Cardiovascular disease (CVD) and management of its risk factors such as blood pressure (BP) and plasma lipids continue to be a major public health problem. Therefore, understanding the genetic basis of these traits and how the environment modulates genetic effects in influencing these traits is important because it may provide important clues for interventions. Over the past several years, the advent of Genome-Wide Association Studies (GWAS) has revolutionized the field with rapid progress in identifying hundreds of common genetic variants associated with many common complex diseases and disease-related traits including cardiovascular traits. Despite these extraordinary accomplishments, most of the identified genetic variants have small effect sizes, confer relatively small increments of risk and, for the most part, explain only small proportions of the trait variance. It is increasingly recognized that the near-exclusive focus on main effects of common variants (which generally have small effects) has become a barrier to the identification of additional genes (with larger effects) underlying these disease traits. These discovery efforts need more sophisticated approaches such as gene- environment interactions, analysis of pleiotropic effects on correlated traits, and pathway analysis. Although important research involving gene-environment interactions is being reported in the literature, this is the first systematic, well-powered large consortium-level effort for systematically evaluating gene- lifestyle interactions using very large sample sizes. We propose to investigate gene-lifestyle interactions, the genetic architecture of correlated traits with pleiotropy analysis, and pathway analysis, each as a means for uncovering more of the unexplained genetic variance in BP and lipids. We will do this by leveraging the extraordinary resources of existing multi-ethnic studies/cohorts that have the phenotypes, relevant lifestyle data and dense genotype data on common (GWAS) as well as rare variants (Exome chip). Our application involves 25 cohorts with GWAS data on 90,673 European Americans, 34,543 African Americans, 13,174 Hispanic Americans, and 12,375 Asians, for an overall total of N=150,765, with Exome Chip data on about 61% of the samples. Replication will be sought from two large consortia with an aggregate sample size of 160,958 subjects (Global BP Genetics or GBPgen, and Global Lipids Genetics Consortium or GLGC). This would represent the most significant effort to date to investigate interactions with an aggregate sample size over 300,000 in either discovery or replication. Timely funding can sustain the great momentum generated by putting together this application, which could ultimately lead to novel therapeutic approaches thus potentially impacting clinical practice.

Public Health Relevance

The primary goal of the proposed research is to leverage existing GWAS and Exome Chip data in 25 large multi-ethnic cohorts to discover additional genetic loci for cardiovascular traits by modeling gene-lifestyle interactions, using pleiotropy analysis of correlated traits, and pathway analysis. The investigation will be carried out in 150,765 samples of European Americans, African Americans, Hispanic Americans, and Asians. Approximately equal sample sizes will be used for replication.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL118305-03
Application #
8987446
Study Section
Special Emphasis Panel (ZRG1-PSE-S (03))
Program Officer
Jaquish, Cashell E
Project Start
2014-01-15
Project End
2017-12-31
Budget Start
2016-01-01
Budget End
2016-12-31
Support Year
3
Fiscal Year
2016
Total Cost
$2,018,676
Indirect Cost
$269,433
Name
Washington University
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Laville, Vincent; Bentley, Amy R; Privé, Florian et al. (2018) VarExp: estimating variance explained by genome-wide GxE summary statistics. Bioinformatics 34:3412-3414
Sung, Yun J (see original citation for additional authors) (2018) A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure. Am J Hum Genet 102:375-400
Rao, D C; Sung, Yun J; Winkler, Thomas W et al. (2017) Multiancestry Study of Gene-Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts: Design and Rationale. Circ Cardiovasc Genet 10:
Justice, Anne E (see original citation for additional authors) (2017) Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits. Nat Commun 8:14977
Li, Changwei; He, Jiang; Chen, Jing et al. (2017) Genome-Wide Gene-Potassium Interaction Analyses on Blood Pressure: The GenSalt Study (Genetic Epidemiology Network of Salt Sensitivity). Circ Cardiovasc Genet 10:
Olfson, E; Saccone, N L; Johnson, E O et al. (2016) Rare, low frequency and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans. Mol Psychiatry 21:601-7
Sung, Yun Ju; Winkler, Thomas W; Manning, Alisa K et al. (2016) An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group. Genet Epidemiol 40:404-15
Ricardo, Ana C; Flessner, Michael F; Eckfeldt, John H et al. (2015) Prevalence and Correlates of CKD in Hispanics/Latinos in the United States. Clin J Am Soc Nephrol 10:1757-66
Loos, Ruth J F; Hagberg, James M; Pérusse, Louis et al. (2015) Advances in exercise, fitness, and performance genomics in 2014. Med Sci Sports Exerc 47:1105-12
Basson, Jacob; Sung, Yun Ju; Fuentes, Lisa de Las et al. (2015) Influence of Smoking Status and Intensity on Discovery of Blood Pressure Loci Through Gene-Smoking Interactions. Genet Epidemiol 39:480-488

Showing the most recent 10 out of 12 publications