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Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals
Polygenic Scores (PSs) describe the genetic component of an individual’s quantitative phenotype or their susceptibility to diseases with a genetic basis. Currently, PSs rely on population-dependent contributions of many associated alleles, with limited applicability to understudied populations and r...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118071/ https://www.ncbi.nlm.nih.gov/pubmed/32242022 http://dx.doi.org/10.1038/s41467-020-15464-w |
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author | Marnetto, Davide Pärna, Katri Läll, Kristi Molinaro, Ludovica Montinaro, Francesco Haller, Toomas Metspalu, Mait Mägi, Reedik Fischer, Krista Pagani, Luca |
author_facet | Marnetto, Davide Pärna, Katri Läll, Kristi Molinaro, Ludovica Montinaro, Francesco Haller, Toomas Metspalu, Mait Mägi, Reedik Fischer, Krista Pagani, Luca |
author_sort | Marnetto, Davide |
collection | PubMed |
description | Polygenic Scores (PSs) describe the genetic component of an individual’s quantitative phenotype or their susceptibility to diseases with a genetic basis. Currently, PSs rely on population-dependent contributions of many associated alleles, with limited applicability to understudied populations and recently admixed individuals. Here we introduce a combination of local ancestry deconvolution and partial PS computation to account for the population-specific nature of the association signals in individuals with admixed ancestry. We demonstrate partial PS to be a proxy for the total PS and that a portion of the genome is enough to improve susceptibility predictions for the traits we test. By combining partial PSs from different populations, we are able to improve trait predictability in admixed individuals with some European ancestry. These results may extend the applicability of PSs to subjects with a complex history of admixture, where current methods cannot be applied. |
format | Online Article Text |
id | pubmed-7118071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71180712020-04-06 Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals Marnetto, Davide Pärna, Katri Läll, Kristi Molinaro, Ludovica Montinaro, Francesco Haller, Toomas Metspalu, Mait Mägi, Reedik Fischer, Krista Pagani, Luca Nat Commun Article Polygenic Scores (PSs) describe the genetic component of an individual’s quantitative phenotype or their susceptibility to diseases with a genetic basis. Currently, PSs rely on population-dependent contributions of many associated alleles, with limited applicability to understudied populations and recently admixed individuals. Here we introduce a combination of local ancestry deconvolution and partial PS computation to account for the population-specific nature of the association signals in individuals with admixed ancestry. We demonstrate partial PS to be a proxy for the total PS and that a portion of the genome is enough to improve susceptibility predictions for the traits we test. By combining partial PSs from different populations, we are able to improve trait predictability in admixed individuals with some European ancestry. These results may extend the applicability of PSs to subjects with a complex history of admixture, where current methods cannot be applied. Nature Publishing Group UK 2020-04-02 /pmc/articles/PMC7118071/ /pubmed/32242022 http://dx.doi.org/10.1038/s41467-020-15464-w Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Marnetto, Davide Pärna, Katri Läll, Kristi Molinaro, Ludovica Montinaro, Francesco Haller, Toomas Metspalu, Mait Mägi, Reedik Fischer, Krista Pagani, Luca Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title | Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title_full | Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title_fullStr | Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title_full_unstemmed | Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title_short | Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
title_sort | ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118071/ https://www.ncbi.nlm.nih.gov/pubmed/32242022 http://dx.doi.org/10.1038/s41467-020-15464-w |
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