My research focuses on the analysis of large-scale genetic and genomic data to help understand the etiology of chronic diseases. To this end, I am involved in a number of large collaborative efforts that utilize high-throughput genetic data, such as genotyping arrays and next-generation sequencing.
The NHLBI Trans-Omics for Precision Medicine (TOPMed) Program
Trans-Omics for Precision Medicine (TOPMed), sponsored by the National Institutes of Health‘s National Heart, Lung and Blood Institute (NHLBI), is a program to generate scientific resources to enhance our understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual’s unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other –omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments.
I am currently involved in TOPMed as an investigator with the Women’s Health Initiative and convener of the TOPMed Inflammation Biomarkers Working Group. I am also deeply involved in TOPMed projects focusing on the genetics of ischemic stroke, thrombosis, and hematological traits.
I am a co-founder of the Blood-Cell Consortium (BCX), an international collaboration established in 2014 to investigate the genetics of hematological traits. The first phase of BCX focused on analyses of Exome-Chip data. We are now transitioning to the second phase of BCX focused on imputation using data from the Haplotype Reference Consortium. Together with data from the UK Biobank, we anticipate analyzing data on close to 700,000 individuals.
Breast Cancer Association Consortium
This international consortium aims to identify genetic susceptibility loci for breast cancer. We will use data from over 50,000 cases and 50,000 controls with Illumina OncoArray data to assess the role of genetic variation in influencing risk for breast cancer. We will also investigate survival, breast cancer sub-types, and interactions with multiple environmental risk factors such as hormone therapy.
Integrative Analyses of The Cancer Genome Atlas (TCGA) data
Along with collaborators in bioinformatics, molecular biology, and pathology, we are pursuing pan-cancer analyses of the TCGA data to comprehensively characterize the genetic and epigenetic factors that influence gene expression in tumor tissue.