ArticleScience advances2020
Tissue-specific genetic features inform prediction of drug side effects in clinical trials.
Article in Science advances, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
28 citing papers in PubMed.
- An integrative mendelian randomisation and drug mechanism framework for target prioritisation and therapeutic repurposing in major depression.Translational psychiatry · 2026Article
- Moving Mendelian Randomization From Traditional Risk Factors to Molecular Targets for Drug Development and Clinical Trials in Nephrology.Kidney international reports · 2026Review
- Safetyome and specialized panels for over 3,000 phenotypes: a systematic and translational approach using human genetics and pharmacology.Toxicological sciences : an official journal of the Society of Toxicology · 2026Article
- Genomics of drug target prioritization for complex diseases.Nature reviews. Genetics · 2026Review
- The gene expression landscape of disease genes.Genome biology · 2026Article
- The polygenic, omnigenic and stratagenic models of complex disease risk.Nature genetics · 2026Review
- Curated and Structure-Based Drug-Target Interactions Improve Underprediction of Drug Side Effects in Network Models.Journal of chemical information and modeling · 2026Article
- Drug toxicity prediction based on genotype-phenotype differences between preclinical models and humans.EBioMedicine · 2025Article
- Development of a genetic priority score to predict drug side effects using human genetic evidence.Nature communications · 2025Article
- Therapeutic Targets for Sepsis: Multicenter Proteome-Wide Analyses and Experimental Validation.Journal of proteome research · 2025Article
- Uncovering New Therapeutic Targets for Amyotrophic Lateral Sclerosis and Neurological Diseases Using Real-World Data.Clinical pharmacology and therapeutics · 2025Article
- PPDPF preserves integrity of proximal tubule by modulating NMNAT activity in chronic kidney diseases.Science advances · 2025Article
- Genetic evidence informs the direction of therapeutic modulation in drug development.npj drug discovery · 2025Article
- Genetic factors associated with reasons for clinical trial stoppage.Nature genetics · 2024Article
- TransTEx: novel tissue-specificity scoring method for grouping human transcriptome into different expression groups.Bioinformatics (Oxford, England) · 2024Article
- Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications.Nature genetics · 2024Article
- Article
- Strategies for translating proteomics discoveries into drug discovery for dementia.Neural regeneration research · 2024Review
- Article
- Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Adverse side effects often account for the failure of drug clinical trials. We evaluated whether a phenome-wide association study (PheWAS) of 1167 phenotypes in >360,000 U.K. Biobank individuals, in combination with gene expression and expression quantitative trait loci (eQTL) in 48 tissues, can inform prediction of drug side effects in clinical trials. We determined that drug target genes with five genetic features-tissue specificity of gene expression, Mendelian associations, phenotype- and tissue-level effects of genome-wide association (GWA) loci driven by eQTL, and genetic constraint-confer a 2.6-fold greater risk of side effects, compared to genes without such features. The presence of eQTL in multiple tissues resulted in more unique phenotypes driven by GWA loci, suggesting that drugs delivered to multiple tissues can induce several side effects. We demonstrate the utility of PheWAS and eQTL data from multiple tissues for informing drug side effect prediction and highlight the need for tissue-specific drug delivery.
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