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Journal Article

Citation

Cavarec L, Vincent L, Le Borgne C, Plusquellec C, Ollivier N, Normandie-Levi P, Allemand F, Salvetat N, Mathieu-Dupas E, Molina F, Weissmann D, Pujol JF. Neurotox Res 2013; 23(1): 49-62.

Affiliation

Biocortech SAS, 8 rue de la Croix de Jarry, BioPark, 75013, Paris, France.

Copyright

(Copyright © 2013, Springer)

DOI

10.1007/s12640-012-9324-9

PMID

22528247

Abstract

Many drugs in clinical trials, or already on the market, can have psychiatric side effects, independently of their therapeutic indication (e.g., Acomplia, Taranabant, and Roaccutane). There is currently no in vitro or in vivo approved test for the detection/prediction of such adverse effects, and the Food and Drugs Administration (FDA) can only issue general alerts on specific therapeutic classes. The development of a screening assay is therefore of real interest. The anti-viral and anti-tumor action of human interferon-alpha (hIFNα) is associated with a variety of neuropsychiatric side effects, including major depression, suicidal ideation and suicide. RNA editing of the serotonin 2C receptor (HTR2C) by adenosine deaminases acting on RNA (ADARs) is a post-transcriptional modification, the regulation of which is altered in depressed suicide victims. In this study, we show that in the SH-SY5Y neuroblastoma cell line, hIFNα specifically activates the ADAR1a isoform and thereby modifies the HTR2C mRNA editing profile. As this hIFNα-induced altered profile partly overlaps with that observed in the brain of depressed suicide victims, we investigated whether it could be used as a signature to identify drugs with depression and/or suicidal side effects. By means of the Biocortech proprietary screening assay, which allows the relative quantification of all the edited HTR2C isoforms in a sample, we blind-tested the effect of 50 marketed molecules on HTR2C mRNA editing in SH-SY5Y cells and identified 17 compounds with an IFN-like editing profile. This new toxicogenomic assay can identify compounds with potential psychiatric adverse events with a positive predictive value of 90 %.


Language: en

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