ArticleNature communications2014
A chemo-centric view of human health and disease.
Article in Nature communications, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Comparison of outcomes and postoperative immunotherapy between patients with non-thymomatous and thymomatous myasthenia gravis following thymectomy.Therapeutic advances in neurological disorders · 2025Article
- Extending the small-molecule similarity principle to all levels of biology with the Chemical Checker.Nature biotechnology · 2020Article
- Human gene and disease associations for clinical-genomics and precision medicine research.Clinical and translational medicine · 2020Article
- Debutant iOS app and gene-disease complexities in clinical genomics and precision medicine.Clinical and translational medicine · 2019Article
- Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects.Nature communications · 2019Article
- DNetDB: The human disease network database based on dysfunctional regulation mechanism.BMC systems biology · 2016Article
- Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms.Wiley interdisciplinary reviews. Systems biology and medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Efforts to compile the phenotypic effects of drugs and environmental chemicals offer the opportunity to adopt a chemo-centric view of human health that does not require detailed mechanistic information. Here we consider thousands of chemicals and analyse the relationship of their structures with adverse and therapeutic responses. Our study includes molecules related to the aetiology of 934 health-threatening conditions and used to treat 835 diseases. We first identify chemical moieties that could be independently associated with each phenotypic effect. Using these fragments, we build accurate predictors for approximately 400 clinical phenotypes, finding many privileged and liable structures. Finally, we connect two diseases if they relate to similar chemical structures. The resulting networks of human conditions are able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning, and show a remarkable coincidence with clinical observations.
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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.