NIKOS SCARMEAS MD, MSc · •Vitamin B12 •Crystal, Ortof et al. 1994, Seshadri, Baser et al. ......
Transcript of NIKOS SCARMEAS MD, MSc · •Vitamin B12 •Crystal, Ortof et al. 1994, Seshadri, Baser et al. ......
Dietary Intervention – Evidence in AD – How can we improve?
NIKOS SCARMEAS MD, MSc Associate Professor of Neurology Columbia University, New York, USA
National and Kapodistrian University of Athens, Greece
Disclosures: None
Research Support: NIA RO1: AG028506, / Alzheimer’s Association IIRG-04-1353
RASAD conference Melbourne, March 2012
Dietary Intervention – Evidence in AD – How can we improve?
• Literature review (brief)
• Limitations of current state of the art
• Attempts to partially address some of these issues
• Future roadmap – some thoughts
Lower risk of AD or slower cognitive decline
•Vitamin C •Masaki, Losonczy et al. 2000; Engelhart, Geerlings et al. 2002; Zandi, Anthony et al. 2004; Morris, Beckett et al. 1998
•Vitamin E •Masaki, Losonczy et al. 2000; Engelhart, Geerlings et al. 2002; Morris, Beckett et al. 1998; Morris, Evans et al. 2002; Morris, Evans et al. 2002; Zandi, Anthony et al. 2004; Corrada, Kawas et al. 2005
•Vitamin B12 •La Rue, Koehler et al. 1997; Clarke, Smith et al. 1998; Wang, Wahlin et al. 2001; Haan et al. 2007; Tangney 2009
•Vitamin B6 •Corrada, Kawas et al. 2005
•Folate •Clarke, Smith et al. 1998; Wang, Wahlin et al. 2001; Ravaglia 2005; Corrada, Kawas et al. 2005; Balk 2007 (metaanal-interv).
•Modest to Moderate ETOH •Orgogozo, Dartigues et al. 1997; Ruitenberg, van Swieten et al. 2002; Truelsen, Thudium et al. 2002; Mukamal, Kuller et al. 2003; Luchsinger, Tang et al. 2004; Ganguli , Vander Bilt et al. 2005; Espeland, Gu et al. 2004; Stampfer Kang et al 2005
•Flavonoids •Commenges, Scotet et al. 2000
•Caroten •Barberger-Gateau et al 2007;
•Fish •Barberger-Gateau, Letenneur et al. 2002; Morris, Evans et al. 2003; Morris, Evans et al. 2005; Huang, Zandi et al; 2005;
Barberger-Gateau et al 2007;
•Unsaturated fatty acids •Kalmijn, Feskens et al. 1997; Morris, Evans et al. 2003; Morris, Evans et al. 2003; Schaefer, Bongard et al. 2006; Laitinen et al.
2006; Barberger-Gateau et al 2007;
•Lower total fats, cholesterol, saturated fats
•Kalmijn, Launer et al. 1997; Kalmijn, vanBoxtel et al. 2004; Morris, Evans et al. 2003; Luchsinger, Tang et al. 2002; Laitinen et al. 2006
•Coffee •Maia, de Mendonca 2002
•Fruits •Dai, Borenstein et al 2006; Barberger-Gateau et al 2007;
•Vegetables (polyphenol antioxidants?) •Dai, Borenstein et al 2006, Kang, Grodstein; Research-Practice AD 2007, Barberger-Gateau et al 2007;
•Curry (curcumin - antiinflammatory? antioxidant?)
•Tze-Pin Ng et al 2006
Risk for AD or cognitive decline not associated with
•Vitamin C •Luchsinger, Tang et al. 2003, Masaki, Losonczy et al. 2000, Heart Protection Study 2002; Laurin, Masaki et al. 2004; Dai, Borenstein et al 2006; Yaffe 2004
•Vitamin E
•Sano 1997; Luchsinger, Tang et al. 2003, Masaki, Losonczy et al. 2000; Heart Protection Study 2002; Laurin, Masaki et al. 2004; Yaffe 2004; Dai, Borenstein et al 2006; Kang 2006
•Vitamin B12
•Crystal, Ortof et al. 1994, Seshadri, Baser et al. 2002; Morris 2006; Ravaglia 2005; Balk 2007 (metaanal-interv); Aisen 2008
•Vitamin B6 •Seshadri, Baser et al. 2002; Morris 2006; Balk 2007 (metaanal-interv); Aisen 2008
•Folate •Seshadri, Baser et al. 2002; Balk 2007 (metaanal-interv); Haan 2007; Middleton 2007; Morris 2006; Aisen 2008
•Fish •Schaefer, Bongard et al. 2006;
•Fats •Engelhart, Geerlings et al. 2002
•Omega-3 •O.van de Rest et al. 2008
•Carotenes •Heart Protection Study 2002; Luchsinger, Tang et al. 2003; Laurin, Masaki et al. 2004; Yaffe 2004.
