Kari North - US grants

DESCRIPTION (provided by applicant): While cigarette smoking is a well-established and potent risk factor for atherosclerotic vascular disease, individual susceptibility to smoking varies considerably, suggesting modifiers such as genomic variation. Several key enzymes involved in the activation and detoxification of mutagenic tobacco smoke compounds, oxidative stress, and DNA damage are expressed in the tissues of the heart and vasculature and represent mechanistic pathways for tobacco-induced pathology. Many of these enzymes have common polymorphisms (greater than or equal too 10% prevalence in the population) with known functional effects. Although restricted to a few enzymes and hampered by shortcomings in design, a small number of studies have suggested that enzymatic activation and detoxification of tobacco smoke modifies the risk of certain cardiovascular outcomes associated with cigarette smoking. The main goal of the proposed study is to evaluate common genetic polymorphisms that, in combination with exposure to tobacco smoke, may modify the risk of atherosclerosis and its clinical sequelae. An average of six polymorphisms, selected on the basis of their prevalence and functional significance, expression in relevant tissues, evaluation in previous studies and biologic plausibility, within 19 genes involved in activation, detoxification, oxidative stress, and DNA repair pathways will be evaluated as an ancillary study to the Atherosclerosis Risk in Communities (ARIC) study. In this well-characterized, bi-ethnic cohort of 15,792 men and women under active follow-up since 1987-89 (completeness of follow-up 96%), five endpoints quantifying subclinical atherosclerosis and validated clinical atherosclerotic events will be studied in case-cohort/case-control mode: incident coronary heart disease, carotid atherosclerosis, peripheral arterial disease, incident stroke, and MRI-detected cerebral infarcts. The proposed investigation is well designed to study how DNA sequence polymorphisms can promote or inhibit the atherogenic effects of smoking and the risk of clinical events, and to contribute new knowledge on the role of genetic variation in the response to environmental insults and toxicants. The findings are expected to be of clinical and public health significance.

The NHLBI Family Blood Pressure Program is made up of four cooperating networks whose overall objective is to localize and characterize genes contributing to variation in blood pressure levels and hypertension status. The four networks were originally separately funded and competitive, but two critical realizations have led to full cooperation and collaboration. First, the oligogenic nature of blood pressure control dictates that large samples are necessary to achieve adequate statistical power for genomic linkage and association analyses. Second, linkage intervals are broad and contain large numbers of genes, so that success in identifying genes and mutations requires the effort of multiple laboratories freely sharing information. This coordination extends far beyond phenotyping and genotyping and is best exemplified by the Program's creation of a pooled data set and agreements about coordinated publications. During the initial funding period, the Program surpassed its original recruitment goals, carried out multiple genome-wide linkage and association analyses and created an interim pooled data set consisting of phenotype and genotype data from more than 10,000 individuals. In this renewal application, the Program proposes five specific aims to be carried out by all four networks. These aims can be grouped according to two complementary themes: First, these applicants will create and analyze a database of blood pressure- related phenotype and genotype data from all FBPP participants (Aim 1). Within linked regions, they will identify allelic variation within positional candidate genes and evaluate the relationship of these polymorphisms with blood pressure levels and hypertension status (Aims 2 and 3). Second, they will use quantitative measures of target organ damage to identify genes that influence susceptibility to develop hypertensive heart and kidney diseases (Aims 4 and 5). In addition to the Program specific aims, each network proposes specific aims to be carried out by that network alone, based on unique aspects of their population and interests and expertise of the investigators. The Family Blood Pressure Program represents the most determined multidisciplinary approach to the genetics of hypertension ever assembled. The resulting synthesis of ideas and amassed data permits rigorous hypothesis testing not otherwise possible and will hasten understanding of the previously elusive genetic variation responsible for disease risk.

