Development of a genetic priority score to predict drug side effects using human genetic evidence

Many drug failures in clinical trials are due to inadequate safety profiles. We developed an in-silico side effect genetic priority score (SE-GPS) that leverages human genetic evidence to inform side effect risk for a given drug target. We construct the SE-GPS in the Open Target dataset using post-marketing side effect data, externally test it in OnSIDES using side effects reported from drug labels and then generate a SE-GPS for 19,422 protein coding genes and 502 phecodes, of which 1.7% had a SE-GPS > 0. To consider drug mechanism, we incorporated the direction of genetic effect into a directional version of the score called the SE-GPS-DOE. We observe that restricting to at least two lines of genetic evidence conferred a 2.3- and 2.5-fold increased risk in side effects in Open Targets and OnSIDES respectively, with increased enrichments in severe drugs. We make all predictions publicly available in a web portal.

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Publication Details

Journal
Nature Communications
Published
2025-09-30
DOI
https://doi.org/10.1038/s41467-025-63762-y
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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Development of a genetic priority score to predict drug side effects using human genetic evidence

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Development of a genetic priority score to predict drug side effects using human genetic evidence

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article en
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Abstract

Many drug failures in clinical trials are due to inadequate safety profiles. We developed an in-silico side effect genetic priority score (SE-GPS) that leverages human genetic evidence to inform side effect risk for a given drug target. We construct the SE-GPS in the Open Target dataset using post-marketing side effect data, externally test it in OnSIDES using side effects reported from drug labels and then generate a SE-GPS for 19,422 protein coding genes and 502 phecodes, of which 1.7% had a SE-GPS > 0. To consider drug mechanism, we incorporated the direction of genetic effect into a directional version of the score called the SE-GPS-DOE. We observe that restricting to at least two lines of genetic evidence conferred a 2.3- and 2.5-fold increased risk in side effects in Open Targets and OnSIDES respectively, with increased enrichments in severe drugs. We make all predictions publicly available in a web portal.

Nature CommunicationsVol. 16(1)
Inserm (FR), Université Paris Cité (FR), Université Paris Sciences et Lettres (FR), Child Health and Development Institute (US), Cardiff University (GB), Icahn School of Medicine at Mount Sinai (US)
Agence Nationale de la Recherche, National Institutes of Health, National Institute of General Medical Sciences
Openalex Percentile: Top 13%
Computational Drug Discovery Methods
1.50
DOIOpen Access PDFOpenAlex
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