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- Publisher Website: 10.1038/nn.4618
- Scopus: eid_2-s2.0-85029944535
- WOS: WOS:000411686400007
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Article: Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry
Title | Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry |
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Authors | |
Issue Date | 2017 |
Citation | Nature Neuroscience, 2017, v. 20, p. 1342-1349 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/248611 |
ISSN | 2023 Impact Factor: 21.2 2023 SCImago Journal Rankings: 12.261 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | So, HC | - |
dc.contributor.author | Chau, CKL | - |
dc.contributor.author | Chiu, WT | - |
dc.contributor.author | Ho, KS | - |
dc.contributor.author | Lo, CP | - |
dc.contributor.author | Yim, SHY | - |
dc.contributor.author | Sham, PC | - |
dc.date.accessioned | 2017-10-18T08:45:52Z | - |
dc.date.available | 2017-10-18T08:45:52Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Nature Neuroscience, 2017, v. 20, p. 1342-1349 | - |
dc.identifier.issn | 1097-6256 | - |
dc.identifier.uri | http://hdl.handle.net/10722/248611 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Nature Neuroscience | - |
dc.title | Analysis of genome-wide association data highlights candidates for drug repositioning in psychiatry | - |
dc.type | Article | - |
dc.identifier.email | Sham, PC: pcsham@hku.hk | - |
dc.identifier.authority | Sham, PC=rp00459 | - |
dc.identifier.doi | 10.1038/nn.4618 | - |
dc.identifier.scopus | eid_2-s2.0-85029944535 | - |
dc.identifier.hkuros | 281962 | - |
dc.identifier.volume | 20 | - |
dc.identifier.spage | 1342 | - |
dc.identifier.epage | 1349 | - |
dc.identifier.eissn | 1546-1726 | - |
dc.identifier.isi | WOS:000411686400007 | - |
dc.identifier.f1000 | 728639679 | - |
dc.identifier.issnl | 1097-6256 | - |