Abstract
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 protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 139 (34%) were not supported by results of colocalization analyses, suggesting that genetic confounding may be widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 105 putatively causal effects between 64 proteins and 51 downstream phenotypes (www.epigraphdb.org/pqtl). Evaluation of historic data from 268 drug development programmes showed that target-indication pairs with MR and colocalization support were considerably more likely to succeed, evidencing the value of this approach in identifying and prioritising potential therapeutic targets.
