Alzheimer s & Dementia Translational Research & Clinical InterventionsBioinformaticsPeer-reviewed journal article
Whole transcriptome in-silico screening implicates cardiovascular and infectious disease in the mechanism of action underlying atypical antipsychotic side-effects
Yasaman MalekizadehiD, Gareth Haydn WilliamsiD, Mark J. KelsoniD, David WhitfieldiD, Jonathan S. MilliD, David Andrew CollieriD, Clive G. BallardiD, Aaron R. JeffriesiD, Byron CreeseiD
Abstract
INTRODUCTIONStroke/thromboembolic events, infections and death are all significantly increased by antipsychotics in dementia but little is known about why they can be harmful. Using a novel application of a drug repurposing paradigm, we aimed to identify potential mechanisms underlying adverse events. METHODWhole transcriptome signatures were generated for SH-SY5Y cells treated with amisulpride, risperidone and volinanserin using RNA-sequencing. Bioinformatic analysis was performed which scored the association between antipsychotic signatures and expression data from 415,252 samples in the NCBI GEO repository. RESULTSAtherosclerosis, venous thromboembolism and influenza NCBI GEO-derived samples scored positively against antipsychotic signatures. Pathways enriched in antipsychotic signatures were linked to the cardiovascular and immune systems (e.g. BDNF, PDGFR-beta, TNF, TGF-beta, selenoamino acid metabolism and influenza infection). CONCLUSIONThese findings for the first time mechanistically link antipsychotics to specific cardiovascular and infectious diseases which are known side effects of their use in dementia, providing new information to explain related adverse events. COMPETING INTERESTSCB has received grants and personal fees from ACADIA Pharmaceuticals and Lundbeck, and personal fees from Heptares, Roche, Lilly, Otsuka, Orion, GlaxoSmithKline and Pfizer. DAC is an employee of Eli Lilly and Company Ltd.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 9
- FWCI
- 1.46
- Field percentile
- top 20%
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