Trans-omics elucidation of genetic architecture underlying cardiovascular and HLBS diseases

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Abstract 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.