[unreadable] DESCRIPTION (provided by applicant): This application aims to identify gene variants in chromosome 17 associated with blood pressure variation and susceptibility to hypertension, by following-up persuasive linkage findings of blood pressure in American Indian participants of the Strong Heart Family Study (SHFS). Prior genome-wide linkage analysis of 1894 SHFS participants detected evidence of a quantitative trait loci (QTL) influencing systolic blood pressure on chromosome 17q25.3. This region has been also identified in the Family Blood Pressure Program (FBPP) Hypertension Genetic Epidemiology Network (HyperGEN) and FBPP Genetics Epidemiology Network of Atherosclerosis (GENOA) participants for blood pressure-related traits and, therefore, may harbor genes with broad significance for blood pressure regulation. We propose to extend this work by comprehensively evaluating genetic variation in this chromosome 17q region in the large and informative cohort of the SHFS using state-of-the-art molecular and statistical genetic analyses. We will test the hypothesis that the chromosome 17 QTL contains one or more polymorphic variants that account for the linkage signal by performing comprehensive linkage disequilibrium mapping of the region in the SHFS samples. For genes with preliminary evidence of association, we will select the most promising candidate genes for resequencing and single nucleotide polymorphism (SNP) discovery. We will use the measured genotype approach and family based association to test for association of identified SNPs and/or haplotypes with our linked traits, while accounting for linkage. We plan to replicate our findings in the FBPP HyperGEN (N=3,855) and GENOA (N=5,174) samples of European American, African American and Hispanic American subjects. The prior findings of linkage of blood pressure traits to 17q in the FBPP population samples to be used for replication are exciting and may allow us to successfully identify gene variants influencing blood pressure and hypertension susceptibility. Identification of the risk alleles underlying this linkage peak may suggest novel mechanisms underlying blood pressure regulation and the development of hypertension. PUBLIC HEALTH RELEVANCE: Given the extensive morbidity associated with hypertension in the US and around the world, understanding its genetic basis is a critical step toward disease mitigation and treatment. The importance of studying hypertension in an American Indian population is highlighted by this population's elevated risk of cardiovascular disease, in addition to the gap in the literature for this relatively understudied group. The proposed study may expand our understanding of the impact of the genes on the natural history of hypertension and mechanisms of blood pressure control. [unreadable] [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Abstract Women's Health Initiative Sequencing Project (WHISP) The overall goal of this project submitted in response to NHLBI RC2 Topic 'Large-scale DNA Sequencing and Molecular Profiling of Well-phenotyped NHLBI Cohorts'(RFA-OD-09-004) is to identify putative functional variants for high-priority heart lung and blood phenotypes among American post-menopausal women from diverse ancestral and geographic backgrounds. Increasingly, genome-wide association studies have reported associations of genetic variants with heart lung and blood related complex traits and diseases such as cardiovascular diseases (CVD), diabetes, and obesity. Many of these associations have been repeatedly confirmed in large studies and are considered "putative genuine variants". For these genes to be considered for clinical or preventive uses, identification of possible rare causal variants directly responsible for the disease- susceptibility is required. Indeed, a sequential strategy is best suited to characterize and catalogue the complete set of causal variants contributing to disease heritability and etiology. To fully examine the genetic architecture of CVD-related traits we will perform CVD phenotype-based resequencing for the unbiased discovery of rare variants having large effects in a subset of participants selected from the tails of multiple CVD related phenotypic distributions in the Women's Health Initiative (WHI) Clinical Trial (CT) (n=68,132) and Observational Study (OS) (n=93,676). We will then validate the newly discovered coding variants by performing selective genotyping in the remaining cohort and other populations selected by the study steering committee, toward a complete characterization of the set of causal variants contributing to disease heritability and development, and to further assess the role of these causal variants in relation to other CVD-related traits and pathways. We will also perform pathway analysis on selected variants to assess whether a particular pathway is enriched with disease risk-associated genes. The WHI is one of the most definitive, far-reaching population-based studies of post-menopausal women's health. This large and diverse study population not only enables us to identify novel rare variants that contribute to these phenotypes (specific aim 1) but allows us to validate these newly discovered coding variants in the remaining cohort participants to begin to characterize the complete set of causal variants contributing to disease heritability and etiology and to further assess the role of these causal variants in relation to other CVD-related traits and (specific aim 2). Information generated from this study will be critical to determine the health impact of any given undisputable variant. Findings may also provide valuable insights into disease pathways and mechanisms, and targets for disease screening, prevention, and treatment. PUBLIC HEALTH RELEVANCE: Genome-wide association studies have reported associations of genetic variants with heart lung and blood related complex traits and diseases such as cardiovascular diseases (CVD), diabetes, and obesity. For these genes to be considered for clinical or preventive uses, identification of possible rare causal variants directly responsible for the disease-susceptibility is required. To fully examine the genetic architecture of CVD- related traits, we propose to perform CVD phenotype-based resequencing followed by validation genotyping for the unbiased discovery of rare variants having large effects in a subset of participants with multiple CVD related phenotypic distributions in the Women's Health Initiative.