•Calcium (high worse) •Van Vliet 2004.
•Wine •Dai, Borenstein et al 2006; Barberger-Gateau et al 2007;
•Flavonoids •Laurin, Masaki et al. 2004.
•Tea •Forster, Newens et al. 1995; Rogers, Simon et al. 1999
•Fruits •Kang, Grodstein; Research-Practice AD 2007
Limitations - Issues
Limitations - Issues
• Nutrients – Cognition U-shaped curve
– Stratification by different levels of nutrient intake
– Consideration of efficacy of supplementation in subgroup analyses
Morris, M. C. et al. JAMA 2011;305:1348-1349 Copyright restrictions may apply.
Nutrient levels are rarely considered in trial inclusion criteria. Further, trial volunteers are typically healthy behavior–seeking individuals and are unlikely to have low nutrient intake. More probably, intake levels are already at the level for optimal functioning (Figure, point a) and further supplementation provides no additional benefit (Figure, point b).
Copyright restrictions may apply.
Kang, J. H. et al. Arch Intern Med 2006;166:2462-2468.
Mean Difference in Rate of Decline in Global Score Between Vitamin E and Placebo Groups: Effect Modification by Major Risk Factors for Cognitive Decline
Characteristics
Mean difference in cognitive decline between groups (95% CI)2
Global Score Verbal score TICS score Category fluency score
Dietary folate intake
<279 mg/d (n = 293) 0.14 (–0.01, 0.29) 0.14 (–0.04, 0.31) 1.24 (0.47, 2.00) –0.19 (–0.61, 0.24)
≥279 mg/d (n = 1637) 0.01 (–0.05, 0.07) 0.00 (–0.06, 0.07) –0.04 (–0.34, 0.26) 0.00 (–0.99, 0.99)
P3 0.11 0.16 0.002 0.73
Dietary vitamin B-6 intake
<1.9 mg/d (n = 524) 0.02 (–0.05, 0.08) 0.07 (–0.05, 0.20) 0.56 (0.03, 1.10) –0.69 (–1.43, 0.05)
≥1.9 mg/d (n = 1406) 0.05 (–0.06, 0.15) 0.01 (–0.07, 0.08) 0.00 (–0.33, 0.33) 0.03 (–0.43, 0.49)
P3 0.63 0.35 0.08 0.10
Dietary vitamin B-12 intake
<2.4 µg/d (n = 82) 0.19 (–0.06, 0.44) 0.10 (–0.21, 0.41) 1.35 (0.16, 2.54) 1.62 (0.11, 3.13)
≥2.4 µg/d (n = 1848) 0.02 (–0.04, 0.08) 0.02 (–0.04, 0.09) 0.10 (–0.18, 0.39) –0.24 (–0.64, 0.17)
P3 0.19 0.62 0.05 0.02
Overall dietary vitamin B intake
Low (n = 573)4 0.09 (–0.01, 0.20) 0.12 (0.00, 0.24) 0.74 (0.23, 1.25) –0.39 (–1.10, 0.32)
Adequate (n = 1357)5 0.00 (–0.07, 0.06) –0.02 (–0.09, 0.06) –0.10 (–0.43, 0.24) –0.07 (–0.54, 0.40)
P3 0.11 0.06 0.01 0.46
TABLE 4 Mean decline between B vitamin and placebo groups: effect modification by major risk factors for cognitive decline1
Kang JH, et al. . A trial of B vitamins and cognitive function among women at high risk of cardiovascular disease. Am J Clin Nutr. 2008;88(6):1602–1610.
