueva PO, Sorkin BC, Yunis EJ, Hartl DL, Goldfeld AE. 2000. Identification of phylogenetic footprints in primate tumor necrosis factor-alpha promoters. Proc Natl Acad Sci U S A 97(12):6614-8.
McGuire MT. 1974. The St. Kitts vervet (Cercopithecus aethiops). J Med Primatol 3(5):285-97.
National Research Council (U.S.), Institute for Laboratory Animal Research (U.S.). 2003. International perspectives : the future of nonhuman primate resources : proceedings of the workshop held April 17-19, 2002. Washington, D.C.: National Academies Press. xii, 249 p. p.
Rudel LL, Reynolds JA, Bullock BC. 1981. Nutritional effects on blood lipid and HDL cholesterol concentrations in two subspecies of African green monkeys (Cercopithecus aethiops). J Lipid Res 22(2):278-86.
Smith DG, McDonough J. 2005. Mitochondrial DNA variation in Chinese and Indian rhesus macaques (Macaca mulatta). Am J Primatol 65(1):1-25.
Swofford DL. 2002. PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods). Version 4. Sunderland,
78
Massachusetts.: Sinauer Associates,. Thompson JD, Higgins DG, Gibson TJ. 1994. CLUSTAL W: improving the sensitivity of
progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22(22):4673-80.
van der Kuyl AC, Dekker JT. 1996. St. Kitts green monkeys originate from West Africa: Genetic evidence from feces. American Journal of Primatology 40(4):361-364.
Wang Y. 2006. Molecular polymorphisms for phylogeny, pedigree and population structure studies [Thesis (Ph D )]: School of Biological Sciences, Faculty of Science, University of Sydney, 2006. xvii, 232 leaves p.
www.genome.gov. Zuccon A, Zuccon D. 2008. MrEnt v.2. Program distributed by authors.
79
CHAPTER IV
TNF SINGLE NUCLEOTIDE POLYMORPHISMS ARE ASSOCIATED WITH BMI, WAIST CIRCUMFERENCE, AND SERUM CHOLESTEROL LEVELS IN A PEDIGREED NONHUMAN
PRIMATE MODEL (CHLOROCEBUS AETHIOPS SSP.)
Stanton B Gray, Carl D Langefeld, Julie T Ziegler, Gregory A Hawkins, Janice D Wagner, Timothy D Howard
The following manuscript will be submitted for publication to the journal BMC
Genomics. Stylistic variations are due to the requirements of the journal. Dr. S.B. Gray
prepared the manuscript and was primarily responsible for performing and directing the
experiments, as well as data analysis and interpretation. Technical assistance was
provided by Ms. J.T. Ziegler and Mr. A.F. Diallo. Analytical assistance was provided by
Drs. C.D. Langefeld and T.D. Howard, and Ms. J.T. Ziegler. Drs. T.D. Howard and J.D.
Wagner acted in an advisory capacity. All co-authors provided editorial input.
80
Introduction
The number of people classified as obese or overweight, defined by a BMI over 30 or 25
kg/m2 respectively, has reached epidemic proportions in the U.S. and around the world
(IOTF 2007), with commensurate social, medical, and public health costs (Wyatt,
Winters et al. 2006). Currently, more than 30% of U.S. adults are obese, with another
35% overweight; in addition, incidence of overweight children and adolescents is now
over 15% (NHANES 2007). Compared to 30 years ago, these figures have approximately
doubled in adults and quadrupled in children and adolescents (NHANES 2007). To put
the magnitude of this epidemic into global perspective, approximately 1 billion adults
are overweight worldwide, with 300 million of those clinically obese according to World
Health Organization estimates (Brundtland 2002). Obesity, and overweight to a lesser
degree, have consistently been associated with increased morbidity and mortality linked
to cardiovascular disease (CVD), hypertension, insulin resistance (IR), type 2 diabetes
(T2D), dyslipidemia, metabolic syndrome (a set of CVD risk factors defined as at least 3
of the following: hypertension, dyslipidemia, central obesity and IR), airway
inflammation, fatty liver disease, gallstones, osteoarthritis, sleep apnea, and certain
forms of cancer (NHLBI 2000; Eckel, Barouch et al. 2002; Klein, Burke et al. 2004; Wellen
and Hotamisligil 2005), with relative risk of these comorbidities being positively
correlated with BMI (Wyatt, Winters et al. 2006).
Over the past 15 years, two critically important elements of the pathogenesis of obesity
and many of its comorbidities have been realized: 1) obesity is associated with chronic,
81
systemic, low-grade, inflammation (Wellen and Hotamisligil 2005), and 2) adipose tissue
is not simply a reservoir for triglycerides, but is an integral endocrine organ, playing a
central role in secretion and mediation of inflammatory cytokines (Hotamisligil, Shargill
et al. 1993; Zhang, Proenca et al. 1994). Chronic, low-grade inflammation associated
with obesity has been shown to be causal in many of its comorbidities (Esteve, Ricart et
al. 2005; Wellen and Hotamisligil 2005; Hotamisligil 2006). For the purposes of this
study, and the nonhuman primate (NHP) model we are developing, we will focus the
discussion on CVD, T2D, and elements of metabolic syndrome in regards to obesity
comorbidities.
Obesity, excluding rare monogenic and syndromic forms, is paradigmatic of complex,
polygenic disease phenotypes that are the resolution of complex gene-gene
interactions, as well as interactions of genotype with environment (Scriver 2001). Thus,
the genetic basis is far from completely understood, but is clearly extensive, with new
candidate genes being discovered at a pace concordant with the rapidly developing
technology behind genome-wide association studies (GWAS) (Li and Loos 2008; Norris,
Langefeld et al. 2009). Adding to this complexity, many environmental, and other non-
genetic components, have been shown to modulate phenotypic expression such as age,
developmental programming (in utero and post-natal), gender, hormonal status and
cycling, lifestyles, nutrition, physical activity level, risk behavior, socioeconomic status,
and stress (Shively and Clarkson 1988; Roseboom, van der Meulen et al. 2001; Hill,
82
Wyatt et al. 2003; Roche, Phillips et al. 2005; Mutch and Clement 2006; Pasquali,
Vicennati et al. 2006; Schneider, Tompkins et al. 2006; Taylor and Poston 2007).
Tumor necrosis factor (TNF) is an obesity candidate gene of central importance. It
encodes a cytokine secreted by adipocytes and other tissues that plays critical roles in
lymphocyte biology, immune responses, and promoting inflammation (Cawthorn and
Sethi 2008). It has been shown to be a principal initiator and mediator of obesity-
related inflammation, with TNF serum levels correlated with obesity and serum levels of
other pro-inflammatory cytokines such as IL-6, leptin, resistin, MCP-1, and PAI-1 (Juge-
Aubry, Henrichot et al. 2005). It also promotes IR by downregulating glucose
transporter 4 (GLUT4) in adipocytes (Hotamisligil, Shargill et al. 1993), serine
phosphorylation of IRS-1 (Hotamisligil, Peraldi et al. 1996), as well as several other
mechanisms. Single nucleotide polymorphisms (SNPs) in the promoter region of TNF
have been extensively characterized in humans, and reports abound in the literature
indicating associations with an array of infectious, immune-mediated, and
inflammatory-related disease phenotypes, including obesity, CVD, T2D, IR, dyslipidemia,
waist circumference, and hypertension [reviewed in (Fernandez-Real 2006)]. However,
controlling for the multitude of environmental risk factors has been a major confounder
of efforts to elucidate the role and relative contribution of variation in TNF and other
candidate genes in human studies (Risch 2000; Botstein and Risch 2003) due to the
complex experimental designs and large sample size they would entail (Mutch and
Clement 2006). Another major difficulty in identifying functional SNPs in TNF, or
83
anywhere within the major histocompatibility complex (MHC), is the strong degree of
linkage disequilibrium (LD) within this region (Shiina, Ota et al. 2006), yielding extended
haplotypes (Ceppellini, Siniscalco et al. 1955).
Research directed at further elucidating the genetic and molecular mechanisms of
obesity and disentangling the age- and environment-related factors through more
relevant animal models has been assigned as one of the highest priorities in the U.S.
(Eckel, Barouch et al. 2002; USHHS 2007). Animal models, in general, have the distinct
advantage of allowing a large degree of control over environmental factors; in addition,
measures can be taken over the lifetime of the animal. Pedigreed colonies of Old World
monkeys (OWM) are particularly important NHP animal models for the study of obesity
and inflammation given their close phylogenetic relationship to humans, comparable fat
distribution (Bergman, Kim et al. 2007; Kavanagh, Fairbanks et al. 2007), similar
reproductive and endocrine physiology to humans, and their potential to exhibit
spontaneous obesity, IR, T2D and CVD (Wagner, Bagdade et al. 1996; Wagner, Carlson et
al. 1996; West and York 1998; Wagner, Cline et al. 2001; Wagner, Kavanagh et al. 2006;
Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones et al. 2007). As part of an ongoing
initiative to further genetically and phenotypically characterize the St. Kitts-origin vervet
monkey (Chlorocebus aethiops ssp.) as a model of obesity, insulin resistance, and type 2
diabetes (Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones et al. 2007), we sequenced
the orthologous TNF gene and its promoter region in 265 monkeys from the pedigreed
Vervet Research Colony (VRC) at the Wake Forest University Primate Center (WFUPC),
84
and performed association analyses between each SNP and each previously defined,
obesity-related trait previously reported to be significantly heritable in this colony (Table
1) (Kavanagh, Fairbanks et al. 2007).
Materials and Methods
Animals. All methods for the care and use of nonhuman primates conformed to U.S.
Department of Agriculture and Public Health Service standards, and all experimental
protocols were approved by the Chancellor’s Animal Research Committee at UCLA and
the Institutional Animal Care and Use Committee for the Department of Veterans Affairs
Greater Los Angeles Healthcare System. Two hundred and sixty five St. Kitts-origin
vervets (Chlorocebus aethiops ssp.) from the VRC were used in this study. The VRC was
founded in 1975 at UCLA from 57 vervets (28 males, 29 females) wild caught from 1975-
1983 in St. Kitts, West Indies, as described in Fairbanks et al. (2004). The current
population includes approximately 450 descendants with 24 of the original matrilines in
their 5th to 8th generation, and now resides at the Wake Forest University Primate
Center (WFUPC) in Winston-Salem, NC, USA. All vervets were fed a commercial primate
laboratory chow which is relatively low fat and high fiber (Laboratory Diet 5038; Purina,
St. Louis, MO) ad libitum supplemented with fresh fruits and vegetables, and were pen-
housed with equal access to exercise.
PCR and Sequencing. Genomic DNA was isolated from peripheral blood samples using
standard protocols previously described (Jasinska, Service et al. 2007). For sequencing,
PCR primers were generated with the PrimerSelect software (Laser Gene software,
85
Table 1. Heritability estimates (h2) for obesity-related phenotypes of VRC vervets
(n=295). Taken from Kavanagh et al. (2007).
Trait h2 (S.E.) P
BMI 0.44 (0.15) 0.0001 WC 0.37 (0.16) 0.02 TPC 0.37 (0.13) 0.0006 TG 0.33 (0.13) 0.0001
HDL-C 0.29 (0.13) 0.002 GHb% 0.18 (0.10) 0.03 Insulin 0.21 (0.11) 0.02
Glucose 0.07 (0.11) 0.26 HOMA-IR 0.02 (0.10) 0.36
86
DNASTAR, Madison, WI.) using a consensus TNF gene sequence created from human,
chimpanzee (Pan troglodytes) and rhesus monkey (Macaca mulatta) from in the NCBI
gene database (www.ncbi.nlm.nih.gov; uc003nui.1, NM_001045511, NM_001047149
respectively). Primer consensus sequences were created using the editing feature in
Sequencher v. 4.8 (Gene Codes Corp., Ann Arbor, MI), and were designed to amplify the
entire TNF gene plus ~1 kb 5’ and ~1 kb 3’ flanking regions. PCR conditions were as
follows: initial denaturation at 95oC for 10 min, followed by 30 cycles of 96oC for 1 min,
58-60oC for 1 min and 72oC for 60-90 sec with final elongation for 10 min at 72oC in a 20-
µl reaction mixture. PCR products were purified (QuickStep, Edge Biosystems Inc.,
Gaithersburg, MD) to remove dNTPs and excess primers that interfere with sequencing
reactions. Purified PCR products were sequenced using dye-terminator chemistry
(BigDye, ABI, Foster City, CA). Sequencing reactions were purified by ethanol
precipitation prior to loading on an ABI3730XL DNA Analyzer using the POP7 sequencing
polymer. The sequences of the primers used are described in Supplementary Table 1.
Sequence Analyses. Sequences from the 265 VRC vervets were aligned and the
genotypes were determined with Sequencher v. 4.8 (Gene Codes Corp., Ann Arbor, MI).
LD structure, allele and haplotype frequencies, and a 2 goodness-of-fit test for
deviations from Hardy-Weinberg equilibrium were determined with Haploview, version
4.0 (Barrett, Fry et al. 2005). Human SNPs were compiled from dbSNP (Build 128,
www.ncbi.nlm.nih.gov) for comparison to orthologous vervet SNPs.
Association Analyses. Association between individual polymorphisms and each
quantitative phenotype was tested using a variance component model as implemented
87
in software SOLAR [(Sequential Linkage Analysis Routines) v. 2.1.2 (Almasy and Blangero
1998)]. For each vervet TNF polymorphism, we used maximum likelihood methods to
estimate and test the possible effects of each genotype on each of 5 phenotypes: BMI,
waist circumference (WC), triglycerides (TG), total plasma cholesterol (TPC), and high
density lipoprotein-cholesterol (HDL-C). To best approximate the distributional
assumptions of the test (i.e., conditional normality and homogeneity of variance), BMI,
TG, and WC values were natural log- and TPC were square root-transformed to better
approximate normal distribution. After removing pregnant females, models for lipid
measures, TG, TPC, and HDL-C, were adjusted for age, gender, and BMI; BMI and WC
models were adjusted for age and gender. Each trait was tested against each SNP under
4 models of inheritance: the two degree of freedom genotypic test and three a priori
genetic models (i.e., additive, dominant, and recessive).
Results
Analysis of ~1 kb 5’ upstream, ~0.9 kb 3’ downstream, all four exons, and all intronic
regions of the vervet TNF gene in 265 vervet monkeys revealed a total of 12
polymorphisms: 11 SNPs and one 4 bp insertion/deletion, with MAF ranging from 0.077
to 0.393 (Table 2). Five SNPs were located in the 5’ putative promoter region, two in
intron 1, one in intron 3, and four in the 3’ UTR (Figure 1). None of the loci which are
polymorphic in vervets have been reported to be polymorphic in human populations
(dbSNP build 129). The +611 (TGAA)4/5 insertion/deletion, located in intron 1, is not
88
Table 2. Polymorphisms in the human ortholog St. Kitts-origin vervet TNF gene and
flanking sequence.
Polymorphism MAF Minor allele
A-809G 0.309 G A-756G 0.311 A G-602T 0.210 G C-352T 0.393 C A-322G 0.312 A C+426G 0.209 C
+611(tgaa) 4 / 5
0.078 (tgaa) 4
G+1285T 0.387 T C+2133T 0.309 T A+2362G 0.316 A A+2405G 0.318 A C+2681T 0.077 C
89
Figure 1. LD structure of the St. Kitts-origin vervet TNF locus. The single haplotype block
(outlined triangle) was determined with the confidence interval algorithm (Gabriel,
Schaffner et al. 2002) of HaploView. Numbers indicate pairwise r2 values multiplied by
100. Darker blocks denote higher correlation and black squares with no numbers
represent complete LD (r2 = 1). Polymorphism names denote nucleotide variants
flanking gene position relative to human transcription start site. Repeat polymorphisms
denoted by repeated sequence in parentheses and repeat number variants subscripted
and separated by a slash (e.g. (tgaa )4/5).
90
reported to be polymorphic and is (TGAA)6 in humans. The entire vervet TNF gene was
contained within a single haplotype block (Figure 1), as determined by the confidence
interval algorithm (Gabriel, Schaffner et al. 2002) implemented within Haploview 4.0
(Barrett, Fry et al. 2005). The C/T+2681 SNP, located at the farthest 3’ portion examined,
was the only SNP not included with this block (Figure 1). Many of the polymorphisms
were in strong or complete LD with one another (Figure 1), as is common within and
between genes and intergenic regions of the primate, including human, MHC
(Ceppellini, Siniscalco et al. 1955; Shiina, Ota et al. 2006). Five haplotypes were
identified in this block, with frequencies ranging from 0.075 to 0.298 (Table 3).
Multiple SNPs in the vervet TNF gene were associated with the obesity-related
phenotypes, BMI, WC, TG, TPC, and HDL-C (Figure 2). Consistent with the LD pattern
and block structure, significant phenotypic associations among several SNPs and
phenotypes were observed (Figure 1, Table 3). All or nearly all of the SNPs (-806, -756, -
352, -322, +1285, +2133, +2362, and +2405) are associated with BMI, WC, TPC, and HDL-
C (Figure 1), and are contained within the same haplotype block (Figure 1).
Interestingly, the minor alleles for each of these form the H1 haplotype and are the risk
alleles for BMI, WC, and TPC; these alleles are not found on other haplotypes in these
vervets (Table 3). They were also associated with higher levels of HDL-C, which would
not traditionally be considered “risk” since HDL-C is involved in reverse cholesterol
transport (Lewis and Rader 2005), and is considered anti-inflammatory (Ley, Laudanna
et al. 2007) and atheroprotective (Castelli, Garrison et al. 1986). Similarly, the set of
91
Table 3. Haplotypes and frequencies of the human ortholog St. Kitts-origin vervet TNF
gene and flanking sequence.
Haplotype name
Haplotype Freq
H1 G A T C A G (tgaa)5 T T A A 0.298
H2 A G G T G G (tgaa)5 G C G G 0.208
H3 A G T T G C (tgaa)5 G C G G 0.205
H4 A G T T G G (tgaa)5 G C G G 0.183
H5 A G T C G G (tgaa)4 T C G G 0.075
92
Figure 2. Association of SNPs in the TNF gene in the St. Kitts-origin vervet monkey of
the VRC. Categorical x-axis lists SNPs. Y-axis is the negative log of the p values for
association. Dashed lines indicate statistical significance with one asterisk (*) denoting
p<0.05, and two asterisks (**) denoting p<0.01.
