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

Azmeraw T. Amare, Ahmad Vaez, Yi Hsiang Hsu, Nese Direk, Zoha Kamali, David M. Howard, Andrew M. McIntosh, Henning Tiemeier, Ute Bültmann, Harold Snieder, Catharina A. Hartman

Research output: Research - peer-reviewArticle

Abstract

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 (rg ± 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 were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for 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.

LanguageEnglish
JournalMolecular Psychiatry
DOIs
StatePublished - 2019

ASJC Scopus subject areas

  • Molecular Biology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience

Cite this

Amare, Azmeraw T. ; Vaez, Ahmad ; Hsu, Yi Hsiang ; Direk, Nese ; Kamali, Zoha ; Howard, David M. ; McIntosh, Andrew M. ; Tiemeier, Henning ; Bültmann, Ute ; Snieder, Harold ; Hartman, Catharina A./ 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. In: Molecular Psychiatry. 2019
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abstract = "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 (rg ± 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 were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for 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.",
author = "Amare, {Azmeraw T.} and Ahmad Vaez and Hsu, {Yi Hsiang} and Nese Direk and Zoha Kamali and Howard, {David M.} and McIntosh, {Andrew M.} and Henning Tiemeier and Ute Bültmann and Harold Snieder and Hartman, {Catharina A.}",
year = "2019",
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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, Azmeraw T.; Vaez, Ahmad; Hsu, Yi Hsiang; Direk, Nese; Kamali, Zoha; Howard, David M.; McIntosh, Andrew M.; Tiemeier, Henning; Bültmann, Ute; Snieder, Harold; Hartman, Catharina A.

In: Molecular Psychiatry, 2019.

Research output: Research - peer-reviewArticle

TY - JOUR

T1 - 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

AU - Amare,Azmeraw T.

AU - Vaez,Ahmad

AU - Hsu,Yi Hsiang

AU - Direk,Nese

AU - Kamali,Zoha

AU - Howard,David M.

AU - McIntosh,Andrew M.

AU - Tiemeier,Henning

AU - Bültmann,Ute

AU - Snieder,Harold

AU - Hartman,Catharina A.

PY - 2019

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N2 - 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 (rg ± 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 were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for 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.

AB - 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 (rg ± 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 were MUC21 for the broad depression phenotype with self-reported MDD and ZNF804A, MIR3143, PSORS1C2, STK19, SPATA31D1, RTN1 and TCF4 for 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.

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