…….targeted individuals who were found to have insufficient folate nutriture based on a stringent set of biochemical criteria
Limitations - Issues
• Clinical trials vs. Observational epidemiological studies – Lack of randomization
– Residual confounding
– Reverse causality
• But if trials (particularly 1ary or 2ary prevention) to be done for nutritional factors – High Cost
– Timing
– Long Duration
– Additional difficulty of implementation - behavioral intervention (if diet and not just supplement)
Limitations - Issues
• Outcome (Cognitive decline - Dementia - AD diagnosis) issue – Accuracy– lack of diagnostic biomarker
– Subjectivity of clinical judgment
– Limitation of objective measures (slopes of cognitive decline)
• Variability of cognitive performance
• Learning effects
– Error / noise increases required sample size
– “The last doctor is the smartest one” – increasing challenge – error/noise with earlier diagnosis
Limitations - Issues
• Exposure - Dietary assessment issues
– Noise in FFQ recordings
• Please fill in your average total consumption of peaches or plums (1 fresh or ½ cup canned) during the last year. Please try to average your seasonal use of foods during the entire year
• <1 serving/month,
• 1-3 servings/month,
• 1 serving/week,
• 2-4 servings/week,
• 5-6 servings/week,
• 1 serving/day,
• 2-3 servings/day,
• 4-5 servings/day,
• >6 servings/day.
Limitations - Issues
• Exposure - Dietary assessment issues
– Reporting accuracy – cognition / informant
– Limited number of foods – nutrients • If specific effect of a specific food – nutrient, will be lost in the FFQ
questions
• Underestimation of total amounts - calories
– Blood nutrient biomarkers – bioavailable levels of nutrients • Interaction of intake + inherent absorption / metabolism etc
• Still not reflective of cerebral penetration – CSF?
• More practical difficulties (blood, urine, transport, freezing, maintenance)
• Cost
• Interactions: ‘foods are more than their nutrients’
• Chemical composition of foods not completely known
Limitations - Issues
• Multiplicity of foods – nutrients
– Individuals do not consume foods or nutrients in isolation but rather as components of their overall daily diet.
– Interactions • Fish consumption had a greater effect in reducing platelet aggregation when part of a
low-fat rather than a high-fat diet (Mori, Beilin et al. 1997).
• Effect of fish consumption in lowering blood pressure (Vandongen, Mori et al. 1993) and blood lipids (Mori, Vandongen et al. 1994) seems to be much more pronounced in subjects following a low fat diet.
• Higher copper consumption associated with faster cognitive decline only among subjects with high intake of saturated and trans fats (Morris, Evans et al. 2006).
– Multiple comparisons
– Colinearity
– Difficulty controlling for dietary cofounding in studies examining other parameters.
Limitations - Issues
• Multiplicity of biological mechanisms – processes leading to cognitive decline
• Potential nutritional effects of opposing directionality
Nutrient (Vit E)
Metabolic
Vascular
Cognition Cognition
Inflammatory
Oxidative
Amyloid
Tau
A - synuclein Harmful Helpful Neutral
Limitations - Issues
• Multiplicity of interactions among many foods-nutrients and many mechanisms
Nutrient A Vit E
Metabolic
Vascular
Cognition Cognition
Inflammatory
Oxidative
Amyloid
Tau
A - synuclein
Harmful Helpful Neutral
Nutrient B …..
Metabolic
Vascular
Cognition Cognition
Inflammatory
Oxidative
Amyloid
Tau
A - synuclein
Cognition
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Dietary Pattern approach
• Can be developed a posteriori on the basis of already existing data (empirical aggregation of individuals with similar diets based on their reported intake of food) – Use of various multivariate methods such as discriminant
analyses, principal components analyses or cluster analyses
• Can be developed a priori on the basis of previous knowledge concerning a favorable or adverse health effect of various dietary constituents
• Or combination of a posteriori and a priori methods: reduced rank regression (RRR) or maximum redundancy analyses
