Nada Lukkahatai, PhD, RN Co-authors: B. Majors, BS; S. Reddy, PhD; B. Walitt, MD; L. Saligan, PhD.
-
Upload
clement-hoover -
Category
Documents
-
view
215 -
download
1
Transcript of Nada Lukkahatai, PhD, RN Co-authors: B. Majors, BS; S. Reddy, PhD; B. Walitt, MD; L. Saligan, PhD.
Nada Lukkahatai, PhD, RN
Co-authors: B. Majors, BS; S. Reddy, PhD; B. Walitt, MD; L. Saligan, PhD
Conflict of Interest
There is no conflict of interest to report.
Study Objective and Questions
Objective:
To examine differential expression of genes from fatigued fibromyalgia women with different levels of pain and catastrophizing.
Specific Research Questions:
Does the gene expression profile different in fatigued fibromyalgia women with high and low pain severities?
Does the gene expression profile different in fatigued fibromyalgia women with high and low catastrophizing?
Fibromyalgia
Fibromyalgia (FM) is characterized by prolonged widespread muscle pain, profound fatigue, and sleep disturbance.
An estimated 10 million Americans and 200-400 million adults worldwide suffer from FM.
Prevalence: 3 times higher among women than men.
5.5 million FM patients visit the ambulatory care per year.
The etiology of the fibromyalgia is unknown.
Diagnostic Criteria for FM
1990 American College of Rheumatology (ACR)
Criteria
1.History of chronic widespread pain
2.Pain in at least 11/18 tender point sites on digital palpation.
2010 ACR Criteria
1. Widespread Pain Index (WPI) > 7 and Symptom Severity (SS) Scale score > 5
or
2.WPI = 3-6 and SS > 9
3.Symptoms present at similar level for > 3 months
4.No other disorder explaining the pain.
Diagnostic Criteria for FM
Catastrophizing
Catastrophizing is an exaggerated negative attention to symptoms.
Pain catastrophizing significantly predicts pain severity, chronic illness-related disability & emotional distress.
High fatigue catastrophizing is associated with high fatigue severity in breast cancer patients and predicts post cancer treatment fatigue.
Cognitive behavioral intervention focus on addressing maladaptive thinking improve fatigue severity and depression in chronic fatigue syndrome.
Gaps in Knowledge
No study has explored the role of catastrophizing in influencing possible biologic correlates of pain and fatigue in FM.
Little is known about the mechanisms that can explain both pain and fatigue symptoms experienced by FM patients.
Few studies have looked at possible genomic correlates of FM.
Study
Actively recruiting MedStar Research Institute protocol.
Women diagnosed with FM based on the 1990 and 2010 diagnostic criteria are currently enrolled in this study.
Methods
Questionnaires:
Pain severity subscale of Brief Pain Inventory (BPI) 4-item subscale; the mean subscale score ranged from 0 to 10. The cutoff score that is clinically significant is 5.
General fatigue subscale - Multidimensional Fatigue Inventory (MFI) 4-item subscale; score range from 4-20. The score of ≥ 13 is significant fatigue.
Pain Catastrophizing Scale (PCS) = 13-item questionnaire; scores ranged from 0 - 52. Suggested clinical cut point is 16.
Gene Expression
Microarray technology using Affymetrix GeneChip® human genome U133 Plus 2.0 array was used on blood collected using Paxgene® tubes.
Differential gene expression was analyzed using Partek software.
Gene selection criteria: over 2-fold increase or decrease, p < 0.05.
Network analyses by Ingenuity® software.
