Research

Primary research strengths

Research activities of the Division of Biostatistics involve both independent and collaborative research which span a wide range of topics dealing with clinical, epidemiological, and genetic studies of a number of disorders of considerable public health importance, providing research opportunities at both theoretical and applied levels. Several research projects involve close interaction and collaboration with a number of research groups at the Medical Center. The present core research programs of the division deal with clinical trials, coordinating center activities, and genetic epidemiology of disease related complex traits.

The Clinical trials core research focuses on the development and implementation of research protocols for collaborative research both within the University and with collaborators across the country. The division actively contributes to all facets of the studies, including the design of the trials, sample size calculations, protocol development, database management, quality control, analysis of data, and manuscript preparation.

Coordinating Center (CC) activities for managing large multi-center studies have been a major focus of the Division since the late 1980’s. This role builds on the research experience established in both Clinical Trials and Genetic Epidemiology. Most of these projects work under a U01 or linked R01 mechanism, where the Coordinating Center (Division) works actively and closely with the Steering Committee (which includes all study center P.I.s and the NIH). The coordinating centers play a major role in all aspects of the studies, including the research protocol, development of the data entry and management system, quality control, tracking recruitment, data analysis and publications, and producing informative and timely reports for the Steering Committee and the Monitoring Board.

Genetic Epidemiology research, largely relating to cardiovascular disease, delves into a number of theoretical and applied problems, including: nature-nurture resolution and identification of the genetic basis of risk factors such as blood pressure and hypertension, obesity, insulin resistance, diabetes, metabolic syndrome; gene-gene interactions, gene-environment interactions including gene-age, gene-sex, gene-obesity interactions; preclinical expressions of atherosclerosis, measures of inflammation; and multivariate associations among multiple risk factors; and localizing, identifying the genes and delineating their etiologies for complex traits. Timely theoretical issues also are addressed, such as the development of new methods and models, especially as they relate to genome-wide scans, challenges of heterogeneity, and combining evidence across multiple studies(meta-analysis).