Mendelian Randomization with Instrumental Variable Synthesis (IVY)

Citations Over Time

Abstract

SUMMARY Mendelian Randomization (MR) is an important causal inference method primarily used in biomedical research. This work applies contemporary techniques in machine learning to improve the robustness and power of traditional MR tools. By denoising and combining candidate genetic variants through techniques from unsupervised probabilistic graphical models, an influential latent instrumental variable is constructed for causal effect estimation. We present results on identifying relationships between biomarkers and the occurrence of coronary artery disease using individual-level real-world data from UK-BioBank via the proposed method. The approach, termed Instrumental Variable sYnthesis (IVY) is proposed as a complement to current methods, and is able to improve results based on allele scoring, particularly at moderate sample sizes.

Related Papers

• → Bayesian methods for instrumental variable analysis with genetic instruments (‘Mendelian randomization’): example with urate transporter SLC2A9 as an instrumental variable for effect of urate levels on metabolic syndrome(2010)47 cited
• → On the use of kernel machines for Mendelian randomization(2017)9 cited
• → Re: "Credible Mendelian Randomization Studies: Approaches For Evaluating The Instrumental Variable Assumptions"(2012)9 cited
• → Re: "Credible Mendelian Randomization Studies: Approaches For Evaluating The Instrumental Variable Assumptions"(2012)4 cited
• → Constrained Instruments and their Application to Mendelian Randomization with Pleiotropy(2017)7 cited