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

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 SNP-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the LD Score Regression (LDSC) 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, HOMA-β, and HOMA-IR by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate GWAS approach with summary statistics from GWAS meta-analyses and reported loci with genome-wide significant bivariate association p-value (p 0.37). Yet, 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. Yet, 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.