DESCRIPTION (provided by applicant): Obesity continues to grow as a modern-day epidemic. Because obesity is a strong risk factor for numerous other metabolic derangements, diabetes, cardiovascular disease, fatty liver disease, various cancers, as well as a host of other morbidities, there is strong motivation to understand the genetic architecture of adiposity traits. Genomewide association scans (GWAS) aimed at adiposity traits recently have produced many findings, implicating numerous novel genes, owing to cooperation of large cohort and family studies in meta-analyses of tens of thousands of subjects. The international Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (Atherosclerosis Risk in Communities Study (ARIC), the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES- Reykjavik Study) was convened to promote the discovery of new genes involved in multiple complex traits using GWAS analysis. The Adiposity Working Group includes these cohorts plus the Family Heart Study (FamHS), the European Special Population Network consortium (EUROSPAN), and the Old Order Amish (OOA), together representing over 37,000 subjects. Data on ~8,200 African-Americans are available from the FamHS and the Candidate gene Association Resource (CARe) resource, which includes the Jackson Heart Study, the Cleveland Family Study, ARIC, CARDIA and MESA. These sample sizes enable detection of variants influencing as little as ~0.5% of trait variance. We propose to extend the meta-analysis approach of these cohorts to investigate body mass index (BMI, wt/ht2), waist circumference (WC), waist-hip ratio (WHR), obesity (BMI>30 kg/m2) and extreme obesity (BMI>40 kg/m2). We will address 4 major aims that go beyond primary gene discovery. We propose to contrast the genetic architecture for adiposity traits between European-Americans and African-Americans;to investigate a series of g x e interaction hypotheses, including sex, age, and smoking;to identify adiposity loci with pleiotropic effects on lipid and glucose metabolism traits to deconstruct the correlations among these risk factors;and to identify and test pathways with high impact on adiposity traits, investigating whether the predominant pathways differ by sex and race. For these aims, we will work with studies from the GIANT (Genetic Investigation of ANthropometric Traits) Consortium to augment power, together potentially including up to ~125,000 European- American subjects. We have a unique opportunity to investigate a number of issues using extant GWAS scans to elucidate the genetic architecture of obesity and related traits in two ethnic groups. Findings from these studies will be validated with additional genotyping and / or sequencing, as warranted. This work will stimulate the discovery of variants and pathways, and potentially extend our understanding of the genetic basis of obesity risk and suggest potential therapeutic targets. PUBLIC HEALTH RELEVANCE: Obesity continues to grow as a modern-day epidemic. Because obesity is a strong risk factor for numerous conditions such as diabetes, cardiovascular disease, fatty liver disease, various cancers, as well as a host of other problems, there is strong motivation to understand the genetic architecture of adiposity traits. Understanding the biological and environmental factors that predispose individuals towards obesity can help us to identify people at high risk for interventions and suggest new therapies to keep them within healthy weight range. New techniques aimed searching the human genome to find adiposity genes recently have produced many new findings, however, they are only a piece of the puzzle. The data suggest that there are many more genes to be found, and that environmental factors may play a role in how genes are expressed. We propose to extend studies of already-collected data on genome-wide association scans (GWAS), basing our work on 8 studies of European-Americans (EA), totaling over 37,000 subjects, and a large dataset of African-Americans (AA), totaling over 16,700 subjects. We will collaborate with another group of studies for these projects, which means we could potentially be analyzing up to 125,000 subjects. Because of this, we expect that our study has great power for discovery of new genes for adiposity and obesity. Specifically, we will study the differences and similarities of the genes associated with adiposity and obesity in EA and AA;we will search for genes whose effects depend of any of sex, age, or smoking;we will test whether genes that influence obesity also have effects on lipid profiles and glucose metabolism;and finally, we will identify biological pathways that may play a part in the development of obesity and test whether those pathways are similar of different by sex and race. We expect that this work will generate many new discoveries and provide important new information regarding the genetic underpinnings of obesity.

