Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses

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 fa... Mehr ...

Verfasser: Brumpton, Ben
Boomsma, Dorret I.
Neale, Michael
Nivard, Michel G.
Davies, Neil M.
Dokumenttyp: Artikel
Erscheinungsdatum: 2020
Reihe/Periodikum: Brumpton , B , Boomsma , D I , Neale , M , Nivard , M G , Davies , N M & The 23andMe Research Team 2020 , ' Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses ' , Nature Communications , vol. 11 , no. 1 , 3519 , pp. 1-13 . https://doi.org/10.1038/s41467-020-17117-4
Schlagwörter: /dk/atira/pure/keywords/cohort_studies/netherlands_twin_register_ntr_ / name=Netherlands Twin Register (NTR) / /dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being / name=SDG 3 - Good Health and Well-being
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-27231468
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://research.vu.nl/en/publications/a088bb51-9702-4937-ba0b-699ed45aac22

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.