1: Identify metabolomic-based biomarkers of dietary and exercise behavior in normal-weight and obese elderly individuals and the genetic variants associating with the baseline levels of these metabolites. 1.A. Identify metabolomic-based biomarkers of dietary behavior in normal-weight and obese aging individuals and the genetic variants associating with endogenous variability of these metabolites. 1.B. Identify metabolomic-based biomarkers of physical activity in normal-weight and obese aging individuals and the genetic variants associating with endogenous variability of these metabolites. 2: Determine the demographic, behavioral, metabolomic and genetic drivers of the excess obesity in elderly population(s) suffering health disparity. 3: Determine the relationships between aging-related changes in gene expression, endogenous and exogenous microRNAs, metabolic factors and chronotype in response to metabolic challenges such as unhealthy dietary habits, high-fat loads and physical inactivity. 4: Identify genomic, and epigenomic and metabolic markers that predict cardiovascular status and metabolic health during aging and define specific dietary, physical activity and other lifestyle factors that are most suitable to an individual’s genetic and epigenetic profile. 5: Use a multi-omics approach to identify multi-level genome/metagenome/diet interactions that modulate inflammation and aging pathways in normal-weight and obese individuals. 5.A. Determine which of a panel of aging and obesity-related phenotypes associate with genetic markers of obesity in an obese-non-obese comparison (or, in a manner dependent on obesity status) and which of those genetic associations are modulated by dietary factors and exercise. 5.B. Assess microRNA expression levels as correlating with the obese condition irrespective of genetics. 5.C. Collect metabolomics data to define individuals metabolically as obese or non-obese, irrespective of anthropometrics. 5.D. Perform gene network, systems biology analysis on those genes and genetic markers showing associations, either modified by diet or exercise or not, with the aging and obesity-related phenotypes.
Our research on the genetic basis of the responses to diet and their metabolic consequences has demonstrated that the onset and progression of age-related disorders depends on an individual’s metabolic flexibility. With respect to cardiometabolic diseases several factors act in concert and converge to challenge metabolic flexibility. These include an inadequate diet, insufficient physical activity, chronodisruption, decreased metabolic reserve, altered gut microbiome, and reduced immune system capacity. Our primary focus is to determine the specific elements from each of these factors that interact together and with common genetic variants to either promote or disrupt a program of metabolic flexibility in the context of aging, obesity and cardiovascular disease. Our approach aims to identify new metabolite-based markers, substantiate intake of certain foods, nutrients or dietary patterns, define the degree and mechanisms by which circadian control affects cardiometabolic diseases, to describe the roles of microRNAs in these diseases, and to do so in the context of populations suffering health disparities. This will be tested, using high throughput “omic” (i.e., genomics, epigenomics, metabolomics) techniques, both in ongoing studies of free-living populations from different ethnic groups and in intervention studies. We also propose to establish statistical methods whereby a genome-optimized diet is evaluated for its ability to lower plasma triglycerides. Lastly, available datasets will be used to construct gene-SNP-metabolite-diet-aging networks for the purpose of generating testable hypotheses relevant to delaying the onset and progression of cardiometabolic disorders. Outcomes of this research will generate new and better strategies for the prevention of age-related disorders and for slowing the aging process using nutritional and behavioral approaches.