DESCRIPTION (provided by applicant): Genetic Epidemiology of Causal Variants Across the Life Course is submitted in response to RFA HG-07-014, as a consortium of well characterized population based studies and a central genotyping and resequencing core laboratory, to accelerate the understanding of the role and population impact of putative causal genetic variants related to complex diseases. This collaborative network includes six of the most informative and demographically diverse population-based studies extant, contributing approximately 58,000 men and women from the main ethnic and racial groups in the U.S., ranging in age from childhood to old adulthood. Those examined in the six studies are extensively characterized for a wide range of phenotypes and traits, and five studies have immediately available stored DNA of high quality for transfer to the core laboratory. The participating studies include population based cohorts with repeat examinations and long term follow up and a national probability sample, with clinical and subclinical measurements on a range of health conditions, their precursors and natural history, characterized across the life course. This collaborative network is designed to provide optimal capabilities to estimate and replicate associations of genetic variants with complex diseases in diverse U.S. populations, in individual and environmental contexts of public health relevance, with power sufficient to identify associations, interactions, and population impact in subgroups. The team of investigators contributes epidemiologic, genetic, methodologic and subject-matter expertise and a demonstrated record of productivity in collaborative, interdisciplinary settings. The network builds on existing capabilities and the proven administrative channels of the assembled partner studies for efficient and timely access to phenotypic, exposure and contextual data, for analyses within each partner study and for replication across studies, and for rapid sharing of the resulting descriptive and association data. The investigators will serve as effective collaborators within the wider study, contributing methodologic innovation and analytic support and serving on committees and working groups set up by the Steering Committee. The collaborative resource assembled in this application will permit the estimation of the role and population impact of selected genetic variants in diversity-based populations, for an array of chronic diseases, their risk factors and intermediate outcomes, at different life epochs, and for groups defined by potentially modifiable contexts. Genomic assays will be conducted as needed to further characterize the reported associations.

Provide a summary of the proposed activity suitable for dissemination to the public. It should be a self-contained description of the project and should contain a statement of objectives and methods to be employed. It should be informative to other persons working in the same or related fields and insofar as possible understandable to a scientifically or technically literate lay reader. This abstract must not include any proprietary or confidential information. This section must be no longer than 30 lines of text. 2.

