Aging, Genetics, and Social Science

A MiCDA Research Signature Theme

MiCDA researchers are developing and testing new interdisciplinary approaches to the study of how genetics and social contexts interact to affect aging. They are also spearheading efforts to incorporate genetic information into behavioral and social surveys, via the establishment of Michigan’s HRS genetic database in 2012, and the promotion of similar population genotyping in other large social science surveys.

Understanding the Connections among Genes, Environment, Family Processes, and Mental Health (Axinn)

Genomic Analysis for Social-Behavioral Scientists (Faul)

Identifying modifiable aspects of gene-by-environment interplay in later-life cognitive decline (Faul)

Interplay of Genetic & Socioeconomic Predictors of Memory Decline in Older Adults (Faul)

The Effects of Collection Procedures on Telomere Length (Faul)

Measurement Error in Population Health Inequity Research using Novel Biomeasures (Geronimus)

Michigan Center for Urban African American Aging Research (Jackson)

Role of Genomics in the Efficacy and Racial Disparity of Cornerstone Heart Failure Pharmacotherapy (Jackson)

A Multi-Ethnic Study of Gene-Lifestyle Interactions in Cardiovascular Traits (Kardia)

Genetic and Psychosocial Predictors of Blood Pressure and Body Mass Index (Kardia)

Genetic Mechanisms of Arteriosclerosis in Hypertensive Sibships (Kardia)

Identification and functional impact of NAFLD associated genetic variants (GOLD functional) (Kardia)

SWAN Repository III (Resubmission) (Kardia)

SWAN Repository IV (Resubmission) (Kardia)

Integrating Information about Aging Surveys : Disseminating Genotyped Data from LASI-DAD (Langa)

Cholinergic genetic effects on health and cognition in older adults: Longitudinal analysis (Lustig)

Applying Whole Genome data to Common Social Science Issues (Mitchell)

A Social Epigenomic Approach to Health Disparities in Cardiovascular Risk Factors (Smith)

Epigenetics of Arteriosclerosis in African American Hypertensive Sibships (Smith)

Characterizing disparities in late-onset Alzheimer's disease risk through polygenic risk and epidemiologic factors in the Health and Retirement Survey (Ware)