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Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions

Major depressive disorder is the most common neuropsychiatric disorder, affecting 11% of veterans. We report results of a large meta-analysis of depression using data from the Million Veteran Program (MVP), 23andMe Inc., UK Biobank, and FinnGen; including individuals of European ancestry (n=1,154,26...

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Autores principales: Levey, Daniel F., Stein, Murray B., Wendt, Frank R., Pathak, Gita A., Zhou, Hang, Aslan, Mihaela, Quaden, Rachel, Harrington, Kelly M., Nuñez, Yaira Z., Overstreet, Cassie, Radhakrishnan, Krishnan, Sanacora, Gerard, McIntosh, Andrew M., Shi, Jingchunzi, Shringarpure, Suyash S., Concato, John, Polimanti, Renato, Gelernter, Joel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404304/
https://www.ncbi.nlm.nih.gov/pubmed/34045744
http://dx.doi.org/10.1038/s41593-021-00860-2
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author Levey, Daniel F.
Stein, Murray B.
Wendt, Frank R.
Pathak, Gita A.
Zhou, Hang
Aslan, Mihaela
Quaden, Rachel
Harrington, Kelly M.
Nuñez, Yaira Z.
Overstreet, Cassie
Radhakrishnan, Krishnan
Sanacora, Gerard
McIntosh, Andrew M.
Shi, Jingchunzi
Shringarpure, Suyash S.
Concato, John
Polimanti, Renato
Gelernter, Joel
author_facet Levey, Daniel F.
Stein, Murray B.
Wendt, Frank R.
Pathak, Gita A.
Zhou, Hang
Aslan, Mihaela
Quaden, Rachel
Harrington, Kelly M.
Nuñez, Yaira Z.
Overstreet, Cassie
Radhakrishnan, Krishnan
Sanacora, Gerard
McIntosh, Andrew M.
Shi, Jingchunzi
Shringarpure, Suyash S.
Concato, John
Polimanti, Renato
Gelernter, Joel
author_sort Levey, Daniel F.
collection PubMed
description Major depressive disorder is the most common neuropsychiatric disorder, affecting 11% of veterans. We report results of a large meta-analysis of depression using data from the Million Veteran Program (MVP), 23andMe Inc., UK Biobank, and FinnGen; including individuals of European ancestry (n=1,154,267; 340,591 cases) and African ancestry (n=59,600; 25,843 cases). Transcriptome-wide association study (TWAS) analyses revealed significant associations with expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. 178 genomic risk loci were fine-mapped, and we identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our TWAS, including TRAF3. Finally, we were able to show substantial replications of our findings in a large independent cohort (N=1,342,778) provided by 23andMe. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits.
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spelling pubmed-84043042021-11-27 Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions Levey, Daniel F. Stein, Murray B. Wendt, Frank R. Pathak, Gita A. Zhou, Hang Aslan, Mihaela Quaden, Rachel Harrington, Kelly M. Nuñez, Yaira Z. Overstreet, Cassie Radhakrishnan, Krishnan Sanacora, Gerard McIntosh, Andrew M. Shi, Jingchunzi Shringarpure, Suyash S. Concato, John Polimanti, Renato Gelernter, Joel Nat Neurosci Article Major depressive disorder is the most common neuropsychiatric disorder, affecting 11% of veterans. We report results of a large meta-analysis of depression using data from the Million Veteran Program (MVP), 23andMe Inc., UK Biobank, and FinnGen; including individuals of European ancestry (n=1,154,267; 340,591 cases) and African ancestry (n=59,600; 25,843 cases). Transcriptome-wide association study (TWAS) analyses revealed significant associations with expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. 178 genomic risk loci were fine-mapped, and we identified likely pathogenicity in these variants and overlapping gene expression for 17 genes from our TWAS, including TRAF3. Finally, we were able to show substantial replications of our findings in a large independent cohort (N=1,342,778) provided by 23andMe. This study sheds light on the genetic architecture of depression and provides new insight into the interrelatedness of complex psychiatric traits. 2021-05-27 2021-07 /pmc/articles/PMC8404304/ /pubmed/34045744 http://dx.doi.org/10.1038/s41593-021-00860-2 Text en http://www.nature.com/authors/editorial_policies/license.html#termsUsers may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Levey, Daniel F.
Stein, Murray B.
Wendt, Frank R.
Pathak, Gita A.
Zhou, Hang
Aslan, Mihaela
Quaden, Rachel
Harrington, Kelly M.
Nuñez, Yaira Z.
Overstreet, Cassie
Radhakrishnan, Krishnan
Sanacora, Gerard
McIntosh, Andrew M.
Shi, Jingchunzi
Shringarpure, Suyash S.
Concato, John
Polimanti, Renato
Gelernter, Joel
Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title_full Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title_fullStr Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title_full_unstemmed Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title_short Bi-Ancestral Depression GWAS in the Million Veteran Program and Meta-Analysis in >1.2 Million Subjects Highlights New Therapeutic Directions
title_sort bi-ancestral depression gwas in the million veteran program and meta-analysis in >1.2 million subjects highlights new therapeutic directions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404304/
https://www.ncbi.nlm.nih.gov/pubmed/34045744
http://dx.doi.org/10.1038/s41593-021-00860-2
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