Expressive

rs11747125 - NIHCOLE - RNU6-334P

Magnitude 2.0 · 2 studies on file

Reported associations

  • Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression - Nature genetics (2025) · Shorter JR, Pasman JA, Kurvits S, Jangmo A, Naamanka J, Harder A, Hagen E, Kowalec K, Frilander N, Zetterberg R, Meijsen JJ, Gådin JR, Bergstedt J, Xiong Y, Hägg S, Landén M, Rück C, Wallert J, Skalkidou A, Koch E, Akdeniz BC, Frei O, Hovatta I, Reichborn-Kjennerud T, Werge TM, Sullivan PF, Andreassen OA, Tesli M, Lehto K, Buil A, Lu Y · PubMed 41233554

    ABSTRACT: Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n = 46,708 cases) and late-onset (loMDD; n = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, rg = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have part

  • Overlapping common genetic architecture between major depressive disorders and anxiety and stress-related disorders. - Progress in neuro-psychopharmacology & biological psychiatry (2022) · Mei L, Gao Y, Chen M, Zhang X, Yue W, Zhang D, Yu H · PubMed 34634379

    Major depressive disorders (MDDs) and anxiety and stress-related disorders (ASRDs) have overlapping symptoms and high rates of comorbidity. However, the underlying mechanisms remain largely unknown. Here, we aimed to examine whether MDD and ASRD share genetic risk factors utilizing recent large-scale genome-wide association studies (GWASs). To examine the genetic overlap between MDD and ASRD, we applied genetic correlation analysis to analyze GWAS summary statistics for MDD (16,823 cases and 25,632 controls) and ASRD (12,665 cases and 19,225 controls). We found positive and significant genetic correlations between MDD and ASRD (GNOVA: rho = 0.59, se = 0.01, P = 5.32 × 10 ). Our latent causal variable (LCV) analysis indicated the genetic correlation result from pleiotropic effects

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