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Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies.

ABSTRACT: Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the analyses in the UK Biobank, a much more homogeneously designed study. We show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population stratification. More generally, our results imply that typical constructions of polygenic scores are sensitive to population stratification and that population-level differences should be interpreted with caution. Editorial note:This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

SUBMITTER: Sohail M

PROVIDER: S-EPMC6428571 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies.

Sohail Mashaal M Maier Robert M RM Ganna Andrea A Bloemendal Alex A Martin Alicia R AR Turchin Michael C MC Chiang Charleston Wk CW Hirschhorn Joel J Daly Mark J MJ Patterson Nick N Neale Benjamin B Mathieson Iain I Reich David D Sunyaev Shamil R SR

eLife 20190321

Genetic predictions of height differ among human populations and these differences have been interpreted as evidence of polygenic adaptation. These differences were first detected using SNPs genome-wide significantly associated with height, and shown to grow stronger when large numbers of sub-significant SNPs were included, leading to excitement about the prospect of analyzing large fractions of the genome to detect polygenic adaptation for multiple traits. Previous studies of height have been b ...[more]

PMID: 30895926

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Project description:IMPORTANCE:Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases). OBJECTIVES:To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. DESIGN, SETTING, AND PARTICIPANTS:Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. MAIN OUTCOMES AND MEASURES:Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. RESULTS:A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P?=?9.26?×?10-9 in the discovery meta-analysis). This association was not replicated (P?=?.32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P?=?2.38?×?10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09?×?10-12?<?P?<?.05) and MDD (4.02?×?10-9?<?P?<?.05) in the 2 other cohorts. CONCLUSIONS AND RELEVANCE:This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.

Dataset Information

Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies.

Publications

Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies.

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