DESCRIPTION (provided by applicant): The objective of the proposed research is to investigate how genetic variation influences weight-related traits during the transition from adolescence to adulthood - a critical risk period for weight gain. Genome wide association studies (GWAS) have identified >70 well-replicated loci influencing weight-related traits, some of which vary by race/ethnicity. Few studies have examined the genetic architecture of these traits during this critical period; the discovered loci are largely common variants that explain only a fraction of the estimated trait heritability. Fine-mapping studies suggest allelic heterogeneity; many causal variants remain to be determined. Recent attention has shifted to coding variants some of which may have larger effect sizes and potential to explain more trait heritability. We build on our successes in R01 HD057194 and capitalize on nationally representative, ethnically diverse, prospective and well-characterized data on 10,581 individuals from the National Longitudinal Study of Adolescent Health (Add Health) to assess the association between weight- related traits and coding variants across a 15-year lifecycle period of dramatic weight gain between adolescence and adulthood. In addition, to make full use of this excellent resource, we combine our data with extant exome data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n>91,000) to further assess associations with adiposity phenotypes, an approach that will be particularly informative and powerful for the discovery of novel coding variants. Further, to fully ensure that we capitalize on the uniqueness of our longitudinal data on adolescent to adult weight gain, we combine our data with two well-characterized, age-matched cohorts with exome data (China Health and Nutrition Survey, CHNS n=1,951; Cebu Longitudinal Health and Nutrition Survey, CLHNS, n=1,691) living under different environmental conditions but experiencing high levels of weight gain analogous to Add Health. Using all three datasets, we will determine the genetic and epidemiological architecture of causal variants; identify functional SNPs and genes; and using advanced and innovative statistical modeling, examine differential genetic effects by age, time, and under varying environmental circumstances to downstream cardiometabolic risk factors (diabetes-, blood pressure-, and inflammatory-related markers). We will test novel hypotheses on tempo and timing of risk as well as address each piece of the complex system linking genetic markers, weight-related outcomes, and cardiometabolic risk factors, in the context of a variety of environmental and behavioral confounders. In sum, these data provide outstanding resources for examining low frequency coding variants associated with weight- related and cardiometabolic traits - a rapidly emerging area of science. Our longitudinal and complex analyses in this understudied age range will provide critical information about risk in the transition from adolescence into adulthood, a period of rapid weight gain when precursors of adult disease are developing. Our work will shed light on the progression of risk to inform efforts to mitigate early development of disease risk.

DESCRIPTION (provided by applicant): Obesity is a leading risk factor for metabolic and cardiovascular diseases and its prevalence has more than doubled since the 1980's, with the greatest burden carried by minority populations. Large-scale genome-wide associations studies (GWAS) have identified >70 genetic loci that are unequivocally associated with obesity-related traits primarily in European descent populations. So far, no large-scale GWAS for any obesity-related traits have been performed in Hispanic /Latinos (HL) populations, despite their increased prevalence of obesity. Although classified under one 'ethnic label', HL populations are incredibly diverse and genetically highly admixed with recent origins from Europe, Africa and the Americas. Hence, genome-wide association will necessitate a large collaborative effort and the use of advanced statistical methods (that go far beyond standard GWAS analyses) to account for and leverage their high degree of genetic diversity. Here, we propose to perform the first large-scale genomic study in search of obesity-susceptibility loci in HL populations. For aim 1, we have assembled the world's GWAS studies in HL populations, including >50,000 HL men and women with high-density SNP array data. Genome-wide imputation to multiethnic reference panels from the 1000 Genomes Project and other unique Amerindian resources will allow for comprehensive testing of common and low frequency variation present in HL populations as well as provide a rich resource for addressing genetic risk heterogeneity at obesity-related loci across HL sub-populations. To elucidate racial/ethnic transferability and fine-map association signals in aim 2, we will leverage data from large-scale GWAS of obesity-related traits in AA and EA populations that are available to us through our work with AA (n>50,000) and EA (GIANT consortium, n>200,000) consortia. In aim 3, we will employ functional analyses in Drosophila and bioinformatic data-mining tools to identify and characterize the target genes and functional alleles, and link associations with biological pathways. We are uniquely positioned and experienced to establish a large-scale collaboration to study the genomics of obesity in HLs. Our proposal is also unique and innovative for taking a GWAS study to the next translational stage, with an experimental research aim for further characterization of obesity specific genetic effects. Our study may improve the understanding of the genomic etiology of obesity, knowledge which may be used to reduce the burden of disease in underserved and understudied minority populations.

