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Translating GWAS findings into therapies for depression and anxiety disorders: gene-set analyses reveal enrichment of psychiatric drug classes and implications for drug repositioning

Published online by Cambridge University Press:  20 December 2018

Hon-Cheong So*
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Zoology Institute of Zoology and The Chinese University of Hong Kong, Shatin, Hong Kong
Carlos Kwan-Long Chau
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
Alexandria Lau
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
Sze-Yung Wong
Affiliation:
Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong
Kai Zhao
Affiliation:
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong
*
Author for correspondence: Hon-Cheong So, E-mail: hcso@cuhk.edu.hk

Abstract

Background

Depression and anxiety disorders (AD) are the first and sixth leading causes of disability worldwide. Despite their high prevalence and significant disability resulted, there are limited advances in new drug development. Recently, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic basis underlying psychiatric disorders.

Methods

Here we employed gene-set analyses of GWAS summary statistics for drug repositioning. We explored five related GWAS datasets, including two on major depressive disorder (MDD2018 and MDD-CONVERGE, with the latter focusing on severe melancholic depression), one on AD, and two on depressive symptoms and neuroticism in the population. We extracted gene-sets associated with each drug from DSigDB and examined their association with each GWAS phenotype. We also performed repositioning analyses on meta-analyzed GWAS data, integrating evidence from all related phenotypes.

Results

Importantly, we showed that the repositioning hits are generally enriched for known psychiatric medications or those considered in clinical trials. Enrichment was seen for antidepressants and anxiolytics but also for antipsychotics. We also revealed new candidates or drug classes for repositioning, some of which were supported by experimental or clinical studies. For example, the top repositioning hit using meta-analyzed p values was fendiline, which was shown to produce antidepressant-like effects in mouse models by inhibition of acid sphingomyelinase.

Conclusion

Taken together, our findings suggest that human genomic data such as GWAS are useful in guiding drug discoveries for depression and AD.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

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