2012 Annual Report
1a.Objectives (from AD-416):
1. Identify new human genes involved in the homeostasis of lipid metabolism using
genome-wide association studies and bioinformatics.
2. Identify candidate genes for overweight and obesity in humans with special emphasis on those modulating the risk for the metabolic syndrome.
3. Identify genetic factors determining differential susceptibility towards chronic disorders in response to a Western-type diet and lifestyle in humans with differing ethnic backgrounds.
4. Identify new longevity genes and describe their modulation by nutritional and environmental factors in animals and humans.
1b.Approach (from AD-416):
Because the predisposition to most common ailments affecting healthy aging and the responses of the individual to nutrients both contain a strong genetic component, our approach aims to uncover sets of genes involved in the predisposition to alterations in fasting and non fasting lipid metabolism and obesity and dietary response and to describe specific gene-diet interactions. This will be tested, using high throughput genotyping techniques, both in ongoing studies of free-living populations from different ethnic groups and in the metabolic ward (intervention studies). Our primary focus is to describe gene-diet interactions affecting/influencing progression of the metabolic syndrome, in particular obesity
and dyslipidemia, often precursors to cardiovascular disease and diabetes. Cardiovascular candidate genes, both those previously described in the literature as well as those we identify through new genetic technologies and bioinformatics analysis will be used to examine associations and interactions on various scales. These include genetic variations, disease-related phenotypes and specific nutrients [fatty acids, cholesterol, fiber) and behavioral habits (alcohol consumption, smoking, physical (in-activity]. Rigorous statistical analysis will uncover the associations between phenotypes indicative of increased risk of metabolic syndrome and the genes responsible for such. Because cardiovascular disease and diabetes are traditionally considered diseases of the aged, we will also continue with our investigations to identify genes responsible for healthy aging. The principal approach taken for these studies involves gene expression microarray in silico analysis of animal models of aging and longevity. Candidate aging genes will then be studied in human populations.
Within the reporting period the project has had significant progress. Of note, is the demonstration that a combination of bioinformatic analyses of public databases, population data from a very large consortium and molecular biology techniques can be used to identify genetic markers for common disease-related traits (i.e., dyslipidemia) and to provide irrefutable evidence of function, a key item when incorporating genetic markers as predictors of both disease risk and dietary response. As a proof of concept of the power of this approach, we have provided both genetic association and functional evidence for a common lipoprotein lipase (LPL, a major player in blood lipid metabolism) variant known as rs13702 in the modulation of human triglyceride (TAG) and high density lipoprotein cholesterol (HDL-C) serum concentrations. Specifically, we have shown that the less common version of this LPL variant disrupts a microRNA (miR) recognition element (MRE) seed site (MRESS) for the human microRNA-410 (miR-410), thereby altering regulation of LPL activity. Moreover, analysis of this variant across 10 cohorts of participants found statistically significant associations with TAG (P = 3.18x10-42) and HDL-C (P = 1.35x10-32). In addition, we observed that greater intake of dietary polyunsaturated fat (PUFA) can further enhance the favorable effect of this variant on TAG levels. This information may be relevant to pharmacological and/or dietary regimens targeting TAG concentrations.
To understand how important genotype by environment interactions (GxE) are in modulating human physiology and disease risk, we used a tool, Genome-wide Complex Trait Analysis (GCTA), to examine the interactions between 16 major dietary and lifestyle factors and a panel of genetic variants across the genome influencing blood lipid levels. We used data from 406 men and 414 women participating in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study. In this population we identified several dietary factors that form critical interactions with human genes: (a) dietary carbohydrates for total cholesterol; (b) alcohol and total fat intake for HDL-C, and (c) PUFA intake for triglycerides. Importantly, our study shows that GxE of one dietary factor can explain up to 37% to the total variation of blood lipids. In summary, we have developed a novel approach to define the extent to which the interaction between genetic variants and dietary/lifestyle factors contribute to variations in blood lipids and which specific factors are important for a given measure of disease risk at the genome-wide level. These findings provide basic evidence on how interaction between genetic variants and dietary/lifestyle factors contribute to age-related diseases and specifically to CVD risk.
Thus, we investigated potential connections between the circadian clock, the biochemical mechanism that oscillates with a period of 24 hours and is coordinated with the day-night cycle. and SIRTUIN1 (SIRT1), a member of a class of proteins that are implicated in influencing aging and longevity. For this purpose, we developed a combination of genetic variants of SIRT1 and CLOCK (Circadian Locomotor Output Cycles Kaput) one of the key genes affecting both the persistence and period of circadian rhythms. Our goal was to identify novel associations with biological rhythms and resistance to weight loss in a behavioral treatment for obesity based on a Mediterranean diet. For this purpose we investigated overweight/obese subjects (n=1465), aged 20-65 years, who attended outpatient obesity clinics. Our data show that subjects carrying less common variants at SIRT1 and CLOCK genes (R group) displayed a higher resistance to weight loss and a lower weekly weight loss rate as compared to persons with two copies of the common versions of SIRT1 and CLOCK (P group). Dietary habits indicated that R subjects had a lower intake of total carbohydrates and monounsaturated fats, and a higher intake of saturated fats than P subjects. Plasma concentrations of ghrelin, a hunger-stimulating peptide, were also significantly higher in R subjects. Therefore, variants of both SIRT1 and CLOCK have an additive effect on resistance to weight loss that could be related to the chronotype of the person, higher plasma levels of ghrelin, and lower adherence to a Mediterranean diet pattern.
