DESCRIPTION:Two sample Mendelian randomisation (2SMR) is a method to estimate the causal effect of an exposure on an outcome using only summary statistics from genome wide association studies (GWAS). Though conceptually straightforward, there are a number of steps that are required to perform the analysis properly, and they can be cumbersome
CITATION:Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., ... & Haycock, P. C. (2018). The MR-Base platform supports systematic causal inference across the human phenome. elife, 7.
SMR
SMR
SHORT NAME: SMR
FULL NAME: Summary-data-based Mendelian Randomization
DESCRIPTION: The SMR software tool was originally developed to implement the SMR & HEIDI methods to test for pleiotropic association between the expression level of a gene and a complex trait of interest using summary-level data from GWAS and expression quantitative trait loci (eQTL) studies (Zhu et al. 2016 Nature Genetics). The SMR & HEIDI methodology can be interpreted as an analysis to test if the effect size of a SNP on the phenotype is mediated by gene expression. This tool can therefore be used to prioritize genes underlying GWAS hits for follow-up functional studies. The methods are applicable to all kinds of molecular QTL (xQTL) data, including DNA methylation QTL (mQTL) and protein abundance QTL (pQTL).
CITATION: Zhu, Z., Zhang, F., Hu, H. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet 48, 481–487 (2016). https://doi.org/10.1038/ng.3538
KEY WORDS: pleiotropy or causality, xQTL, eQTL, MR, HEIDI, linkage
SMR-multi
MeCS
Concepts&Principals
CITATION:Pierce, B. L., & Burgess, S. (2013). Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. American journal of epidemiology, 178(7), 1177-1184.
CITATION:Bowden, J., Davey Smith, G., & Burgess, S. (2015). Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International journal of epidemiology, 44(2), 512-525.
CITATION:Davey Smith, G., & Ebrahim, S. (2003). ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?. International journal of epidemiology, 32(1), 1-22.
CITATION: Hemani, G., Tilling, K., & Davey Smith, G. (2017). Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS genetics, 13(11), e1007081.
CITATION: Howe, L. J., Tudball, M., Davey Smith, G., & Davies, N. M. (2022). Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment. International journal of epidemiology, 51(3), 948-957.
Reviews&Tutorials
CITATION: Benn, M., & Nordestgaard, B. G. (2018). From genome-wide association studies to Mendelian randomization: novel opportunities for understanding cardiovascular disease causality, pathogenesis, prevention, and treatment. Cardiovascular research, 114(9), 1192-1208.
CITATION: Teumer, A. (2018). Common methods for performing Mendelian randomization. Frontiers in cardiovascular medicine, 5, 51.
CITATION: Davies, N. M., Holmes, M. V., & Smith, G. D. (2018). Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. bmj, 362.
CITATION: Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., ... & Davey Smith, G. (2022). Mendelian randomization. Nature Reviews Methods Primers, 2(1), 1-21.
CITATION: Minelli, C., Del Greco M, F., van der Plaat, D. A., Bowden, J., Sheehan, N. A., & Thompson, J. (2021). The use of two-sample methods for Mendelian randomization analyses on single large datasets. International journal of epidemiology, 50(5), 1651-1659.
CITATION: Zheng, J., Baird, D., Borges, M. C., Bowden, J., Hemani, G., Haycock, P., ... & Smith, G. D. (2017). Recent developments in Mendelian randomization studies. Current epidemiology reports, 4(4), 330-345.
CITATION: Emdin, C. A., Khera, A. V., & Kathiresan, S. (2017). Mendelian randomization. Jama, 318(19), 1925-1926.
CITATION: Lawlor, D. A. (2016). Commentary: Two-sample Mendelian randomization: opportunities and challenges. International journal of epidemiology, 45(3), 908.