Article (Périodiques scientifiques)
Trans-ancestry polygenic models for the prediction of LDL blood levels: an analysis of the United Kingdom Biobank and Taiwan Biobank
HASSANIN, Emadeldin Saeed Fathy Elsayed; Lee, Ko-Han; Hsieh, Tzung-Chien et al.
2023In Frontiers in Genetics, 14
Peer reviewed vérifié par ORBi Dataset
 

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Mots-clés :
Genetics; Molecular Medicine; LDL; Polygenic risk scores
Résumé :
[en] Polygenic risk score (PRS) predictions often show bias toward the population of available genome-wide association studies (GWASs), which is typically of European ancestry. This study aimed to assess the performance differences of ancestry-specific PRS and test the implementation of multi-ancestry PRS to enhance the generalizability of low-density lipoprotein (LDL) cholesterol predictions in the East Asian (EAS) population. In this study, we computed ancestry-specific and multi-ancestry PRSs for LDL using data obtained from the Global Lipid Genetics Consortium, while accounting for population-specific linkage disequilibrium patterns using the PRS-CSx method in the United Kingdom Biobank dataset (UKB, n = 423,596) and Taiwan Biobank dataset (TWB, n = 68,978). Population-specific PRSs were able to predict LDL levels better within the target population, whereas multi-ancestry PRSs were more generalizable. In the TWB dataset, covariate-adjusted R2 values were 9.3% for ancestry-specific PRS, 6.7% for multi-ancestry PRS, and 4.5% for European-specific PRS. Similar trends (8.6%, 7.8%, and 6.2%) were observed in the smaller EAS population of the UKB (n = 1,480). Consistent with R2 values, PRS stratification in EAS regions (TWB) effectively captured a heterogenous variability in LDL blood cholesterol levels across PRS strata. The mean difference in LDL levels between the lowest and highest EAS-specific PRS (EAS_PRS) deciles was 0.82, compared to 0.59 for European-specific PRS (EUR_PRS) and 0.76 for multi-ancestry PRS. Notably, the mean LDL values in the top decile of multi-ancestry PRS were comparable to those of EAS_PRS (3.543 vs. 3.541, p = 0.86). Our analysis of the PRS prediction model for LDL cholesterol further supports the issue of PRS generalizability across populations. Our targeted analysis of the EAS population revealed that integrating non-European genotyping data with a powerful European-based GWAS can enhance the generalizability of LDL PRS.
Centre de recherche :
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Médecine générale & interne
Génétique & processus génétiques
Auteur, co-auteur :
HASSANIN, Emadeldin Saeed Fathy Elsayed ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Lee, Ko-Han
Hsieh, Tzung-Chien
Aldisi, Rana
Lee, Yi-Lun
BOBBILI, Dheeraj Reddy ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Krawitz, Peter
MAY, Patrick  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Chen, Chien-Yu
Maj, Carlo
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Trans-ancestry polygenic models for the prediction of LDL blood levels: an analysis of the United Kingdom Biobank and Taiwan Biobank
Date de publication/diffusion :
23 novembre 2023
Titre du périodique :
Frontiers in Genetics
eISSN :
1664-8021
Maison d'édition :
Frontiers Media SA
Volume/Tome :
14
Peer reviewed :
Peer reviewed vérifié par ORBi
Focus Area :
Systems Biomedicine
Objectif de développement durable (ODD) :
3. Bonne santé et bien-être
Projet FnR :
FNR14429377 - Reduced Penetrance In Hereditary Movement Disorders: Elucidating Mechanisms Of Endogenous Disease Protection, 2020 (01/07/2020-30/06/2023) - Anne Grünewald
FNR16394868 - Epileptogenesis Of Genetic Epilepsies, 2021 (01/10/2021-...) - Alexander Skupin
Organisme subsidiant :
National Science and Technology Council (NSTC), Taiwan
N° du Fonds :
MOST 109-2221-E-002-162-MY3, MOST 111-2221-E-002-66-MY3, NSTC 112-2221-E -002-184-MY3
Jeu de données :
Commentaire :
Publicly available datasets were analyzed in this study. These data can be found at: http://www.ukbiobank.ac.uk/about-biobankuk/ and https://www.biobank.org.tw/. The codes related to the statistical analysis for this study have been deposited on GitLab, and the generated ancestry-specific and multi-ancestry PRS weights for LDL (excluding UK Biobank samples) are available on Zenodo at the following location (doi:10.17881/8wqn-x712).
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depuis le 24 novembre 2023

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