Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer's disease

基于内表型的计算机网络药物发现与保险记录数据挖掘相结合,将西地那非确定为阿尔茨海默病的候选药物

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作者:Jiansong Fang, Pengyue Zhang, Yadi Zhou, Chien-Wei Chiang, Juan Tan, Yuan Hou, Shaun Stauffer, Lang Li, Andrew A Pieper, Jeffrey Cummings, Feixiong Cheng

Abstract

We developed an endophenotype disease module-based methodology for Alzheimer's disease (AD) drug repurposing and identified sildenafil as a potential disease risk modifier. Based on retrospective case-control pharmacoepidemiologic analyses of insurance claims data for 7.23 million individuals, we found that sildenafil usage was significantly associated with a 69% reduced risk of AD (hazard ratio = 0.31, 95% confidence interval 0.25-0.39, P<1.0×10-8). Propensity score stratified analyses confirmed that sildenafil is significantly associated with a decreased risk of AD across all four drug cohorts we tested (diltiazem, glimepiride, losartan and metformin) after adjusting age, sex, race, and disease comorbidities. We also found that sildenafil increases neurite growth and decreases phospho-tau expression in AD patient-induced pluripotent stem cells-derived neuron models, supporting mechanistically its potential beneficial effect in Alzheimer's disease. The association between sildenafil use and decreased incidence of AD does not establish causality or its direction, which requires a randomized clinical trial approach.

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