4.3 Article

Bivariate Genome-Wide Association Study of Depressive Symptoms With Type 2 Diabetes and Quantitative Glycemic Traits

Journal

PSYCHOSOMATIC MEDICINE
Volume 80, Issue 3, Pages 242-251

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/PSY.0000000000000555

Keywords

depression; meta-analysis; Type 2 diabetes; pleiotropy; GWAS

Funding

  1. doctoral program of psychology, learning, and education
  2. Academy of Finland
  3. National Heart, Lung, and Blood Institute
  4. MESA investigators
  5. National Heart, Lung, and Blood Institute [N02-HL-64278]
  6. [P30AG10161]
  7. [R01AG15819]
  8. [R01AG17917]
  9. [HHSN268201500003I]
  10. [N01-HC-95159]
  11. [N01-HC-95160]
  12. [N01-HC-95161]
  13. [N01-HC-95162]
  14. [N01-HC-95163]
  15. [N01-HC-95164]
  16. [N01-HC-95165]
  17. [N01-HC-95166]
  18. [N01-HC-95167]
  19. [N01-HC-95168]
  20. [N01-HC-95169]
  21. [UL1-TR-000040]
  22. [UL1-TR-001079]
  23. [UL1-TR-001420]
  24. [UL1-TR-001881]
  25. [DK063491]
  26. [R01 HL101161]
  27. [P60 MD 002249]
  28. DIVISION OF EPIDEMIOLOGY AND CLINICAL APPLICATIONS [N01HC095164, N01HC095160, N01HC095159, N01HC095169, N01HC095162, N01HC095163, N01HC095168, N01HC095161, N01HC095165, N01HC095166, N01HC095167] Funding Source: NIH RePORTER
  29. NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UL1TR000040, UL1TR001881, UL1TR001420, UL1TR001079] Funding Source: NIH RePORTER
  30. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL064278, R44HL095169, R43HL095160, R01HL101161, R13HL095166, R43HL095169, R21HL095165, R01HL095163, R43HL095161, R43HL095167] Funding Source: NIH RePORTER
  31. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [R21AR056405] Funding Source: NIH RePORTER
  32. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [P30DK063491] Funding Source: NIH RePORTER
  33. NATIONAL INSTITUTE ON AGING [ZIAAG007420, ZIAAG000965, R01AG015819, ZIAAG007380, RF1AG015819, R01AG023629, P30AG010161, R01AG017917] Funding Source: NIH RePORTER
  34. National Institute on Minority Health and Health Disparities [P60MD002249] Funding Source: NIH RePORTER

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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 beta-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 x 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.

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