Large-scale genome-wide association studies (GWAS), through genotyping or sequencing, have identified thousands of loci that appear to influence complex traits and diseases. A fundamental limitation of this approach, however, is that it reveals statistical correlation between the genotype at a variant and the phenotype, but does not identify functional variants. With a few exceptions, the precise functional variants in non-coding regions remain unknown, much less the mechanism through which these variants affect phenotype. Few strategies are currently available for systematically delineating the molecular events that connect genetic variants to phenotype. This proposal builds upon an existing collaboration between researchers in statistics, genomics and cardiovascular epidemiology at Stanford University and Fred Hutchinson Cancer Research Center. Leveraging the unique multi-omics resources generated by Trans Omics for Precision Medicine (TOPMed) program, the objective of this application is to implement and apply analytic strategies for elucidating the genetic basis and molecular mechanisms underlying chronic conditions related to heart, lung, blood and sleep. Using cardiovascular diseases (CVD) as an entry point, which has become a leading cause of morbidity and mortality worldwide, the three Specific Aims are (1) to identify genetic-, epigenetic-, RNA-, protein- and metabolite-based disease risk factors relevant to minority populations, and to construct polygenic disease risk scores for minority individuals; (2) to identify epistatic interaction of disease risk; and (3) to construct multi-omics molecular signatures that predict disease risk as well as define disease subtypes. Our rationale is that each type of omics data offers a quantitative intermediate phenotype linking the genome and the disease phenotype; hence jointly modeling multiple omics data may enable us to reconstruct key biological processes related to disease pathogenesis. Our proposed framework is generally applicable, and offers an efficient and principled strategy to probe into the genetic basis of complex diseases. Successful completion of this research will contribute to human biology, minority health and clinical practice.

Public Health Relevance

The proposed research will provide analytic strategies for jointly analyzing multiple types of -omics data in large population cohorts. Focusing on cardiovascular diseases but applicable to a wide array of disorders related to heart, lung, blood and sleep, the research has the potential to offer important biological insights and to guide the implementation of precision medicine that benefits all individuals, regardless of race or ethnicity. The research has broad impact because it will provide a road map for deciphering the molecular basis of complex diseases by combing large-scale, multi-ethnic, cohorts with high-throughput -omics technologies.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL142017-01A1
Application #
9732881
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Beer, Rebecca Lynn
Project Start
2019-05-01
Project End
2021-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Genetics
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305