Functional characterization of non-coding variants for Alzheimer’s disease
Multi-scale analysis in schizophrenia and bipolar disorder
Large-scale transcriptome and epigenome association analysis across multiple traits
Supported by Veterans Administration (Merit BX004189).
Precision Medicine refers to the customization of medical treatment to the individual characteristics of each patient. The Million Veteran Program (MVP) provides a unique opportunity to perform large-scale genome-wide association studies (GWAS) across multiple traits and diseases towards the successful application of Precision Medicine. While well powered GWAS have identified multiple risk variants, due to their small effect sizes there has been limited conclusive findings on the genetic factors contributing to complex traits. In addition, the majority of common risk variants are within non-coding regions of the genome and, as such, the functional relevance of most discovered loci remains unclear. Our group and others have shown that a large proportion of phenotypic variability in disease risk can be explained by regulatory variants, i.e. genetic variants that affect epigenetic mechanisms and the expression levels of genes. The study of gene expression and epigenome changes directly in the MVP samples is not feasible as such data are not available.
To overcome these limitations, we propose to apply a machine learning approach that leverages existing molecular data (unrelated to MVP) as a reference panel to directly impute multi-tissue and genome-wide gene expression and epigenome profiles in MVP samples using existing MVP genotypes. As reference panel, we will use large-scale datasets with genotyping and molecular profiling that our group and others have generated, including, but not limited to, the PsychENCODE project, CommonMind Consortium and Accelerating Medicine Partnership for Alzheimer’s Disease. Imputed MVP gene expression and epigenome data provides a powerful cohort to “translate” genetic findings to the dysregulation of specific molecular pathways across multiple traits that will enhance drug discovery.