Observed variables used in current step of analysis
Nutrients:SFA, MUFA, ω-3 PUFA, ω-6 PUFA,Vit E, Vit B12, Folate
Alzheimer’s Disease/Cognitive Performance
Nutrients:SFA, MUFA, ω-3 PUFA, ω-6 PUFA,Vit E, Vit B12, Folate
Nutrients:SFA, MUFA, ω-3 PUFA, ω-6 PUFA,Vit E, Vit B12, Folate
30 Food groups:Fruits, Fish,Nuts, Red Meat, etc.
Principal Components Analysis
Response variables(Nutrient Factors)
Factor Scores
(Dietary Patterns)
Regression
Alzheimer’s Disease/Cognitive Performance
Response variables(Nutrient factors)
Nutrients:SFA, MUFA, ω-3 PUFA, ω-6 PUFA,Vit E, Vit B12, Folate
Factor Scores
(Dietary Patterns)
Alzheimer’s Disease/Cognitive Performance
Response variables(Nutrient factors)
Outcome Risk Estimation Model
30 Food groups:Fruits, Fish,Nuts, Red Meat, etc.
30 Food groups:Fruits, Fish,Nuts, Red Meat, etc.
30 Food groups:Fruits, Fish,Nuts, Red Meat, etc.
Alzheimer’s Disease/Cognitive Performance
Latent variables used in current step of analysis
Observed variables not used in current step of analysis
Latent variables not used in current step of analysis
New latent variables developed from current step of analysis
RRR Step 1
RRR Step 2
RRR Step 3
Biological Mechanism
Copyright restrictions may apply.
Gu, Y. et al. Arch Neurol 2010;67:699-706.
Explained Variations of Nutrients and Food Groups by Extracted DPs and Correlations Between Nutrients and DP Scores
Dietary Pattern 2
NUTRIENTS
SFA,
B12
Ω3 PUFA
Ω6 PUFA
Vit E
Folate
↓
↑
Dietary Pattern
higher intakes ↑ salad dressing
nuts
fish
tomatoes
poultry
cruciferous vegetables
fruits
dark and green leafy vegetables
lower intake ↓
high-fat dairy
red meat
organ meat
butter
NUTRIENTS
SFA,
B12
Ω3 PUFA
Ω6 PUFA
Vit E
Folate
↓
↑
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Gu, Y. et al. Arch Neurol 2010;67:699-706.
Survival curves based on Cox analysis comparing cumulative Alzheimer disease incidence in subjects belonging to each dietary pattern (DP) score 2 tertile (P for
trend <.001)
Dietary Pattern approach
•Disadvantages •Subjectivity in selection / weighting •Due to above, issues with external reproducibility •Limited elucidation of our understanding of the biological mechanisms that mediate their association with disease.
•Advantages •Interaction – confouding reduction •Colinearity •Multiple comparisons – type I error •Public health •Summarize diet (to be used as a covariate ) in other
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Scarmeas, N. et al. JAMA 2009;302:627-637.
Cox Proportional Hazard Ratios (HRs) for Alzheimer Disease (AD) Incidence by Physical Activity and Mediterranean-Type Diet Scores
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Scarmeas, N. et al. JAMA 2009;302:627-637.
Alzheimer Disease (AD) Incidence in Individuals by No, Some, or Much Physical Activity and Low, Middle, and High Mediterranean-Type Diet Adherence Scores
Unadjusted HR: 0.78 (0.53-1.14) 0.63 (0.43-0.92) 0.46 (0.31-0.69) 0.33 (0.19-0.57) Trend: 0.77 (0.69-0.85) p<0.001
Adjusted HR: 0.96 (0.60-1.55) 0.92 (0.59-1.43) 0.58 (0.36-0.95) 0.39 (0.20-0.76) Trend: 0.80 (0.71-0.90) p<0.001
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Tangney et al. Neurology® 2011;77: 1276–1282
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Diet
Metabolic Insulin
Adiponectin
Vascular Clinical
Homocysteine
Alzheimer’s disease Inflammatory
IL-6 IL-1 CRP
Oxidative Isoprostanes
MeDi
Vascular Variables
Heart disease,
Stroke,
Diabetes,
Hypertension
HDL, TG, LDL
Alzheimer’s disease
MeDi Alzheimer’s
disease
Simple Model
Vascular Mediation Model
Copyright restrictions may apply.
Scarmeas, N. et al. Arch Neurol 2006;63:1709-1717.
