Systolic Blood Pressure Is Associated with Increased Brain Amyloid Load in Mild Cognitively Impaired Participants: Alzheimer's Disease Neuroimaging Initiatives Study.

BACKGROUND: Cardiovascular disease (CVD), including elevated blood pressure (BP), is known to promote Alzheimer's disease (AD) risk. Although brain amyloid load is a recognized hallmark of pre-symptomatic AD, its relationship to increased BP is less known. The objective of this study was to examine the relationship of BP to brain estimates of amyloid-ß (Aß) and standard uptake ratio (SUVr). We hypothesized that increased BP is associated with increased SUVr. METHODS: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we stratified BP according to the Seventh Joint National Committee (JNC) on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure Classification (JNC VII). Florbetapir (AV-45) SUVr was derived from the averaged frontal, anterior cingulate, precuneus, and parietal cortex relative to the cerebellum. A linear mixed-effects model enabled the elucidation of amyloid SUVr relationships to BP. The model discounted the effects of demographics, biologics, and diagnosis at baseline within APOE genotype groups. The least squares means procedure was used to estimate the fixed-effect means. All analyses were performed using the Statistical Analysis System (SAS). RESULTS: In non-ɛ4 carrier MCI subjects, escalating JNC categories of BP was associated with increasing mean SUVr using JNC-4 as a reference point (low-normal (JNC1) p = 0.018; normal (JNC-1) p = 0.039; JNC-2 p = 0.018 and JNC-3 p = 0.04). A significantly higher brain SUVr was associated with increasing BP despite adjustment for demographics and biological variables in non-ɛ4 carriers but not in ɛ4-carriers. This observation supports the view that CVD risk may promote increased brain amyloid load, and potentially, amyloid-mediated cognitive decline. CONCLUSION: Increasing levels of JNC classification of BP is dynamically associated with significant changes in brain amyloid burden in non-ɛ4 carriers but not in ɛ4-carrier MCI subjects. Though not statistically significant, amyloid burden tended to decrease with increasing BP in ɛ4 homozygote, perhaps motivated by increased vascular resistance and the need for higher brain perfusion pressure.

Secondary analyses for genome-wide association studies using expression quantitative trait loci.

Genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with complex traits; however, the identified SNPs account for a fraction of trait heritability, and identifying the functional elements through which genetic variants exert their effects remains a challenge. Recent evidence suggests that SNPs associated with complex traits are more likely to be expression quantitative trait loci (eQTL). Thus, incorporating eQTL information can potentially improve power to detect causal variants missed by traditional GWAS approaches. Using genomic, transcriptomic, and platelet phenotype data from the Genetic Study of Atherosclerosis Risk family-based study, we investigated the potential to detect novel genomic risk loci by incorporating information from eQTL in the relevant target tissues (i.e., platelets and megakaryocytes) using established statistical principles in a novel way. Permutation analyses were performed to obtain family-wise error rates for eQTL associations, substantially lowering the genome-wide significance threshold for SNP-phenotype associations. In addition to confirming the well known association between PEAR1 and platelet aggregation, our eQTL-focused approach identified a novel locus (rs1354034) and gene (ARHGEF3) not previously identified in a GWAS of platelet aggregation phenotypes. A colocalization analysis showed strong evidence for a functional role of this eQTL.

Revisiting methods for modeling longitudinal and survival data: Framingham Heart Study.

