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.
This report documents research conducted under 1 project in a Non-Assistance Cooperative Agreement between ARS and TUFTS UNIVERSITY. Additional details for the research are associated with project 8050-51000-098-01S, Nutrition, Obesity, Cardiovascular Health and Genomics. Within the reporting period the project has had significant progress. Of note are the advances made in the areas of obesity and chronobiology. Obesity is heritable and predisposes many diseases. However, the current knowledge related to the genetics of obesity is still very limited. To understand the genetic basis of obesity better, we conducted, in collaboration with an international team of investigators, a genome-wide association study (GWAS) and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identified 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which were novel candidate genes for these anthropometric measures. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis, all of them related to pathways of interest to our project objectives. In addition to the more traditional anthropometric traits related to the previous analysis, body fat distribution is becoming a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, we conducted a GWAS meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identified 49 loci (33 new) associated with waist-to-hip ratio adjusted for BMI, and an additional 19 loci newly associated with related waist and hip circumference measures. Moreover, in line with the relevance of defining sex-related differences, 20 of the 49 loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms. It is interesting to highlight that whereas whole adiposity is strongly defined by the central nervous system, the fat distribution is more closely related to adipose tissue related metabolism. However, it is important to highlight that most of the current knowledge is based on individuals of European ancestry (EA) and that more research is needed in minorities in order to detect specific genetic factors pertinent to other ethnic groups, as well as to identify global genetic markers of obesity. In this regard 12 of 14 loci identified EA samples retained strong associations with waist to hip ratio. Moreover, trans-ethnic analyses at five genes (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86 and ITPR2-SSPN) contributed to the identification of a selected set of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity, we will be able to identify more precise localizations of potential functional variants and suggest a possible regulatory role in order to prioritize variants for possible functionality and with potential for dietary targeting. In addition to genetics, epigenetic factors may play a significant role in defining obesity risk. Thus, we conducted an epigenome-wide analysis of DNA methylation and obesity related traits. To that end, we quantified DNA methylation in CD4+ T-cells using the Illumina Infinium HumanMethylation450 array in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN). We modeled methylation at individual cytosine-phosphate-guanine (CpG) sites as a function of BMI and waist circumference (WC), adjusting for age, gender, study site, T-cell purity, smoking, and family structure. We identified epigenome-wide significant associations between eight CpG sites and BMI and five CpG sites and WC, successfully replicating the top hits in whole blood samples from the Framingham Heart Study (n=2,377) and the Atherosclerosis Risk in Communities study (n=2,097). Top findings were in CPT1A, PHGDH, CD38, and long intergenic non-coding RNA 00263, regions with biologically plausible relationships to adiposity. Therefore, this large-scale epigenome-wide study has discovered and replicated robust associations between DNA methylation at CpG loci and obesity indices, that together with the previously genetic work described above, lays the groundwork for future integrated diagnostic, preventive and therapeutic applications. In terms of chronobiology, we have found that dysregulation in the circadian system is associated with type 2 diabetes (T2D), obesity and other age-related metabolic disorders. Given these findings and the novelty and relevance of this research, the genetics of chronobiology has become one of the main objectives. Along these lines, common circadian-related gene variants associate with increased risk for these metabolic alterations. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol). As part of our objectives, we conducted meta-analyses of results of adjusted 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. We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG, and replicated known MTNR1B associations with glycemic traits. We observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol, with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (>/=9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (>/=7 to <9 h). Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. However, until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet should continue to be emphasized among individuals with the investigated circadian-related gene variants.
1. Sleep duration associates with body mass index (BMI) and macronutrient intake and may be modulated by genes involved in the regulation of the circadian rhythm. Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. In addition, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) gene have been associated with sleep duration and with energy intake, making it important to investigate the relations between sleep duration, BMI, macronutrient intake and CLOCK gene variants in order to achieve a more effective and personalized prevention of age-related common diseases. To elucidate this question, ARS funded researchers at the the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University in Boston, Massachusetts, conducted a meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy, as well as their interactions with CLOCK gene variants, using data from 9 cohort studies. Overall, we found that longer sleep duration was associated with lower BMI; however, associations between sleep duration and relative macronutrient intake were dependent on age and sex. The influence of obesity-associated CLOCK gene polymorphisms on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration in combination with an appropriate dietary profile could ameliorate the genetic predisposition to obesity.
2. Epigenetic Factors are associated with sunlight exposure highlighting the influence of seasonal variation on gene expression. Sunlight exposure has been shown to alter DNA methylation patterns, one of the most relevant epigenetic markers, across several human cell-types. Since epigenetic changes establish gene expression profiles, changes in DNA methylation induced by sunlight exposure warrant investigation. The purpose of this study was to assess the effects of sunlight exposure on CD4+ T-cell methylation patterns on the whole epigenome in a North American population of European origin (n=991). To investigate this novel question, ARS funded researchers at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University in Boston, Massachusetts, used linear regression to test the associations between methylation scores at 461,281 cytosine-phosphate-guanine (CpG) potential methylation sites and sunlight exposure, followed by a genome-wide association analysis to test for associations between methylation within the most informative CpG sites and common genetic variants. Our preliminary results support the role of sunlight exposure in epigenetic processes, and lay the groundwork for future studies of the molecular link between sunlight and physiologic processes such as tumorigenesis and metabolism.
3. Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in United States (U.S.) populations. The relation between relative dietary macronutrient (i.e., fats, carbohydrates) intake and obesity is controversial, giving origin to different dietary models that may or may not be effective or even healthy for certain individuals. Therefore, identifying the right diet for the right individual will be crucial to achieve successful prevention and therapy for obesity and other chronic diseases. Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. To advance this important area of translational investigation, ARS funded researchers at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University in Boston, Massachusetts, developed an obesity GRS, calculated on the basis of 63 obesity-associated variants, and analyzed its association and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake. These findings support the notion that a targeted reduction of total fat and specially SFAs in subjects with high genetic predisposition towards obesity could be a cost effective and successful approach to alleviate the epidemic of obesity and its harmful consequences in the U.S.
4. Lipoprotein Lipase gene variant is associated with stroke incidence and modulated by diet via an epigenetic mechanism. Stroke is a leading cause of death and an important cause of serious, long-term disability in the United StatesS. Stroke has a significant genetic component and some genes have been associated with its risk. To build upon novel findings made on the role of microRNAs (molecules involved in gene regulation) as a regulator of cardiovascular diseases, ARS funded researchers at the Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University in Boston, Massachusetts, investigated the interaction between the rs13702 polymorphism and fat intake on triglycerides at baseline and longitudinally by using a dietary intervention design, as well as the association of this variant with CVD incidence and its modulation by the Mediterranean diet (MedDiet). This polymorphism was associated with lower stroke risk only in the MedDiet intervention group but not in the control group. These data provide new knowledge to design more precise dietary intervention for individuals at risk of stroke.
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