? DESCRIPTION (provided by applicant): Human genome studies are providing fresh insights into heart, lung, and blood (HLB) traits, with opportunities for translation of research findings t clinical and community settings for disease prevention and health promotion. Yet, there remain an insufficient number of HLB genetic epidemiologists who can design and implement multidisciplinary HLB genetic epidemiology research that combines technological advances in genome measurement with cutting-edge statistical tools to advance understanding of the genomic basis of HLB traits and associated diseases in the most-burdened populations. The Genetic Epidemiology of Heart, Lung, and Blood Traits (or GenHLB) Training Grant responds to these research gaps by providing interdisciplinary, integrated, and comprehensive instruction in the genetic epidemiology of HLB traits from an outstanding team of research mentors with expertise spanning four proposed training dimensions: HLB genetic epidemiology; computation/methods; `OMICs; and culture, diversity, and disparities. The Training Program will encompass formal didactics based on an individual development plan; tailored mentorship; research experiences in two training dimensions; presentations; manuscript and grant preparation; research seminars and colloquia; and instruction in the responsible conduct of research. The GenHLB training program also will include careful evaluation of the quality and effectiveness of the Training Program, ensuring that fellows achieve the competencies and skills necessary for success as future HLB genetic epidemiology research leaders. The five-year program aims to support four (two pre-doctoral and two postdoctoral) fellows at initiation, increasing to six (three pre-doctoral and three postdoctoral) fellows in year 03. Among the postdoctoral fellows, prior expertise in epidemiology, human genetics, biostatistics, bioinformatics, computational biology, medicine, and applied mathematics will be sought. Pre-doctoral fellows will be required to pursue a doctoral degree in epidemiology, specializing in HLB genetic epidemiology. Our selection of internationally known research mentors with established research collaborations, unique and multidisciplinary training environment, and unparalleled research opportunities make us exceptionally well-positioned to lead this novel training program and develop the next generation of genetic epidemiology leaders who are well-equipped to investigate the genetic underpinnings of HLB traits and associated diseases.

ABSTRACT An estimated 53% of U.S. adults have dyslipidemia, putting a majority of the U.S. adult population at high risk for related chronic diseases such as cardiovascular diseases, non-alcoholic fatty liver disease, and gallbladder disease. US Hispanic/Latinos (H/L) ages 18?74 have an overall prevalence of dyslipidemia of 65%, among the highest reported in the US. Lipid traits are highly heritable; estimates range from 20 to 70%, with common genetic variants explaining ~30% of the variance for these traits in Europeans. As serum concentrations of lipids are established therapeutic targets for many lipid-related chronic diseases, researchers have invested considerable effort into understanding the genetic epidemiology of lipid traits, however these large-scale efforts have almost exclusively considered Caucasians. Understudied at-risk populations provide a powerful design to gain insight into genetic mechanisms for disease because they can exhibit finer haplotypic structure and have different underlying causal variants. To ensure ancestrally diverse populations are not the last to benefit from the new era of precision medicine, we must both increase representation of ancestrally diverse populations in genetic research and develop expedited strategies for translating genomics for clinical utility. First, to enrich discovery, we will conduct the first large-scale GWAS and rare variant analyses for lipid- related traits in H/L. We will meta-analyze, fine-map, perform multivariate associations, and validate effects in all available H/L samples in analyses that will include >50,000 samples. Second, to interpret function, we will move GWAS findings into an interpretable biological context and characterize the regulatory mechanisms involved in lipid regulation via tissue-specific functional analysis, and ancestry-specific validation of effects using RNAseq data in two independent H/L cohorts. Identification of genes and pathways associated with lipid levels elucidates important basic biology about human metabolism, but isn?t necessarily clinically translatable. Thus, to evaluate clinical significance of lipid-associated genetic risk factors, we will use multiple massive genetic and electronic medical record repositories (including the Multiethnic Cohort, BioME, and BioVU) to identify clinical outcomes associated with single variants and genetically regulated expression of lipid- associated genes in H/L phenome-wide. Our design focuses effort on discovery of new variants and loci by pioneering genetic studies of lipid-related traits in diverse H/L populations, functional interpretation of variant effects via gene-based annotation and expression prediction with robust validation, and characterizing the clinical outcomes predicted by lipid-associated genetics in three large DNA bio-banks with linked electronic medical records. These population-specific, function- and outcome-oriented approaches will advance understanding of the genetic etiology of lipids and related traits with high H/L disparities of risk, revealing new biologic pathways and providing new avenues for precision treatment for H/L, a population that will constitute ~35% of the US population by the year 2050.

