Bivariate genome-wide association analyses of the broad depression phenotype combined with major depressive disorder, bipolar disorder or schizophrenia reveal eight novel genetic loci for depression


Amare A. T. , Vaez A., Hsu Y., Direk N. , Kamali Z., Howard D. M. , ...Daha Fazla

MOLECULAR PSYCHIATRY, cilt.25, sa.7, ss.1420-1429, 2020 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Konu: 7
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1038/s41380-018-0336-6
  • Dergi Adı: MOLECULAR PSYCHIATRY
  • Sayfa Sayıları: ss.1420-1429

Özet

Although a genetic basis of depression has been well established in twin studies, identification of genome-wide significant loci has been difficult. We hypothesized that bivariate analyses of findings from a meta-analysis of genome-wide association studies (meta-GWASs) of the broad depression phenotype with those from meta-GWASs of self-reported and recurrent major depressive disorder (MDD), bipolar disorder and schizophrenia would enhance statistical power to identify novel genetic loci for depression. LD score regression analyses were first used to estimate the genetic correlations of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia. Then, we performed four bivariate GWAS analyses. The genetic correlations (r(g) +/- SE) of broad depression with self-reported MDD, recurrent MDD, bipolar disorder and schizophrenia were 0.79 +/- 0.07, 0.24 +/- 0.08, 0.53 +/- 0.09 and 0.57 +/- 0.05, respectively. From a total of 20 independent genome-wide significant loci, 13 loci replicated of which 8 were novel for depression. These wereMUC21for the broad depression phenotype with self-reported MDD andZNF804A,MIR3143,PSORS1C2,STK19,SPATA31D1,RTN1andTCF4for the broad depression phenotype with schizophrenia. Post-GWAS functional analyses of these loci revealed their potential biological involvement in psychiatric disorders. Our results emphasize the genetic similarities among different psychiatric disorders and indicate that cross-disorder analyses may be the best way forward to accelerate gene finding for depression, or psychiatric disorders in general.