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
1.80
2.00
2.20
2.40
2.60
2.80
3.00
-80
9 A
/G
-75
6 G
/A
-60
2 T/G
-35
2 T/C
-32
2 G
/A
+42
6 G
/C
+61
1 5
/4
+12
85
G/T
+21
33
C/T
+23
62
G/A
+24
05
G/A
+26
81
T/C
BMI WC TPC TG HDL-C
**
*
93
SNPs with no significant phenotypic associations were not in LD (had r2 values 0.02-0.16)
with these SNPs (Figure 1). No significant associations were observed between any SNP
and TG levels.
Figure 3 illustrates a sequence comparison of the TNF promoter region, and the
respective SNPs, between the St. Kitts-origin vervet and human. The transcription
binding sites NFAT, ETS, 3, CRE, and SP1, confirmed to be essential for TNF gene
regulation (Goldfeld, McCaffrey et al. 1993; Tsai, Jain et al. 1996; Tsai, Yie et al. 1996;
Falvo, Uglialoro et al. 2000; Tsai, Falvo et al. 2000; Tsytsykova and Goldfeld 2002;
Barthel, Tsytsykova et al. 2003) are noted, as well as the sites for 1 and 2, which bind
NF- B proteins, but are not essential to TNF gene regulation (Goldfeld, Doyle et al.
1990). There is complete conservation of those sites essential for gene regulation
between vervet and human, and also among several other apes, and Old and New
World monkeys as reported elsewhere (Leung, McKenzie et al. 2000). The vervet,
rhesus, and baboon (Leung, McKenzie et al. 2000) contain an A instead of a G in 2
(position -206), but 1 is completely conserved between vervet and human, as well as
the other primate species just mentioned (Leung, McKenzie et al. 2000).
94
-1153 -1072 -1055
H sapien GGGAGCAAGAGCTGTGGGGAGAACAAAAGGATAA-GGGCTCAGAGAGCTTCAGGGATATGTGATGGACTCACCAGGTGAGGCYGCCAGACTGCTGCAGGG
C aethiops ..................................A.....................C.........................C.................
-1054 -1030 -955
H sapien GAAGCAAAGGAGAAGCTGAGAAGAYGAAGGAAAAGTCAGGGTCTGGAGGGGCGGGGGTCAGGGAGCTCCTGGGAGATATGGCCACATGTAGCGGCTCTGA
C aethiops ........................CA...................A........................................A....T........
-954 -862 -856
H sapien GGAATGGGTTACAGGAGACCTCTGGGGAGATGTGACCACAGCAATGGGTAGGAGAATGTCCAGGGCTATGGAAGTCGAGTATGGGGACCCCCMCTTAAYG
C aethiops ............................................A...........A..............GG..T................C.---GCC
-854 -805 -781 -758
H sapien AAGACAGGGCCATGTAGAGGGCCCCAGGGAGTGAAAGAGCCTCCAGGACYTCCAGGTATGGAATACAGGGGACRTTTAAGAAGATATGGCCACACAMTGG
C aethiops ........................T....................R...C..T....................G......................T.R.
-754 -655
H sapien GGCCCTGAGAAGTGAGAGCTTCATGAAAAAAATCAGGGACCCCAGAGTTCCTTGGAAGCCAAGACTGAAACCAGCATTATGAGTCTCCGGGTCAGAATGA
C aethiops ..................T...........................................................G......C..........G...
-654 -645 1 -571-569 -556
H sapien AAGAAGAAGRCCTGCCCCAGTGGGGTCTGTGAATTCCCGGGGGTGATTTCACTCCCC-GGGGCTGTCCCAGGCTTGTCCCTGCTMCMCCCACCCAGCCTT
C aethiops .........G..............................T...........K....-..........................A.C.............
-555 -510 -458
H sapien TCCTGAGGCCTCAAGCCTGCCACCAAGCCCCCAGCTCCTTCTCCCSGCAGGGACCCAAACACAGGCCTCAGGACTCAACACAGCTTTTC-CC-TCCAACC
C aethiops C.........CTG........C.......................CCA...A.....................................T..C.......
-457 -375 -358
H sapien CCGTTTTCTCTCCCTCAAGGACTCAGCTTTCTGAAGCCCCTCCCAGTTCTAGTTCTATCTTTTTCCTGCATCCTGTCTGGAARTTAGAAGGAAACAGACC
C aethiops ..A........A...................................................................A..A.C...G...........
-357 -307 -258
H sapien ACAGACCTGGTCCCCAAAAGAAATGGAGGCAATAGGTTTTGAGGGGCATGRGGACGGGGTTCAGCCTCCAGGGTCCTACACACAAATCAGTCAGTGGCCC
C aethiops .....Y..........G..................RC...........G.A.C.....A....A.......A....C.......................
-257 -243 -237 2 -158
H sapien AGAAGACCCCCCTCRGAATCRGAGCAGGGAGGATGGGGAGTGTGAGGGGTATCCTTGATGCTTGTGTGTCCCCAACTTTCCAAATCCCCGCCCCCGCGAT
C aethiops ..............G.....G.........T.G.......A......A................G...................................
-157 NFAT/Ets CRE NFAT5/ 3 ETS NFAT/5 -58
H sapien GGAGAAGAAACCGAGACAGAAGGTGCAGGGCCCACTACCGCTTCCTCCAGATGAGCTCATGGGTTTCTCCACCAAGGAAGTTTTCCGCTGGTTGAATGAT
C aethiops ...........A...G....................................................................................
-57 SP1 +1 +11 +24
H sapien TCTTTCCCCGCCCTCCTCTCGCCCCAGGGACATATAAAGGCAGTTGTTGGCACACCCAGCCAGCAGAYGCTCCCTCAGCAA
C aethiops ..............---....................C..........T..................C.............
Figure 3. Sequence comparison of TNF 5’ promoter region between humans (H sapien)
and St. Kitts-origin vervet (C aethiops ssp.). SNPs are underlined and bolded with
adjacent nucleotide position for human SNPs. Nucleotide positions are relative to the
human TSS. The single letter code is used to identify SNPs : M=A/C, R=A/G, W=A/T,
S=C/G, Y=C/T, K=G/T. Transcription factor binding sites are underlined with names
above the sequence. NFAT (nuclear factor of activated T cells), Ets, 3, CRE (cyclic AMP
response element), and SP-1 are critical for TNF gene regulation (Goldfeld, McCaffrey et
al. 1993; Tsai, Jain et al. 1996; Tsai, Yie et al. 1996; Falvo, Uglialoro et al. 2000; Tsai,
Falvo et al. 2000; Tsytsykova and Goldfeld 2002; Barthel, Tsytsykova et al. 2003); 1 and
2 are reported to bind NF- B proteins and are not essential for gene regulation
(Goldfeld, Doyle et al. 1990; Leung, McKenzie et al. 2000).
95
Discussion
For an initial genetic characterization of the St. Kitts-origin vervet of the VRC as a model
of obesity and metabolic syndrome, we performed sequencing and genotyping of the
orthologous vervet TNF gene in 265 of the originally characterized 295 vervets
(Kavanagh et al. 2007). We report a total of five SNPs within the 5’ UTR and putative
promoter region, and another six SNPs, plus one insertion/deletion polymorphism, in
the introns, 3’ UTR, and 3’ flanking regions (Table 2, Figures 1 and 3). All
polymorphisms, except one (C/T+2681), were contained within a single haplotype block
(Figure 1), which contains five haplotypes (Table 3) within the VRC population. All
polymorphisms fall outside major conserved regions of transcription factor binding,
known to be critical for TNF gene regulation (Figure 3). In addition, there is non-random
clustering of SNPs between these vervets and humans (Figure 3), and also within Pan
troglodytes and Macaca mulatta at sites shown to contain alleles in humans significantly
associated with risk for a variety of inflammatory- or innate immunity-related diseases,
including obesity- and diabetes-related phenotypes (i.e. -308, -857, -863) (Fernandez-
Real 2006). Thus, we have previously reported that we believe the distribution of TNF
promoter SNPs in this vervet monkey model can be considered analogous to human.
The concept that polymorphisms have accumulated independently in NHPs, and confer
analogous disease phenotypes and risk, has been demonstrated in the St. Kitts-origin
VRC vervet (Bailey, Breidenthal et al. 2007) and the rhesus macaque (Lesch, Meyer et al.
1997; Bennett, Lesch et al. 2002; Miller, Bendor et al. 2004) as models for
96
neurobehavioral disorders, and also in baboons modeling hypertension (Zheng,
Kammerer et al. 2009). Three of these four previous reports of analogous NHP
polymorphisms and associated phenotypes represent functional exonic polymorphisms,
thus more closely modeling a monogenic, Mendelian disorder (Miller, Bendor et al.
2004; Bailey, Breidenthal et al. 2007; Zheng, Kammerer et al. 2009). One of these four is
within the promoter region of the serotonin transporter gene (Lesch, Meyer et al. 1997),
but is a 21-bp insertion/deletion polymorphism with much greater potential to exert
differential transcriptional activity than a SNP. We have suggested that the SNP
distribution in the vervet TNF promoter/enhancer region is analogous to the distribution
of SNPs in the human TNF promoter/enhancer region, and that this constitutes the first
report, to our knowledge, of SNP characterization in a NHP to model applicable to a
polygenic (additive) model of inheritance for a complex, quantitative trait.
Summarizing the phenotypic and genetic characterization of the St. Kitts-origin vervet
model of obesity prior to this report, it has been shown to display obesity-related
phenotypes with significant heritabilities (Table 1) (Kavanagh, Fairbanks et al. 2007;
Kavanagh, Jones et al. 2007), as well as SNP distribution along the TNF promoter is
analogous to humans. The question that follows from these findings is whether these
vervet TNF SNPs show associations with the obesity-related phenotypes. We have
demonstrated that a subset of SNPs in strong LD (-809, -756, -352, -322, +1285, +2133,
+2362, and +2405) within the putative promoter, introns, 3’ UTR, and 3’ flanking regions
all have significant associations with BMI, WC, TPC, and HDL-C (Figure 2). The minor
97
alleles of this subset of SNPs (Table 2) are found exclusively on haplotype H1 (Table 3),
and are associated with increased BMI, WC, TPC, and HDL-C, which obviated the need to
perform an additional haplotypic association analysis. It is not unexpected that this
pattern of genetic associations is observed given the LD pattern and that all “risk” alleles
are located on a single haplotype, H1. An important question is whether there is one
“functional” SNP which is responsible for the phenotypic differences, possibly by
modulating transcription factor binding, and the other SNPs show phenotypic
association simply due to strong LD with the functional SNP. At the other end of the
spectrum of possibilities is that this set of SNPs, inherited together in a haplotype block,
act together to modulate the phenotype, possibly through a combination of differential
transcription factor binding and intronic splicing. The data presented here seems to
suggest that if one SNP is responsible for most or all of the phenotypic differences, that
-322 is the most likely candidate given that it displays the greatest number of, and most
highly significant, associations (Figure2). This idea is particularly intriguing since -322 is
near SNP -308 in humans, -331 in chimpanzees, and -334 in rhesus macaques . There is
an abundance of reports in the literature of significant associations between the -308
SNP in humans and various inflammatory- and immune-related disease phenotypes,
including BMI, WC, and TPC (Fernandez-Real 2006).
The same set of alleles located on haplotype H1 associated with ‘risk’ phenotypes BMI,
WC, and TPC, was also associated with increased values of HDL-C, representing a novel
association not previously seen in human studies. HDL-C levels have traditionally been
98
regarded as negative risk factors for CVD based on its relatively well-characterized role
in reverse cholesterol transport (Lewis and Rader 2005), its inhibition of adhesion
molecules ICAM-1 and VCAM-1 (Ley, Laudanna et al. 2007), as well as epidemiological
studies (Castelli, Garrison et al. 1986; Singh, Shishehbor et al. 2007). Thus, ‘risk’ has
been linked to low levels of HDL-C, and human studies have shown lower values to be
associated with certain risk alleles within the TNF promoter (Dalziel, Gosby et al. 2002;
Parra-Rojas, Ruiz-Madrigal et al. 2006). The positive associations between higher levels
of HDL-C and haplotype H1 in these VRC vervets is therefore quite intriguing. Factors
contributing to this result could include one or more of the following: 1) Chlorocebus
aethiops ssp. have been shown to have high HDL-C relative to humans and other NHPs
(Rudel, Reynolds et al. 1981), 2) Rudel et al. (1981) further demonstrated a high degree
of correlation between TPC and HDL-C in these vervets and this is also reflected in this
VRC subset (r2 = 0.75, Kavanagh, unpublished data) and, 3) soy has been shown to
increase HDL-C in cynomolgus macaques (Greaves, Wilson et al. 2000) and in a human
meta-analysis (Zhan and Ho 2005). However, the fact that HDL-C levels are positively
associated with haplotype H1 in the present study may be providing some small glimpse
into a changing paradigm related to HDL-C. That is, HDLs are extremely diverse in
structure and function, and mounting evidence suggests that the notion of higher levels
always conferring, and being indicative of, protection from CVD and inflammatory-
related disease states could be overly simplistic. Specifically, the cardioprotective effect
of HDL-C is increasingly thought to be due to the apolipoprotein apoA-I and apoA-II
content rather than simply HDL-C levels (Watts, Barrett et al. 2008). For example, a
99
major post-hoc analysis recently indicated that very high HDL-C levels (>70 mg/dL) in
humans conferred a two-fold increase in risk of CVD (van der Steeg, Holme et al. 2008).
In conclusion, we have provided additional validation of the St. Kitts-origin vervet model
of obesity and metabolic syndrome by demonstrating analogous SNP distribution and
phenotypic associations with the orthologous TNF gene. Given the complex, polygenic
nature of obesity and its comorbidities, development of a NHP model of obesity and its
inflammatory-related comorbidities is of paramount importance to address some of the
limitations of genetic studies in humans. In addition, with metabolism, inflammation,
immune function, and dyslipidemia being inextricably linked, evolutionarily conserved
physiologic processes (Esteve, Ricart et al. 2005; Hotamisligil 2006), we believe a NHP
model offers insight into the ancestral state of human risk alleles that cannot be realized
in non-primate models (Di Rienzo and Hudson 2005).
Acknowledgements This work was funded, in part, by the Wake Forest University
School of Medicine Venture Fund, the Skorich Diabetes Research Fund, the Monty
Blackmon Diabetes Research Fund (JDW), T32 RR07009 from NIH/NCRR (SBG), an
Animal and Biological Materials Resources grant from the National Center for Research
Resources (P40 RR 019963 to Dr. Lynn Fairbanks at UCLA), and the Center for Public
Health Genomics (CDL, JTZ) at WFUSM. The authors would also like to thank Drs. Lynn
Fairbanks (UCLA), Nelson Friemer (UCLA), Matthew Jorgensen (WFUSM), Kylie Kavanagh
(WFUSM), Larry Rudel (WFUSM), Jay Kaplan (WFUSM), Yongmei Liu (WFUSM) and Don
100
Bowden (WFUSM) for their input and collaboration. This work constitutes partial
fulfillment of Ph.D. requirements for Dr. Gray.
101
References Almasy, L. and J. Blangero (1998). "Multipoint quantitative-trait linkage analysis in
general pedigrees." Am J Hum Genet 62(5): 1198-211. Bailey, J. N., S. E. Breidenthal, et al. (2007). "The association of DRD4 and novelty
seeking is found in a nonhuman primate model." Psychiatr Genet 17(1): 23-7. Barrett, J. C., B. Fry, et al. (2005). "Haploview: analysis and visualization of LD and
haplotype maps." Bioinformatics 21(2): 263-5. Barthel, R., A. V. Tsytsykova, et al. (2003). "Regulation of tumor necrosis factor alpha
gene expression by mycobacteria involves the assembly of a unique enhanceosome dependent on the coactivator proteins CBP/p300." Mol Cell Biol 23(2): 526-33.
Bennett, A. J., K. P. Lesch, et al. (2002). "Early experience and serotonin transporter gene variation interact to influence primate CNS function." Mol Psychiatry 7(1): 118-22.
Bergman, R. N., S. P. Kim, et al. (2007). "Abdominal obesity: role in the pathophysiology of metabolic disease and cardiovascular risk." Am J Med 120(2 Suppl 1): S3-8; discussion S29-32.
Botstein, D. and N. Risch (2003). "Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex disease." Nat Genet 33 Suppl: 228-37.
Brundtland, G. H. (2002). "From the World Health Organization. Reducing risks to health, promoting healthy life." JAMA 288(16): 1974.
Cawthorn, W. P. and J. K. Sethi (2008). "TNF-alpha and adipocyte biology." FEBS Lett 582(1): 117-31.
Ceppellini, R., M. Siniscalco, et al. (1955). "The estimation of gene frequencies in a random-mating population." Ann Hum Genet 20(2): 97-115.
Di Rienzo, A. and R. R. Hudson (2005). "An evolutionary framework for common diseases: the ancestral-susceptibility model." Trends Genet 21(11): 596-601.
Eckel, R. H., W. W. Barouch, et al. (2002). "Report of the National Heart, Lung, and Blood Institute-National Institute of Diabetes and Digestive and Kidney Diseases Working Group on the pathophysiology of obesity-associated cardiovascular disease." Circulation 105(24): 2923-8.
Esteve, E., W. Ricart, et al. (2005). "Dyslipidemia and inflammation: an evolutionary conserved mechanism." Clin Nutr 24(1): 16-31.
Fairbanks, L. A., T. K. Newman, et al. (2004). "Genetic contributions to social impulsivity and aggressiveness in vervet monkeys." Biol Psychiatry 55(6): 642-7.
Falvo, J. V., A. M. Uglialoro, et al. (2000). "Stimulus-specific assembly of enhancer complexes on the tumor necrosis factor alpha gene promoter." Mol Cell Biol 20(6): 2239-47.
Fernandez-Real, J. M. (2006). "Genetic predispositions to low-grade inflammation and type 2 diabetes." Diabetes Technol Ther 8(1): 55-66.
Gabriel, S. B., S. F. Schaffner, et al. (2002). "The structure of haplotype blocks in the human genome." Science 296(5576): 2225-9.
102
Goldfeld, A. E., C. Doyle, et al. (1990). "Human tumor necrosis factor alpha gene regulation by virus and lipopolysaccharide." Proc Natl Acad Sci U S A 87(24): 9769-73.
Goldfeld, A. E., P. G. McCaffrey, et al. (1993). "Identification of a novel cyclosporin-sensitive element in the human tumor necrosis factor alpha gene promoter." J Exp Med 178(4): 1365-79.
