AI Article Synopsis

  • Mendelian randomisation (MR) is a method used to determine if environmental and biological risk factors cause diseases, but this can be complicated by horizontal pleiotropy, where genetic variants affect multiple disease pathways.
  • The use of proteins as risk factors strengthens the reliability of MR studies since proteins are directly involved in biological processes and are also key targets for many medications.
  • This research introduces a new mathematical framework for MR analysis focused on proteins, highlighting model decisions and providing tools to enhance the power and reliability of these studies in drug development.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320010PMC
http://dx.doi.org/10.1038/s41467-020-16969-0DOI Listing

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