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Extreme Polygenicity of Complex Traits Is Explained by Negative Selection.
O'Connor, Luke J; Schoech, Armin P; Hormozdiari, Farhad; Gazal, Steven; Patterson, Nick; Price, Alkes L.
Afiliação
  • O'Connor LJ; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Bioinformatics and Integrative Genomics, Harvard Graduate School of Arts and Sciences, Boston, MA 02115, USA. Electronic address: loconnor@g.harvard.edu.
  • Schoech AP; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Hormozdiari F; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Gazal S; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.
  • Patterson N; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
  • Price AL; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address: aprice@hsph.harvard.edu.
Am J Hum Genet ; 105(3): 456-476, 2019 09 05.
Article em En | MEDLINE | ID: mdl-31402091
ABSTRACT
Complex traits and common diseases are extremely polygenic, their heritability spread across thousands of loci. One possible explanation is that thousands of genes and loci have similarly important biological effects when mutated. However, we hypothesize that for most complex traits, relatively few genes and loci are critical, and negative selection-purging large-effect mutations in these regions-leaves behind common-variant associations in thousands of less critical regions instead. We refer to this phenomenon as flattening. To quantify its effects, we introduce a mathematical definition of polygenicity, the effective number of independently associated SNPs (Me), which describes how evenly the heritability of a trait is spread across the genome. We developed a method, stratified LD fourth moments regression (S-LD4M), to estimate Me, validating that it produces robust estimates in simulations. Analyzing 33 complex traits (average N = 361k), we determined that heritability is spread ∼4× more evenly among common SNPs than among low-frequency SNPs. This difference, together with evolutionary modeling of new mutations, suggests that complex traits would be orders of magnitude less polygenic if not for the influence of negative selection. We also determined that heritability is spread more evenly within functionally important regions in proportion to their heritability enrichment; functionally important regions do not harbor common SNPs with greatly increased causal effect sizes, due to selective constraint. Our results suggest that for most complex traits, the genes and loci with the most critical biological effects often differ from those with the strongest common-variant associations.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Seleção Genética / Herança Multifatorial Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Am J Hum Genet Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Seleção Genética / Herança Multifatorial Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Am J Hum Genet Ano de publicação: 2019 Tipo de documento: Article