Genetic drug target validation using Mendelian randomisation

TLDR

Mendelian randomisation is a key method for inferring causal effects of risk factors, but its validity can be compromised by horizontal pleiotropy; proteins, as proximal effectors and common drug targets, are increasingly studied as MR instruments in drug development. The study aims to strengthen the no‑horizontal‑pleiotropy assumption for protein‑based risk factors and to introduce a mathematical framework contrasting protein MR with distal risk‑factor MR. The authors present a mathematical framework that contrasts protein‑based MR with distal risk‑factor MR, illustrating key model decisions and providing an analytical approach to maximize power and assess robustness.

Abstract

Mendelian randomisation (MR) analysis is an important tool to elucidate the causal relevance of environmental and biological risk factors for disease. However, causal inference is undermined if genetic variants used to instrument a risk factor also influence alternative disease-pathways (horizontal pleiotropy). Here we report how the 'no horizontal pleiotropy assumption' is strengthened when proteins are the risk factors of interest. Proteins are typically the proximal effectors of biological processes encoded in the genome. Moreover, proteins are the targets of most medicines, so MR studies of drug targets are becoming a fundamental tool in drug development. To enable such studies, we introduce a mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. We illustrate key model decisions and introduce an analytical framework for maximising power and evaluating the robustness of analyses.