title: Accuracy of heritability estimations in presence of hidden population stratification.
abstract: The heritability of a trait is the proportion of its variance explained by genetic factors; it has historically been estimated using familial data. However, new methods have appeared for estimating heritabilities using genomewide data from unrelated individuals. A drawback of this strategy is that population stratification can bias the estimates. Indeed, an environmental factor associated with the phenotype may differ among population subgroups. This factor being associated both with the phenotype and the genetic variation in the population would be a confounder. A common solution consists in adjusting on the first Principal Components (PCs) of the genomic data. We study this procedure on simulated data and on 6000 individuals from the Three-City Study. We analyse the geographical coordinates of the birth cities, which are not genetically determined, but the heritability of which should be overestimated due to population stratification. We also analyse various anthropometric traits. The procedure fails to correct the bias in geographical coordinates heritability estimates. The heritability estimates of the anthropometric traits are affected by the inclusion of the first PC, but not by the following PCs, contrarily to geographical coordinates. We recommend to be cautious with heritability estimates obtained from a large population.
authors.affiliation: CESP, Inserm, Univ. Paris-Sud, Université Paris-Saclay, Villejuif, France.
authors.forename: Claire
authors.initials: C
authors.lastname: Dandine-Roulland
authors.affiliation: UMR1167 - Labex Distalz, Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, F-59000 Lille, France.
authors.forename: Céline
authors.initials: C
authors.lastname: Bellenguez
authors.affiliation: Université de Bordeaux, Bordeaux, France.|Inserm U1219, Bordeaux, France.|CHU de Bordeaux, Bordeaux, France.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Debette
authors.affiliation: UMR1167 - Labex Distalz, Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, F-59000 Lille, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Amouyel
authors.affiliation: Inserm, UMR 1078, Brest, France.|Université Bretagne Occidentale, Brest, France.|Centre Hospitalier Régional Universitaire, Brest, France.
authors.forename: Emmanuelle
authors.initials: E
authors.lastname: Génin
authors.affiliation: CESP, Inserm, Univ. Paris-Sud, Université Paris-Saclay, Villejuif, France.
authors.forename: Hervé
authors.initials: H
authors.lastname: Perdry
mesh_terms: D001827:Body Height / Q000235:genetics; D005260:Female; D005602:France; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D058974:Phylogeography; D025341:Principal Component Analysis; D040641:Quantitative Trait Loci; D049629:Waist-Hip Ratio