Causal Inference with Mendelian Randomization in Biomedical Studies

Explore the innovative application of Mendelian Randomization (MR) in biomedical research for establishing causal relationships from observational data. Delve into the use of genetic variants as instrumental variables to overcome confounding issues in traditional epidemiological studies. Learn about the fundamental principles of MR analysis and discover innovative methods developed for one-sample MR and longitudinal MR analysis. Understand how these advancements enhance the robustness and applicability of MR, addressing key challenges such as IV selection bias and weak instruments. Through simulation and case studies, gain insights into deciphering causal relationships between exposure and disease outcomes, offering valuable perspectives on the complexity of human diseases. Applicable to researchers and health professionals across various fields, this talk provides a comprehensive overview of MR's evolving potential in the genomic era for establishing causality in biomedical studies.

Yuehua Cui: Causal inference with Mendelian randomization in biomedical studies #ICBS2024