title: 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.
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.
authors.affiliation: Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. ebakshis@umich.edu.|Institute of Social Research, University of Michigan, 1415 Washington Heights #4614, Ann Arbor, MI, 48109, USA. ebakshis@umich.edu.
authors.forename: Erin B
authors.initials: EB
authors.lastname: Ware
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA. bhramar@umich.edu.
authors.forename: Bhramar
authors.initials: B
authors.lastname: Mukherjee
authors.affiliation: Department of Epidemiology, Emory University, Atlanta, GA, USA. yvsun@emory.edu.
authors.forename: Yan V
authors.initials: YV
authors.lastname: Sun
authors.affiliation: Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, PA, USA. avd37@drexel.edu.
authors.forename: Ana V
authors.initials: AV
authors.lastname: Diez-Roux
authors.affiliation: Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. skardia@umich.edu.
authors.forename: Sharon L R
authors.initials: SL
authors.lastname: Kardia
authors.affiliation: Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA. smjenn@umich.edu.
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Smith
mesh_terms: D001741:Black or African American / Q000235:genetics; D050197:Atherosclerosis / Q000150:complications / Q000235:genetics*; D003863:Depression / Q000150:complications / Q000235:genetics*; D005006:Ethnicity / Q000235:genetics*; D005260:Female; D055106:Genome-Wide Association Study; D006801:Humans; D008297:Male; D015201:Meta-Analysis as Topic; D008875:Middle Aged; D010641:Phenotype; D044469:Racial Groups / Q000235:genetics*; D018709:Statistics, Nonparametric; D044465:White People / Q000235:genetics