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Beyond the Hype of Mendelian Randomization for Rheumatology: What It Is Good for, What It Cannot Do, and How to Read It Critically

Year: 2026
Type: article
Abstract: Mendelian randomization (MR) has become abundant in the literature, with variation in quality and frequent overinterpretation of causality. This creates a problem for clinical readers, reviewers, and editors. Some MR studies can sharpen causal thinking, prioritize drug targets, and challenge misleading observational claims, whereas others are little more than automated exposure outcome scans with causal claims disproportionate to the evidence. MR can strengthen causal inference when randomized controlled trials are impractical and conventional observational studies are vulnerable to confounding, reverse causation, or selection bias. In rheumatology, credible MR can contribute to questions about disease etiology, modifiable risk factors, therapeutic target validation, anticipation of adverse effects, and phenotype validation. However, its interpretation depends on whether (1) the exposure is plausibly instrumentable; (2) the genetic instruments are biologically defensible; (3) assumptions are interrogated in ways appropriate to the design; and (4) findings are triangulated with clinical, observational, experimental, and mechanistic evidence. Instead of recapping all methodological issues of MR, this review aims to help rheumatologists quickly distinguish robust MR from weak or overinterpreted analyses. We provide an accessible framework for reading and triaging MR studies in rheumatology. Papers that use poorly justified instruments, treat medication use as drug target evidence, interpret genetic liability as diagnosis, rely on mechanical sensitivity analyses, ignore prior evidence, or ask no clinically meaningful questions can often be passed over by readers. The goal is not to discourage MR in rheumatology but to raise the standard. Useful MR should clarify causal reasoning rather than simply generate another statistically significant association.
Language: English
Subfield: Genetics
Open Access status: bronze
OpenAlex ID: W7204067878
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