BACKGROUND: Statistical methods for modeling longitudinal and time-to-event data has received much attention in medical research and is becoming increasingly useful. In clinical studies, such as cancer and AIDS, longitudinal biomarkers are used to monitor disease progression and to predict survival. These longitudinal measures are often missing at failure times and may be prone to measurement errors. More importantly, time-dependent survival models that include the raw longitudinal measurements may lead to biased results. In previous studies these two types of data are frequently analyzed separately where a mixed effects model is used for the longitudinal data and a survival model is applied to the event outcome. METHODS: In this paper we compare joint maximum likelihood methods, a two-step approach and a time dependent covariate method that link longitudinal data to survival data with emphasis on using longitudinal measures to predict survival. We apply a Bayesian semi-parametric joint method and maximum likelihood joint method that maximizes the joint likelihood of the time-to-event and longitudinal measures. We also implement the Two-Step approach, which estimates random effects separately, and a classic Time Dependent Covariate Model. We use simulation studies to assess bias, accuracy, and coverage probabilities for the estimates of the link parameter that connects the longitudinal measures to survival times. RESULTS: Simulation results demonstrate that the Two-Step approach performed best at estimating the link parameter when variability in the longitudinal measure is low but is somewhat biased downwards when the variability is high. Bayesian semi-parametric and maximum likelihood joint methods yield higher link parameter estimates with low and high variability in the longitudinal measure. The Time Dependent Covariate method resulted in consistent underestimation of the link parameter. We illustrate these methods using data from the Framingham Heart Study in which lipid measurements and Myocardial Infarction data were collected over a period of 26 years. CONCLUSIONS: Traditional methods for modeling longitudinal and survival data, such as the time dependent covariate method, that use the observed longitudinal data, tend to provide downwardly biased estimates. The two-step approach and joint models provide better estimates, although a comparison of these methods may depend on the underlying residual variance.

Aerobic Exercise Training-Induced Changes on DNA Methylation in Mild Cognitively Impaired Elderly African Americans: Gene, Exercise, and Memory Study - GEMS-I.

BACKGROUND: DNA methylation at CpG sites is a vital epigenetic modification of the human genome affecting gene expression, and potentially, health outcomes. However, evidence is just budding on the effects of aerobic exercise-induced adaptation on DNA methylation in older mild cognitively impaired (MCI) elderly African American (AAs). Therefore, we examined the effects of a 6-month aerobic exercise-intervention on genome-wide DNA methylation in elderly AA MCI volunteers. DESIGN: Elderly AA volunteers confirmed MCI assigned into a 6-month program of aerobic exercise (eleven participants) underwent a 40-min supervised-training 3-times/week and controls (eight participants) performed stretch training. Participants had maximal oxygen consumption (VO2max) test and Genome-wide methylation levels at CpG sites using the Infinium HumanMethylation450 BeadChip assay at baseline and after a 6-month exercise program. We computed false discovery rates (FDR) using Sidak to account for multiplicity of tests and performed quantitative real-time polymerase chain-reaction (qRT-PCR) to confirm the effects of DNA methylations on expression levels of the top 5 genes among the aerobic participants. CpG sites identified from aerobic-exercise participants were similarly analyzed by the stretch group to quantify the effects of exercise-induced methylation changes among the group of stretch participants. RESULTS: Eleven MCI participants (aerobic: 73% females; mean age 72.3 ± 6.6 years) and eight MCI participants (stretch: 75% female; mean age 70.6 ± 6.7 years) completed the training. Aerobic exercise-training was associated with increases in VO2max and with global hypo- and hypermethylation changes. The most notable finding was CpG hypomethylation within the body of the VPS52 gene (P = 5.4 × 10-26), a Golgi-associated protein, involved in intracellular protein trafficking including amyloid precursor protein. qRT-PCR confirmed a nearly twofold increased expression of VPS52. Other top findings with FDR q-value < 10-5, include hypomethylations of SCARB1 (8.8 × 10-25), ARTN (6.1 × 10-25), NR1H2 (2.1 × 10-18) and PPP2R5D (9.8 × 10-18). CONCLUSION: We conclude that genome-wide DNA methylation patterns is associated with exercise training-induced methylation changes. Identification of methylation changes around genes previously shown to interact with amyloid biology, intracellular protein trafficking, and lipoprotein regulations provide further support to the likely protective effect of exercise in MCI. Future studies in larger samples are needed to confirm our findings.

Genetic correlations of psychiatric traits with body composition and glycemic traits are sex- and age-dependent.

Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies.

Exercise Training Induced Changes In Nuclear Magnetic Resonance-Measured Lipid Particles In Mild Cognitively Impaired Elderly African American Volunteers: A Pilot Study.

