The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (https://www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

人类蛋白质组是治疗靶点的主要来源。最近对血浆蛋白质组的遗传关联分析能够系统地评估血浆蛋白质水平变化的因果关系。在这里，我们使用两样本孟德尔随机化 (MR) 和共定位估计了 1,002 种蛋白质对 225 种表型的影响。在 MR 证据支持的 413 个关联中，共定位分析结果不支持 130 个（31.5%），这表明由于连锁不平衡导致的遗传混杂在蛋白质的幼稚全表型关联研究中很普遍。在顺式中结合 MR 和共定位证据- 仅分析，我们确定了 65 种蛋白质和 52 种疾病相关表型之间的 111 种推定因果效应（https://www.epigraphdb.org/pqtl/）。对历史药物开发计划数据的评估表明，具有 MR 和共定位支持的靶标适应症对更有可能获得批准，这证明了这种方法在识别和优先考虑潜在治疗靶点方面的价值。