1. Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
- Author
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Yoonsu Cho, Ben Michael Brumpton, Jaakko Kaprio, Johan Håkon Bjørngaard, Elliot M. Tucker-Drob, Tim T Morris, Neil M Davies, Sean Harrison, Laurence J. Howe, Wei-Min Chen, Nancy L. Pedersen, Gunnhild Åberge Vie, Kristian Hveem, Karl Heilbron, Fernando Pires Hartwig, Michel G. Nivard, Gibran Hemani, Laura D Howe, George Davey Smith, David M. Evans, Michael C. Neale, Bjørn Olav Åsvold, Eleanor Sanderson, Adam Auton, Andrew D. Grotzinger, Shuai Li, Amanda Hughes, Cristen J. Willer, Chandra A. Reynolds, Frank Windmeijer, Dorret I. Boomsma, John L. Hopper, Alexandra Havdahl, Institute for Molecular Medicine Finland, Department of Public Health, University of Helsinki, HUS Helsinki and Uusimaa Hospital District, APH - Methodology, APH - Mental Health, Biological Psychology, Brumpton, Ben [0000-0002-3058-1059], Sanderson, Eleanor [0000-0001-5188-5775], Hartwig, Fernando Pires [0000-0003-3729-0710], Harrison, Sean [0000-0002-7966-0700], Vie, Gunnhild Åberge [0000-0003-1552-5291], Cho, Yoonsu [0000-0001-6118-6652], Havdahl, Alexandra [0000-0002-9268-0423], Neale, Michael [0000-0003-4887-659X], Nivard, Michel G [0000-0003-2015-1888], Grotzinger, Andrew [0000-0001-7852-9244], Morris, Tim [0000-0001-8178-6815], Willer, Cristen [0000-0001-5645-4966], Evans, David M [0000-0003-0663-4621], Kaprio, Jaakko [0000-0002-3716-2455], Davey Smith, George [0000-0002-1407-8314], Hemani, Gibran [0000-0003-0920-1055], Davies, Neil M [0000-0002-2460-0508], and Apollo - University of Cambridge Repository
- Subjects
0301 basic medicine ,Male ,Netherlands Twin Register (NTR) ,gene-environment correlation ,Epidemiology ,General Physics and Astronomy ,Matematikk og Naturvitenskap: 400::Basale biofag: 470 [VDP] ,Body Mass Index ,0302 clinical medicine ,HEIGHT ,Risk Factors ,Genetics research ,genetics ,030212 general & internal medicine ,lcsh:Science ,Multidisciplinary ,Confounding ,Mendelian Randomization Analysis ,ASSOCIATION ,3142 Public health care science, environmental and occupational health ,educational attainment ,Female ,TRAITS ,TRANSMISSION ,Science ,Biology ,Population stratification ,Polymorphism, Single Nucleotide ,Article ,General Biochemistry, Genetics and Molecular Biology ,BMI ,03 medical and health sciences ,Medical research ,SDG 3 - Good Health and Well-being ,Mendelian randomization ,Genetics ,LINKAGE ,Humans ,Matematikk og Naturvitenskap: 400 [VDP] ,COMMON ,Linkage (software) ,EDUCATIONAL-ATTAINMENT ,Assortative mating ,Gene-environment correlation ,General Chemistry ,confounding ,BODY-MASS INDEX ,3141 Health care science ,030104 developmental biology ,Matematikk og Naturvitenskap: 400::Basale biofag: 470::Genetikk og genomikk: 474 [VDP] ,INFERENCE ,lcsh:Q ,DISEQUILIBRIUM ,Body mass index ,height ,Demography - Abstract
Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies., Family-based study designs have been applied to resolve confounding by population stratification, dynastic effects and assortative mating in genetic association analyses. Here, Brumpton et al. describe theory and simulations for overcoming such biases in Mendelian randomization through within-family studies.
- Published
- 2020