Hill, J. O., H. R. Wyatt, et al. (2003). "Obesity and the environment: where do we go from here?" Science 299(5608): 853-5.
Hotamisligil, G. S. (2006). "Inflammation and metabolic disorders." Nature 444(7121): 860-7.
Hotamisligil, G. S., P. Peraldi, et al. (1996). "IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance." Science 271(5249): 665-8.
Hotamisligil, G. S., N. S. Shargill, et al. (1993). "Adipose expression of tumor necrosis factor-alpha: direct role in obesity-linked insulin resistance." Science 259(5091): 87-91.
IOTF. (2007, August 2007). "Prevalence of Adult Obesity." from http://www.iotf.org/database/GlobalAdultTableJune07.htm.
Jasinska, A. J., S. Service, et al. (2007). "A genetic linkage map of the vervet monkey (Chlorocebus aethiops sabaeus)." Mamm Genome 18(5): 347-60.
Juge-Aubry, C. E., E. Henrichot, et al. (2005). "Adipose tissue: a regulator of inflammation." Best Pract Res Clin Endocrinol Metab 19(4): 547-66.
Kavanagh, K., L. A. Fairbanks, et al. (2007). "Characterization and heritability of obesity and associated risk factors in vervet monkeys." Obesity (Silver Spring) 15(7): 1666-74.
Kavanagh, K., K. L. Jones, et al. (2007). "Trans fat diet induces abdominal obesity and changes in insulin sensitivity in monkeys." Obesity (Silver Spring) 15(7): 1675-84.
Klein, S., L. E. Burke, et al. (2004). "Clinical implications of obesity with specific focus on cardiovascular disease: a statement for professionals from the American Heart Association Council on Nutrition, Physical Activity, and Metabolism: endorsed by the American College of Cardiology Foundation." Circulation 110(18): 2952-67.
Lesch, K. P., J. Meyer, et al. (1997). "The 5-HT transporter gene-linked polymorphic region (5-HTTLPR) in evolutionary perspective: alternative biallelic variation in rhesus monkeys. Rapid communication." J Neural Transm 104(11-12): 1259-66.
Leung, J. Y., F. E. McKenzie, et al. (2000). "Identification of phylogenetic footprints in primate tumor necrosis factor-alpha promoters." Proc Natl Acad Sci U S A 97(12): 6614-8.
Li, S. and R. J. Loos (2008). "Progress in the genetics of common obesity: size matters." Curr Opin Lipidol 19(2): 113-21.
Miller, G. M., J. Bendor, et al. (2004). "A mu-opioid receptor single nucleotide polymorphism in rhesus monkey: association with stress response and aggression." Mol Psychiatry 9(1): 99-108.
Mutch, D. M. and K. Clement (2006). "Genetics of human obesity." Best Pract Res Clin Endocrinol Metab 20(4): 647-64.
103
NHANES. (2007). "National Health and Nutrition Examination Survey." from http://www.cdc.gov/nchs/nhanes.htm.
NHLBI (2000). The Practical Guide: Identification, Evaluation, and Treatment of Overweight and Obesity in Adults. Washington DC, NHLBI produced publications: 88.
Norris, J. M., C. D. Langefeld, et al. (2009). "Genome-wide Association Study and Follow-up Analysis of Adiposity Traits in Hispanic Americans: The IRAS Family Study." Obesity (Silver Spring).
Pasquali, R., V. Vicennati, et al. (2006). "The hypothalamic-pituitary-adrenal axis activity in obesity and the metabolic syndrome." Ann N Y Acad Sci 1083: 111-28.
Risch, N. J. (2000). "Searching for genetic determinants in the new millennium." Nature 405(6788): 847-56.
Roche, H. M., C. Phillips, et al. (2005). "The metabolic syndrome: the crossroads of diet and genetics." Proc Nutr Soc 64(3): 371-7.
Roseboom, T. J., J. H. van der Meulen, et al. (2001). "Effects of prenatal exposure to the Dutch famine on adult disease in later life: an overview." Mol Cell Endocrinol 185(1-2): 93-8.
Schneider, J. G., C. Tompkins, et al. (2006). "The metabolic syndrome in women." Cardiol Rev 14(6): 286-91.
Scriver, C. R. (2001). The metabolic & molecular bases of inherited disease. New York, McGraw-Hill.
Shiina, T., M. Ota, et al. (2006). "Rapid evolution of major histocompatibility complex class I genes in primates generates new disease alleles in humans via hitchhiking diversity." Genetics 173(3): 1555-70.
Shively, C. A. and T. B. Clarkson (1988). "Regional obesity and coronary artery atherosclerosis in females: a non-human primate model." Acta Med Scand Suppl 723: 71-8.
Taylor, P. D. and L. Poston (2007). "Developmental programming of obesity in mammals." Exp Physiol 92(2): 287-98.
Tsai, E. Y., J. V. Falvo, et al. (2000). "A lipopolysaccharide-specific enhancer complex involving Ets, Elk-1, Sp1, and CREB binding protein and p300 is recruited to the tumor necrosis factor alpha promoter in vivo." Mol Cell Biol 20(16): 6084-94.
Tsai, E. Y., J. Jain, et al. (1996). "Tumor necrosis factor alpha gene regulation in activated T cells involves ATF-2/Jun and NFATp." Mol Cell Biol 16(2): 459-67.
Tsai, E. Y., J. Yie, et al. (1996). "Cell-type-specific regulation of the human tumor necrosis factor alpha gene in B cells and T cells by NFATp and ATF-2/JUN." Mol Cell Biol 16(10): 5232-44.
Tsytsykova, A. V. and A. E. Goldfeld (2002). "Inducer-specific enhanceosome formation controls tumor necrosis factor alpha gene expression in T lymphocytes." Mol Cell Biol 22(8): 2620-31.
USHHS (2007). Overweight and Obesity: A Vision for the Future. van der Steeg, W. A., I. Holme, et al. (2008). "High-density lipoprotein cholesterol, high-
density lipoprotein particle size, and apolipoprotein A-I: significance for
104
cardiovascular risk: the IDEAL and EPIC-Norfolk studies." J Am Coll Cardiol 51(6): 634-42.
Wagner, J. D., J. D. Bagdade, et al. (1996). "Increased glycation of plasma lipoproteins in diabetic cynomolgus monkeys." Lab Anim Sci 46(1): 31-5.
Wagner, J. D., C. S. Carlson, et al. (1996). "Diabetes mellitus and islet amyloidosis in cynomolgus monkeys." Lab Anim Sci 46(1): 36-41.
Wagner, J. D., J. M. Cline, et al. (2001). "Naturally occurring and experimental diabetes in cynomolgus monkeys: a comparison of carbohydrate and lipid metabolism and islet pathology." Toxicol Pathol 29(1): 142-8.
Wagner, J. E., K. Kavanagh, et al. (2006). "Old world nonhuman primate models of type 2 diabetes mellitus." ILAR J 47(3): 259-71.
Watts, G. F., P. H. Barrett, et al. (2008). "HDL metabolism in context: looking on the bright side." Curr Opin Lipidol 19(4): 395-404.
Wellen, K. E. and G. S. Hotamisligil (2005). "Inflammation, stress, and diabetes." J Clin Invest 115(5): 1111-9.
West, D. B. and B. York (1998). "Dietary fat, genetic predisposition, and obesity: lessons from animal models." Am J Clin Nutr 67(3 Suppl): 505S-512S.
Wyatt, S. B., K. P. Winters, et al. (2006). "Overweight and obesity: prevalence, consequences, and causes of a growing public health problem." Am J Med Sci 331(4): 166-74.
Zhang, Y., R. Proenca, et al. (1994). "Positional cloning of the mouse obese gene and its human homologue." Nature 372(6505): 425-32.
Zheng, X., C. M. Kammerer, et al. (2009). "Association of SLC34A2 variation and sodium-lithium countertransport activity in humans and baboons." Am J Hypertens 22(3): 288-93.
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CHAPTER V
CLINICOPATHOLOGIC CHARACTERIZATION OF NATURALLY OCCURRING DIABETES MELLITUS IN VERVET MONKEYS
Jennifer A. Cann, Kylie Kavanagh, Sunish Mohanan, Matthew J. Jorgensen, Stanton B. Gray, Timothy D. Howard, Lynn A. Fairbanks, Gregory A. Hawkins, Janice D. Wagner
The following manuscript will be submitted for publication to the journal Veterinary
Pathology. Stylistic variations are due to the requirements of the journal. Dr. J.A. Cann
prepared the manuscript which is an expansion of the following: Gray SB, Cann JA,
Trybus JA, Kavanagh K, Wagner JD. Characterization of clinical pathology and pancreatic
islet pathology in captive, spontaneously diabetic vervet monkeys. J of Am Assoc of Lab
Anim Sci 2007, 46(4), abstr P25. Dr. S.B. Gray prepared this abstract and poster
presentation and was directly involved in gene sequencing and interpretation.
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ABSTRACT
Diabetes mellitus (DM) is a group of chronic metabolic diseases characterized by
hyperglycemia due to defects in insulin production, secretion, or action in target tissues.
Numerous subtypes of DM have been identified including the polygenic forms, Type 1
and Type 2. Animal models have played an important role in elucidating the
pathophysiology of Type 1 and Type 2 DM. In contrast to the polygenic forms, some
monogenic forms display normal body weight and insulin production, and islet
amyloidosis is not seen. We describe 4 cases of naturally occurring diabetes mellitus in
vervet monkeys (Chlorocebus aethiops sabaeus), three of which have presentation and
inheritance patterns resembling an atypical monogenic form of diabetes.
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INTRODUCTION
Diabetes mellitus (DM) is a group of chronic metabolic diseases characterized by
hyperglycemia due to defects in insulin production, secretion, or action in target tissues.
Numerous subtypes of DM have been identified including Type 1, Type 2, and Maturity
Onset Diabetes of the Young (MODY). Animal models have played an important role in
elucidating the pathophysiology of Type 1 and Type 2 DM, however, monogenic forms
of diabetes have not previously been characterized in NHPs.
Type 1 DM is a polygenic autoimmune disease in which pancreatic beta cells are
targeted and destroyed.(Pinkse, Tysma et al. 2005) It presents more commonly in
children and adolescents than adults, however adult-onset Type 1 DM does occur.
Treatment generally consists of exogenous insulin administration, although pancreatic
islet cell transplantation is being investigated experimentally.(Rood, Buhler et al.
2006),(Gaur 2004) Spontaneous Type 1 DM occurs at a low frequency in
macaques.(Wagner, Cline et al. 2001) Other useful animal models of Type 1 DM include
the NOD mouse and streptozotocin-treated animals.(von Herrath and Nepom
2009),(Thomas, Contreras et al. 2001; Contreras, Smyth et al. 2004),(Gaur, Nepom et al.
2001) Conversely, Type 2 DM more commonly develops in adults, but prevalence in
children is increasing as childhood obesity incidence grows. This form of DM accounts
for >90% of overall diabetes prevalence, with U.S. and worldwide incidence increasing at
epidemic rates.(Zimmet, Alberti et al. 2001) This is a complex, polygenic form of the
disease in which persistent insulin resistance in target tissues (e.g. liver, muscle, fat)
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results in a compensatory increase in pancreatic insulin production in attempts to
maintain euglycemia. Insulin secretion is accompanied by co-production of islet amyloid
polypeptide, also known as amylin. Amylin has been shown to induce beta cell
apoptosis, (Huang, Lin et al. 2007) and the accumulation of islet amyloid with
concurrent islet cell loss is a hallmark of Type 2 DM. Of its 37 constituent amino acids,
the amyloidogenic properties of the amylin protein are thought to result from a lack of
proline within amino acid residues 20-29.(Westermark, Engstrom et al. 1990) This lack
of proline within the amyloidogenic region has been demonstrated in people,
macaques, dogs, and cats with naturally occurring Type 2 DM.(Westermark, Engstrom et
al. 1990; O'Brien, Wagner et al. 1996) Conversely, rodent species have proline residues
within this region, and amyloid deposition does not occur unless the human IAPP gene is
inserted experimentally.(D'Alessio, Verchere et al. 1994) In macaques, the close
phylogenetic relationship to humans, their similar reproductive and endocrine
physiology to humans, and their potential to exhibit spontaneous obesity and insulin
resistance, make them a valuable animal model of Type 2 DM.(O'Brien, Wagner et al.
1996; Wagner, Carlson et al. 1996; Wagner, Kavanagh et al. 2006)
MODY is a heterogeneous group of disorders which comprises about 5% of the clinical
cases of diabetes in the U.S. and the world.(Fajans, Bell et al. 2001) There are at least six
types, each associated with monogenic mutations in different autosomal genes: HNF4A
(hepatic nuclear factor 4 alpha; MODY 1), GCK (glucokinase; MODY 2), HNF1A (MODY 3),
IPF1 (insulin promoter factor 1; MODY 4), HNF1B (MODY 5), and NEUROD1 (neurogenic
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differentiation 1; MODY 6). Of these, all except glucokinase (GCK, MODY 2) are
transcription factors which regulate expression of insulin and other proteins involved in
glucose metabolism and transport within the pancreatic beta cell.(Fajans, Bell et al.
2001) The result of these mutations is defective glucose sensing or insulin signaling
resulting in impaired insulin secretion in the face of normal or near-normal insulin
production and islet morphology.
We describe 4 cases of naturally occurring diabetes mellitus in vervet monkeys
(Chlorocebus aethiops sabaeus), three of which have clinicopathologic and inheritance
similarities to a monogenic form of diabetes, perhaps similar to MODY.
MATERIALS AND METHODS
Animals
All four vervets were part of the multigenerational pedigreed Vervet Research Colony
(VRC), currently located at Wake Forest University Primate Center. The VRC was
founded in 1975 at UCLA from founder animals (28 males, 29 females) wild caught from
1975-1983 in St. Kitts, West Indies, as described in McGuire (1974)(McGuire 1974) and
Fairbanks et al (2004).(Fairbanks, Newman et al. 2004) The current population consists
of ~500 descendants with 24 of the original matrilines now in their 2nd to 8th generation.
All animals were handled in accord with the Guide for the Care and Use of Laboratory
Animals, the Institutional Animal Care and Use Committee at Wake Forest University
Health Sciences, and the Animal Research Committee at UCLA. Diet consisted of a
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commercial primate laboratory chow relatively low in fat and high in fiber, as well as
fresh fruits, vegetables and water ad libitum.
Clinical Pathology
Animals were fasted overnight and sedated with ketamine hydrochloride (10-15mg/kg
IM) (Ketaset, Fort Dodge Animal Health, Fort Dodge, IA) prior to examination and
sample collection. Circulating glucose, insulin, HbA1c, and triglyceride concentrations
were determined as previously reported.(Kavanagh, Fairbanks et al. 2007) Briefly,
glucose was measured in whole blood by glucometer (One Touch Ultra Glucometer;
Lifescan, Inc., Milpitas, CA) or in plasma by the glucose oxidase method (Roche, Basel,
Switzerland). Samples were analyzed for insulin and glycation of hemoglobin A1c
(HbA1c) using a commercial ELISA kit (Mercodia, Uppsala, Sweden) and via HPLC (Primus
PDQ, Primus Diagnostics, Kansas City, MO), respectively. (Kavanagh 2007) Triglycerides
were measured enzymatically. Body condition was assessed on routine physical
examination by an experienced primate veterinarian.
Histopathology and Immunohistochemistry
5um sections of formalin-fixed paraffin-embedded pancreata from each animal were
stained with hematoxylin & eosin (H&E) and Congo Red. For immunohistochemistry
5um sections were incubated with guinea pig anti-insulin polyclonal antibody
(prediluted; Biomeda, Foster City, CA), rabbit anti-glucagon polyclonal antibody
(prediluted; BioGenex, San Ramon, CA), or rabbit anti-amylin polyclonal antibody (1:75;
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BioGenex, San Ramon, CA) for 75 minutes at 35°C. Pancreas from a diabetic cynomolgus
macaque (Macaca fascicularis) was used as positive control tissue and the negative
controls were incubated with non-immune sera instead of primary antibody for 75
minutes at 35°C. Primary antibodies were localized with appropriate biotinylated
secondary antibodies, streptavidin-alkaline phosphatase (Biogenex, San Ramon, CA) and
Vector Red (Vector Labs, Burlingame, CA) substrate. Sections were counterstained with
Mayer’s Hematoxylin and examined by light microscopy by a board-certified veterinary
pathologist (JAC).
Amylin PCR and Amino Acid Sequencing
Genomic DNA was isolated from peripheral blood samples using standard protocols. For
DNA sequencing, PCR primers were generated with the PrimerSelect software (Laser
Gene software, DNASTAR, Madison, WI.) using a consensus amylin (IAPP) gene
sequence created from human, chimpanzee (Pan troglodytes) and rhesus monkey
(Macaca mulatta) found in the NCBI gene database (www.ncbi.nlm.nih.gov;
NC_000012.10, NC_006479.2, NC_007868.1 respectively). Primer consensus sequences
were created using the editing feature in Sequencher v4.6 (Gene Codes Corp., Ann
Arbor, MI), and were designed to amplify the IAPP gene encompassing the
amyloidogenic region. PCR conditions were as follows: initial denaturation at 95oC for
10 min, followed by 30 cycles of 96oC for 1 min, 58oC for 1 min and 72oC for 60 sec with
final elongation for 10 min at 72oC in a 20-µl reaction mixture. PCR products were
purified (QuickStep, Edge Biosystems Inc., Gaithersburg, MD) to remove dNTPs and
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excess primers that interfere with sequencing reactions. Purified PCR products were
sequenced using dye-terminator chemistry (BigDye, ABI, Foster City, CA). Dye-
terminator reactions were performed in 5-10 µl reactions in 96-well plates. The dye-
terminator kit was diluted fourfold using a 2.5X dilution buffer (50 mM Tris, 10 mM
MgCl2 pH 9.0). Sequencing reactions were purified by ethanol precipitation prior to
loading on an ABI3730XL DNA Analyzer using the POP7 sequencing polymer. Nucleotide
gene sequence was evaluated using Sequencher v4.6, and the proper protein coding
reading frame, and hence amino acid sequence, was determined through sequence
comparison to human, chimp, and rhesus monkey.
RESULTS
Clinical Findings
Routine clinical examination of animals within the VRC between 2001 and 2008 revealed
a number of vervets with fasting hyperglycemia (Kavanagh et al. 2007). Four adult
female vervets with mild to moderate fasting hyperglycemia are presented here.