MicroRNA Mediates Gene-Diet Interaction Related to Obesity. ARS and ARS-funded researchers at JMUSDA-HNRCA at Tufts University, Boston, Massachusetts, genotyped seven single nucleotide polymorphisms (SNPs) from men and women of mostly white European ancestry enrolled in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study and the Framingham Offspring Study. Carriers of one of the gene variants tended to weigh more and exhibit higher body mass index (BMI), which would increase their risk of becoming obese. Yet carriers with higher omega-3 fatty acid intakes tended to weigh less than carriers who consumed little or no omega-3 fatty acids. This is the first example of a genetic variant that creates a miR binding site that influences obesity-related traits through gene-diet interaction. Although further research is necessary, the findings suggest that miRNA activity is indeed a possible target for dietary-based weight-loss therapies for obesity. We then conducted a genome-wide survey for SNPs altering microRNA seed sites as a means to identify in GWAS those SNPs of functional consequence. We focused on functional variants related to the binding of microRNAs (miR), utilizing SNP data, including newly released 1000 Genomes Project data, to perform a genome-wide scan of SNPs that abrogate or create miR recognition element seed sites (MRESS). We also gathered previously published links between gene expression activity and genetic variants supporting a functional role for four of these SNPs shown to associate with disease phenotypes. In summary, we have demonstrated the potential of publicly available resources to identify high priority candidate SNPs for functional studies and for disease risk prediction and more successful obesity prevention and therapy using targeted dietary recommendations.
Systems biology and gene networks approach to predict gene-environment (GxE) interactions. Gene networks were built based on protein-protein interactions, seeded by genes carrying variants known to show GxE interactions involving physical activity. ARS and ARS-funded researchers at JMUSDA-HNRCA at Tufts University, Boston, Massachusetts, added data to this network from gene expression studies (response to exercise, baseline activity in key metabolic tissues), genetic association tests from the GOLDN study, a set of human disease genes published by a group at the National Institute of Aging, and assignments to biochemical and physiological pathways. The network itself and analysis of its constituent entities allowed identification of candidate variants involved in HDL-cholesterol and responsive to the level of physical activity. This knowledge will pave the way for more comprehensive tactics to disease prevention using both dietary and physical activity approaches.
Identification of genetic variants for genotyping, genotyping, analysis of genotyping for positive selection. Based on positive selection SNP databases, ARS and ARS-funded researchers at JMUSDA-HNRCA at Tufts University, Boston, Massachusetts identified and ranked a list of promising adaptive variants have been identified and ranked by combining with miRNA SNP and genome-wide association and sequence databases, and 1000 genome database. SNPs that alter microRNA seed sites are associated with higher levels of environmental adaptation. As a proof of concept, several SNPs were further tested in different populations for their association with CVD risk: (1) LPL rs13702 is associated with TG and HDL-C, and interact with PUFA intake in 10 populations; (2) GFOD2 rs12449157 is associated with LDL-C change in response to dietary intervention to prevent metabolic syndrome in Mexicans; (3) PSMD3 rs4795413 interacts with dietary n-3 PUFA intake influencing insulin resistance in GOLDN (HOMA-IR). In summary, identification of adaptive variants in the human genome may provide better insight about the implementation of specific dietary recommendations or dietary patterns in selected populations.
Statistical analysis of genotype data related to aging genes. Based on identified human orthologues of lifespan genes, ARS-funded researchers at JMUSDA-HNRCA at Tufts University, Boston, Massachusetts have identified and examined 41 candidate genes that may influence type 2 diabetes risk. We found six genes in the insulin signal pathway that show strong association and interaction with dietary fat intake influencing insulin resistance. We also found a set of diabetes risk genes displaying strong interactions with vitamin D and affecting insulin resistance. A similar approach was taken to examine if lifespan genes are associated with inflammation biomarkers. We identified a set of genes interacted with dietary intakes and lifestyles and exhibited strong association with inflammation biomarkers. Further, in collaboration with Zhejiang University Researchers in China, demonstrated that a set of aging genes were downregulated by dietary intake curcumin (curry), consumption of which increased the mean lifespan in flies. The results demonstrated that curry intake can promote healthy aging through regulating lifespan-related genes.
Plasma HDL cholesterol and risk of myocardial infarction. A Mendelian randomization study. ARS-funded researchers at JMUSDA-HNRCA at Tufts University, Boston, Massachusetts, in collaboration with an international consortium, have thoroughly analyzed whether high plasma HDL cholesterol is associated with reduced risk of myocardial infarction. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, the concept of Mendelian randomization can be used to test the hypothesis that the association of a plasma biomarker with disease is causal. We performed two Mendelian randomization analyses. First , we used as an instrument a single nucleotide polymorphisms (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20,913 myocardial infarction cases, 95,407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in 12,482 cases of myocardial infarction and 41,331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol. Our findings clearly demonstrate that some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the long-held concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction. Moreover, this information opens new paradigms for the prevention and treatment of cardiovascular diseases.