Whole blood Collected using Paxgene tubes
Extracted RNA
Microarray
Biological sample collection and analysis:
U133 Plus 2.0
Sample Characteristics
9 Caucasian, female, diagnosed with FM, 26-64 years old
Min Max Mean (SD) Clinical Cut-off
General Fatigue 13 20 17.1 (2.7) >13
Pain severity 0.5 6.3 4.1 (1.9) >5
Catastrophizing 4.0 36.0 17.0 (9.8) >16
Categories of Pain and Catastrophizing
N = 9
Pain:
- Low pain (pain severity < 5) n = 6
- High pain (pain severity ≥ 5) n = 3
Catastrophizing:
- Low catastrophizing (PCS < 16) n = 4
- High catastrophizing (PCS ≥ 16) n = 5
High Pain Severity vs. Low Pain Severity (112 genes)
Gene Symbol
Gene Title Functionp-
valueFold-
Change
BATF2
basic leucine zipper
transcription factor, ATF-
like 2
Protein binding/ protein
dimerization activity
0.0002 2.1
CASP5
caspase 5, apoptosis-
related cysteine
peptidase
Cyteine-type endopeptidase
activity0.0003 2.7
CCR1chemokine (C-C motif) receptor 1
C-C chemokine binding,
chemokine (C-C motif) activity
0.0004 2.2
CEACAM1
carcinoembryonic antigen-related cell adhesion
molecule 1
Molecular function, protein
binding0.001 2.4
COMMD6COMM domain
containing 6
NF-kappa-B binding/ protein
binding0.001 4.1
Gene Symbol
Gene Title Functionp-
valueFold-
Change
RPL7ribosomal protein L7
protein dimerization
activity0.02 -2.9
SH2D1BSH2 domain containing
1B
Immune responses
0.04 -2.8
SIGLEC1
sialic acid binding Ig-
like lectin 1, sialoadhesin
Carbonydrate binding
0.04 -2.7
UQCRB
ubiquinol-cytochrome c
reductase binding protein
ubiquinol-cytochrome-c
reductase activity
0.05 -2.6
ZCCHC2
zinc finger, CCHC domain
containing 2
Nucleic acid binding
0.05 -2.6
Up- regulated genes Down- regulated genes
Network Analysis for high pain vs. low pain
High Catastrophizing vs. Low Catastrophizing (63 genes)
Gene Symbol
Gene Title function p-valueFold-
Change
USP46ubiquitin specific
peptidase 46
Ubiquitin-specific protease activity
0.001 -2.2
SEPT10 septin 10 GTP binding 0.002 -2.0
CLEC4DC-type lectin
domain family 4, member D
Carbonydrate binding
0.005 -2.3
ZDHHC2zinc finger, DHHC-type containing 2
Zinc ion binding
0.005 -2.2
FAS
Fas (TNF receptor
superfamily, member 6)
Identical protein binding/ signal
transducer activity
0.010 -2.0
Gene Symbol
Gene Title functionp-
valueFold-
Change
SPP1secreted
phosphoprotein 1Cytokine activity
0.01 2.1
TMTC1
transmembrane and
tetratricopeptide repeat containing
1
Integral to membrane
0.02 2.5
SLC6A8
solute carrier family 6
(neurotransmitter transporter, creatine), member 8
Creatine transporter
activity/ molecular function
0.03 2.4
NPRL3
nitrogen permease
regulator-like 3 (S. cerevisiae)
Molecular function
0.04 2.1
HEMGN hemogenProtein binding
0.04 2.2
Up- regulated genes Down- regulated genes
Network Analysis high vs. low catastrophizing
Differentially Expressed Genes of Interest
Basic leucine zipper protein (BATF2) is regulated by interferon and serves as a suppressor of activating protein-1 (AP-1).
Caspase 5, apoptosis-related cysteine peptidase (CASP5) and chemokine (C-C motif) receptor 1 (CCR1) are associated with immune response and inflammation in musculoskeletal disorders.
Secreted phosphoprotein 1 (SPP1 or Osteopontin) is up-regulated during inflammation and associated with muscular dystrophies.
Ubiquitin specific peptidase 46 (USP46) is a GABA regulation gene. In animal study, deletion of USP46 is associated with depression-like behaviors in mice and rats.
High vs Low Pain High vs Low Catastrophizing
Discussion
FibromyalgiaFibromyalgia
Physiological responses: Pain and fatigue
Physiological responses: Pain and fatigue
Behavioral responses: Catastrophizing,
depression
Behavioral responses: Catastrophizing,
depression
STRESSOR
USP46
Pituitary adrenocorticotropin (ACTH)
InflammationInflammation
Inflammatory Cells: Leukocytes, Lymphocytes, Platelets, Mast
Cells, Macrophages
Inflammatory Cells: Leukocytes, Lymphocytes, Platelets, Mast
Cells, Macrophages
Cytokines, Nerve Growth factor, prostaglandins,
Thromboxanes, Leukotrienes, Serotonin
Cytokines, Nerve Growth factor, prostaglandins,
Thromboxanes, Leukotrienes, Serotonin
BATF2CASP5CCR1
SPP1
Conclusion of Preliminary Study
Differentially expressed genes may delineate mechanisms between pain and fatigue.
Catastrophizing may serve as a behavioral correlate in FM.
Differentially expressed genes may serve as a biological correlate for catastrophizing.
Leorey N. Saligan, PhD, CRNPTenure-Track Investigator
National Institute of Nursing Research, Intramural Research Program
Brian Walitt, MD, MPH, FACRAssociate Professor of Medicine
Georgetown University Medical Center
Benjamin Majors, BSNational Institute of Nursing Research, Intramural Research Program
Swarnalatha Reddy, PhDNational Institute of Nursing Research, Intramural Research Program
Acknowledgements
1. Wolfe, F., & Hawley, D. J. (1999). Evidence of disordered symptom appraisal in fibromyalgia: Increased rates of reported comorbidity and comorbidity severity. Clinical and Experimental Rheumatology, 17, 297–303.