Within the reporting period the project has had significant progress. Of note are the advances made in the areas of obesity and cardio-metabolic genetics and epigenetics. The field of genomics related to common age-related diseases during the last decade has experienced an exciting time of discovery based on the so-called genome-wide association studies that has allowed the discovery of hundreds of common genetic variants associated with the traditional cardiovascular risk factors (i.e., obesity, diabetes, plasma lipid levels), as well as cardiovascular diseases. However, the scientific consensus is that technology has reached the ceiling in terms of information and that the next wave of discoveries will be provided by rare variants detected though whole genome sequencing in large sets of individuals. In this regard, we investigated the relation between rare genetic variants in the Scavenger receptor BI (SR-BI) and high-density lipoprotein (HDL) cholesterol (HDL-C). SR-BI is the major receptor for HDL. High amounts of HDL-C in plasma have been traditionally associated with a lower risk of coronary heart disease (CHD). Nevertheless, our recent research supports the notion that this traditional perception in populations may not be applicable to the individual. Thus, mice that have depleted SR-BI (SR-BI knockout mice) have markedly elevated HDL-C levels but, paradoxically, increased atherosclerosis. The impact of SR-BI on HDL metabolism and CHD risk in humans has been unclear. Through targeted sequencing of coding regions of lipid-modifying genes in 328 individuals with extremely high plasma HDL-C levels, we identified a homozygote for a loss-of-function variant, in which leucine replaces proline 376 (P376L), in SCARB1, the gene encoding SR-BI. The P376L variant impairs posttranslational processing of SR-BI and abrogates selective HDL-C uptake in transfected cells, in hepatocyte-like cells derived from the homozygous subject, and in mice. Large population-based studies revealed that subjects who are heterozygous carriers of the P376L variant have significantly increased levels of plasma HDL-C due to the defect on SR-BI function and a significantly increased risk of CHD. This discovery opens new avenues for more precise detection and prevention of cardiovascular diseases, well beyond current knowledge. Besides genomics, epigenomics represents a major bridge between our genome and the exogenous factors that surround the individual, including diet. One of the most studied epigenetic marks is DNA methylation. DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression. We aimed to explore whether the gene-by-diet interactions that shape our inflammation status and thus our aging process, act through DNA methylation. Omega-3 PUFAs (n-3 PUFAs) reduce Interleukin-6 (IL-6) gene expression, but their effects on transcription regulatory mechanisms are unknown. We aimed to conduct an integrated analysis with both population and in vitro studies to systematically explore the relationships among n-3 PUFA, DNA methylation, single nucleotide polymorphisms (SNPs), gene expression, and protein concentration of IL6. Using data in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study and the Encyclopedia of DNA Elements (ENCODE) consortium, we found that higher methylation of IL6 promoter cg01770232 was associated with higher IL-6 plasma concentration (p = 0.03) and greater IL6 gene expression (p = 0.0005). Higher circulating total n-3 PUFA was associated with lower cg01770232 methylation (p = 0.007) and lower IL-6 concentration (p = 0.02). Moreover, an allele of IL6 rs2961298 was associated with higher cg01770232 methylation (p = 2.55 × 10(-7)). The association between n-3 PUFA and cg01770232 methylation was dependent on rs2961298 genotype (p = 0.02), but higher total n-3 PUFA was associated with lower cg01770232 methylation in the heterozygotes (p = 0.04) not in the homozygotes. Therefore, higher n-3 PUFA is associated with lower methylation at IL6 promoter, which may be modified by IL6 SNPs. This work underscores the importance of integrating genetic, epigenetic and dietary information to achieve a better understanding of the cross talk between dietary and metabolic factors. Continuing with epigenetics, we conducted an epigenome-wide analysis of DNA methylation and obesity traits. DNA methylation was quantified in CD4+ T-cells using the Illumina Infinium HumanMethylation450 array in 991 GOLDN participants. We modeled methylation at individual cytosine-phosphate-guanine (CpG) sites as a function of body mass index (BMI) and waist circumference (WC), adjusting for age, gender, study site, T-cell purity, smoking, and family structure. We found epigenome-wide significant associations between eight CpG sites and BMI and five CpG sites and WC. Moreover, we were able to successfully replicate the top findings in whole blood samples from the Framingham Heart Study (n=2,377) and the Atherosclerosis Risk in Communities study (n=2,097). Top findings, all of them with very high levels of statistical significance for BMI and WC, were in CPT1A, CD38 and long intergenic non-coding RNA 00263 all of the regions with biologically plausible relationships to adiposity. Our large-scale epigenome-wide study discovered and replicated robust associations between DNA methylation at CpG loci and obesity indices, laying the groundwork for future diagnostic and/or therapeutic applications.
1. Gene-environment interactions of circadian-related genes impacts cardiometabolic traits. Our previous work has shown that common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants and cardiometabolic traits. ARS and Tufts University researchers in Boston, Massachusetts, conducted meta-analyses of results of associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Further examination of these interactions could lead to the development of specific dietary recommendations for individuals based on their personal genetic makeup.
