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So HC, Chau CK, Chiu WT, et al. Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry. Nat Neurosci. 2017;20(10):1342-1349doi: 10.1038/nn.4618.
So, H. C., Chau, C. K., Chiu, W. T., Ho, K. S., Lo, C. P., Yim, S. H., & Sham, P. C. (2017). Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry. Nature neuroscience, 20(10), 1342-1349. https://doi.org/10.1038/nn.4618
So, Hon-Cheong, et al. "Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry." Nature neuroscience vol. 20,10 (2017): 1342-1349. doi: https://doi.org/10.1038/nn.4618
So HC, Chau CK, Chiu WT, Ho KS, Lo CP, Yim SH, Sham PC. Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry. Nat Neurosci. 2017 Oct;20(10):1342-1349. doi: 10.1038/nn.4618. Epub 2017 Aug 14. PMID: 28805813.
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Nat Neurosci. 2017 Oct;20(10):1342-1349. doi: 10.1038/nn.4618. Epub 2017 Aug 14.

Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry.

Nature neuroscience

Hon-Cheong So, Carlos Kwan-Long Chau, Wan-To Chiu, Kin-Sang Ho, Cho-Pong Lo, Stephanie Ho-Yue Yim, Pak-Chung Sham

Affiliations

  1. School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
  2. KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Zoology Institute of Zoology and The Chinese University of Hong Kong, China.
  3. Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong, China.
  4. Univeristy of Exeter Medical School, Exeter, UK.
  5. Department of Psychiatry, University of Hong Kong, Pokfulam, Hong Kong, China.
  6. Centre for Genomic Sciences, University of Hong Kong, Pokfulam, Hong Kong, China.
  7. State Key Laboratory for Cognitive and Brain Sciences, University of Hong Kong, Pokfulam, Hong Kong, China.
  8. Centre for Reproduction, Development and Growth, University of Hong Kong, Pokfulam, Hong Kong, China.

PMID: 28805813 DOI: 10.1038/nn.4618

Abstract

Knowledge of psychiatric disease genetics has advanced rapidly during the past decade with the advent of genome-wide association studies (GWAS). However, less progress has been made in harnessing these data to reveal new therapies. Here we propose a framework for drug repositioning by comparing transcriptomes imputed from GWAS data with drug-induced gene expression profiles from the Connectivity Map database and apply this approach to seven psychiatric disorders. We found a number of repositioning candidates, many supported by preclinical or clinical evidence. Repositioning candidates for a number of disorders were also significantly enriched for known psychiatric medications or therapies considered in clinical trials. For example, candidates for schizophrenia were enriched for antipsychotics, while those for bipolar disorder were enriched for both antipsychotics and antidepressants. These findings provide support for the usefulness of GWAS data in guiding drug discovery.

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