ArticleNature communications2018
Network-based approach to prediction and population-based validation of in silico drug repurposing.
Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 279 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
279 citing papers in PubMed, 1 synthesis or guideline pooled it, 558 citations in OpenAlex.
- Meta-analysis and review of in silico methods in drug discovery - part 1: technological evolution and trends from big data to chemical space.The pharmacogenomics journal · 2025Pooled it
- Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer's disease.Nature aging · 2021Trial
- Multimodal single-cell omics analysis identifies epithelium-immune cell interactions and immune vulnerability associated with sex differences in COVID-19.Signal transduction and targeted therapy · 2021Trial
- Unraveling Aberrant Metabolic Patterns in Alzheimer's Disease Subtypes: From Perturbed Metabolic Pathways to Candidate Drug Targets.Molecular neurobiology · 2026Article
- Integrative Single-Cell Transcriptomic, Mendelian Randomization and In Silico Perturbation Analyses Prioritize MUC20 as a Candidate Gene Associated with Osteoporosis and Metabolic Dysfunction-Associated Steatotic Liver Disease in the Liver-Bone Axis.International journal of molecular sciences · 2026Article
- Reviewing the Computational Landscape of Drug Repurposing: Evolution from Structure-Based Methods to LLM-Based Methods.Biomolecules · 2026Review
- Multi-omics analysis of perfluorooctanoic acid and glioblastoma: insights from Mendelian randomization, network toxicology, and molecular docking.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Integrative network analysis reveals organizational principles of the endocannabinoid system.Journal of cannabis research · 2026Article
- A network medicine framework for multi-modal data integration in therapeutic target discovery.Communications chemistry · 2026Article
- Precision Medicine Through Network Language: Integrating Clinical Insight and Data Expertise.Genes · 2026Review
- STDrug enables spatially informed personalized drug repurposing from spatial transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- The Mitochondrial Guardian α-Amyrin Mitigates Alzheimer's Disease Pathology via Modulation of the DLK-SARM1-ULK1 Axis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Computational framework for therapeutic target discovery via perturbation simulation: application to cystic fibrosis airway disease.Briefings in bioinformatics · 2026Article
- BioMNEDR: mechanism-guided network embedding for drug repurposing.Briefings in bioinformatics · 2026Article
- Genomics of drug target prioritization for complex diseases.Nature reviews. Genetics · 2026Review
- ncFN: a comprehensive non-coding RNA function annotation framework based on a global and heterogeneous biomolecular network.Non-coding RNA research · 2026Article
- Artificial Intelligence to Guide Repurposing of Drugs.Annual review of medicine · 2026Review
- Deciphering Cancer Therapy-Induced Cardiotoxicity in the Era of Spatial and Multi-Omics from Systemic Mechanisms toJournal of Cancer · 2026Review
- Generative AI in drug repurposing and biomarker discovery: a multimodal approach.Frontiers in bioinformatics · 2026Article
- A network pharmacology-guided multi-omics and spatial single-cell framework nominates WT1 as a spironolactone-linked immune biomarker in prostate cancer.Frontiers in pharmacology · 2026Article
219 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Here we identify hundreds of new drug-disease associations for over 900 FDA-approved drugs by quantifying the network proximity of disease genes and drug targets in the human (protein-protein) interactome. We select four network-predicted associations to test their causal relationship using large healthcare databases with over 220 million patients and state-of-the-art pharmacoepidemiologic analyses. Using propensity score matching, two of four network-based predictions are validated in patient-level data: carbamazepine is associated with an increased risk of coronary artery disease (CAD) [hazard ratio (HR) 1.56, 95% confidence interval (CI) 1.12-2.18], and hydroxychloroquine is associated with a decreased risk of CAD (HR 0.76, 95% CI 0.59-0.97). In vitro experiments show that hydroxychloroquine attenuates pro-inflammatory cytokine-mediated activation in human aortic endothelial cells, supporting mechanistically its potential beneficial effect in CAD. In summary, we demonstrate that a unique integration of protein-protein interaction network proximity and large-scale patient-level longitudinal data complemented by mechanistic in vitro studies can facilitate drug repurposing.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.