Odds Ratios for Subjects With Alzheimer Disease vs, Nondemented Subjects by Mediterranean Diet Score in Continuous and Tertile Form
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Diet
Metabolic Insulin
Adiponectin
Vascular Clinical,
Homocysteine MRI SCI, WMH
Alzheimer’s disease Inflammatory
IL-6 IL-1 CRP
Oxidative Isoprostanes
MeDi Alzheimer’s
disease
Initial Simple Model
MeDi Mediating Variables
hs CRP
Insulin
Adiponectin
Alzheimer’s disease
Inflammatory / Metabolic Mediation Model
• 1219 non demented subjects
• hsCRP, Insulin, Adiponectin measured at baseline
• 118 incident AD cases after 4 years of follow-up
Diet
Vascular
Cognition
Inflammatory
Oxidative
Metabolic
Amyloid
Nutrientsintakeandplasmaβ-amyloid Yian Gu, PhD1, Nicole Schupf, PhD1,2,3, Stephanie A. Cosentino, PhD1,2,4,
Jose A. Luchsinger, MD 1,2,5, Nikolaos Scarmeas, MD 1,2,4
Gu et al. Neurology. In press.
ABSTRACT
Objective: The widely-reported associations between various nutrients and cognition may occur through many biological
pathways including those of beta-amyloid (Aβ). However, little is known about the possible associations of dietary factors with
plasma Aβ40 or Aβ42. The current study aims to evaluate the association between nutrients intake and plasma Aβ levels.
Methods: In this cross-sectional study, plasma Aβ40 and Aβ42 and dietary data were obtained from 1219 cognitively healthy
elderly (age>65), who were participants of a community-based multi-ethnic cohort. Information on dietary intake was obtained 1.2
years, on average, before Aβ assay. The associations of plasma Aβ40 and Aβ42 levels and dietary intake of 10 nutrients were
examined using linear regression models, adjusted for age, gender, ethnicity, education, caloric intake, Apolipoprotein E genotype,
and recruitment wave. Nutrients examined included saturated fatty acid, mono-unsaturated fatty acid, ω-3 poly-unsaturated fatty
acid (PUFA), ω-6 PUFA, vitamin E, vitamin C, β-carotene, vitamin B12, folate, and vitamin D.
Results: In unadjusted models that simultaneously included all nutrients, higher intake of ω-3 PUFA was associated with lower
levels of Aβ40 (β=-24.7, p<0.001) and lower levels of Aβ42 (β=-12.3, p<0.001). In adjusted models, ω-3 PUFA remained a strong
predictor of Aβ42 (β=-7.31, p=0.02), while its association with Aβ40 was attenuated (β=-11.96, p=0.06). Other nutrients were not
associated with plasma Aβ levels.
Conclusions: Our data suggest that higher dietary intake of ω-3 PUFA is associated with lower plasma levels of Aβ42, a profile
linked with reduced risk of incident AD and slower cognitive decline in our cohort.
Gu et al. Neurology. In press.
Model‡ Predictor
Number β p Number β
Model 1 Vitamin E 1219 -0.34 0.68 1208 -0.1
Vitamin C -0.01 0.69 0.02
Folate 0 0.86 0
Vitamin B12 0.21 0.34 0
Vitamin D 0.02 0.29 0.01
β carotene 0 0.86 0
ω-6 PUFA 1.94 0.09 0.63
SFA 0.93 0.15 0.53
MUFA -1.21 0.11 -0.65
ω-3 PUFA -24.74 <0.001 -12.31
Model 2 Vitamin E 1200 -0.06 0.93 1189 -0.01
Vitamin C -0.03 0.24 0.01
Folate -0.01 0.65 -0.01
Vitamin B12 0.31 0.11 0.07
Vitamin D 0.02 0.38 0
β carotene 0 0.76 0
ω-6 PUFA 0.33 0.74 0.07
SFA -0.47 0.41 -0.06
MUFA 0.33 0.62 0
ω-3 PUFA -11.96 0.06 -7.31
Model 3 Vitamin E 1137 -0.62 0.41 1137 -0.12
Vitamin C -0.02 0.36 0.02
Folate -0.01 0.61 -0.01
Vitamin B12 0.33 0.11 0.07
Vitamin D 0.01 0.44 0
β carotene 0 0.56 0
ω-6 PUFA 0.03 0.98 -0.02
SFA -0.6 0.32 -0.06
MUFA 0.57 0.41 0.03
ω-3 PUFA -10.13 0.13 -7.7
0.96
0.84
0.92
0.02
p
0.75
0.13
0.26
0.45
0.75
0.78
0.69
0.86
0.88
0.83
0.99
0.02
0.07
<0.001
0.97
0.22
0.44
0.46
0.87
0.96
0.57
0.84
0.23
0.08
Aβ40 (dependent variable) Aβ42 (dependent variable)
0.78
0.1
‡: Model 1, unadjusted. Model 2, adjusted for age, sex, education, ethnicity, caloric intake, APOE genotype, and recruitment wave. Model 3,
adjusted for all the covariates in Model 2, plus alcohol drinking, use of medications (medications affecting blood vessel thrombus formation
propensity and anti-diabetic agents), and use of nutrients from supplements. A total of 563, 594, 518, 497, 464, 449, 18, and 7 subjects in
the study sample reported taking vitamin E, vitamin C, folate, vitamin B12, vitamin D, β carotene, ω-6, and ω-3 PUFA supplements,
respectively.
