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Title: Mendelian randomization: how it can--and cannot--help confirm causal relations between nutrition and cancer.
Authors: Schatzkin A,  Abnet CC,  Cross AJ,  Gunter M,  Pfeiffer R,  Gail M,  Lim U,  Davey-Smith G
Journal: Cancer Prev Res (Phila)
Date: 2009 Feb
Branches: NEB, BB
PubMed ID: 19174578
PMC ID: PMC3052774
Abstract: Observational epidemiologic studies of nutrition and cancer have faced formidable methodologic obstacles, including dietary measurement error and confounding. We consider whether Mendelian randomization can help surmount these obstacles. The Mendelian randomization strategy, building on both the accuracy of genotyping and the random assortment of alleles at meiosis, involves searching for an association between a nutritional exposure-mimicking gene variant (a type of "instrumental variable") and cancer outcome. Necessary assumptions are that the gene is independent of cancer, given the exposure, and also independent of potential confounders. An allelic variant can serve as a proxy for diet and other nutritional factors through its effects on either metabolic processes or consumption behavior. Such a genetic proxy is measured with little error and usually is not confounded by nongenetic characteristics. Examples of potentially informative genes include LCT (lactase), ALDH2 (aldehyde dehydrogenase), and HFE (hemochromatosis), proxies, respectively, for dairy product intake, alcoholic beverage drinking, and serum iron levels. We show that use of these and other genes in Mendelian randomization studies of nutrition and cancer may be more complicated than previously recognized and discuss factors that can invalidate the instrumental variable assumptions or cloud the interpretation of these studies. Sample size requirements for Mendelian randomization studies of nutrition and cancer are shown to be potentially daunting; strong genetic proxies for exposure are necessary to make such studies feasible. We conclude that Mendelian randomization is not universally applicable, but, under the right conditions, can complement evidence for causal associations from conventional epidemiologic studies.