ABSTRACT Cardiovascular diseases (CVD) remain leading causes of morbidity, mortality, and early disability, and are exacerbated by obesity. It is well known that obesity stresses metabolic pathways, thereby accelerating CVD risk. Yet, the specific biologic mechanisms remain poorly understood. Metabolites are biologically active small- molecule intermediates and byproducts of metabolism that lie along pathways linking genetic susceptibility with CVD and are responsive to obesity, related health behaviors, and CVD risk factors. Thus, metabolites can be powerful disease biomarkers and therapeutic targets and may provide targetable ?mechanistic bridges? linking genome-wide association study (GWAS) findings with CVD risk factors and clinical disease. We hypothesize that: (1) genetic susceptibility influences CVD risk along specific metabolic pathways; (2) that metabolites on these pathways (i) affect and (ii) are affected by CVD risk factors to (3) increase clinical disease risk; and that (4) obesity modifies a subset of metabolite effects. Yet, the majority of metabolomics studies to-date have been largely cross-sectional or clinical efforts in older, European-ancestry populations, with inconsistent control of confounders, including diet, and they have ignored plausible modifiers, including obesity. To address these major research gaps, we will generate longitudinal untargeted and targeted metabolomics profiles in the biracial (47% African American) CARDIA study (n=5,115; 18-30 years in 1985-86; n~3,270 in 2020-21). The CARDIA study is uniquely suited to test the proposed study hypotheses, with 35 years of longitudinal data collected over the key your adult lifecycle period when CVD risk accelerates in concert with increasing obesity. We will develop and employ cutting-edge metabolomics and statistical methods to characterize known and unknown metabolite signals. Longitudinal data, Mendelian randomization, and pathway-based modeling enable assessment of (i) metabolic perturbations that influence CVD and (ii) CVD risk factors that influence metabolic perturbations, (iii) overall and in the context of a growing obesity burden. We address the following specific aims: 1) identify metabolites and major metabolic pathways that influence metabolic CVD risk factors (cholesterol, blood pressure, and glycemic phenotypes); 2) identify metabolic CVD risk factors that influence metabolites and major metabolic pathways; 3) leverage statistical innovations and existing `omics, phenotype, and covariate data for causal inference, to evaluate mechanistic frameworks, and characterize novel metabolites; and 4) test metabolites identified in the CARDIA study for evidence of association with CVD risk factors and clinical endpoints (coronary heart disease, heart failure, and stroke) in the biracial Atherosclerosis Risk in Communities (ARIC) study. We anticipate that the proposed project, prepared by a multi-disciplinary team with expertise in CVD and metabolic epidemiology, nutritional biochemistry, metabolomics, bioinformatics, biostatistics, and genetics, will inform disease mechanisms, with strong potential for identifying biomarkers of CVD risk. Together, our innovations will help identify novel therapeutic and nutritional targets to reduce the global burden of CVD.