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Copyright restrictions may apply. Galasko, D. R. et al. Arch Neurol 2012;0:archneurol.2012.85v1-6.
Copyright restrictions may apply. Galasko, D. R. et al. Arch Neurol 2012;0:archneurol.2012.85v1-6.
Vitamin C Vitamin E
ALA
Tau Cognition ? Cognition ?
Amyloid
Oxidation
Inflammation?
Metabolic ?
A – synuclein ? Harmful Helpful Neutral Unknown
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
High vit B (B1, B2, B6, Folate, B12), C, D, E
Bowman G et al. Neurology 2012;78:241-249
©2012 by Lippincott Williams & Wilkins
High transfat
High omega 3
Tangney et al. Neurology® 2011;77: 1276–1282
The homocysteine-global cognition effect was modified and no longer statistically significant with adjustment for white matter volume or cerebral infarcts. The effect of homocysteine on cognitive performance may be mediated through increased white matter hyperintensity and cerebral infarcts. The methylmalonate-global cognition effect was modified and no longer significant with adjustment for total brain volume. Methylmalonate, a specific marker of B12 deficiency, may affect cognition by reducing total brain volume Vitamin B12 status may affect the brain through multiple mechanisms.
Payne ME et al. Nutrition Research 28 (2008) 285–292
Honolulu-Asia Aging Study (HAAS) , Honolulu Heart Program (HHP); Cognitive Abilities Screening Instrument (CASI)
White LR et al. Journal of the American College of Nutrition, 2000;19(2): 242–255
Virtanen et al. Neurology® 2008;71:439–446
Figure 2 White matter grades according to fish consumption Adjustments were made for fried
fish or tuna/other fish consumption and age, sex, race, enrollment center, diabetes,
education, smoking status, pack-years of smoking, body mass index, coronary heart...
Virtanen J K et al. Neurology 2008;71:439-446 ©2008 by Lippincott Williams & Wilkins
Copyright restrictions may apply.
Paul, C. A. et al. Arch Neurol 2008;65:1363-1367.
Mean total cranial brain volume, including confidence intervals illustrated as error bars, adjusted for age, sex, body mass index (calculated as weight in kilograms divided by height in meters
squared), and Framingham Stroke Risk Profile (slope = -0.25; P < .01; R2 = 0.96)
Copyright restrictions may apply.
Paul, C. A. et al. Arch Neurol 2008;65:1363-1367.
Mean values for total cranial brain volume, including confidence intervals illustrated by error bars, for men (slope = -0.20; P = .02) and women (slope = -0.025; P = .02), adjusted for age, sex, body mass index (calculated as weight in kilograms divided by height in meters squared), and
Framingham Stroke Risk Profile
Population Alcohol WMH Infarcts Atrophy Stratified analysis
Mukamal
KJ, 2001
Stroke
Cardiovascular
Health Study
(CHS), 3660
adults ≥65 years
, mean 75 yrs,
none, former,
<1, 1-7, 7-15,
and ≥15
drink/week.
moderate 1-
7/wk ↓ WMH,
U-shape
heavy
(>=15/wk) ↓
infarcts
heavy (>=15/wk)
↑ atrophy
(↑ventricular and
sulcal sizes)
No modification by
sex, race, APOE.
Types of alcohol have
similar results.
Ding J
2004
Stroke.
Atherosclerosis
Risk in
Communities
(ARIC) Study;
1909 middle-
aged adults
(40% men and
49% blacks)
never, former,
<1, 1-7, and ≥7
drinks/week.
No linear
association
No association
after ajdustment
↑ atrophy
(↑ventricular and
sulcal sizes)
No modification by
sex or race. No types
of alcohol
information.
den Heijer
T, 2004
Am J Clin
Nutr
Rotterdam Scan
Study. 1074
persons aged 60-
90 without
dementia
Lifetime
abstention,
former, <1, 1-7,
7-28, and ≥28
drinks/week
moderate 1-
7/wk ↓ WMH,
U-shape
moderate 1-
7/wk ↓ infarcts
(not
signnificant)
↑ hippocampal
and amygdalar
volumes in
carriers APOE
e4 only.
Modified by APOE.
Modification by sex
not tested. No types of
alcohol information.
Paul CA,
Arch
Neurol.
2008
Framingham
Offspring
Study;1839
(861M); 60 yrs
(range33-88)
abstainers,
former, 1-7, 8-
14, and ≥ 14
drink/week N/A N/A
↑ atrophy
(↓TCBV),
stronger in
women than in
men.
Modified by sex; No
types of alcohol.
Fukuda K,
2009 J
Neuro Sci
385 Japan >or=
40 years, mean
67.2
non-drinkers,<7,
and moderate
drinkers (≥7
drinks/week)
moderate ↑
WMH
moderate ↑
infarcts
moderate ↑
atrophy (↓brain
volume)
Modification by sex
not tested. No types of
alcohol information.
ETOH
Metabolic ?
Atrophy Neuronal death
Cognition ? Cognition ?
Infarcts Vascular
WMH Vascular? Amyloid?
Amyloid ?
Tau ?
A – synuclein ?
Harmful Helpful Unkonwn
Copyright restrictions may apply.
Gardener, H. et al. Arch Neurol 2012;69:251-256.
Association Between Mediterranean Diet and White Matter Hyperintensity Volume
Copyright restrictions may apply.
Gardener, H. et al. Arch Neurol 2012;69:251-256.
Association Between Each Component of the Mediterranean Diet Score and White Matter Hyperintensity Volume
Small infarct (<1cm)
Large infarct (>1cm)
Scarmeas et al. Annals of Neurology, 2010
– Multiplicity of nutrients – food groups
• DIETARY PATTERNS
– FFQ noise
• Nutrient biomarkers
– Explore – clarify mechanisms
• Clinical tools
• Plasma tools
• CSF tools
• Imaging tools
Attempts to partially address some of these issues
Roadmap
• Continue to investigate specific neurobiological mechanisms (plasma, CSF, imaging etc)
• Select best (in terms of strength and consistency of association) nutrients, foods, patterns.
• Replicability in other datasets • Prospective component • Combine multiple datasets in ‘nutritional meta-
analyses’ • Biomarker-powered preliminary interventional
randomized studies • Large trials informed by above
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Paul, C. A. et al. Arch Neurol 2008;65:1363-1367.
Distribution of Alcohol Consumption in the Total Sample, Men, and Women
Payne ME et al. Nutrition Research 28 (2008) 285–292
Gray and white matter lesion areas were selected based upon a set of rules that allows trained analysts to reliably select lesion regions. Periventricular lesions were defined as regions that were contiguous with lateral ventricle and did not extend into the white matter tracts. These lesions were classified as white matter lesions. Deep white matter lesions were located in the white matter tracts and may or may not have adjoined periventricular lesions. Subcortical gray matter lesions were defined as lesions within the basal ganglia or thalamus. Total lesion volumes were composed of both gray matter lesions and white matter lesions, although white matter lesions predominated.
Tangney et al. Neurology® 2011;77: 1276–1282
Tangney et al. Neurology® 2011;77: 1276–1282
Initial N:1410 (vs. 2258)
Incident AD: 66 (vs. 262)
Medicare Spending on Alzheimer’s Disease (in billions)
$62$91
$160 $189$229
$294
$394
$529
$696
$879
$1.049
$0
$200
$400
$600
$800
$1.000
$1.200
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Source: “Saving Lives, Saving Money: Dividends for Americans Investing in
Alzheimer’s Research”, The Lewin Group & the Alzheimer’s Association,
June 2004.
