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Polygenic scoring accuracy varies across the genetic ancestry continuum.
Ding, Yi; Hou, Kangcheng; Xu, Ziqi; Pimplaskar, Aditya; Petter, Ella; Boulier, Kristin; Privé, Florian; Vilhjálmsson, Bjarni J; Olde Loohuis, Loes M; Pasaniuc, Bogdan.
Afiliación
  • Ding Y; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA. yiding920@ucla.edu.
  • Hou K; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
  • Xu Z; Department of Computer Science, UCLA, Los Angeles, CA, USA.
  • Pimplaskar A; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
  • Petter E; Department of Computer Science, UCLA, Los Angeles, CA, USA.
  • Boulier K; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
  • Privé F; National Centre for Register-based Research, Aarhus University, Aarhus, Denmark.
  • Vilhjálmsson BJ; National Centre for Register-based Research, Aarhus University, Aarhus, Denmark.
  • Olde Loohuis LM; Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
  • Pasaniuc B; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute, Cambridge, MA, USA.
Nature ; 618(7966): 774-781, 2023 Jun.
Article en En | MEDLINE | ID: mdl-37198491
ABSTRACT
Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use1-3. PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R2)4, ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank5 (ATLAS, n = 36,778) along with the UK Biobank6 (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries7 in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries. The decreasing trend is well captured by a continuous measure of genetic distance (GD) from the PGS training data Pearson correlation of -0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained on individuals labelled as white British in the UKBB to individuals with European ancestries in ATLAS, individuals in the furthest GD decile have 14% lower accuracy relative to the closest decile; notably, the closest GD decile of individuals with Hispanic Latino American ancestries show similar PGS performance to the furthest GD decile of individuals with European ancestries. GD is significantly correlated with PGS estimates themselves for 82 of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestries in PGS interpretation. Our results highlight the need to move away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGSs.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Herencia Multifactorial / Grupos Raciales Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: America do norte / Europa Idioma: En Revista: Nature Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Herencia Multifactorial / Grupos Raciales Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: America do norte / Europa Idioma: En Revista: Nature Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos