Bivariate genome-wide association study of depressive symptoms with type 2 diabetes and quantitative glycemic traits

Research output: Contribution to journalArticle

Abstract

Objective: Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. Methods: We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 10−8). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. Results: The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes). Conclusions: We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.

Details

Authors
  • Kadri Haljas
  • Azmeraw T. Amare
  • Behrooz Z. Alizadeh
  • Yi Hsiang Hsu
  • Thomas Mosley
  • Anne Newman
  • Joanne Murabito
  • Henning Tiemeier
  • Toshiko Tanaka
  • Cornelia Van Duijn
  • Jingzhong Ding
  • David J. Llewellyn
  • David A. Bennett
  • Antonio Terracciano
  • Lenore Launer
  • Karl Heinz Ladwig
  • Marylin C. Cornelis
  • Alexander Teumer
  • Hans Grabe
  • Sharon L.R. Kardia
  • Erin B. Ware
  • Jennifer A. Smith
  • Harold Snieder
  • Johan G. Eriksson
  • Katri Räikkönen
  • Jari Lahti
Organisations
External organisations
  • University of Helsinki
  • University Medical Center Groningen
  • University of Pittsburgh
  • Boston University
  • Erasmus University Rotterdam
  • National Institute on Aging, United States
  • Wake Forest University
  • University of Exeter
  • Florida State University
  • Helmholtz Zentrum München
  • Klinikum rechts der Isar
  • German Center for Neurodegenerative Diseases (DZNE), Bonn
  • University of Michigan
  • Folkhälsan Research Center
  • University of Groningen
  • Harvard University
  • University of Mississippi
  • University of Mississippi Medical Center
  • National Heart Lung and Blood Institute
  • Erasmus University Medical Center
  • Centre for Medical Systems Biology, Leiden
  • Rush Alzheimer's Disease Center
  • German Center for Diabetes Research
  • Northwestern University
  • University of Greifswald
  • Helios Hanseklinikum Stralsund
  • Institute for Molecular Medicine Finland (FIMM)
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Endocrinology and Diabetes

Keywords

  • Depression, GWAS, Meta-analysis, Pleiotropy, Type 2 diabetes
Original languageEnglish
Pages (from-to)242-251
Number of pages10
JournalPsychosomatic Medicine
Volume80
Issue number3
Publication statusPublished - 2018
Publication categoryResearch
Peer-reviewedYes