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| Phenome-wide screening of the putative causal determinants of depression using genetic data. |
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| ABSTRACT |
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| Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies (GWAS) summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels, and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity, and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden. |
| © The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com. |
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| DATE PUBLISHED |
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| HISTORY |
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| PUBSTATUS |
PUBSTATUSDATE |
| received |
2022/01/11 |
| revised |
2022/03/30 |
| entrez |
2022/04/08 08:47 |
| pubmed |
2022/04/09 06:00 |
| medline |
2022/04/09 06:00 |
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| AUTHORS |
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| NAME |
COLLECTIVENAME |
LASTNAME |
FORENAME |
INITIALS |
AFFILIATION |
AFFILIATIONINFO |
| Aman AM |
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Aman |
Asma M |
AM |
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Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Munich, Germany. |
| García-Marín LM |
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García-Marín |
Luis M |
LM |
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School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane QLD Australia. |
| Thorp JG |
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Thorp |
Jackson G |
JG |
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Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. |
| Campos AI |
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Campos |
Adrian I |
AI |
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Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia. |
| Cuellar-Partida G |
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Cuellar-Partida |
Gabriel |
G |
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The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia. |
| Martin NG |
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Martin |
Nicholas G |
NG |
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Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia. |
| Rentería ME |
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Rentería |
Miguel E |
ME |
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School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane QLD Australia. |
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| INVESTIGATORS |
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| JOURNAL |
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| ISSUE: |
| TITLE: Human molecular genetics |
| ISOABBREVIATION: Hum Mol Genet |
| YEAR: 2022 |
| MONTH: Apr |
| DAY: 08 |
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| SEASON: |
| CITEDMEDIUM: Internet |
| ISSN: 1460-2083 |
| ISSNTYPE: Electronic |
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| MEDLINE JOURNAL |
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| MEDLINETA: Hum Mol Genet |
| COUNTRY: England |
| ISSNLINKING: 0964-6906 |
| NLMUNIQUEID: 9208958 |
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| Journal Article |
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