PURPOSE: Poor cardiorespiratory fitness (CRF) is linked to cognitive deterioration, but its effects on lipid heterogeneity and functional properties in older African American (AA) subjects with mild cognitive impairment (MCI) need elucidation. This study determined whether exercise training-induced changes in blood lipid particle sizes (LPS) were associated with CRF determined by VO2Max in elderly AAs with MCI. Given the pivotal role of brain-derived neurotrophic factor (BDNF) on glucose metabolism, and therefore, "diabetic dyslipidemia", we also determined whether changes in LPS were associated with the levels of serum BDNF. METHODS: This analysis included 17 of the 29 randomized elderly AAs with MCI who had NMR data at baseline and after a 6-month training. We used Generalized Linear Regression (GLM) models to examine cardiorespiratory fitness (VO2Max) effects on training-induced change in LPS in the stretch and aerobic groups. Additionally, we determined whether the level of BDNF influenced change in LPS. RESULTS: Collectively, mean VO2Max (23.81±6.17) did not differ significantly between aerobic and stretch groups (difference=3.17±3.56, P=0.495). Training-related changes in very low-density lipoprotein, chylomicrons, and total low-density lipoprotein (LDL) particle sizes correlated significantly with VO2Max, but not after adjustment for age and gender. However, increased VO2Max significantly associated with reduced total LDL particle size after similar adjustments (P = 0.046). While stretch exercise associated with increased protective large high-density lipoprotein particle size, the overall effect was not sustained following adjustments for gender and age. However, changes in serum BDNF were associated with changes in triglyceride and cholesterol transport particle sizes (P < 0.051). CONCLUSION: Promotion of stretch and aerobic exercise to increase CRF in elderly AA volunteers with MCI may also promote beneficial changes in lipoprotein particle profile. Because high BDNF concentration may reduce CVD risk, training-related improvements in BDNF levels are likely advantageous. Large randomized studies are needed to confirm our observations and to further elucidate the role for exercise therapy in reducing CVD risk in elderly AAs with MCI.

GENERATING SURVIVAL TIMES WITH TIME-VARYING COVARIATES USING THE LAMBERT W FUNCTION.

Simulation studies provide an important statistical tool in evaluating survival methods, requiring an appropriate data-generating process to simulate data for an underlying statistical model. Many studies with time-to-event outcomes use the Cox proportional hazard model. While methods for simulating such data with time-invariant predictors have been described, methods for simulating data with time-varying covariates are sorely needed. Here, we describe an approach for generating data for the Cox proportional hazard model with time-varying covariates when event times follow an Exponential or Weibull distribution. For each distribution, we derive a closed-form expression to generate survival times and link the time-varying covariates with the hazard function. We consider a continuous time-varying covariate measured at regular intervals over time, as well as time-invariant covariates, in generating time-to-event data under a number of scenarios. Our results suggest this method can lead to simulation studies with reliable and robust estimation of the association parameter in Cox-Weibull and Cox-Exponential models.

Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium.

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P < 1 × 10-6) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.

Genomics of body fat percentage may contribute to sex bias in anorexia nervosa.

Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex-specific GWAS in a healthy and medication-free subsample of the UK Biobank (n = 155,961), identifying 77 genome-wide significant loci associated with body fat percentage (BF%) and 174 with fat-free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue-associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p < .0001, δ = -0.17), suggesting that the female preponderance in AN may, in part, be explained by sex-specific anthropometric and metabolic genetic factors increasing liability to AN.

Associations of Pulse and Blood Pressure with Hippocampal Volume by APOE and Cognitive Phenotype: The Alzheimer's Disease Neuroimaging Initiative (ADNI).

BACKGROUND: It is increasingly evident that high blood pressure can promote reduction in global and regional brain volumes. While these effects may preferentially affect the hippocampus, reports are inconsistent. METHODS: Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we examined the relationships of hippocampal volume to pulse pressure (PPR) and systolic (SBP) and diastolic (DBP) blood pressure according to apolipoprotein (APOE) ɛ4 positivity and cognitive status. The ADNI data included 1,308 participants: Alzheimer disease (AD = 237), late mild cognitive impairment (LMCI = 454), early mild cognitive impairment (EMCI = 254), and cognitively normal (CN = 365), with up to 24 months of follow-up. RESULTS: Higher quartiles of PPR were significantly associated with lower hippocampal volumes (Q1 vs. Q4, p = 0.034) in the CN and AD groups, but with increasing hippocampal volume (Q1, p = 0.008; Q2, p = 0.020; Q3, p = 0.017; Q4 = reference) in the MCI groups. In adjusted stratified analyses among non-APOE ɛ4 carriers, the effects in the CN (Q1 vs. Q4, p = 0.006) and EMCI groups (Q1, p = 0.002; Q2, p = 0.013; Q3, p = 0.002; Q4 = reference) remained statistically significant. Also, higher DBP was significantly associated with higher hippocampal volume (p = 0.002) while higher SBP was significantly associated with decreasing hippocampal volume in the EMCI group (p = 0.015). CONCLUSION: Changes in PPR, SBP, and DBP differentially influenced hippocampal volumes depending on the cognitive and APOE genotypic categories.

Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.

BACKGROUND: Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences. OBJECTIVE: To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption. DESIGN: We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts. RESULTS: Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA. CONCLUSIONS: These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

APOEε4 impacts up-regulation of brain-derived neurotrophic factor after a six-month stretch and aerobic exercise intervention in mild cognitively impaired elderly African Americans: A pilot study.

Possession of the Apolipoprotein E (APOE) gene ε4 allele is the most prevalent genetic risk factor for late onset Alzheimer's disease (AD). Recent evidence suggests that APOE genotype differentially affects the expression of brain-derived neurotrophic factor (BDNF). Notably, aerobic exercise-induced upregulation of BDNF is well documented; and exercise has been shown to improve cognitive function. As BDNF is known for its role in neuroplasticity and survival, its upregulation is a proposed mechanism for the neuroprotective effects of physical exercise. In this pilot study designed to analyze exercise-induced BDNF upregulation in an understudied population, we examined the effects of APOEε4 (ε4) carrier status on changes in BDNF expression after a standardized exercise program. African Americans, age 55years and older, diagnosed with mild cognitive impairment participated in a six-month, supervised program of either stretch (control treatment) or aerobic (experimental treatment) exercise. An exercise-induced increase in VO2Max was detected only in male participants. BDNF levels in serum were measured using ELISA. Age, screening MMSE scores and baseline measures of BMI, VO2Max, and BDNF did not differ between ε4 carriers and non-ε4 carriers. A significant association between ε4 status and serum BDNF levels was detected. Non-ε4 carriers showed a significant increase in BDNF levels at the 6month time point while ε4 carriers did not. We believe we have identified a relationship between the ε4 allele and BDNF response to physiologic adaptation which likely impacts the extent of neuroprotective benefit gained from engagement in physical exercise. Replication of our results with inclusion of diverse racial cohorts, and a no-exercise control group will be necessary to determine the scope of this association in the general population.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

BACKGROUND: Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. METHODS: In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. RESULTS: In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. CONCLUSIONS: We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

The Evaluation of Syncope in a Predominantly Black Population: Focus on Neuroimaging.

BACKGROUND: Current guidelines do not support the routine use of computed tomography (CT) scan of the head in the diagnostic workup of syncope. There is a lack of research to support whether these guidelines apply to the Black population. AIMS: This study aims to evaluate the yield of neuroimaging in the evaluation of Syncope in a predominantly Black patient population and to test whether current guidelines based on studies conducted in other populations hold true in this group. MATERIAL AND METHODS: A retrospective review of records of 151 patients admitted to a University Hospital with Syncope from 2011 to 2014 was performed. Data collected include CT head, magnetic resonance imaging of the brain, magnetic resonance angiogram, electroencephalogram, and orthostatic vital signs. Demographic data, admitting service, and comorbid conditions were identified. Syncope was classified as cardiogenic, orthostatic, vasovagal, situational, or undetermined. Statistical analysis was performed to determine which diagnostic tools were useful in identifying the potential causes of syncope. Data analysis was conducted using the Statistical Analysis System software 9.3 (SAS Institute, Cary, NC) and Statistical Analysis and Graphics (NCSS 9.0.7, Kaysville, UT). RESULTS: One hundred and twenty eight (84.8%) of the patients were Black. The average age was 56.62 ± 18.78 standard deviation and 68.2% (103) were female. One hundred and fourteen patients (75.5%) had a CT brain. Five out of 114 patients had an acute abnormality on CT (4.4%). Only 1 of these 5 patients had an abnormality that was related to syncope. CT brain (P = 0.978) was not found to be predictive of underlying etiology of syncope despite high frequency of use. CONCLUSIONS: CT head was not useful in determining the etiology of syncope in a predominantly Black population. Current guidelines and studies conducted in other populations have detected similar findings.

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.

BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry.

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption.

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.