2. About Fibromyalgia: Prevalence, National Fibromyalgia Association, 2009, http://www.fmaware.org/
3. Lawrence, R.C. et al., (2008). Estimate of prevalence of arthritis and other rheumatic conditions in the United State. Part II. Arthritis Rheumatology. 58(1), 26-35
4. Sacks JJ , Luo YH, Helmick CG. (2010) Prevalence of specific types of arthritis and other rheumatic conditions in the ambulatory health care system in the United States, 2001-2005. Arth Care Res; 62(4):460-4
5. Burger A., Dukes E., Martin, S. Edelsberg, J. Oster G. (2007). Characteristics and healthcare costs of patients with fibromyalgia syndrome. International Journal of Clinical Practice; 61(9): 1498-1508
6. Light, KC, White, A.T., Tadler, S. Iacob, E., Light, AR. (2012). Genetics and gene expression involving stress and distress pathways in Fibromyalgia with and without comorbid Chronic Fatigue Syndrome. Pain Research and Treatment; doi:10.1155/2012/427869
7. Lee, YH, Choi SJ, Ji JD, Song GG. (2012), Candidate gene studies of fibromyalgia: a systematic review and meta-analysis. Rheumatology International 32(2): 417-26
8. Wolfe F, Hauser W. (2010). Fibromyalgia diagnosis and diagnostic criteria. Ann. Med. 43(7): 495-502
9. Pavlin DJ, Sullivan MJ, Freund PR, Rosen K. (2005). Catastrophizing: a risk factor for postsurgical pain. Clinical journal of pain. 21(1): 83-90.
10. Edward RR, Cahalan C, Mensing G, Smith M, Haythornthwaite JA (2011). Pain, catastrophizing and depression in the rheumatic diseases. Nat Rev Rheumatol. 7(4): 216-24
11. Jacobsen PB, Andrykowski MA, Thors CL (2004). Relationship of catastrophizing to fatigue among women receiving treament for breast cancer. Journal of consult Clinical Psychology 72(2): 355-61
References
12. Andrykowski MA, Donovan KA, Loronga C. Jacobsen PB. (2010). Prevalence, predictors and characterisitics of off-treatment fatigue in breast cancer survivors. Cancer. 116(24). 5740-8. doi: 10.1002/cncr.25294. Epub 2010 Aug 23.
13. Friedberg F, Krupp LB (1994). A comparison of cognitive behavioral treatment for chronic fatigue syndrome and primary depression. Clinical Infectious diseases. 18 Suppl 1: S105-10
14. Martinez-Lavin M. (2007). Biology and therapy of fibromyalgia. Stress, the stress response system, and fibromyalgia. Arthritis Res Ther. 9(4): 216
15. Castel LD, Abernethy AP, Li Y, Depuy V, Saville BR, Hartmann KE. (2007). Hazards for pain severity and pain interference with daily living, with exploratioin of brief pain inventory cutpoints, among women with metastatic breast cancer. Journal of Pain and symptoms Management. 34(4): 380-92
16. Reeves WC, Wagner D, Nisenbaum, R, Jones JF, Gurbaxani B, Solomon L, Papanicolaou DA, Unger ER, Vernon SD, Heim, C. (2005). Chronic fatigue syndrome- A clinically empirical approach to it definition and study. BMC Med. 15; 3-19
17. Riddle DL, Wade JB, Jiranek WA, Kong X. (2010). Preoperative pain catastrophizing predicts pain outcome after knee arthroplasty. Clinical Orthopedic Related research. 468(3): 798-806
18. Ma H, Liang X, Chen Y, Pan K, Sun J, Wang H, Wang Q, Li Y, Zhao J, Li J, Chen M. Xia J. (2011) Decreased expression of BATF2 is associated with poor prognosis in hepatocellular carcinoma. International Journal of Cancer. 15; 128(4): 771-7
19 Huang W. Sowa G. (2011) Biomarker development for musculoskeletal diseases. PM.R. 3 (6 Suppl 1): S39-44
20. Xu G, et al. (2005). Overexpression of osteopontin in rheumatoid synovial mononuclear cells is associated with joint inflammation, not with genetic polymorphism. Journal of Rheumatology. 32(3): 410-6
21. Fukuo Y. et al., (2011). Possible association between ubiquitin-specific peptidase 46 gene and major depressive disorder in the Japanese population. J Affect Disord. 133 (1-2): 150-7
22 Zhang W. et al., (2011) Lysine 92 amino residue of USP46, a gene associated with “behavioral despair” in mice, influences the deubiquitinating enzyme activity. PLoS One. 2011;6(10):e26297. Epub 2011 Oct 17
References