Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis

• Authors: Erin B. Ware, University of Michigan; Bhramar Mukherjee, University of Michigan; Yan Sun, Emory University; Ana V. Diez-Roux, Drexel University; Sharon L.R. Kardia, University of Michigan; Jennifer A. Smith, University of Michigan
• Journal Title: BMC Genetics
• Volume: Volume 16, Number 1
• Publisher: BioMed Central | 2015-10-12, Pages 118-None
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1186/s12863-015-0274-0
• Subjects: Health Sciences, Epidemiology; Health Sciences, Mental Health; Biology, Genetics
• Keywords: Depressive symptoms; Generalized estimating equations; Genome-wide association studies; Longitudinal; Psychogenetics

Abstract

Background Time-varying phenotypes have been studied less frequently in the context of genome-wide analyses across ethnicities, particularly for mood disorders. This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Methods This study uses genome-wide association studies of depressive symptoms in a longitudinal framework and across multiple ethnicities to find common variants for depressive symptoms. Ethnicity-specific GWAS for depressive symptoms were conducted using three approaches: a baseline measure, longitudinal measures averaged over time, and a repeated measures analysis. We then used meta-analysis to jointly analyze the results across ethnicities within the Multi-ethnic Study of Atherosclerosis (MESA, n = 6,335), and then within ethnicity, across MESA and a sample from the Health and Retirement Study African- and European-Americans (HRS, n = 10,163). Results Several novel variants were identified at the genome-wide suggestive level (5×10−8 < p-value ≤ 5×10−6) in each ethnicity for each approach to analyzing depressive symptoms. The repeated measures analyses resulted in typically smaller p-values and an increase in the number of single-nucleotide polymorphisms (SNP) reaching genome-wide suggestive level. Conclusions For phenotypes that vary over time, the detection of genetic predictors may be enhanced by repeated measures analyses.