Monkey 982 was mildly overweight, and 978 and 1005 were in average body condition.
Monkey 1988-014 had a previous history of weight gain followed by gradual weight loss
in response to dietary management. Age, body weight, fasting blood glucose
concentrations, HbA1c, and plasma insulin and triglyceride concentrations are shown in
Table 1. Age-matched means for vervets and values from a cynomolgus macaque with
Type 2 DM are shown for comparison. Serum insulin and glucose tolerance test results
for animals 978 and 982 are shown in Figure 1; values from a non-diabetic vervet (979)
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Table 1. Clinical Characteristics
NS = not sampled
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Figure 1. Glucose (top) and insulin (bottom) responses during intravenous glucose
tolerance tests in diabetic (982, 978) and nondiabetic (979) monkeys
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are shown for comparison.
Monkeys 978 and 1005 had a 6-month and 2-month history of DM, respectively, and
were managed with parenteral NPH insulin (Novolin 70/30; NovoNordisk, Bagsvaerd,
Denmark) at a dose adapted from diabetic cynomolgus macaques (Wagner et al. 1996).
Both animals were found to be very sensitive to parenteral insulin as evidenced by rapid
rebounding hypoglycemia. Both animals succumbed to hypoglycemic complications
within four months of initiation of insulin therapy. Animal 982 had a 3-year history of
mild to moderate fasting hyperglycemia (72-119 mg/dL) and did not require insulin
therapy. Final clinical examination revealed a grade II-III heart murmur, hypothermia
(91.8°F), hyperglycemia (301mg/dL), severe anemia (HCT 7.5%), azotemia (BUN 70
mg/dL), and hyperkalemia (3.1 mEq/L); humane euthanasia was elected. Animal 1988-
014 had a 6-year history of intermittent fasting hyperglycemia (75-165 mg/dL), and also
did not receive insulin therapy. This monkey was euthanized and sections of pancreas
were fixed in10% neutral buffered formalin and submitted to WFUPC for histologic
evaluation.
Pathologic Findings
All animals underwent complete diagnostic necropsies with gross and histologic
evaluations of all major organs, except 1988-014 in which case only formalin-fixed
pancreas was examined. No gross lesions were noted in the pancreata or in any other
organs involved in glucose metabolism (liver, adrenal glands, pituitary gland). Pancreatic
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histology was normal in monkeys 978, 1005, and 1988-014. In monkey 982, multifocal,
mild to moderate, segmental amyloidosis was seen on H&E and confirmed with Congo
Red staining (Figure 2). In all four cases, immunohistochemistry for insulin, glucagon,
and amylin revealed diffuse, moderate to intense, cytoplasmic staining within 60-90% of
pancreatic islet cells (Figure 2). In monkey 982, insulin staining was reduced in islets
containing amyloid. For comparison, pancreas from a Type 2 DM cynomolgus macaque
(Macaca fascicularis) was examined and marked diffuse effacement of pancreatic islets
by pale eosinophilic, relatively acellular, hyaline material which stained pale orange-pink
with Congo Red (amyloid) was seen. Immunohistochemistry for insulin revealed intense
cytoplasmic staining in <10% of islet cells; and moderate to intense cytoplasmic staining
for glucagon was seen in 30-90% of islet cells. Anti-amylin staining was diffuse and
intense in nearly all islets (Figure 2).
Amylin Sequencing
Hypothesizing that the lack of amyloid accumulation within pancreatic islets of diabetic
vervets may be due to the presence of a proline within the amyloidogenic region of the
amylin protein, we sequenced the amylin gene (IAPP) and extrapolated the amino acid
sequence for vervet amylin. Results are shown in Figure 3. Similar to humans,
macaques, dogs, and cats, (Westermark, Engstrom et al. 1990; O'Brien, Wagner et al.
1996) no proline residues are predicted in the amyloidogenic region.
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Figure 2. All images 200X magnification; bars = 100um
Panels A-O: Pancreatic histology and immunohistochemistry of three vervet monkeys
suspected to have MODY: 978, 1988-014, 1005. H&E: normal morphology of pancreatic
islets and surrounding exocrine acini. Congo Red: normal; no staining within islets
Insulin, glucagon, and amylin immunohistochemistry: normal; diffuse, moderate to
intense, cytoplasmic staining within 60-90% of pancreatic islet cells.
Panels P-T: Pancreatic histology and immunohistochemistry of vervet monkey
suspected to have Type 2 DM. H&E: upper islet is normal; in the lower islet the
preexisting endocrine cells are replaced by pale eosinophilic acellular hyaline material
(amyloid). Congo Red: pale pink-orange staining in areas expanded amyloid
Insulin immunohistochemistry: reduced insulin staining in islets containing amyloid.
Glucagon, and amylin immunohistochemistry: normal
Panels U-Y: Pancreatic histology and immunohistochemistry of confirmed Type 2 DM in
a cynomolgus macaque (Macaca fascicularis). H&E: Marked diffuse effacement of
pancreatic islets by pale eosinophilic, relatively acellular, hyaline material (amyloid);
adipocyte infiltration throughout the exocrine pancreas. Congo Red: pale pink-orange
staining in areas expanded amyloid. Insulin immunohistochemistry: reduced insulin
staining (<10%) in islets containing amyloid. Glucagon and amylin
immunohistochemistry: normal
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Figure 2. Pancreatic Histology and Immunohistochemistry
H&E Congo Red Insulin Glucagon Amylin
978 1988-014 1005
982
Type 2 DM control (M. fascicularis)
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Figure 3. Comparison of amylin amino acid sequences
1 8 18 29 37
Human KCNTATCATQRLANFLVHSSNNFGAILSSTNVGSNTY
Macaque -----------------R------T----------D—
Vervet -----------------R------T-----D------
Cat ----------------IR----L------P-------
Dog -----------------RT---L------P-------
Rat -----------------R----L-PV-PP--------
Mouse -----------------R----L-PV-PP--------
Figure 3. Amino acid sequence comparison of amylin between various species. Vervet
sequence determined by extrapolation from nucleotide sequence, whereas others were
by both nucleotide and direct amino acid sequencing reported previously in the
literature. Human, macaque, vervet, dog, and cat sequences reveal a lack of proline
within the amyloidogenic region (yellow).
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Pedigree Analysis
Given that the MODY form of DM in humans is passed as an autosomal dominant trait,
we evaluated blood glucose concentrations of relatives of animal 1988-014. This animal
had five offspring, from three different fathers, and all offspring had elevated fasting
blood glucose concentrations (Figure 4). In addition, a maternal half-sibling of 1988-014,
1989-017, also had elevated fasting blood glucose concentrations. These pedigree data
are consistent with either an autosomal dominant or mitochondrial inheritance pattern.
DISCUSSION
Clinical diagnosis of DM is not difficult as blood glucose concentrations are routinely
measured and hyperglycemia is easily identified. However, differentiating between the
different types of DM can be challenging. Described here, the clinicopathologic
presentation of monkey 982 was similar to cynomolgus macaques with Type 2 DM
where overweight body condition, persistent hyperglycemia, islet amyloidosis, and
reduced insulin staining are common features. This is in contrast to animals 978, 1005,
and 1988-014, all of whom presented in a manner more closely resembling MODY in
humans. With MODY, obesity, islet amyloidosis, and reduced insulin production are not
primary features, and were not found in these three cases. In addition, with MODY,
insulin sensitivity in target tissues is maintained, and at least two of these animals were
found to be extremely sensitive to exogenous insulin therapy. Thus, from a clinical
perspective these findings indicate that it is important to determine the type of DM in
monkeys before initiating therapy. In human medicine, MODY is generally considered
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Figure 4. Pedigree Analysis
Figure 4. A familial pattern of increased blood glucose concentrations of relatives of
animal 1988-014 are depicted by solid symbols. This animal had five offspring, from
three different fathers, and all offspring had elevated fasting blood glucose
concentrations. A maternal half-sibling of 1988-014, 1989-017, also had elevated fasting
blood glucose concentrations. These pedigree data are consistent with either an
autosomal dominant or mitochondrial inheritance pattern.
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easier to manage than the polygenic Type 1 and Type 2 forms of DM; oral hypoglycemic
agents are generally sufficient, although parenteral insulin therapy is sometimes
required.(Fajans, Bell et al. 2001) It is also important to note that while in our cases the
animals were adults at the time of diagnosis, and in spite of its name, MODY can present
clinically in both adults and adolescents.(Fajans, Bell et al. 2001). It is not the intention
of this report to suggest the atypical presentation of diabetes is similar to MODY.
However, there are apparent similarities in some cliniopathologic features and
inheritance patterns.
Prior to presentation of monkey 982, we suspected that the vervet amylin gene might
contain proline residues within its amyloidogenic region, thus preventing amyloid
accumulation. However, extrapolation of the amino acid sequence revealed that a
proline residue is not predicted in this region (amino acids 20-29), which suggests that
vervets are indeed susceptible to the development of islet amyloidosis, as we later saw
in monkey 982. In addition, a recent publication describes three different types of
amyloidosis in an aged male vervet, including islet amyloidosis.(Nakamura, Okabayashi
et al. 2008)
Interestingly, pedigree analysis of animal 1988-014 revealed that all five of this animal’s
offspring were hyperglycemic. These cases may represent a less common, but also
monogenic and highly heritable form of DM, referred to as “mitochondrial diabetes”
due to its association with mutations in mitochondrial DNA.(Maassen, LM et al. 2004)
123
The hallmark of mitochondrial inheritance is that all offspring of affected mothers are
affected, whereas no offspring from affected fathers are affected since fathers
contribute little to no mitochondria to their offspring. In mitochondrial diabetes, gradual
aging-associated beta cell dysfunction is the main mechanism by which glucose
intolerance develops. In our atypical cases, insulin production as assessed
immunohistochemically was within normal limits, making this form less likely. In
humans, definitive diagnosis of MODY is made via genetic testing of target genes,
including HNF4A (MODY 1), GCK (MODY 2), HNF1A (MODY 3), IPF1 (MODY 4), HNF1B
(MODY 5), and NEUROD1 (MODY 6).(Fajans, Bell et al. 2001). It is possible that the
current linkage map for the vervet monkey (Jasinska, Service et al. 2007) could aid in
identifying a candidate region responsible for this apparently monogenic atypical form
of diabetes.
Acknowledgments This work was funded, in part, by the Wake Forest University School
of Medicine Venture Fund, the Skorich Diabetes Research Fund, the Monty Blackmon
Diabetes Research Fund (JDW), T32 RR07009 from NIH/NCRR (SBG), and an Animal and
Biological Materials Resources grant from the National Center for Research Resources
(P40RR019963: original PI, Lynn Fairbanks, UCLA; current PI, Jay Kaplan, Wake Forest).
The authors would also like to thank Drs. Nelson Friemer (UCLA) and Jay Kaplan
(WFUSM) for their input and collaboration and Abdoulaye Diallo for technical support.
124
REFERENCES
1 Contreras JL, Smyth CA, Curiel DT, Eckhoff DE: Nonhuman primate models in type 1 diabetes research. ILAR J 45: 334-342, 2004
2 D'Alessio DA, Verchere CB, Kahn SE, Hoagland V, Baskin DG, Palmiter RD, Ensinck JW: Pancreatic expression and secretion of human islet amyloid polypeptide in a transgenic mouse. Diabetes 43: 1457-1461, 1994
3 Fairbanks LA, Newman TK, Bailey JN, Jorgensen MJ, Breidenthal SE, Ophoff RA, Comuzzie AG, Martin LJ, Rogers J: Genetic contributions to social impulsivity and aggressiveness in vervet monkeys. Biol Psychiatry 55: 642-647, 2004
4 Fajans SS, Bell GI, Polonsky KS: Molecular mechanisms and clinical pathophysiology of maturity-onset diabetes of the young. N Engl J Med 345: 971-980, 2001
5 Gaur LK: Nonhuman primate models for islet transplantation in type 1 diabetes research. ILAR J 45: 324-333, 2004
6 Gaur LK, Nepom GT, Lernmark A: Low-dose streptozotocin induces sustained hyperglycemia in Macaca nemestrina. Autoimmunity 33: 103-114, 2001
7 Huang CJ, Lin CY, Haataja L, Gurlo T, Butler AE, Rizza RA, Butler PC: High expression rates of human islet amyloid polypeptide induce endoplasmic reticulum stress mediated beta-cell apoptosis, a characteristic of humans with type 2 but not type 1 diabetes. Diabetes 56: 2016-2027, 2007
8 Kavanagh K, Fairbanks LA, Bailey JN, Jorgensen MJ, Wilson M, Zhang L, Rudel LL, Wagner JD: Characterization and heritability of obesity and associated risk factors in vervet monkeys. Obesity (Silver Spring) 15: 1666-1674, 2007
9 Maassen JA, LM TH, Van Essen E, Heine RJ, Nijpels G, Jahangir Tafrechi RS, Raap AK, Janssen GM, Lemkes HH: Mitochondrial diabetes: molecular mechanisms and clinical presentation. Diabetes 53 Suppl 1: S103-109, 2004
10 McGuire MT: The St. Kitts vervet (Cercopithecus aethiops). J Med Primatol 3: 285-297, 1974
11 Nakamura S, Okabayashi S, Ageyama N, Koie H, Sankai T, Ono F, Fujimoto K, Terao K: Transthyretin amyloidosis and two other aging-related amyloidoses in an aged vervet monkey. Vet Pathol 45: 67-72, 2008
12 O'Brien TD, Wagner JD, Litwak KN, Carlson CS, Cefalu WT, Jordan K, Johnson KH, Butler PC: Islet amyloid and islet amyloid polypeptide in cynomolgus macaques (Macaca fascicularis): an animal model of human non-insulin-dependent diabetes mellitus. Vet Pathol 33: 479-485, 1996
13 Pinkse GG, Tysma OH, Bergen CA, Kester MG, Ossendorp F, van Veelen PA, Keymeulen B, Pipeleers D, Drijfhout JW, Roep BO: Autoreactive CD8 T cells associated with beta cell destruction in type 1 diabetes. Proc Natl Acad Sci U S A 102: 18425-18430, 2005
14 Rood PP, Buhler LH, Bottino R, Trucco M, Cooper DK: Pig-to-nonhuman primate islet xenotransplantation: a review of current problems. Cell Transplant 15: 89-104, 2006
15 Thomas JM, Contreras JL, Smyth CA, Lobashevsky A, Jenkins S, Hubbard WJ, Eckhoff DE, Stavrou S, Neville DM, Jr., Thomas FT: Successful reversal of streptozotocin-
125
induced diabetes with stable allogeneic islet function in a preclinical model of type 1 diabetes. Diabetes 50: 1227-1236, 2001
16 von Herrath M, Nepom GT: Animal models of human type 1 diabetes. Nat Immunol 10: 129-132, 2009
17 Wagner JD, Carlson CS, O'Brien TD, Anthony MS, Bullock BC, Cefalu WT: Diabetes mellitus and islet amyloidosis in cynomolgus monkeys. Lab Anim Sci 46: 36-41, 1996
18 Wagner JD, Cline JM, Shadoan MK, Bullock BC, Rankin SE, Cefalu WT: Naturally occurring and experimental diabetes in cynomolgus monkeys: a comparison of carbohydrate and lipid metabolism and islet pathology. Toxicol Pathol 29: 142-148, 2001
19 Wagner JE, Kavanagh K, Ward GM, Auerbach BJ, Harwood HJ, Jr., Kaplan JR: Old world nonhuman primate models of type 2 diabetes mellitus. ILAR J 47: 259-271, 2006
20 Westermark P, Engstrom U, Johnson KH, Westermark GT, Betsholtz C: Islet amyloid polypeptide: pinpointing amino acid residues linked to amyloid fibril formation. Proc Natl Acad Sci U S A 87: 5036-5040, 1990
21 Zimmet P, Alberti KG, Shaw J: Global and societal implications of the diabetes epidemic. Nature 414: 782-787, 2001
126
CHAPTER VI
OVERALL DISCUSSION AND CONCLUSIONS
127
The purpose of this study was to further genetically define the St. Kitts-origin
vervet monkey (Chlorocebus aethiops ssp.) as a model for polygenic obesity and its
inflammation-related comorbidities, specifically T2D. As an initial step towards that
ongoing objective, the gene for TNF-alpha was chosen to sequence and analyze for
genetic variants within the VRC population. Utilizing bioinformatic analyses, that
sequence was used to determine percentage identity among the St. Kitts-origin vervet
monkey, human, and other NHPs used in biomedical research, providing an initial
baseline validation. Further, sequence information was utilized to perform phylogenetic
analyses using the TNF putative promoter region to provide greater insight into the
uncertain taxonomic classification of the St. Kitts vervet. Polymorphisms within TNF and
its flanking regions were similarly compared, in regards to placement and spacing,
among the St. Kitts-origin vervet, human, and other NHPs using the NCBI database and
NHP literature reports. Lastly, leveraging the pedigree information of the VRC to match
genotype information with previously defined obesity-related phenotypes, association
analyses were performed to determine if any particular alleles, genotypes, or
haplotypes were associated with, and presumably conferred risk for, obesity and
obesity-related traits in the St. Kitts-origin vervet monkey. Concurrent with the central
thesis project involving genetic characterization were continued efforts to
phenotypically characterize the clinopathologic presentation of naturally-occurring
diabetes in the St. Kitts-origin vervet. The results of these investigations into the
diabetic disease phenotype have significant implications on the genetic association
results presented here.
128
Initial validation consisted of sequencing 24 St. Kitts vervet monkeys presumably
unrelated to St. Kitts-origin vervets of the VRC. This was done as proof of principle to
demonstrate that the St. Kitts-origin vervets of the VRC were not genetically dissimiliar
in sequence or variation from vervets taken directly from the island of St. Kitts. We
showed that sequence between these 24 and the 265 of the VRC had exact sequence
indentity for the orthologous TNF gene and its flanking regions, and that the genetic
polymorphisms were essentially identical. The only discrepancy was that an additional
rare SNP (MAF 0.078) at +2681 (Chapter 2, Table 1) was discovered upon sequencing
the 265 monkeys of the VRC. This was not unexpected given that the power to detect
genetic polymorphisms with MAF of 0.05 or greater was 91.47% in 24 unrelated
monkeys (using the equation P = 1-(1-fq)2N where P = power to detect polymorphism; fq
= the lowest frequency of detection desired; 2N = number of chromosomes screened,
where N = number of DNA samples). This finding suggests that genetic variation has
been maintained within the VRC despite the current gene pool being derived from 57
founders (28 males, 29 females) wild caught from St. Kitts from 1975-1983. One
practical ramification of this finding is that the unrelated 24 have been validated as a
SNP screen for the VRC thereby saving considerable expense and time for any future
genotyping of TNF or sequencing/genotyping of other candidate genes within the VRC.
