ArticleThe American journal of clinical nutrition2016
Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies.
Article in The American journal of clinical nutrition, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 358 papers, 5 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
358 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Review of Mendelian randomization studies on common male-specific diseases.Frontiers in endocrinology · 2025Pooled it
- Genetically predicted circulating serum homocysteine levels on osteoporosis: a two-sample mendelian randomization study.Scientific reports · 2023Pooled it
- Pooled it
- Association betweenPeerJ · 2023Pooled it
- Identifying molecular mediators of the relationship between body mass index and endometrial cancer risk: a Mendelian randomization analysis.BMC medicine · 2022Pooled it
- Article
- Comparing genome-wide significant and chemosensory variants as instruments for dietary patterns in Mendelian randomization.International journal of epidemiology · 2026Article
- Mendelian randomization in ovarian research: applications in PCOS, ovarian aging, and assisted reproductive technology.Journal of ovarian research · 2026Review
- Applying Artificial Intelligence and machine learning in precision nutrition.Nature communications · 2026Review
- Genetically Informed Research Designs in Perinatal Pharmacoepidemiology: A Methodological Overview.Drug safety · 2026Review
- Shared genetic architecture between ADHD and intelligence varies across ADHD subtypes.BMC medicine · 2026Article
- Integrative omics analysis incorporating cardiovascular magnetic resonance imaging pinpoints potentially druggable plasma proteins for cardiovascular diseases.Life metabolism · 2026Article
- Comparison of two-stage methods for count data in Mendelian randomization: a simulation study.Journal of comparative effectiveness research · 2026Article
- Association between genetically predicted dietary patterns and atrial fibrillation: a two sample Mendelian randomization study.European journal of nutrition · 2026Article
- Causal association between Epstein-Barr virus infection and malignant gynecologic and breast tumors: a two-sample Mendelian randomization study.Discover oncology · 2026Article
- Mind the gap: Characterizing bias due to population mismatch in two-sample Mendelian randomization.American journal of human genetics · 2026Article
- Comprehensive analysis for the role of macrophage-driven genes in abdominal aortic aneurysm.Cardiovascular diagnosis and therapy · 2026Article
- Metformin provides superior neuroprotective potential compared to semaglutide in preventing diabetes-associated Alzheimer's disease via dual actions.Communications medicine · 2026Article
- Iron status modulates immune cell proportions to drive epigenetic age acceleration: A 2-step Mendelian randomization study.Medicine · 2026Article
- Causal Association Between Transferrin Saturation and Periodontitis: A Mendelian Randomization Study.Oral health & preventive dentistry · 2026Article
298 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Mendelian randomization (MR) is an increasingly important tool for appraising causality in observational epidemiology. The technique exploits the principle that genotypes are not generally susceptible to reverse causation bias and confounding, reflecting their fixed nature and Mendel’s first and second laws of inheritance. The approach is, however, subject to important limitations and assumptions that, if unaddressed or compounded by poor study design, can lead to erroneous conclusions. Nevertheless, the advent of 2-sample approaches (in which exposure and outcome are measured in separate samples) and the increasing availability of open-access data from large consortia of genome-wide association studies and population biobanks mean that the approach is likely to become routine practice in evidence synthesis and causal inference research. In this article we provide an overview of the design, analysis, and interpretation of MR studies, with a special emphasis on assumptions and limitations. We also consider different analytic strategies for strengthening causal inference. Although impossible to prove causality with any single approach, MR is a highly cost-effective strategy for prioritizing intervention targets for disease prevention and for strengthening the evidence base for public health policy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.