Nature Communications (Jul 2020)
Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
- Ben Brumpton,
- Eleanor Sanderson,
- Karl Heilbron,
- Fernando Pires Hartwig,
- Sean Harrison,
- Gunnhild Åberge Vie,
- Yoonsu Cho,
- Laura D. Howe,
- Amanda Hughes,
- Dorret I. Boomsma,
- Alexandra Havdahl,
- John Hopper,
- Michael Neale,
- Michel G. Nivard,
- Nancy L. Pedersen,
- Chandra A. Reynolds,
- Elliot M. Tucker-Drob,
- Andrew Grotzinger,
- Laurence Howe,
- Tim Morris,
- Shuai Li,
- The Within-family Consortium,
- The 23andMe Research Team,
- Adam Auton,
- Frank Windmeijer,
- Wei-Min Chen,
- Johan Håkon Bjørngaard,
- Kristian Hveem,
- Cristen Willer,
- David M. Evans,
- Jaakko Kaprio,
- George Davey Smith,
- Bjørn Olav Åsvold,
- Gibran Hemani,
- Neil M. Davies
Affiliations
- Ben Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- Eleanor Sanderson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Karl Heilbron
- 23andMe, Inc.
- Fernando Pires Hartwig
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Sean Harrison
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Gunnhild Åberge Vie
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- Yoonsu Cho
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Laura D. Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Amanda Hughes
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam
- Alexandra Havdahl
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne
- Michael Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
- Michel G. Nivard
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam
- Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet
- Chandra A. Reynolds
- Department of Psychology, University of California Riverside
- Elliot M. Tucker-Drob
- Department of Psychology and Population Research Center, University of Texas at Austin
- Andrew Grotzinger
- Department of Psychology and Population Research Center, University of Texas at Austin
- Laurence Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Tim Morris
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne
- The Within-family Consortium
- The 23andMe Research Team
- 23andMe, Inc.
- Adam Auton
- 23andMe, Inc.
- Frank Windmeijer
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Wei-Min Chen
- Center for public health genomics, Department of public health sciences, University of Virginia
- Johan Håkon Bjørngaard
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- Cristen Willer
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan
- David M. Evans
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Jaakko Kaprio
- Department of Public Health, University of Helsinki
- George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Bjørn Olav Åsvold
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, University of Bristol
- Neil M. Davies
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology
- DOI
- https://doi.org/10.1038/s41467-020-17117-4
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 13
Abstract
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.