Additional proof-of-priniciple validation came from comparing orthologous St.
Kitts-origin vervet TNF gene sequence with human, and other NHPs used in biomedical
research. Sequence identity of TNF between vervet and human is 93-94%, nearly
129
identical to rhesus macaque compared to human; further, vervet and rhesus share 98-
99% identity (Chapter 2, Tables 3A &B). Distance matrices (D.M.), which weigh
nucleotide position in each codon of the reading frame, are estimates of evolutionary
divergence with lower scores indicating more recent divergence, and thus closer
phylogenetic relationships. Percentages of sequence identities and distance matrices
among St. Kitts-origin vervet, rhesus macaque, chimpanzee, and human appear to agree
with published phylogenetic relationships based on intronic regions of the serum
albumin gene (Page & Goodman, 2001).
The third aspect of the initial characterization of TNF which falls under the
category of proof-of-principle involves analysis of the LD structure, which demonstrated
that 11 of the 12 polymorphisms along the entire orthologous vervet TNF gene, were
contained within a single haplotype block (Chapter 2, Figure 1). Many of the
polymorphisms within this block were found to be in strong or complete LD with one
another which is consistent with expectations, as many genes within the primate MHC
region have been shown to be in strong LD (Shiina, Ota et al. 2006), often yielding
extended haplotypes (Ceppellini, Siniscalco et al. 1955).
A total of five SNPs within the 5’ UTR and putative promoter region, with
another six SNPs plus one insertion/deletion polymorphism in the intronic and 3’ UTR of
the orthologous St. Kitts-origin vervet TNF gene and flanking regions is reported here
(Chapter 2, Figure 1). This is the most extensive report of SNPs, haplotypes, and LD for
130
any NHP of the TNF gene and flanking regions, as well as the first report of complete
TNF gene sequence for any Chlorocebus species. Not only are these orthologous vervet
TNF putative promoter SNPs shown to be non-randomly and non-uniformly distributed
outside TF binding sites and other conserved regions, but this is also true for reported
SNPs in the same region of human, chimpanzee, and rhesus macaque (Chapter 2, Table
4). In addition, the consensus of all SNPs from all four of these species demonstrates
the same non-uniform, non-random distribution. The fact that SNPs in all four species
cluster together in two regions on the TNF promoter/enhancer region is particularly
interesting (Chapter 2, Figure 3B). That is, SNP clusters are within 50 nucleotides of
three important human SNPs ( -308 and -857/-863) which have been significantly
associated with numerous inflammatory- and immune-related phenotypes, including
BMI, WC, and TPC (Chapter 1, Table 2) (Fernandez-Real 2006). Thus, the distribution of
SNPs along the orthologous vervet TNF putative promoter can be described as
analogous to that of human. This observation hints that polymorphisms in these
specific regions across species could be important in modulating transcription of TNF,
with presumed subsequent phenotypic effect, upon which natural selection may act. A
logical question to follow from such an observation is whether NHP polymorphisms in
these clustered regions similarly associate with NHP obesity-related phenotypes (or
indeed any of the numerous immune- and inflammation-related phenotypes) as has
been demonstrated in humans.
131
To put the results and conclusions of the vervet association analyses in
perspective, it is useful to first briefly summarize the results, assumptions and
limitations of selected human TNF association studies at the -308 promoter locus. In
vitro results from Wilson et al. (1997) and Kroeger et al. (1997) have shown that the -
308 A allele increases transcriptional activation of the TNF gene. Although there have
been a number of inconsistencies, the majority of in vivo human association studies
have reported an association between the -308 A allele and obesity and related traits
(Sookoian, Gonzalez et al. 2005). These inconsistencies are presumed to be a function
of the inherent limitations of human studies. Namely, 1) there is a large degree of
uncontrolled environmental variability affecting the phenotype, 2) genetic and
phenotypic associations are partly a function of correlation between traits and, 3)
genetic associations can vary by the ethnicity and/or admixture of the study population
(Fernandez and Shiver 2004; Enoch, Shen et al. 2006).
Selected association reports between the -308 A allele and the following obesity-
related phenotypes are summarized here: BMI (Hoffstedt, Eriksson et al. 2000;
Corbalan, Marti et al. 2004), WC (Corbalan, Marti et al. 2004), impaired glucose
tolerance (Kubaszek, Pihlajamaki et al. 2003), insulin resistance (Dalziel, Gosby et al.
2002; Wybranska, Malczewska-Malec et al. 2003), TG (Wybranska, Malczewska-Malec et
al. 2003), and decreased HDL-C (Dalziel, Gosby et al. 2002). Interestingly, all of these
reports found associations within groups classified as obese and/or T2D. Examples of
reports which failed to show associations between -308 A and diabetic or obesity
132
phenotypes involved non-obese or non-diabetic control groups (Hamann, Mantzoros et
al. 1995; Walston, Seibert et al. 1999). The most relevant examples to the present
discussion are: 1) Dalziel et al (2002) showed that an association between HOMA-IR and
BMI/WC existed in all obese, non-diabetic subjects, but a negative correlation between
HDL-C and HOMA-IR was only seen with certain genotypes (-308 GA or AA); 2) increased
dietary intake of polyunsaturated fatty acids (PUFAs) by subjects with T2D was positively
associated with increased HDL-C in carriers of the -238 A and -308 G alleles, but an
inverse association was seen in carriers of the -238 GG genotype and the -308 A allele
(Fontaine-Bisson, Wolever et al. 2007) and; 3) carriers of the -308 A allele with T2D
showed an attenuated response to rosiglitazone, a PPAR agonist (Liu, Lin et al. 2008).
Taken together, the results of these human association studies show the -308 A allele to
be associated with obesity-related phenotypes, pre-diabetic states, and unfavorable
lipid profiles within individuals classified as either obese or T2D. Thus, it is appropriately
termed the ‘risk’ allele; however, the context of that risk is a state of presumed chronic
inflammation as seen in obesity and T2D.
Association analyses of the VRC vervets revealed that a subset of SNPs in strong
LD within the 5’ UTR, putative promoter, introns, 3’ UTR, and flanking regions all have
significant positive associations with BMI, WC, TPC, and HDL-C (Chapter 4, Figure 2).
The minor alleles of this subset are associated with increased BMI, WC, TPC, and HDL-C,
and are found exclusively on haplotype H1 which represents about 30% of the sample
population (Chapter 4, Table 3). No significant associations were found between TG
133
and any of the polymorphisms tested. Thus, genetic associations have been
demonstrated that are similar to humans with BMI, WC, and TPC.
Although a lack of association should not be weighted comparably to positive
associations for making interpretations, one possibility for why TG had no significant
associations could be that the range of values for TG was not sufficiently wide in this
sample population to statistically detect partitioning by genotype. This could be due to
one or more of the following: 1) TG values tend to be lower for Chlorocebus species
relative to humans and other NHPs (Rudel, Reynolds et al. 1981), 2) animals were fed a
soy-based chow diet at the time of blood collection and soy has been shown to lower
human TG values in large epidemiologic studies (Zhan and Ho 2005) and, 3) TNFα has
been shown to stimulate both lipolysis and hepatic FA synthesis in chow-fed animals
whereas TNFα only induces FA synthesis in sucrose-fed animals (Feingold, Adi et al.
1990; Esteve, Ricart et al. 2005). Thus, although a proportion of these VRC vervets have
previously been shown to display obesity, insulin resistance, and associated lipid profiles
(Kavanagh, Fairbanks et al. 2007; Kavanagh, Jones et al. 2007), the number of individuals
displaying obesity-related inflammation or insulin resistance sufficient to induce TG
elevations is thought to be nominal. It is expected that dietary manipulation involving a
composition more closely resembling that of a typical Western diet would increase the
phenotypic expression of obesity and its associated dyslipidemic profiles.
The same set of alleles located on haplotype H1 associated with ‘risk’
phenotypes BMI, WC, and TPC, was also associated with increased values of HDL-C,
134
representing a novel association not previously seen in human studies. HDL-C levels
have traditionally been regarded as negative risk factors for CVD based on its relatively
well-characterized role in reverse cholesterol transport (Lewis and Rader 2005), its
inhibition of adhesion molecules ICAM-1 and VCAM-1 (Ley, Laudanna et al. 2007), as
well as epidemiological studies (Castelli, Garrison et al. 1986; Singh, Shishehbor et al.
2007). Thus, ‘risk’ has been linked to low levels of HDL-C, and human studies have
shown lower values to be associated with certain risk alleles within the TNF promoter
(Dalziel, Gosby et al. 2002; Parra-Rojas, Ruiz-Madrigal et al. 2006). The positive
associations between higher levels of HDL-C and haplotype H1 in these VRC vervets is
therefore quite intriguing. Factors contributing to this result could include one or more
of the following: 1) Chlorocebus aethiops ssp. have been shown to have high HDL-C
relative to humans and other NHPs (Rudel, Reynolds et al. 1981), 2) Rudel et al. (1981)
further demonstrated a high degree of correlation between TPC and HDL-C in these
vervets and this is also reflected in this VRC subset (r2 = 0.75, Kavanagh, unpublished
data) and, 3) soy has been shown to increase HDL-C in cynomolgus macaques (Greaves,
Wilson et al. 2000) and in a human meta-analysis (Zhan and Ho 2005). However, the
fact that HDL-C levels are positively associated with haplotype H1 in the present study
may be providing some small glimpse into a changing paradigm related to HDL-C. That
is, HDLs are extremely diverse in structure and function, and mounting evidence
suggests that the notion of higher levels always conferring, and being indicative of,
protection from CVD and inflammatory-related disease states could be overly simplistic.
Specifically, the cardioprotective effect of HDL-C is increasingly thought to be due to the
135
apolipoprotein apoA-I and apoA-II content rather than simply HDL-C levels (Watts,
Barrett et al. 2008). For example, a major post-hoc analysis recently indicated that very
high HDL-C cholesterol levels (>70 mg/dL) in humans conferred a two-fold increase in
risk of CVD (van der Steeg, Holme et al. 2008).
In an effort to explore the possibility that the positive associations could be due
to the large correlation between TPC and HDL-C, we ran additional association analyses
with the estimated values for non-HDL-C, or all apoB-containing cholesterol such as
VLDL and LDL. Although a slight trend was seen with the same set of ‘risk’ alleles
located on haplotype H1, the results failed to yield any highly significant associations
(data not shown).
The data presented here cannot explain the association of H1 with HDL-C.
However, subsequent studies may provide the unique opportunity to explore this
further. As of 2009, the VRC was switched from a soy-based chow diet to a diet
designed to reflect the composition of a typical American diet (TAD). It is expected that
consumption of this diet will result in a much greater proportion of the population
exhibiting obesity, high WC, insulin resistance, and associated dyslipidemic profiles. The
next likely steps to address the novel HDL-C association would be to measure
phenotypic traits again at the end of 2009, after the vervets have acclimated to the diet
and have been eating it consistently for at least 6 months. In addition to remeasuring
BMI, WC, TPC, TG, and HDL-C, it would be useful to remeasure GHb% and insulin
136
resistance, as well as a reliable proxy measure of inflammation such as CRP. Association
analyses on these more recent measures may provide greater insight into the dynamics
of inflammation, TPC, and HDL-C in the VRC population. Based on previous
investigations into the HDL-C response in vervets (Rudel, Reynolds et al. 1981; Rudel,
Nelson et al. 1984), it would be expected that increasing amounts of dietary cholesterol
would eventually shift the correlation between TPC and HDL-C from a positive to a
negative relationship. How these lipid profile dynamics associate or not with the H1
‘risk’ haplotype reported here may provide some insight into the newly inflammatory
role of HDL-C.
Additional future studies will certainly include additional clinicopathologic
characterization of all present and future diabetic vervets of the VRC to better delineate
those vervets with a more typical T2D presentation, and those with the more atypical
insulin sensitive presentation with little to no islet amyloid deposition. Such atypical
presentations could be due to a vastly different pathogenesis, perhaps independent of
inflammatory pathways, as well as vastly different modes of inheritance, perhaps
dominant or maternal (Chapter 5, Figure 4). These individuals have enormous potential
to confound genetic association studies which attempt to dissect environmental and
genetic components of polygenic, inflammatory-related obesity and its comorbidities.
Another potential confounder to association studies is the possibility of
population stratification. The phylogenetic analyses presented here provide relatively
137
strong evidence to suggest that the St. Kitts-origin vervet should not bear the same
subspecies designation as the African-origin Chlorocebus aethiops sabaeus. However, it
raises some concern that the St. Kitts vervet may be stratified by introgression of more
than one subspecies founding that island population. Current projects at separate
institutions involve genome sequencing as well as genome-wide SNP markers in the
vervet monkey (www.genome.gov), which will provide essential tools to explore
additional investigations into phylogeny and population stratification.
In summary, the data presented here demonstrates: 1) SNP distribution along
the putative TNF promoter in St. Kitts-origin vervets analogous to that of human as well
as other NHPs, 2) evidence to discard the current taxonomic classification of St. Kitts
vervets which designates them as identical to African Chlorocebus aethiops sabaeus, 3)
genetic associations between TNF SNPs and BMI, WC, and TPC which are analogous to
that shown in human literature, and 4) novel association between the same set of ‘risk’
SNPs and HDL-C.
BIBLIOGRAPHY
Abel, E. D., O. Peroni, et al. (2001). "Adipose-selective targeting of the GLUT4 gene impairs insulin action
in muscle and liver." Nature 409(6821): 729-33.
138
Adams, M., M. J. Reginato, et al. (1997). "Transcriptional activation by peroxisome proliferator-activated
receptor gamma is inhibited by phosphorylation at a consensus mitogen-activated protein kinase
site." J Biol Chem 272(8): 5128-32.
Almasy, L. and J. Blangero (1998). "Multipoint quantitative-trait linkage analysis in general pedigrees."
Am J Hum Genet 62(5): 1198-211.
Arkan, M. C., A. L. Hevener, et al. (2005). "IKK-beta links inflammation to obesity-induced insulin
resistance." Nat Med 11(2): 191-8.
Baena, A., J. Y. Leung, et al. (2002). "TNF-alpha promoter single nucleotide polymorphisms are markers
of human ancestry." Genes Immun 3(8): 482-7.
Baena, A., A. R. Mootnick, et al. (2007). "Primate TNF promoters reveal markers of phylogeny and
evolution of innate immunity." PLoS ONE 2(7): e621.
Bailey, J. N., S. E. Breidenthal, et al. (2007). "The association of DRD4 and novelty seeking is found in a
nonhuman primate model." Psychiatr Genet 17(1): 23-7.
Barrett, J. C., B. Fry, et al. (2005). "Haploview: analysis and visualization of LD and haplotype maps."
Bioinformatics 21(2): 263-5.
Barthel, R., A. V. Tsytsykova, et al. (2003). "Regulation of tumor necrosis factor alpha gene expression by
mycobacteria involves the assembly of a unique enhanceosome dependent on the coactivator
proteins CBP/p300." Mol Cell Biol 23(2): 526-33.
Bennett, A. J., K. P. Lesch, et al. (2002). "Early experience and serotonin transporter gene variation interact
to influence primate CNS function." Mol Psychiatry 7(1): 118-22.
Berg, A. H., T. P. Combs, et al. (2001). "The adipocyte-secreted protein Acrp30 enhances hepatic insulin
action." Nat Med 7(8): 947-53.
Bergman, R. N., S. P. Kim, et al. (2007). "Abdominal obesity: role in the pathophysiology of metabolic
disease and cardiovascular risk." Am J Med 120(2 Suppl 1): S3-8; discussion S29-32.
Berk, B. C., W. S. Weintraub, et al. (1990). "Elevation of C-reactive protein in "active" coronary artery
disease." Am J Cardiol 65(3): 168-72.
Beutler, B., I. W. Milsark, et al. (1985). "Passive immunization against cachectin/tumor necrosis factor
protects mice from lethal effect of endotoxin." Science 229(4716): 869-71.
Black, R. A., C. T. Rauch, et al. (1997). "A metalloproteinase disintegrin that releases tumour-necrosis
factor-alpha from cells." Nature 385(6618): 729-33.
Boffelli, D., J. McAuliffe, et al. (2003). "Phylogenetic shadowing of primate sequences to find functional
regions of the human genome." Science 299(5611): 1391-4.
Botstein, D. and N. Risch (2003). "Discovering genotypes underlying human phenotypes: past successes
for mendelian disease, future approaches for complex disease." Nat Genet 33 Suppl: 228-37.
Brundtland, G. H. (2002). "From the World Health Organization. Reducing risks to health, promoting
healthy life." JAMA 288(16): 1974.
Bullo, M., P. Garcia-Lorda, et al. (2003). "Systemic inflammation, adipose tissue tumor necrosis factor, and
leptin expression." Obes Res 11(4): 525-31.
Cai, D., M. Yuan, et al. (2005). "Local and systemic insulin resistance resulting from hepatic activation of
IKK-beta and NF-kappaB." Nat Med 11(2): 183-90.
Castelli, W. P., R. J. Garrison, et al. (1986). "Incidence of coronary heart disease and lipoprotein
cholesterol levels. The Framingham Study." JAMA 256(20): 2835-8.
Cawthorn, W. P., F. Heyd, et al. (2007). "Tumour necrosis factor-alpha inhibits adipogenesis via a beta-
catenin/TCF4(TCF7L2)-dependent pathway." Cell Death Differ 14(7): 1361-73.
Cawthorn, W. P. and J. K. Sethi (2008). "TNF-alpha and adipocyte biology." FEBS Lett 582(1): 117-31.
Ceppellini, R., M. Siniscalco, et al. (1955). "The estimation of gene frequencies in a random-mating
population." Ann Hum Genet 20(2): 97-115.
Cermak, J., N. S. Key, et al. (1993). "C-reactive protein induces human peripheral blood monocytes to
synthesize tissue factor." Blood 82(2): 513-20.
Chae, G. N. and S. J. Kwak (2003). "NF-kappaB is involved in the TNF-alpha induced inhibition of the
differentiation of 3T3-L1 cells by reducing PPARgamma expression." Exp Mol Med 35(5): 431-7.