P-value*
<0.0001
/
0.001‡,║
0.004‡,║
0.08
0.56
0.44
0.73
0.22
0.29
0.78
76.3 (6.5)
76.3 (6.5)
Aβ40 tertiles
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
76.3 (6.5)
SRT total recall 38.28 (9.9) 38.78 (9.93) 38.33 (9.47)
SRT delayed recall 5.47 (2.59) 5.53 (2.57) 5.48 (2.53)
Moderate alcohol intake,
N (%) 413 (34) 144 (35) 145 (36)
Memory
Others, N (%) 13 (1) 5 (1) 5 (1)
APOE -ε4 +, N (%) 314 (26) 110 (27) 99 (25)
Black, N (%) 388 (32) 131 (32) 119 (29)
Hispanic, N (%) 458 (38) 149 (37) 149 (37)
Ethnicity
White, N (%) 360 (30) 122 (30) 133 (33)
Caloric intake (Kcal/day),
mean(SD) 1433(525) 1453(539) 1461(506)
Female, N (%) 831 (68) 279 (69) 269 (66)
Age (years), mean(SD) 75.4 (6.1) 74.6 (5.7) 75.1 (5.8)
Education (years),
mean(SD) 10.1 (4.8 ) 10.5 (4.7) 10.3 (4.9)
range 9-588 9-51.4 51.5-101 101.1-588
Aβ40 (pg/mL), mean(SD) 81.9 (58) 26.5 (15) 76.2 (15) 143.0 (54)
N 1219 407 406 406
Total lowest middle highest
Gu et al. Neurology. In press.
lowest middle highest P-value*
403 403 402
14.5 ( 5.3 ) 33.9 ( 5.3 ) 67.9 ( 26 ) <0.0001
25-May 25-43 44-272 /
74.8 (5.7) 75.0 (6.0) 76.2 (6.3) 0.002‡,║
10.4 ( 4.7 ) 10.3 (4.7 ) 9.6 ( 4.9 ) 0.045‡
1434 ( 529 ) 1453 ( 561) 1412 ( 483) 0.55
287 (71) 259 (64) 277 (69) 0.1
0.73
119 (30) 105 (33) 132 (30)
132 (33) 142 (26) 111 (32)
148 (37) 151 (38) 155 (38)
4 (1) 5 (1) 3 (1)
108 (27) 106 (26) 97 (24) 0.68
147 (37) 134 (33) 127 (32) 0.33
38.96 (10.04) 38.3 (9.47) 37.6 (10.19) 0.21
5.58 (2.57) 5.52 (2.59) 5.33 (2.6) 0.43SRT-delayed recall 5.49 (2.58)
Memory
SRT-total recall 38.33 (9.9)
APOE-ε4 +, N (%) 311 (26)
Moderate alcohol
intake, N (%) 408 (34)
Hispanic, N (%) 454 (38)
Others, N (%) 13 (1)
White, N (%) 356 (30)
Black, N (%) 385 (32)
Female, N (%) 823 (68)
Ethnicity
Education (years),
mean(SD) 10.0 ( 4.8 )
Caloric intake
(Kcal/day), mean(SD) 1433 ( 525 )
Aβ42 (pg/mL),
mean(SD) 38.7 ( 27 )
range 5-272
Age (years), mean(SD) 75.3 (6.0)
Aβ42 tertiles
Total
N 1208
Gu et al. Neurology. In press.
Diet
Metabolic Insulin
Adiponectin
Vascular Clinical,
Homocysteine MRI SCI, WMH
Alzheimer’s disease Inflammatory
IL-6 IL-1 CRP
Oxidative Isoprostanes
Diet
Metabolic Insulin
Adiponectin
Vascular Clinical,
Homocysteine
Alzheimer’s disease Inflammatory
IL-6 IL-1 CRP
Oxidative Isoprostanes
Virtanen et al. Neurology® 2008;71:439–446
!!! Choose this slide or the next one. I think this one is good enough.
Virtanen et al. Neurology® 2008;71:439–446
White LR et al. Journal of the American College of Nutrition, 2000;19(2): 242–255