Phenome-wide screening of the putative causal determinants of depression using genetic data

Author:

Aman Asma M1,García-Marín Luis M2345ORCID,Thorp Jackson G4563,Campos Adrian I7ORCID,Cuellar-Partida Gabriel8,Martin Nicholas G23,Rentería Miguel E2345

Affiliation:

1. Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München , Munich 81377 , Germany

2. Department of Genetics and Computational Biology , , Brisbane, Queensland 4006 , Australia

3. QIMR Berghofer Medical Research Institute , , Brisbane, Queensland 4006 , Australia

4. School of Biomedical Sciences , Faculty of Medicine, , Brisbane, Queensland 4006 , Australia

5. The University of Queensland , Faculty of Medicine, , Brisbane, Queensland 4006 , Australia

6. Translational Neurogenomics , , Brisbane, Queensland 4006 , Australia

7. Institute for Molecular Bioscience, The University of Queensland , Brisbane, Queensland 4072 , Australia

8. Diamantina Institute, The University of Queensland , Woolloongabba, Queensland 4102 , Australia

Abstract

Abstract 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 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.

Funder

University of Queensland

Publisher

Oxford University Press (OUP)

Subject

Genetics (clinical),Genetics,Molecular Biology,General Medicine

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