Abstract

AbstractBackgroundRisks of stroke/thromboembolic events, infections and death are all significantly increased by antipsychotics in people with dementia but specific mechanisms are unclear. In a novel application of a drug repurposing paradigm, we aimed to identify candidate underlying mechanisms in‐silico by leveraging publicly available transcriptomic data.MethodsWhole transcriptome signatures were first generated for three antipsychotics (amisulpride, risperidone and volinanserin) using RNA‐sequencing in SHSY‐5Y cell lines. These compounds were chosen to represent a range of mechanisms of action relevant to clinically used compounds and novel compounds in development. An unbiased high throughput screen generated correlations between each compound and a public repository of over 100,000 human disease samples. From a long list of statistically significant hits, correlations between each antipsychotic and conditions/diseases related to known side effects of antipsychotic use in dementia were identified and gene set enrichment analysis performed.ResultsStatistically significant associations were found between antipsychotic transcriptional signatures and atherosclerosis (amisulpride p=0.002; risperidone p=6.98x10‐6; volinanserin p=5.5x10‐8), venous thromboembolism (risperidone p=8.13x10‐7; volinanserin p=0.002) and influenza (amisulpride p=0.002). Pathways enriched in antipsychotic signatures were linked to the cardiovascular system, the immune system and inflammation (including brain derived neurotrophic factor, platelet derived growth factor receptor beta, tumor necrosis factor alpha signalling).ConclusionUsing a novel, high throughput approach, these findings implicate cardiovascular disease and the immune system in the mechanisms of action of atypical antipsychotics, providing a list of priority candidate mechanisms of harm relevant to dementia research. This approach could have implications for drug safety screening of psychotropic drugs in dementia.

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