2. CLOCK gene variation is associated with incidence of type-2 diabetes and cardiovascular diseases in type-2 diabetic subjects. Circadian rhythms regulate key biological processes influencing metabolic pathways. Abnormalities or impairments in these processes are associated with multiple age-related diseases, including type 2 diabetes (T2D) and cardiovascular diseases (CVD). The body’s circadian rhythms are generated by a feedback process involving core clock genes, and one of those core genes, known as CLOCK has been associated in cross-sectional human studies with obesity, hypertension, and T2D prevalence. ARS and Tufts University researchers in Boston, Massachusetts, analyzed the association between a CLOCK gene variant and incidence of T2D and CVD in the 7,098 participants of the PREDIMED trial over 5 years. Our analysis demonstrates a significant association between this CLOCK gene variant and T2D incidence in 3,671 of the participants who were T2D-free at the beginning of the study. Namely, those who were carriers of the variant allele showed decreased incidence of T2D during the period of the study. Moreover, we detected a statistically significant interaction between the CLOCK gene variant and T2D status on stroke incidence. This is the first time an association between a CLOCK polymorphism and stroke in T2D subjects has been reported, suggesting that core clock genes may significantly contribute to increased CVD risk in T2D.
3. Functional genomics analysis of big data identifies novel peroxisome proliferator-activated receptor gamma target single nucleotide polymorphisms that are associated with cardiometabolic outcomes. Cardiovascular Disease (CVD) and type-2 diabetes (T2D) represent overlapping diseases where a large portion of the variation attributable to genetics remains unexplained. An important factor in the disease development for both is a receptor called PPAR-gamma, which is involved in lipid and glucose metabolism and maintenance of metabolic homeostasis. ARS and Tufts University researchers in Boston, Massachusetts, used a functional genomics methodology to interrogate available Big Data sets to select single nucleotides polymorphisms (SNPs) that fell within sites in the genome, which are targets of PPAR-gamma. Of the 146 variations identified, 16 showed significant enrichment when screened against genome-wide association studies (GWAS) for cardiometabolic traits and 8 were significantly associated with altered gene expression in human fat tissue. This seminal study demonstrated the use of functional genomics, in the context of Big Data, to identify potentially functional SNPs. This targeted method may be used by researchers to uncover functional SNPs that do not reach significance thresholds in the agnostic approach of GWAS.
4. Dietary lipids modulate the expression of miR-107, a microRNA that regulates the circadian system. Long-chain n-3 poly-unsaturated fatty acids (PUFAs) have been shown to have cardio protective effects, partially due to their ability to regulate gene expression. In this regard, increasing attention has been dedicated to the role of microRNAs (miRs) as non-genetic regulators of metabolic pathways in which abnormalities or impairments have been associated with cardiovascular disease risk. ARS and Tufts University rsearchers in Boston, Massachusetts, investigated whether dietary fats regulate miRNA expression in a well-characterized intestinal cell model (Caco-2). Our results showed that fats significantly modulated several miRNAs in this model, and one of them, miR-107, was differentially expressed by all treatments. Some of the presumed target genes of miR-107 have key roles in circadian rhythm and we demonstrated that binding of miR-107 to the circadian locomotor output cycles kaput (CLOCK) gene results in the deregulation of the circadian rhythm of the cells. Since chronodisruption has been linked to metabolic disorders such as T2D, obesity, and CVD, these findings provide evidence that dietary factors may influence circadian rhythm and metabolic risk via non-genetic mechanisms.
A major emphasis has been placed on identifying the genetic basis that puts elderly Hispanics at higher risk of developing age-related diseases, including diabetes, obesity, hypertension and neurological disorders. In this regard, Tufts and ARS researchers the Jean Mayer USDA-Human Nutrition Research Center on Aging in Boston, Massachusetts are conducting highly-controlled dietary intervention studies in this population focusing on gene-diet interactions. Moreover, we are conducting the first genome-wide study to identify the genetic basis that makes this population especially vulnerable to age-related diseases when exposed to a westernized dietary and behavioral environment. Finally, in view of the information gap regarding Genome Wide Analysis in minorities, we have significantly enriched the genomic analysis of African-Americans, Hispanics, and Chinese.
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