@article{smith_mendelian_2014,
	title = {Mendelian randomization: genetic anchors for causal inference in epidemiological studies},
	volume = {23},
	issn = {1460-2083},
	url = {https://pubmed.ncbi.nlm.nih.gov/25064373/},
	doi = {10.1093/HMG/DDU328},
	abstract = {Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including twosample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research. © The Author 2014. Published by Oxford University Press.},
	number = {R1},
	urldate = {2022-01-26},
	journal = {Human molecular genetics},
	author = {Smith, George Davey and Hemani, Gibran},
	year = {2014},
	pmid = {25064373},
	note = {Publisher: Hum Mol Genet},
	keywords = {Causality, Epidemiologic Studies, Genetic Variation, George Davey Smith, Gibran Hemani, Humans, MEDLINE, Mendelian Randomization Analysis / methods*, NCBI, NIH, NLM, National Center for Biotechnology Information, National Institutes of Health, National Library of Medicine, Non-U.S. Gov't, PMC4170722, PubMed Abstract, Randomized Controlled Trials as Topic, Research Support, Review, doi:10.1093/hmg/ddu328, pmid:25064373},
}

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The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including twosample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research. © The Author 2014. Published by Oxford University Press.","number":"R1","urldate":"2022-01-26","journal":"Human molecular genetics","author":[{"propositions":[],"lastnames":["Smith"],"firstnames":["George","Davey"],"suffixes":[]},{"propositions":[],"lastnames":["Hemani"],"firstnames":["Gibran"],"suffixes":[]}],"year":"2014","pmid":"25064373","note":"Publisher: Hum Mol Genet","keywords":"Causality, Epidemiologic Studies, Genetic Variation, George Davey Smith, Gibran Hemani, Humans, MEDLINE, Mendelian Randomization Analysis / methods*, NCBI, NIH, NLM, National Center for Biotechnology Information, National Institutes of Health, National Library of Medicine, Non-U.S. Gov't, PMC4170722, PubMed Abstract, Randomized Controlled Trials as Topic, Research Support, Review, doi:10.1093/hmg/ddu328, pmid:25064373","bibtex":"@article{smith_mendelian_2014,\n\ttitle = {Mendelian randomization: genetic anchors for causal inference in epidemiological studies},\n\tvolume = {23},\n\tissn = {1460-2083},\n\turl = {https://pubmed.ncbi.nlm.nih.gov/25064373/},\n\tdoi = {10.1093/HMG/DDU328},\n\tabstract = {Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including twosample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research. © The Author 2014. 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