Chandran, M., S. A. Phillips, et al. (2003). "Adiponectin: more than just another fat cell hormone?"
Diabetes Care 26(8): 2442-50.
Chehab, F. F., K. Mounzih, et al. (1997). "Early onset of reproductive function in normal female mice
treated with leptin." Science 275(5296): 88-90.
139
Cinti, S., G. Mitchell, et al. (2005). "Adipocyte death defines macrophage localization and function in
adipose tissue of obese mice and humans." J Lipid Res 46(11): 2347-55.
Cioffi, J. A., A. W. Shafer, et al. (1996). "Novel B219/OB receptor isoforms: possible role of leptin in
hematopoiesis and reproduction." Nat Med 2(5): 585-9.
Clyne, B. and J. S. Olshaker (1999). "The C-reactive protein." J Emerg Med 17(6): 1019-25.
Coenen, K. R., M. L. Gruen, et al. (2007). "Diet-induced increases in adiposity, but not plasma lipids,
promote macrophage infiltration into white adipose tissue." Diabetes 56(3): 564-73.
Comuzzie, A. G., S. A. Cole, et al. (2003). "The baboon as a nonhuman primate model for the study of the
genetics of obesity." Obes Res 11(1): 75-80.
Contreras, J. L., C. A. Smyth, et al. (2004). "Nonhuman primate models in type 1 diabetes research." ILAR
J 45(3): 334-42.
Cooper, G. M. and A. Sidow (2003). "Genomic regulatory regions: insights from comparative sequence
analysis." Curr Opin Genet Dev 13(6): 604-10.
Coppack, S. W. (2001). "Pro-inflammatory cytokines and adipose tissue." Proc Nutr Soc 60(3): 349-56.
Corbalan, M. S., A. Marti, et al. (2004). "Influence of two polymorphisms of the tumoral necrosis factor-
alpha gene on the obesity phenotype." Diabetes Nutr Metab 17(1): 17-22.
Csehi, S. B., S. Mathieu, et al. (2005). "Tumor necrosis factor (TNF) interferes with insulin signaling
through the p55 TNF receptor death domain." Biochem Biophys Res Commun 329(1): 397-405.
Curat, C. A., A. Miranville, et al. (2004). "From blood monocytes to adipose tissue-resident macrophages:
induction of diapedesis by human mature adipocytes." Diabetes 53(5): 1285-92.
D'Alessio, D. A., C. B. Verchere, et al. (1994). "Pancreatic expression and secretion of human islet amyloid
polypeptide in a transgenic mouse." Diabetes 43(12): 1457-61.
Dahlman, I., M. Forsgren, et al. (2006). "Downregulation of electron transport chain genes in visceral
adipose tissue in type 2 diabetes independent of obesity and possibly involving tumor necrosis
factor-alpha." Diabetes 55(6): 1792-9.
Dalziel, B., A. K. Gosby, et al. (2002). "Association of the TNF-alpha -308 G/A promoter polymorphism
with insulin resistance in obesity." Obes Res 10(5): 401-7.
Dandona, P., A. Aljada, et al. (2004). "Inflammation: the link between insulin resistance, obesity and
diabetes." Trends Immunol 25(1): 4-7.
Das, U. N. (2001). "Is obesity an inflammatory condition?" Nutrition 17(11-12): 953-66.
de Maat, M. P., A. Pietersma, et al. (1996). "Association of plasma fibrinogen levels with coronary artery
disease, smoking and inflammatory markers." Atherosclerosis 121(2): 185-91.
De Taeye, B. M., T. Novitskaya, et al. (2007). "Macrophage TNF-alpha contributes to insulin resistance
and hepatic steatosis in diet-induced obesity." Am J Physiol Endocrinol Metab 293(3): E713-25.
de Vries, A., M. C. Holmes, et al. (2007). "Prenatal dexamethasone exposure induces changes in nonhuman
primate offspring cardiometabolic and hypothalamic-pituitary-adrenal axis function." J Clin Invest
117(4): 1058-67.
Denham, W. W. (1987). West Indian green monkeys : problems in historical biogeography. Basel ; New
York, Karger.
Di Rienzo, A. and R. R. Hudson (2005). "An evolutionary framework for common diseases: the ancestral-
susceptibility model." Trends Genet 21(11): 596-601.
Eckel, R. H., W. W. Barouch, et al. (2002). "Report of the National Heart, Lung, and Blood Institute-
National Institute of Diabetes and Digestive and Kidney Diseases Working Group on the
pathophysiology of obesity-associated cardiovascular disease." Circulation 105(24): 2923-8.
Eizirik, E., W. J. Murphy, et al. (2001). "Molecular dating and biogeography of the early placental mammal
radiation." J Hered 92(2): 212-9.
Emanuelli, B., P. Peraldi, et al. (2001). "SOCS-3 inhibits insulin signaling and is up-regulated in response
to tumor necrosis factor-alpha in the adipose tissue of obese mice." J Biol Chem 276(51): 47944-9.
Engeli, S., M. Feldpausch, et al. (2003). "Association between adiponectin and mediators of inflammation
in obese women." Diabetes 52(4): 942-7.
Engelman, J. A., A. H. Berg, et al. (2000). "Tumor necrosis factor alpha-mediated insulin resistance, but
not dedifferentiation, is abrogated by MEK1/2 inhibitors in 3T3-L1 adipocytes." Mol Endocrinol
14(10): 1557-69.
Engstrom, G., B. Hedblad, et al. (2003). "Inflammation-sensitive plasma proteins are associated with future
weight gain." Diabetes 52(8): 2097-101.
140
Enoch, M. A., P. H. Shen, et al. (2006). "Using ancestry-informative markers to define populations and
detect population stratification." J Psychopharmacol 20(4 Suppl): 19-26.
Esposito, K., F. Nappo, et al. (2002). "Inflammatory cytokine concentrations are acutely increased by
hyperglycemia in humans: role of oxidative stress." Circulation 106(16): 2067-72.
Esteve, E., W. Ricart, et al. (2005). "Dyslipidemia and inflammation: an evolutionary conserved
mechanism." Clin Nutr 24(1): 16-31.
Fain, J. N., A. K. Madan, et al. (2004). "Comparison of the release of adipokines by adipose tissue, adipose
tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese
humans." Endocrinology 145(5): 2273-82.
Fairbanks, L. A., T. K. Newman, et al. (2004). "Genetic contributions to social impulsivity and
aggressiveness in vervet monkeys." Biol Psychiatry 55(6): 642-7.
Fajans, S. S., G. I. Bell, et al. (2001). "Molecular mechanisms and clinical pathophysiology of maturity-
onset diabetes of the young." N Engl J Med 345(13): 971-80.
Falvo, J. V., A. M. Uglialoro, et al. (2000). "Stimulus-specific assembly of enhancer complexes on the
tumor necrosis factor alpha gene promoter." Mol Cell Biol 20(6): 2239-47.
Fantuzzi, G. (2005). "Adipose tissue, adipokines, and inflammation." J Allergy Clin Immunol 115(5): 911-
9; quiz 920.
Fasshauer, M., J. Klein, et al. (2002). "Hormonal regulation of adiponectin gene expression in 3T3-L1
adipocytes." Biochem Biophys Res Commun 290(3): 1084-9.
Fei, H., H. J. Okano, et al. (1997). "Anatomic localization of alternatively spliced leptin receptors (Ob-R) in
mouse brain and other tissues." Proc Natl Acad Sci U S A 94(13): 7001-5.
Feingold, K. R., S. Adi, et al. (1990). "Diet affects the mechanisms by which TNF stimulates hepatic
triglyceride production." Am J Physiol 259(2 Pt 1): E177-84.
Fernandez-Real, J. M. (2006). "Genetic predispositions to low-grade inflammation and type 2 diabetes."
Diabetes Technol Ther 8(1): 55-66.
Fernandez-Real, J. M., C. Gutierrez, et al. (1997). "The TNF-alpha gene Nco I polymorphism influences
the relationship among insulin resistance, percent body fat, and increased serum leptin levels."
Diabetes 46(9): 1468-72.
Fernandez-Real, J. M. and W. Ricart (2003). "Insulin resistance and chronic cardiovascular inflammatory
syndrome." Endocr Rev 24(3): 278-301.
Fernandez, J. R. and M. D. Shiver (2004). "Using genetic admixture to study the biology of obesity traits
and to map genes in admixed populations." Nutr Rev 62(7 Pt 2): S69-74.
Festa, A., R. D'Agostino, Jr., et al. (2001). "The relation of body fat mass and distribution to markers of
chronic inflammation." Int J Obes Relat Metab Disord 25(10): 1407-15.
Finck, B. N. and R. W. Johnson (2000). "Tumor necrosis factor (TNF)-alpha induces leptin production
through the p55 TNF receptor." Am J Physiol Regul Integr Comp Physiol 278(2): R537-43.
Fontaine-Bisson, B., T. M. Wolever, et al. (2007). "Genetic polymorphisms of tumor necrosis factor-alpha
modify the association between dietary polyunsaturated fatty acids and fasting HDL-cholesterol
and apo A-I concentrations." Am J Clin Nutr 86(3): 768-74.
Freimer, N. B., K. Dewar, et al. (2007). "The Importance of the Vervet (African Green Monkey) as a
Biomedical Model." from www.genome.gov.
Freimer, N. B., S. K. Service, et al. (2007). "A quantitative trait locus for variation in dopamine metabolism
mapped in a primate model using reference sequences from related species." Proc Natl Acad Sci U
S A 104(40): 15811-6.
Fried, S. K. and R. Zechner (1989). "Cachectin/tumor necrosis factor decreases human adipose tissue
lipoprotein lipase mRNA levels, synthesis, and activity." J Lipid Res 30(12): 1917-23.
Friedman, J. M. and J. L. Halaas (1998). "Leptin and the regulation of body weight in mammals." Nature
395(6704): 763-70.
Furukawa, S., T. Fujita, et al. (2004). "Increased oxidative stress in obesity and its impact on metabolic
syndrome." J Clin Invest 114(12): 1752-61.
Gabriel, S. B., S. F. Schaffner, et al. (2002). "The structure of haplotype blocks in the human genome."
Science 296(5576): 2225-9.
Gatanaga, T., C. D. Hwang, et al. (1990). "Purification and characterization of an inhibitor (soluble tumor
necrosis factor receptor) for tumor necrosis factor and lymphotoxin obtained from the serum
ultrafiltrates of human cancer patients." Proc Natl Acad Sci U S A 87(22): 8781-4.
141
Gaur, L. K. (2004). "Nonhuman primate models for islet transplantation in type 1 diabetes research." ILAR
J 45(3): 324-33.
Gaur, L. K., G. T. Nepom, et al. (2001). "Low-dose streptozotocin induces sustained hyperglycemia in
Macaca nemestrina." Autoimmunity 33(2): 103-14.
Gloire, G., S. Legrand-Poels, et al. (2006). "NF-kappaB activation by reactive oxygen species: fifteen years
later." Biochem Pharmacol 72(11): 1493-505.
Goldfeld, A. E., C. Doyle, et al. (1990). "Human tumor necrosis factor alpha gene regulation by virus and
lipopolysaccharide." Proc Natl Acad Sci U S A 87(24): 9769-73.
Goldfeld, A. E., J. Y. Leung, et al. (2000). "Post-genomics and the neutral theory: variation and
conservation in the tumor necrosis factor-alpha promoter." Gene 261(1): 19-25.
Goldfeld, A. E., P. G. McCaffrey, et al. (1993). "Identification of a novel cyclosporin-sensitive element in
the human tumor necrosis factor alpha gene promoter." J Exp Med 178(4): 1365-79.
Greaves, K. A., M. D. Wilson, et al. (2000). "Consumption of soy protein reduces cholesterol absorption
compared to casein protein alone or supplemented with an isoflavone extract or conjugated equine
estrogen in ovariectomized cynomolgus monkeys." J Nutr 130(4): 820-6.
Green, A., J. M. Rumberger, et al. (2004). "Stimulation of lipolysis by tumor necrosis factor-alpha in 3T3-
L1 adipocytes is glucose dependent: implications for long-term regulation of lipolysis." Diabetes
53(1): 74-81.
Groves, C. P. (2001). Primate taxonomy. Washington, DC, Smithsonian Institution Press.
Grunfeld, C., C. Zhao, et al. (1996). "Endotoxin and cytokines induce expression of leptin, the ob gene
product, in hamsters." J Clin Invest 97(9): 2152-7.
Guldstrand, M., B. Ahren, et al. (2003). "Improved beta-cell function after standardized weight reduction in
severely obese subjects." Am J Physiol Endocrinol Metab 284(3): E557-65.
Hamann, A., C. Mantzoros, et al. (1995). "Genetic variability in the TNF-alpha promoter is not associated
with type II diabetes mellitus (NIDDM)." Biochem Biophys Res Commun 211(3): 833-9.
Handler, J. S., F. W. Lange, et al. (1978). Plantation slavery in Barbados : an archaeological and historical
investigation. Cambridge, Harvard University Press.
Haudek, S. B., B. E. Natmessnig, et al. (1998). "Genetic sequences and transcriptional regulation of the
TNFA promoter: comparison of human and baboon." Immunogenetics 48(3): 202-7.
Hermann, G. E., S. L. Hebert, et al. (2004). "TNF alpha-p55 receptors: medullary brainstem
immunocytochemical localization in normal and vagus nerve-transected rats." Brain Res 1004(1-
2): 156-66.
Higasa, K. and K. Hayashi (2006). "Periodicity of SNP distribution around transcription start sites." BMC
Genomics 7: 66.
Hill, J. O., H. R. Wyatt, et al. (2003). "Obesity and the environment: where do we go from here?" Science
299(5608): 853-5.
Hirosumi, J., G. Tuncman, et al. (2002). "A central role for JNK in obesity and insulin resistance." Nature
420(6913): 333-6.
Hoffstedt, J., P. Eriksson, et al. (2000). "Excessive fat accumulation is associated with the TNF alpha-308
G/A promoter polymorphism in women but not in men." Diabetologia 43(1): 117-20.
Hong, S. C., S. W. Yoo, et al. (2007). "Correlation between estrogens and serum adipocytokines in
premenopausal and postmenopausal women." Menopause Publish Ahead of Print.
Hosogai, N., A. Fukuhara, et al. (2007). "Adipose tissue hypoxia in obesity and its impact on adipocytokine
dysregulation." Diabetes 56(4): 901-11.
Hotamisligil, G. S. (2003). "Inflammatory pathways and insulin action." Int J Obes Relat Metab Disord 27
Suppl 3: S53-5.
Hotamisligil, G. S. (2006). "Inflammation and metabolic disorders." Nature 444(7121): 860-7.
Hotamisligil, G. S., P. Arner, et al. (1997). "Differential regulation of the p80 tumor necrosis factor
receptor in human obesity and insulin resistance." Diabetes 46(3): 451-5.
Hotamisligil, G. S., P. Peraldi, et al. (1996). "IRS-1-mediated inhibition of insulin receptor tyrosine kinase
activity in TNF-alpha- and obesity-induced insulin resistance." Science 271(5249): 665-8.
Hotamisligil, G. S., N. S. Shargill, et al. (1993). "Adipose expression of tumor necrosis factor-alpha: direct
role in obesity-linked insulin resistance." Science 259(5091): 87-91.
Houstis, N., E. D. Rosen, et al. (2006). "Reactive oxygen species have a causal role in multiple forms of
insulin resistance." Nature 440(7086): 944-8.
142
Hu, E., J. B. Kim, et al. (1996). "Inhibition of adipogenesis through MAP kinase-mediated phosphorylation
of PPARgamma." Science 274(5295): 2100-3.
Hu, E., P. Liang, et al. (1996). "AdipoQ is a novel adipose-specific gene dysregulated in obesity." J Biol
Chem 271(18): 10697-703.
Hu, P., Z. Han, et al. (2006). "Autocrine tumor necrosis factor alpha links endoplasmic reticulum stress to
the membrane death receptor pathway through IRE1alpha-mediated NF-kappaB activation and
down-regulation of TRAF2 expression." Mol Cell Biol 26(8): 3071-84.
Huang, C. J., C. Y. Lin, et al. (2007). "High expression rates of human islet amyloid polypeptide induce
endoplasmic reticulum stress mediated beta-cell apoptosis, a characteristic of humans with type 2
but not type 1 diabetes." Diabetes 56(8): 2016-27.
Huvers, F. C., C. Popa, et al. (2007). "Improved insulin sensitivity by anti-TNFalpha antibody treatment in
patients with rheumatic diseases." Ann Rheum Dis 66(4): 558-9.
Im, J. A., J. W. Lee, et al. (2006). "Plasma adiponectin levels in postmenopausal women with or without
long-term hormone therapy." Maturitas 54(1): 65-71.
IOTF. (2007, August 2007). "Prevalence of Adult Obesity." from
http://www.iotf.org/database/GlobalAdultTableJune07.htm.
Jain, R. G., K. D. Phelps, et al. (1999). "Tumor necrosis factor-alpha initiated signal transduction in 3T3-L1
adipocytes." J Cell Physiol 179(1): 58-66.
Jasinska, A. J., S. Service, et al. (2007). "A genetic linkage map of the vervet monkey (Chlorocebus
aethiops sabaeus)." Mamm Genome 18(5): 347-60.
Juge-Aubry, C. E., E. Henrichot, et al. (2005). "Adipose tissue: a regulator of inflammation." Best Pract
Res Clin Endocrinol Metab 19(4): 547-66.
Kappes, A. and G. Loffler (2000). "Influences of ionomycin, dibutyryl-cycloAMP and tumour necrosis
factor-alpha on intracellular amount and secretion of apM1 in differentiating primary human
preadipocytes." Horm Metab Res 32(11-12): 548-54.
Kavanagh, K., L. A. Fairbanks, et al. (2007). "Characterization and heritability of obesity and associated
risk factors in vervet monkeys." Obesity (Silver Spring) 15(7): 1666-74.
Kavanagh, K., K. L. Jones, et al. (2007). "Trans fat diet induces abdominal obesity and changes in insulin
sensitivity in monkeys." Obesity (Silver Spring) 15(7): 1675-84.
Kawakami, M., T. Murase, et al. (1987). "Human recombinant TNF suppresses lipoprotein lipase activity
and stimulates lipolysis in 3T3-L1 cells." J Biochem 101(2): 331-8.
Kawanami, D., K. Maemura, et al. (2004). "Direct reciprocal effects of resistin and adiponectin on vascular
endothelial cells: a new insight into adipocytokine-endothelial cell interactions." Biochem Biophys
Res Commun 314(2): 415-9.
