Cohort Development

Cohort Development includes the creation, curation, and exposure of novel datasets enabling precision health research throughout campus, as well as the recruitment, engagement, and retention of a large, diverse community of consented participants.

Workgroup Leaders:

Bhramar Mukherjee, PhD
Associate Workgroup Director

Bhramar Mukherjee is a Professor in the Department of Biostatistics and in the Department of Epidemiology. She completed her PhD in 2001 from Purdue University. Dr. Mukherjee’s principal research interests lie in Bayesian methods in epidemiology and studies of gene-environment interaction. Her collaborative interests focus on genetic and environmental epidemiology, ranging from investigating the genetic architecture of colorectal cancer in relation to environmental exposures to studies of air pollution on pediatric asthma events in Detroit. She is actively engaged in Global Health Research.


Jennifer Smith, PhD
Associate Workgroup Director

Jennifer Smith is an Associate Professor in the Department of Epidemiology. She studies the ways that genetic factors influence age-related chronic diseases, subclinical phenotypes, and their risk factors. Her work encompasses a broad range of phenotypes. She is particularly interested in the interaction between genetic and nongenetic determinants of health (such as demographic, social, and psychosocial factors) in shaping disease risk. Her research also includes biological markers that may lend insight into disease etiology and molecular mechanisms, including epigenetics, gene expression, and telomere length. Dr. Smith holds appointments in the Department of Epidemiology (School of Public Health) and the Survey Research Center (Institute for Social Research) at the University of Michigan.

Workgroup Goals:

  • Develop and expose a novel integrated dataset
    • Integrate data spanning various clinical, administrative, and mobile sources, obviating the need for individual researchers to perform data integration
    • Transparently curate and clean data to allow researchers access to re-usable datasets
    • Incorporate techniques to minimize privacy risks while maximizing re-use of data
    • Identify and overcome internal and external regulatory burdens to data access
    • Integrate publicly available datasets regarding environmental exposure, socioeconomic status, and disparities
  • Transform the Michigan Genomics Initiative recruiting process into a modern, scalable participant community for precision health research across campus
    • Continue to recruit, consent, and retain 10,000 participants per year through the Michigan Medicine perioperative process
    • Expand to include patients recruited through outpatient clinics
    • Expand to include pediatric patients recruited through the perioperative process
    • Enrich the dataset with novel datastreams including wearables, new sensors, and focused sub-groups
    • Transform specimen collection, processing, and analysis into a CLIA-compliant system that enables novel analytics
    • Increase outreach, participant engagement, and follow-up communication