Michele Sale

Primary Appointment

  • Associate Professor, Medicine- Cardiovascular Medicine

Contact

Research Interest(s)

Genetics of complex disease

Research Description



My group’s research is aimed at identifying and characterizing genetic contributors to complex disease susceptibility.

Type 2 diabetes: We are using a genome-wide association study (GWAS) approach to: (1) identify and characterize genetic variants that contribute to type 2 diabetes susceptibility in African American Sea Islanders of coastal South Carolina and Georgia, and (2) identify variants contributing to lipoprotein subclasses – predictors of cardiovascular outcomes – measured using nuclear magnetic resonance (NMR).  [NIH Grant DK084350]

Stroke: About 25 percent of people who recover from their first stroke will have another stroke within 5 years.  The Vitamin Intervention for Stroke Prevention (VISP) trial enrolled ischemic stroke patients, randomized them to either high or low dose folic acid, vitamin B6 and vitamin B12, then documented incident vascular events over 2 years.  Our studies aim to (1) identify genetic variants associated with recurrent ischemic stroke and combined vascular endpoints; (2) gain insights into individual responses to B vitamin therapy; (3) develop predictive models of recurrent stroke, incorporating genetic and clinical information.  This study is part of GARNET, the Genomics and Randomized Trials Network.  [NIH Grant HG005160]

Otitis media is an inflammation of the middle ear caused by infection.  Family studies have demonstrated a role for genetic factors in disease susceptibility.  Projects underway aim to (1) identify susceptibility variants for chronic and recurrent otitis media using both GWAS and linkage approaches, (2) characterize their role in disease, and (3) survey the microbial diversity of the adenoid surface in children with a history of chronic infection. [NIH Grant DC00316]

Selected Publications

  • Manichaikul A, Mychaleckyj J, Rich S, Daly K, Sale M, Chen W. Robust relationship inference in genome-wide association studies. Bioinformatics (Oxford, England). 2010;26(22): 2867-73. PMID: 20926424 | PMCID: PMC3025716