Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference.

ABSTRACT: Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR helps address unmeasured confounding and reverse causation, offering a quasi-experimental framework to evaluate causal effects of modifiable exposures on health outcomes. Despite its promise, MR faces substantial methodological challenges, including invalid instruments, weak instrument bias, and design complexities across different data structures. In this tutorial review, we aim to provide a systematic overview of MR methods for causal inference, emphasizing clarity of causal interpretation, study design comparisons, availability of software tools, and practical guidance for applied scientists. We organize the revi

SUBMITTER: Yao M 

PROVIDER: S-EPMC12917735 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature