ArticleNature communications2019
Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects.
Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 56 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on sex differences in adverse drug reactions related to psychotropic, cardiovascular, and analgesic medications.Frontiers in pharmacology · 2023Pooled it
- Predictive Safety in the Era of Artificial Intelligence: Promises, Limits, and the Case for an Enterprise Lifecycle Evidence Ecosystem.Drug safety · 2026Review
- Target-biology and interactome-derived signatures predict target-level associations with safety-related drug attrition.Scientific reports · 2026Article
- A genomic-led strategy to anticipate drug safety effects.PLoS genetics · 2026Article
- 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
- Curated and Structure-Based Drug-Target Interactions Improve Underprediction of Drug Side Effects in Network Models.Journal of chemical information and modeling · 2026Article
- Mapping rare protein-coding variants on multi-organ imaging traits.Nature communications · 2025Article
- 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
- In-cell proximity target validation methods for heterobifunctional molecules with CRBN- or VHL-binder using AirID.Communications biology · 2025Article
- Phenotypic similarity of adverse drug reactions and disease phenotypes is a bridge to mechanistic discovery.npj drug discovery · 2025Article
- Prioritizing disease-associated missense variants with chemoproteomic-detected amino acids.American journal of human genetics · 2025Article
- Uncovering New Therapeutic Targets for Amyotrophic Lateral Sclerosis and Neurological Diseases Using Real-World Data.Clinical pharmacology and therapeutics · 2025Article
- Bayesian inference of genetic pleiotropy identifies drug targets and repurposable medicines for human complex diseases.medRxiv : the preprint server for health sciences · 2025Article
- PPDPF preserves integrity of proximal tubule by modulating NMNAT activity in chronic kidney diseases.Science advances · 2025Article
- Human genetic evidence enriched for side effects of approved drugs.PLoS genetics · 2025Article
- Genetic evidence informs the direction of therapeutic modulation in drug development.npj drug discovery · 2025Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Only a small fraction of early drug programs progress to the market, due to safety and efficacy failures, despite extensive efforts to predict safety. Characterizing the effect of natural variation in the genes encoding drug targets should present a powerful approach to predict side effects arising from drugging particular proteins. In this retrospective analysis, we report a correlation between the organ systems affected by genetic variation in drug targets and the organ systems in which side effects are observed. Across 1819 drugs and 21 phenotype categories analyzed, drug side effects are more likely to occur in organ systems where there is genetic evidence of a link between the drug target and a phenotype involving that organ system, compared to when there is no such genetic evidence (30.0 vs 19.2%; OR = 1.80). This result suggests that human genetic data should be used to predict safety issues associated with drug targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.