Mendelian randomization
- PMID: 37325194
- PMCID: PMC7614635
- DOI: 10.1038/s43586-021-00092-5
Mendelian randomization
Abstract
Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.
Conflict of interest statement
Competing interest The authors declare no competing interests.
References
-
- Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? International journal of epidemiology. 2003;32:1–22. - PubMed
-
- Angrist JD, Imbens GW, Rubin DB. Identification of causal effects using instrumental variables. Journal of the American statistical Association. 1996;91:444–455.
-
- Hernán MA, JM R. Causal Inference: What If. Chapman & Hall/CRC; Boca Raton: 2020.
-
- Greenland S. An introduction to instrumental variables for epidemiologists. International journal of epidemiology. 2000;29:722–729. - PubMed
-
- Zuccolo L, Holmes MV. Commentary: Mendelian randomization-inspired causal inference in the absence of genetic data. International journal of epidemiology. 2017;46:962–965. - PubMed
Grants and funding
LinkOut - more resources
Full Text Sources