Kelley, D. S. (2001). "Modulation of human immune and inflammatory responses by dietary fatty acids."
Nutrition 17(7-8): 669-73.
Kemnitz, J. W. (1984). "Obesity in macaques: spontaneous and induced." Adv Vet Sci Comp Med 28: 81-
114.
Kern, P. A. (1988). "Recombinant human tumor necrosis factor does not inhibit lipoprotein lipase in
primary cultures of isolated human adipocytes." J Lipid Res 29(7): 909-14.
Kern, P. A., G. B. Di Gregorio, et al. (2003). "Adiponectin expression from human adipose tissue: relation
to obesity, insulin resistance, and tumor necrosis factor-alpha expression." Diabetes 52(7): 1779-
85.
Kim, K. Y., J. K. Kim, et al. (2005). "c-Jun N-terminal kinase is involved in the suppression of adiponectin
expression by TNF-alpha in 3T3-L1 adipocytes." Biochem Biophys Res Commun 327(2): 460-7.
Kiortsis, D. N., A. K. Mavridis, et al. (2005). "Effects of infliximab treatment on insulin resistance in
patients with rheumatoid arthritis and ankylosing spondylitis." Ann Rheum Dis 64(5): 765-6.
Kirchgessner, T. G., K. T. Uysal, et al. (1997). "Tumor necrosis factor-alpha contributes to obesity-related
hyperleptinemia by regulating leptin release from adipocytes." J Clin Invest 100(11): 2777-82.
Kissebah, A. H., G. E. Sonnenberg, et al. (2000). "Quantitative trait loci on chromosomes 3 and 17
influence phenotypes of the metabolic syndrome." Proc Natl Acad Sci U S A 97(26): 14478-83.
Kita, A., H. Yamasaki, et al. (2005). "Identification of the promoter region required for human adiponectin
gene transcription: Association with CCAAT/enhancer binding protein-beta and tumor necrosis
factor-alpha." Biochem Biophys Res Commun 331(2): 484-90.
Klein, S., L. E. Burke, et al. (2004). "Clinical implications of obesity with specific focus on cardiovascular
disease: a statement for professionals from the American Heart Association Council on Nutrition,
143
Physical Activity, and Metabolism: endorsed by the American College of Cardiology Foundation."
Circulation 110(18): 2952-67.
Knight, J. C., I. Udalova, et al. (1999). "A polymorphism that affects OCT-1 binding to the TNF promoter
region is associated with severe malaria." Nat Genet 22(2): 145-50.
Kolb-Bachofen, V. (1991). "A review on the biological properties of C-reactive protein." Immunobiology
183(1-2): 133-45.
Kriegler, M., C. Perez, et al. (1988). "A novel form of TNF/cachectin is a cell surface cytotoxic
transmembrane protein: ramifications for the complex physiology of TNF." Cell 53(1): 45-53.
Kroeger, K. M., K. S. Carville, et al. (1997). "The -308 tumor necrosis factor-alpha promoter
polymorphism effects transcription." Mol Immunol 34(5): 391-9.
Kubaszek, A., J. Pihlajamaki, et al. (2003). "Promoter polymorphisms of the TNF-alpha (G-308A) and IL-6
(C-174G) genes predict the conversion from impaired glucose tolerance to type 2 diabetes: the
Finnish Diabetes Prevention Study." Diabetes 52(7): 1872-6.
Kuller, L. H., R. P. Tracy, et al. (1996). "Relation of C-reactive protein and coronary heart disease in the
MRFIT nested case-control study. Multiple Risk Factor Intervention Trial." Am J Epidemiol
144(6): 537-47.
Kumada, M., S. Kihara, et al. (2004). "Adiponectin specifically increased tissue inhibitor of
metalloproteinase-1 through interleukin-10 expression in human macrophages." Circulation
109(17): 2046-9.
Lesch, K. P., J. Meyer, et al. (1997). "The 5-HT transporter gene-linked polymorphic region (5-HTTLPR)
in evolutionary perspective: alternative biallelic variation in rhesus monkeys. Rapid
communication." J Neural Transm 104(11-12): 1259-66.
Leung, J. Y., F. E. McKenzie, et al. (2000). "Identification of phylogenetic footprints in primate tumor
necrosis factor-alpha promoters." Proc Natl Acad Sci U S A 97(12): 6614-8.
Lewis, G. F. and D. J. Rader (2005). "New insights into the regulation of HDL metabolism and reverse
cholesterol transport." Circ Res 96(12): 1221-32.
Ley, K., C. Laudanna, et al. (2007). "Getting to the site of inflammation: the leukocyte adhesion cascade
updated." Nat Rev Immunol 7(9): 678-89.
Li, S. and R. J. Loos (2008). "Progress in the genetics of common obesity: size matters." Curr Opin Lipidol
19(2): 113-21.
Lin, Y., A. H. Berg, et al. (2005). "The hyperglycemia-induced inflammatory response in adipocytes: the
role of reactive oxygen species." J Biol Chem 280(6): 4617-26.
Liu, H. L., Y. G. Lin, et al. (2008). "Impact of genetic polymorphisms of leptin and TNF-alpha on
rosiglitazone response in Chinese patients with type 2 diabetes." Eur J Clin Pharmacol 64(7): 663-
71.
Loffreda, S., S. Q. Yang, et al. (1998). "Leptin regulates proinflammatory immune responses." FASEB J
12(1): 57-65.
Lopez-Soriano, J., M. Llovera, et al. (1997). "Lipid metabolism in tumour-bearing mice: studies with
knockout mice for tumour necrosis factor receptor 1 protein." Mol Cell Endocrinol 132(1-2): 93-9.
Lowell, B. B. and G. I. Shulman (2005). "Mitochondrial dysfunction and type 2 diabetes." Science
307(5708): 384-7.
Lumeng, C. N., J. L. Bodzin, et al. (2007). "Obesity induces a phenotypic switch in adipose tissue
macrophage polarization." J Clin Invest 117(1): 175-84.
Maassen, J. A., T. H. LM, et al. (2004). "Mitochondrial diabetes: molecular mechanisms and clinical
presentation." Diabetes 53 Suppl 1: S103-9.
MacEwan, D. J. (2002). "TNF receptor subtype signalling: differences and cellular consequences." Cell
Signal 14(6): 477-92.
Maeda, K., K. Okubo, et al. (1996). "cDNA cloning and expression of a novel adipose specific collagen-
like factor, apM1 (AdiPose Most abundant Gene transcript 1)." Biochem Biophys Res Commun
221(2): 286-9.
Maedler, K., P. Sergeev, et al. (2004). "Leptin modulates beta cell expression of IL-1 receptor antagonist
and release of IL-1beta in human islets." Proc Natl Acad Sci U S A 101(21): 8138-43.
Markovic, O., G. O'Reilly, et al. (2004). "Role of single nucleotide polymorphisms of pro-inflammatory
cytokine genes in the relationship between serum lipids and inflammatory parameters, and the
lipid-lowering effect of fish oil in healthy males." Clin Nutr 23(5): 1084-95.
144
Masaki, T., S. Chiba, et al. (2004). "Adiponectin protects LPS-induced liver injury through modulation of
TNF-alpha in KK-Ay obese mice." Hepatology 40(1): 177-84.
Matsuzawa, Y. (2005). "Adiponectin: Identification, physiology and clinical relevance in metabolic and
vascular disease." Atheroscler Suppl 6(2): 7-14.
McGuire, M. T. (1974). "The St. Kitts vervet (Cercopithecus aethiops)." J Med Primatol 3(5): 285-97.
McTernan, P. G., A. L. Harte, et al. (2002). "Insulin and rosiglitazone regulation of lipolysis and
lipogenesis in human adipose tissue in vitro." Diabetes 51(5): 1493-8.
Memon, R. A., K. R. Feingold, et al. (1998). "Regulation of fatty acid transport protein and fatty acid
translocase mRNA levels by endotoxin and cytokines." Am J Physiol 274(2 Pt 1): E210-7.
Mendall, M. A., P. Patel, et al. (1996). "C reactive protein and its relation to cardiovascular risk factors: a
population based cross sectional study." BMJ 312(7038): 1061-5.
Miles, P. D., O. M. Romeo, et al. (1997). "TNF-alpha-induced insulin resistance in vivo and its prevention
by troglitazone." Diabetes 46(11): 1678-83.
Miller, C., J. Bartges, et al. (1998). "Tumor necrosis factor-alpha levels in adipose tissue of lean and obese
cats." J Nutr 128(12 Suppl): 2751S-2752S.
Miller, G. M., J. Bendor, et al. (2004). "A mu-opioid receptor single nucleotide polymorphism in rhesus
monkey: association with stress response and aggression." Mol Psychiatry 9(1): 99-108.
Mohamed-Ali, V., S. Goodrick, et al. (1999). "Production of soluble tumor necrosis factor receptors by
human subcutaneous adipose tissue in vivo." Am J Physiol 277(6 Pt 1): E971-5.
Moller, D. E. (2000). "Potential role of TNF-alpha in the pathogenesis of insulin resistance and type 2
diabetes." Trends Endocrinol Metab 11(6): 212-7.
Montgomery, S. B., O. L. Griffith, et al. (2006). "ORegAnno: an open access database and curation system
for literature-derived promoters, transcription factor binding sites and regulatory variation."
Bioinformatics 22(5): 637-40.
Mori, Y., S. Otabe, et al. (2002). "Genome-wide search for type 2 diabetes in Japanese affected sib-pairs
confirms susceptibility genes on 3q, 15q, and 20q and identifies two new candidate Loci on 7p and
11p." Diabetes 51(4): 1247-55.
Mutch, D. M. and K. Clement (2006). "Genetics of human obesity." Best Pract Res Clin Endocrinol Metab
20(4): 647-64.
Mutch, D. M. and K. Clement (2006). "Unraveling the genetics of human obesity." PLoS Genet 2(12):
e188.
Nakamura, S., S. Okabayashi, et al. (2008). "Transthyretin amyloidosis and two other aging-related
amyloidoses in an aged vervet monkey." Vet Pathol 45(1): 67-72.
Nakanishi, S., K. Yamane, et al. (2003). "Elevated C-reactive protein is a risk factor for the development of
type 2 diabetes in Japanese Americans." Diabetes Care 26(10): 2754-7.
Nakano, Y., T. Tobe, et al. (1996). "Isolation and characterization of GBP28, a novel gelatin-binding
protein purified from human plasma." J Biochem (Tokyo) 120(4): 803-12.
Nakatani, Y., H. Kaneto, et al. (2005). "Involvement of endoplasmic reticulum stress in insulin resistance
and diabetes." J Biol Chem 280(1): 847-51.
National Research Council (U.S.) and Institute for Laboratory Animal Research (U.S.) (2003). International
perspectives : the future of nonhuman primate resources : proceedings of the workshop held April
17-19, 2002. Washington, D.C., National Academies Press.
Neel, J. V. (1962). "Diabetes mellitus: a "thrifty" genotype rendered detrimental by "progress"?" Am J
Hum Genet 14: 353-62.
Neels, J. G. and J. M. Olefsky (2006). "Inflamed fat: what starts the fire?" J Clin Invest 116(1): 33-5.
Newman, T. K., L. A. Fairbanks, et al. (2002). "Effectiveness of human microsatellite loci for assessing
paternity in a captive colony of vervets (Chlorocebus aethiops sabaeus)." Am J Primatol 56(4):
237-43.
NHANES. (2007). "National Health and Nutrition Examination Survey." from
http://www.cdc.gov/nchs/nhanes.htm.
NHLBI (2000). The Practical Guide: Identification, Evaluation, and Treatment of Overweight and Obesity
in Adults. Washington DC, NHLBI produced publications: 88.
Nisoli, E., L. Briscini, et al. (1997). "Tumor necrosis factor-alpha induces apoptosis in rat brown
adipocytes." Cell Death Differ 4(8): 771-8.
Norris, J. M., C. D. Langefeld, et al. (2009). "Genome-wide Association Study and Follow-up Analysis of
Adiposity Traits in Hispanic Americans: The IRAS Family Study." Obesity (Silver Spring).
145
O'Brien, T. D., J. D. Wagner, et al. (1996). "Islet amyloid and islet amyloid polypeptide in cynomolgus
macaques (Macaca fascicularis): an animal model of human non-insulin-dependent diabetes
mellitus." Vet Pathol 33(5): 479-85.
Ouchi, N., S. Kihara, et al. (1999). "Novel modulator for endothelial adhesion molecules: adipocyte-
derived plasma protein adiponectin." Circulation 100(25): 2473-6.
Ovcharenko, I., D. Boffelli, et al. (2004). "eShadow: a tool for comparing closely related sequences."
Genome Res 14(6): 1191-8.
Ozawa, K., M. Miyazaki, et al. (2005). "The endoplasmic reticulum chaperone improves insulin resistance
in type 2 diabetes." Diabetes 54(3): 657-63.
Ozcan, U., Q. Cao, et al. (2004). "Endoplasmic reticulum stress links obesity, insulin action, and type 2
diabetes." Science 306(5695): 457-61.
Ozcan, U., E. Yilmaz, et al. (2006). "Chemical chaperones reduce ER stress and restore glucose
homeostasis in a mouse model of type 2 diabetes." Science 313(5790): 1137-40.
Page, S. L. and M. Goodman (2001). "Catarrhine phylogeny: noncoding DNA evidence for a diphyletic
origin of the mangabeys and for a human-chimpanzee clade." Mol Phylogenet Evol 18(1): 14-25.
Pannacciulli, N., F. P. Cantatore, et al. (2001). "C-reactive protein is independently associated with total
body fat, central fat, and insulin resistance in adult women." Int J Obes Relat Metab Disord
25(10): 1416-20.
Parra-Rojas, I., B. Ruiz-Madrigal, et al. (2006). "Influence of the -308 TNF-alpha and -174 IL-6
polymorphisms on lipid profile in Mexican subjects." Hereditas 143(2006): 167-72.
Pasquali, R., V. Vicennati, et al. (2006). "The hypothalamic-pituitary-adrenal axis activity in obesity and
the metabolic syndrome." Ann N Y Acad Sci 1083: 111-28.
Paul, A., K. W. Ko, et al. (2004). "C-reactive protein accelerates the progression of atherosclerosis in
apolipoprotein E-deficient mice." Circulation 109(5): 647-55.
Pellme, F., U. Smith, et al. (2003). "Circulating adiponectin levels are reduced in nonobese but insulin-
resistant first-degree relatives of type 2 diabetic patients." Diabetes 52(5): 1182-6.
Pepys, M. B., I. F. Rowe, et al. (1985). "C-reactive protein: binding to lipids and lipoproteins." Int Rev Exp
Pathol 27: 83-111.
Peraldi, P., C. Filloux, et al. (2001). "Insulin induces suppressor of cytokine signaling-3 tyrosine
phosphorylation through janus-activated kinase." J Biol Chem 276(27): 24614-20.
Peraldi, P., G. S. Hotamisligil, et al. (1996). "Tumor necrosis factor (TNF)-alpha inhibits insulin signaling
through stimulation of the p55 TNF receptor and activation of sphingomyelinase." J Biol Chem
271(22): 13018-22.
Peraldi, P., M. Xu, et al. (1997). "Thiazolidinediones block tumor necrosis factor-alpha-induced inhibition
of insulin signaling." J Clin Invest 100(7): 1863-9.
Perez, C., I. Albert, et al. (1990). "A nonsecretable cell surface mutant of tumor necrosis factor (TNF) kills
by cell-to-cell contact." Cell 63(2): 251-8.
Pickup, J. C. (2004). "Inflammation and activated innate immunity in the pathogenesis of type 2 diabetes."
Diabetes Care 27(3): 813-23.
Pinkse, G. G., O. H. Tysma, et al. (2005). "Autoreactive CD8 T cells associated with beta cell destruction
in type 1 diabetes." Proc Natl Acad Sci U S A 102(51): 18425-30.
Pradhan, A. D., J. E. Manson, et al. (2001). "C-reactive protein, interleukin 6, and risk of developing type 2
diabetes mellitus." JAMA 286(3): 327-34.
Ramsay, T. G. (1996). "Fat cells." Endocrinol Metab Clin North Am 25(4): 847-70.
Ridker, P. M., M. Cushman, et al. (1997). "Inflammation, aspirin, and the risk of cardiovascular disease in
apparently healthy men." N Engl J Med 336(14): 973-9.
Risch, N. J. (2000). "Searching for genetic determinants in the new millennium." Nature 405(6788): 847-
56.
Roche, H. M., C. Phillips, et al. (2005). "The metabolic syndrome: the crossroads of diet and genetics."
Proc Nutr Soc 64(3): 371-7.
Rood, P. P., L. H. Buhler, et al. (2006). "Pig-to-nonhuman primate islet xenotransplantation: a review of
current problems." Cell Transplant 15(2): 89-104.
Roseboom, T. J., J. H. van der Meulen, et al. (2001). "Effects of prenatal exposure to the Dutch famine on
adult disease in later life: an overview." Mol Cell Endocrinol 185(1-2): 93-8.
146
Ross, S. E., R. L. Erickson, et al. (2002). "Microarray analyses during adipogenesis: understanding the
effects of Wnt signaling on adipogenesis and the roles of liver X receptor alpha in adipocyte
metabolism." Mol Cell Biol 22(16): 5989-99.
Ruan, H., N. Hacohen, et al. (2002). "Tumor necrosis factor-alpha suppresses adipocyte-specific genes and
activates expression of preadipocyte genes in 3T3-L1 adipocytes: nuclear factor-kappaB activation
by TNF-alpha is obligatory." Diabetes 51(5): 1319-36.
Ruan, H. and H. F. Lodish (2003). "Insulin resistance in adipose tissue: direct and indirect effects of tumor
necrosis factor-alpha." Cytokine Growth Factor Rev 14(5): 447-55.
Ruan, H., P. D. Miles, et al. (2002). "Profiling gene transcription in vivo reveals adipose tissue as an
immediate target of tumor necrosis factor-alpha: implications for insulin resistance." Diabetes
51(11): 3176-88.
Ruan, H., H. J. Pownall, et al. (2003). "Troglitazone antagonizes tumor necrosis factor-alpha-induced
reprogramming of adipocyte gene expression by inhibiting the transcriptional regulatory functions
of NF-kappaB." J Biol Chem 278(30): 28181-92.