SUMMARY In 2019, ~100 million Americans were obese, fueling increases in obesity-related morbidity, mortality, and health care costs, largely from cardiometabolic diseases (CMD). Large scale genetic studies have laid the foundation for many downstream investigations into the pathogenesis of disease and the translation of this information into public health applications. Over the last decade genome-wide association studies (GWAS) have substantially improved our understanding of the genetic architecture of obesity related traits. The potential of these study findings cannot be overstated for elucidating the biological or pathophysiological underpinnings of obesity and its costly morbidities. Although GWAS on common variants have made strides in identifying > 1,000 signals for obesity related traits, these studies are inherently limited without further translation into more actionable findings. In this proposal, we will narrow association signals and map causal genes and pathways underlying known obesity risk loci by applying innovative methods to integrate multiple OMICs (genOMICs, epigenOMICs, transcriptOMICs and metabolOMICs). Additionally, we will explore the clinical relevance of obesity susceptibility variants, genes, and pathways in a large BioBank linked to electronic health records (EHR) to validate expected phenotypic associations and reveal novel phenotypic associations. Finally, we will conduct in vitro functional studies of key variants and genes in physiologically relevant cells to reveal putative regulatory mechanisms of variants and effects on metabolites and thus the underlying mechanisms critical to obesity pathogenesis. Thus, in this proposal we leverage collaborations in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), TransOMICs for Precision Medicine (TOPMed) Program, the Genome Sequencing Project (GSP), and the EHR database from the Geisinger MyCODE Community Health Initiative study (MyCode) to narrow in on genes underlying GWAS signals, perform clinical characterization, and conduct in vitro functional studies to characterize the molecular underpinnings and biological mechanisms of obesity-risk loci. Our approach will substantially move the field away from tag variants and loci to causal variants, genes, and mechanisms. We anticipate that this work will generate fundamental and important insights into the underlying etiology of obesity and ultimately point the way forward towards prevention and treatment.

ABSTRACT Human genome studies continue to provide new insights into heart, lung, and blood (HLB) traits, with opportunities for translation of research findings for disease prevention and health promotion. Yet, an insufficient number of HLB genetic epidemiologists can design and implement multidisciplinary HLB genetic epidemiology studies that combine technological advances in genomics with cutting-edge statistical tools to advance understanding of the genetic basis of HLB traits and associated diseases across populations. The Genetic Epidemiology of Heart, Lung, and Blood Traits (or GenHLB) Training Grant addresses these research gaps by providing interdisciplinary, integrated, and comprehensive instruction in the genetic epidemiology of HLB traits from an outstanding team of research mentors with expertise spanning four training dimensions: HLB genetic epidemiology; computational methods; `OMICs; and culture, diversity, and disparities. The training program encompasses formal didactics based on an individual development plan, tailored mentorship, research in two training dimensions, presentations, manuscript and grant preparation, research seminars and colloquia, and instruction in the responsible conduct of research and research rigor and reproducibility. The GenHLB training program also includes careful evaluation of the quality and effectiveness of the program, ensuring that fellows achieve the competencies and skills necessary for success as future HLB genetic epidemiology research leaders. This renewal application proposes continued support of three pre-doctoral and three postdoctoral fellows each year. Postdoctoral fellows have prior expertise in epidemiology, human genetics, biostatistics, bioinformatics, computational biology, or medicine and gain interdisciplinary training. Pre-doctoral fellows pursue a PhD in epidemiology, specializing in HLB genetic epidemiology with a second area of training. Both applicant pools are highly selective. During our first cycle of funding, the 11 fellows trained by our program successfully conducted transdisciplinary research, published in leading journals, secured independent funding, and obtained competitive positions interrogating the genetic epidemiology of HLB traits. For the next five years, we propose an expansion of the computational training dimension to include a focus on causal inference and a research theme of precision medicine. Specifically, we include faculty with expertise in causal inference and added coursework and practicum experiences in precision medicine. An enhanced focus on lung and blood traits, leadership training, and participation in an interdisciplinary public health professional development seminar series also is proposed. Our program of internationally known research mentors with established research collaborations, unique and multidisciplinary training environment, and a multitude of research opportunities make us exceptionally well-positioned to continue training the next generation of genetic epidemiology leaders who are well-equipped to investigate the genetic underpinnings of HLB traits and associated diseases.