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Assortative mating biases marker-based heritability estimators.
Border, Richard; O'Rourke, Sean; de Candia, Teresa; Goddard, Michael E; Visscher, Peter M; Yengo, Loic; Jones, Matt; Keller, Matthew C.
Affiliation
  • Border R; Departments of Neurology and Computer Science, University of California, Los Angeles, California, USA. border.richard@gmail.com.
  • O'Rourke S; Institute for Behavioral Genetics, University of Colorado Boulder, Colorado, USA. border.richard@gmail.com.
  • de Candia T; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Massachusetts, USA. border.richard@gmail.com.
  • Goddard ME; Department of Mathematics, University of Colorado Boulder, Colorado, USA.
  • Visscher PM; Institute for Behavioral Genetics, University of Colorado Boulder, Colorado, USA.
  • Yengo L; Faculty of Veterinary and Agricultural Science, University of Melbourne, Victoria, Australia.
  • Jones M; Department of Economic Development, Jobs, Transport and Resources, Biosciences Research Division, Victoria, Australia.
  • Keller MC; Institute for Molecular Bioscience, University of Queensland, Saint Lucia, QLD, Australia.
Nat Commun ; 13(1): 660, 2022 02 03.
Article in En | MEDLINE | ID: mdl-35115518
ABSTRACT
Many traits are subject to assortative mating, with recent molecular genetic findings confirming longstanding theoretical predictions that assortative mating induces long range dependence across causal variants. However, all marker-based heritability estimators implicitly assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments and likelihood-based estimators are biased in the presence of assortative mating and derive corrected heritability estimators for traits subject to assortment. Finally, we demonstrate that the empirical patterns of estimates across methods and sample sizes for real traits subject to assortative mating are congruent with expected assortative mating-induced biases. For example, marker-based heritability estimates for height are 14% - 23% higher than corrected estimates using UK Biobank data.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Reproduction / Algorithms / Genetics, Population / Models, Genetic Type of study: Prognostic_studies Limits: Female / Humans / Male Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2022 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Reproduction / Algorithms / Genetics, Population / Models, Genetic Type of study: Prognostic_studies Limits: Female / Humans / Male Language: En Journal: Nat Commun Journal subject: BIOLOGIA / CIENCIA Year: 2022 Document type: Article Affiliation country: United States