Within family Mendelian randomization studies

Author:

Davies Neil M12ORCID,Howe Laurence J12,Brumpton Ben134,Havdahl Alexandra156,Evans David M17,Davey Smith George12

Affiliation:

1. Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, United Kingdom

2. Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom

3. K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway

4. Clinic of Thoracic and Occupational Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway

5. Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway

6. Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway

7. University of Queensland Diamantina Institute, University of Queensland, Brisbane, 4102, Australia

Abstract

AbstractMendelian randomization (MR) is increasingly used to make causal inferences in a wide range of fields, from drug development to etiologic studies. Causal inference in MR is possible because of the process of genetic inheritance from parents to offspring. Specifically, at gamete formation and conception, meiosis ensures random allocation to the offspring of one allele from each parent at each locus, and these are unrelated to most of the other inherited genetic variants. To date, most MR studies have used data from unrelated individuals. These studies assume that genotypes are independent of the environment across a sample of unrelated individuals, conditional on covariates. Here we describe potential sources of bias, such as transmission ratio distortion, selection bias, population stratification, dynastic effects and assortative mating that can induce spurious or biased SNP–phenotype associations. We explain how studies of related individuals such as sibling pairs or parent–offspring trios can be used to overcome some of these sources of bias, to provide potentially more reliable evidence regarding causal processes. The increasing availability of data from related individuals in large cohort studies presents an opportunity to both overcome some of these biases and also to evaluate familial environmental effects.

Funder

Medical Research Council

Economics and Social Research Council

Publisher

Oxford University Press (OUP)

Subject

Genetics(clinical),Genetics,Molecular Biology,General Medicine

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