Rudel, L. L., C. A. Nelson, et al. (1984). "Atherogenic diet-induced modification of the subfraction
distribution of high density lipoproteins in monkeys." Arteriosclerosis 4(6): 636-46.
Rudel, L. L., J. A. Reynolds, et al. (1981). "Nutritional effects on blood lipid and HDL cholesterol
concentrations in two subspecies of African green monkeys (Cercopithecus aethiops)." J Lipid Res
22(2): 278-86.
Ryden, M., A. Dicker, et al. (2002). "Mapping of early signaling events in tumor necrosis factor-alpha -
mediated lipolysis in human fat cells." J Biol Chem 277(2): 1085-91.
Salpeter, S. R., J. M. Walsh, et al. (2006). "Meta-analysis: effect of hormone-replacement therapy on
components of the metabolic syndrome in postmenopausal women." Diabetes Obes Metab 8(5):
538-54.
Scherer, P. E., S. Williams, et al. (1995). "A novel serum protein similar to C1q, produced exclusively in
adipocytes." J Biol Chem 270(45): 26746-9.
Schneider, J. G., C. Tompkins, et al. (2006). "The metabolic syndrome in women." Cardiol Rev 14(6): 286-
91.
Scriver, C. R. (2001). The metabolic & molecular bases of inherited disease. New York, McGraw-Hill.
Serino, M., R. Menghini, et al. (2007). "Mice heterozygous for tumor necrosis factor-alpha converting
enzyme are protected from obesity-induced insulin resistance and diabetes." Diabetes 56(10):
2541-6.
Sethi, J. K. and A. J. Vidal-Puig (2007). "Thematic review series: adipocyte biology. Adipose tissue
function and plasticity orchestrate nutritional adaptation." J Lipid Res 48(6): 1253-62.
Seufert, J. (2004). "Leptin effects on pancreatic beta-cell gene expression and function." Diabetes 53 Suppl
1: S152-8.
Shiina, T., M. Ota, et al. (2006). "Rapid evolution of major histocompatibility complex class I genes in
primates generates new disease alleles in humans via hitchhiking diversity." Genetics 173(3):
1555-70.
Shively, C. A. and T. B. Clarkson (1988). "Regional obesity and coronary artery atherosclerosis in females:
a non-human primate model." Acta Med Scand Suppl 723: 71-8.
Siegrist-Kaiser, C. A., V. Pauli, et al. (1997). "Direct effects of leptin on brown and white adipose tissue." J
Clin Invest 100(11): 2858-64.
Sierra-Honigmann, M. R., A. K. Nath, et al. (1998). "Biological action of leptin as an angiogenic factor."
Science 281(5383): 1683-6.
Singh, I. M., M. H. Shishehbor, et al. (2007). "High-density lipoprotein as a therapeutic target: a systematic
review." JAMA 298(7): 786-98.
Singh, K. K. and J. Schmidtke (2005). "Single nucleotide polymorphisms within the promoter region of the
rhesus monkey tumor necrosis factor-alpha gene." Immunogenetics 57(3-4): 289-92.
Skoog, T., P. Eriksson, et al. (2001). "Tumour necrosis factor-alpha (TNF-alpha) polymorphisms-857C/A
and -863C/A are associated with TNF-alpha secretion from human adipose tissue." Diabetologia
44(5): 654-5.
Smith, D. G. and J. McDonough (2005). "Mitochondrial DNA variation in Chinese and Indian rhesus
macaques (Macaca mulatta)." Am J Primatol 65(1): 1-25.
Sookoian, S. C., C. Gonzalez, et al. (2005). "Meta-analysis on the G-308A tumor necrosis factor alpha gene
variant and phenotypes associated with the metabolic syndrome." Obes Res 13(12): 2122-31.
147
Sorensen, T. I. (1995). "The genetics of obesity." Metabolism 44(9 Suppl 3): 4-6.
Stephens, J. M., J. Lee, et al. (1997). "Tumor necrosis factor-alpha-induced insulin resistance in 3T3-L1
adipocytes is accompanied by a loss of insulin receptor substrate-1 and GLUT4 expression
without a loss of insulin receptor-mediated signal transduction." J Biol Chem 272(2): 971-6.
Stephens, J. M. and P. H. Pekala (1991). "Transcriptional repression of the GLUT4 and C/EBP genes in
3T3-L1 adipocytes by tumor necrosis factor-alpha." J Biol Chem 266(32): 21839-45.
Strissel, K. J., Z. Stancheva, et al. (2007). "Adipocyte death, adipose tissue remodeling, and obesity
complications." Diabetes 56(12): 2910-8.
Suzawa, M., I. Takada, et al. (2003). "Cytokines suppress adipogenesis and PPAR-gamma function through
the TAK1/TAB1/NIK cascade." Nat Cell Biol 5(3): 224-30.
Swofford, D. L. (2002). PAUP*. Phylogenetic Analysis Using Parsimony
(*and Other Methods). Version 4. Sunderland,
Massachusetts., Sinauer Associates,.
Takeda, S., F. Elefteriou, et al. (2002). "Leptin regulates bone formation via the sympathetic nervous
system." Cell 111(3): 305-17.
Tam, L. S., B. Tomlinson, et al. (2007). "Impact of TNF inhibition on insulin resistance and lipids levels in
patients with rheumatoid arthritis." Clin Rheumatol 26(9): 1495-8.
Tang, X., A. Guilherme, et al. (2006). "An RNA interference-based screen identifies MAP4K4/NIK as a
negative regulator of PPARgamma, adipogenesis, and insulin-responsive hexose transport." Proc
Natl Acad Sci U S A 103(7): 2087-92.
Taylor, P. D. and L. Poston (2007). "Developmental programming of obesity in mammals." Exp Physiol
92(2): 287-98.
Thomas, J. M., J. L. Contreras, et al. (2001). "Successful reversal of streptozotocin-induced diabetes with
stable allogeneic islet function in a preclinical model of type 1 diabetes." Diabetes 50(6): 1227-36.
Thompson, J. D., D. G. Higgins, et al. (1994). "CLUSTAL W: improving the sensitivity of progressive
multiple sequence alignment through sequence weighting, position-specific gap penalties and
weight matrix choice." Nucleic Acids Res 22(22): 4673-80.
Thompson, S. G., J. Kienast, et al. (1995). "Hemostatic factors and the risk of myocardial infarction or
sudden death in patients with angina pectoris. European Concerted Action on Thrombosis and
Disabilities Angina Pectoris Study Group." N Engl J Med 332(10): 635-41.
Tillett, W. S. and T. Francis (1930). "Serological reactions in pneumonia with a non-protein somatic
fraction of the pneumococcus." Journal of Experimental Medicine 52: 561-71.
Togashi, N., N. Ura, et al. (2002). "Effect of TNF-alpha--converting enzyme inhibitor on insulin resistance
in fructose-fed rats." Hypertension 39(2 Pt 2): 578-80.
Torti, F. M., B. Dieckmann, et al. (1985). "A macrophage factor inhibits adipocyte gene expression: an in
vitro model of cachexia." Science 229(4716): 867-9.
Trayhurn, P. (2005). "The biology of obesity." Proc Nutr Soc 64(1): 31-8.
Trayhurn, P. and I. S. Wood (2004). "Adipokines: inflammation and the pleiotropic role of white adipose
tissue." Br J Nutr 92(3): 347-55.
Trujillo, M. E., M. J. Lee, et al. (2006). "Tumor necrosis factor alpha and glucocorticoid synergistically
increase leptin production in human adipose tissue: role for p38 mitogen-activated protein kinase."
J Clin Endocrinol Metab 91(4): 1484-90.
Tsai, E. Y., J. V. Falvo, et al. (2000). "A lipopolysaccharide-specific enhancer complex involving Ets, Elk-
1, Sp1, and CREB binding protein and p300 is recruited to the tumor necrosis factor alpha
promoter in vivo." Mol Cell Biol 20(16): 6084-94.
Tsai, E. Y., J. Jain, et al. (1996). "Tumor necrosis factor alpha gene regulation in activated T cells involves
ATF-2/Jun and NFATp." Mol Cell Biol 16(2): 459-67.
Tsai, E. Y., J. Yie, et al. (1996). "Cell-type-specific regulation of the human tumor necrosis factor alpha
gene in B cells and T cells by NFATp and ATF-2/JUN." Mol Cell Biol 16(10): 5232-44.
Tsytsykova, A. V. and A. E. Goldfeld (2002). "Inducer-specific enhanceosome formation controls tumor
necrosis factor alpha gene expression in T lymphocytes." Mol Cell Biol 22(8): 2620-31.
Udalova, I. A., A. Richardson, et al. (2000). "Functional consequences of a polymorphism affecting NF-
kappaB p50-p50 binding to the TNF promoter region." Mol Cell Biol 20(24): 9113-9.
Ueki, K., T. Kondo, et al. (2004). "Suppressor of cytokine signaling 1 (SOCS-1) and SOCS-3 cause insulin
resistance through inhibition of tyrosine phosphorylation of insulin receptor substrate proteins by
discrete mechanisms." Mol Cell Biol 24(12): 5434-46.
148
Um, J. Y., B. K. Kang, et al. (2004). "Polymorphism of the tumor necrosis factor alpha gene and waist-hip
ratio in obese Korean women." Mol Cells 18(3): 340-5.
Urano, F., X. Wang, et al. (2000). "Coupling of stress in the ER to activation of JNK protein kinases by
transmembrane protein kinase IRE1." Science 287(5453): 664-6.
USHHS (2007). Overweight and Obesity: A Vision for the Future.
Uysal, K. T., S. M. Wiesbrock, et al. (1997). "Protection from obesity-induced insulin resistance in mice
lacking TNF-alpha function." Nature 389(6651): 610-4.
van der Kuyl, A. C. and J. T. Dekker (1996). "St. Kitts green monkeys originate from West Africa: Genetic
evidence from feces." American Journal of Primatology 40(4): 361-364.
van der Steeg, W. A., I. Holme, et al. (2008). "High-density lipoprotein cholesterol, high-density
lipoprotein particle size, and apolipoprotein A-I: significance for cardiovascular risk: the IDEAL
and EPIC-Norfolk studies." J Am Coll Cardiol 51(6): 634-42.
VandeBerg, J. L. and S. Williams-Blangero (2003). International perspectives : the future of nonhuman
primate resources : proceedings of the workshop held April 17-19, 2002. Washington, D.C.,
National Academies Press.
Villinger, F., S. S. Brar, et al. (1995). "Comparative sequence analysis of cytokine genes from human and
nonhuman primates." J Immunol 155(8): 3946-54.
Vinson, A., M. C. Mahaney, et al. (2008). "A pleiotropic QTL on 2p influences serum Lp-PLA2 activity
and LDL cholesterol concentration in a baboon model for the genetics of atherosclerosis risk
factors." Atherosclerosis 196(2): 667-73.
Vionnet, N., E. H. Hani, et al. (2000). "Genomewide search for type 2 diabetes-susceptibility genes in
French whites: evidence for a novel susceptibility locus for early-onset diabetes on chromosome
3q27-qter and independent replication of a type 2-diabetes locus on chromosome 1q21-q24." Am J
Hum Genet 67(6): 1470-80.
Visser, M., L. M. Bouter, et al. (1999). "Elevated C-reactive protein levels in overweight and obese adults."
JAMA 282(22): 2131-5.
Volanakis, J. E. (1982). "Complement activation by C-reactive protein complexes." Ann N Y Acad Sci
389: 235-50.
von Herrath, M. and G. T. Nepom (2009). "Animal models of human type 1 diabetes." Nat Immunol 10(2):
129-32.
Wagner, J. D., J. D. Bagdade, et al. (1996). "Increased glycation of plasma lipoproteins in diabetic
cynomolgus monkeys." Lab Anim Sci 46(1): 31-5.
Wagner, J. D., C. S. Carlson, et al. (1996). "Diabetes mellitus and islet amyloidosis in cynomolgus
monkeys." Lab Anim Sci 46(1): 36-41.
Wagner, J. D., J. M. Cline, et al. (2001). "Naturally occurring and experimental diabetes in cynomolgus
monkeys: a comparison of carbohydrate and lipid metabolism and islet pathology." Toxicol Pathol
29(1): 142-8.
Wagner, J. E., K. Kavanagh, et al. (2006). "Old world nonhuman primate models of type 2 diabetes
mellitus." ILAR J 47(3): 259-71.
Walston, J., M. Seibert, et al. (1999). "Tumor necrosis factor-alpha-238 and -308 polymorphisms do not
associated with traits related to obesity and insulin resistance." Diabetes 48(10): 2096-8.
Wang, Y. (2006). Molecular polymorphisms for phylogeny, pedigree and population structure studies,
School of Biological Sciences, Faculty of Science, University of Sydney, 2006.: xvii, 232 leaves.
Watts, G. F., P. H. Barrett, et al. (2008). "HDL metabolism in context: looking on the bright side." Curr
Opin Lipidol 19(4): 395-404.
Weisberg, S. P., D. McCann, et al. (2003). "Obesity is associated with macrophage accumulation in adipose
tissue." J Clin Invest 112(12): 1796-808.
Wellen, K. E. and G. S. Hotamisligil (2005). "Inflammation, stress, and diabetes." J Clin Invest 115(5):
1111-9.
West, D. B. and B. York (1998). "Dietary fat, genetic predisposition, and obesity: lessons from animal
models." Am J Clin Nutr 67(3 Suppl): 505S-512S.
Westermark, P., U. Engstrom, et al. (1990). "Islet amyloid polypeptide: pinpointing amino acid residues
linked to amyloid fibril formation." Proc Natl Acad Sci U S A 87(13): 5036-40.
Wilson, A. G., J. A. Symons, et al. (1997). "Effects of a polymorphism in the human tumor necrosis factor
alpha promoter on transcriptional activation." Proc Natl Acad Sci U S A 94(7): 3195-9.
149
Wolf, A. M., D. Wolf, et al. (2004). "Adiponectin induces the anti-inflammatory cytokines IL-10 and IL-
1RA in human leukocytes." Biochem Biophys Res Commun 323(2): 630-5.
Wulster-Radcliffe, M. C., K. M. Ajuwon, et al. (2004). "Adiponectin differentially regulates cytokines in
porcine macrophages." Biochem Biophys Res Commun 316(3): 924-9.
www.genome.gov.
Wyatt, S. B., K. P. Winters, et al. (2006). "Overweight and obesity: prevalence, consequences, and causes
of a growing public health problem." Am J Med Sci 331(4): 166-74.
Wybranska, I., M. Malczewska-Malec, et al. (2003). "The TNF-alpha gene NcoI polymorphism at position
-308 of the promoter influences insulin resistance, and increases serum triglycerides after
postprandial lipaemia in familiar obesity." Clin Chem Lab Med 41(4): 501-10.
Xu, H., G. T. Barnes, et al. (2003). "Chronic inflammation in fat plays a crucial role in the development of
obesity-related insulin resistance." J Clin Invest 112(12): 1821-30.
Xu, H., J. Hirosumi, et al. (2002). "Exclusive action of transmembrane TNF alpha in adipose tissue leads to
reduced adipose mass and local but not systemic insulin resistance." Endocrinology 143(4): 1502-
11.
Xu, H., J. K. Sethi, et al. (1999). "Transmembrane tumor necrosis factor (TNF)-alpha inhibits adipocyte
differentiation by selectively activating TNF receptor 1." J Biol Chem 274(37): 26287-95.
Xu, H., K. T. Uysal, et al. (2002). "Altered tumor necrosis factor-alpha (TNF-alpha) processing in
adipocytes and increased expression of transmembrane TNF-alpha in obesity." Diabetes 51(6):
1876-83.
Yamauchi, T., J. Kamon, et al. (2002). "Adiponectin stimulates glucose utilization and fatty-acid oxidation
by activating AMP-activated protein kinase." Nat Med 8(11): 1288-95.
Yamauchi, T., J. Kamon, et al. (2003). "Globular adiponectin protected ob/ob mice from diabetes and
ApoE-deficient mice from atherosclerosis." J Biol Chem 278(4): 2461-8.
Yamauchi, T., J. Kamon, et al. (2001). "The fat-derived hormone adiponectin reverses insulin resistance
associated with both lipoatrophy and obesity." Nat Med 7(8): 941-6.
Yuan, M., N. Konstantopoulos, et al. (2001). "Reversal of obesity- and diet-induced insulin resistance with
salicylates or targeted disruption of Ikkbeta." Science 293(5535): 1673-7.
Yudkin, J. S., C. D. Stehouwer, et al. (1999). "C-reactive protein in healthy subjects: associations with
obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating
from adipose tissue?" Arterioscler Thromb Vasc Biol 19(4): 972-8.
Zahorska-Markiewicz, B., J. Janowska, et al. (2000). "Serum concentrations of TNF-alpha and soluble
TNF-alpha receptors in obesity." Int J Obes Relat Metab Disord 24(11): 1392-5.
Zhan, S. and S. C. Ho (2005). "Meta-analysis of the effects of soy protein containing isoflavones on the
lipid profile." Am J Clin Nutr 81(2): 397-408.
Zhang, Y., R. Proenca, et al. (1994). "Positional cloning of the mouse obese gene and its human
homologue." Nature 372(6505): 425-32.
Zheng, X., C. M. Kammerer, et al. (2009). "Association of SLC34A2 variation and sodium-lithium
countertransport activity in humans and baboons." Am J Hypertens 22(3): 288-93.
Zick, Y. (2005). "Ser/Thr phosphorylation of IRS proteins: a molecular basis for insulin resistance." Sci
STKE 2005(268): pe4.
Zimmet, P., K. G. Alberti, et al. (2001). "Global and societal implications of the diabetes epidemic." Nature
414(6865): 782-7.
Zuccon, A. and D. Zuccon (2008). "MrEnt v.2. Program distributed by authors.".
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SCHOLASTIC VITA
STANTON BRADLEY GRAY
BORN: September 22, 1968, Oklahoma City, Oklahoma UNDERGRADUATE University of Oklahoma STUDY: Norman, Oklahoma B.S., Zoology, 1991 GRADUATE STUDY: Oklahoma State University College of Veterinary Medicine
151
Stillwater, Oklahoma D.V.M., 2001 Wake Forest University Winston Salem, North Carolina Ph.D., 2009 SCHOLASTIC AND PROFESSIONAL EXPERIENCE Residency, Comparative Medicine, SUNY at Buffalo, 2004-2005 Post-doctoral Fellowship, Comparative Medicine, Wake Forest University Health
Sciences, Winston Salem, NC, 2005-2008