期刊
NATURE COMMUNICATIONS
卷 9, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-018-05116-5
关键词
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资金
- NIH from NHGRI [P50-HG004233, U01-HG001715, U01-HG007690]
- NIH from NIGMS [P50-GM107618]
- NIH from NHLBI [PO1-HL083069, R37-HL061795, RC2-HL101543, U01-HL108630, RC4-HL106373, K99HL138272]
- NIH from PCORI [ME-1303-5638]
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.
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