Rich, Stephen S.
Primary Appointment
Professor, Genome Sciences, Public Health Sciences
Education
- PhD, Genetics, Purdue University
Contact Information
PO Box 800717, MSB Room3232
1300 Jefferson Park Ave
Charlottesville, VA 22908
Telephone: 434-243-7356
Fax: 434-982-1815
Email: ssr4n@virginia.edu
Research Disciplines
Bioinformatics and Genomics, Biology, Cardiovascular Biology, Epigenetics, Genetics, Immunology, Translational Science
Research Interests
Genetic basis of common human disease, including type 1 diabetes, diabetic complications, ischemic stroke, atherosclerosis
Research Description
Dr. Rich's research is centered on understanding the genetic epidemiology of complex human disease, including the genes contributing to atherosclerosis, stroke and intermediate phenotypes (risk factors). These studies range from estimating the familial aggregation of disease and subclinical markers of disease within families, to gene mapping, gene discovery and functional significance of the gene variants. In the realm of atherosclerosis and risk factors, the primary study population is the Multi-Ethnic Study of Atherosclerosis (MESA), a collection of ~6,000 adults (aged 45+) without evidence of clinical disease. These subjects (Caucasian, African-American, Hispanic-American, Chinese-American) have extensive imaging, biomarker and clinical longitudinal data, as well as DNA for genetic studies. Currently, over 200 candidate genes related to atherosclerosis are being assessed, and both a genome-wide association scan (1 million SNPs) and linkage scan (6K SNPs in families) are being used to discover new genes and pathways. Examination of the genetic contribution to risk of ischemic stroke is the primary focus of the Siblings With Ischemic Stroke Study (SWISS) and the Ischemic Stroke Genetic Study (ISGS). Family-based linkage (SWISS), candidate gene (SWISS, ISGS) and genome-wide association (ISGS) methods have been utilized to detect stroke susceptibility genes. A primary goal of these research efforts is to identify novel genes and pathways that can serve a predictors of risk, identify those at highest risk of disease and, therefore, amenable to intervention, and to develop models of disease through manipulation of these genes and thus identify potential therapeutic targets.