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Genotype imputation and polygenic score estimation in northwestern Russian population
Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic stu...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239469/ https://www.ncbi.nlm.nih.gov/pubmed/35763490 http://dx.doi.org/10.1371/journal.pone.0269434 |
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author | Kolosov, Nikita Rezapova, Valeriia Rotar, Oxana Loboda, Alexander Freylikhman, Olga Melnik, Olesya Sergushichev, Alexey Stevens, Christine Voortman, Trudy Kostareva, Anna Konradi, Alexandra Daly, Mark J. Artomov, Mykyta |
author_facet | Kolosov, Nikita Rezapova, Valeriia Rotar, Oxana Loboda, Alexander Freylikhman, Olga Melnik, Olesya Sergushichev, Alexey Stevens, Christine Voortman, Trudy Kostareva, Anna Konradi, Alexandra Daly, Mark J. Artomov, Mykyta |
author_sort | Kolosov, Nikita |
collection | PubMed |
description | Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance. |
format | Online Article Text |
id | pubmed-9239469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92394692022-06-29 Genotype imputation and polygenic score estimation in northwestern Russian population Kolosov, Nikita Rezapova, Valeriia Rotar, Oxana Loboda, Alexander Freylikhman, Olga Melnik, Olesya Sergushichev, Alexey Stevens, Christine Voortman, Trudy Kostareva, Anna Konradi, Alexandra Daly, Mark J. Artomov, Mykyta PLoS One Research Article Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance. Public Library of Science 2022-06-28 /pmc/articles/PMC9239469/ /pubmed/35763490 http://dx.doi.org/10.1371/journal.pone.0269434 Text en © 2022 Kolosov et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kolosov, Nikita Rezapova, Valeriia Rotar, Oxana Loboda, Alexander Freylikhman, Olga Melnik, Olesya Sergushichev, Alexey Stevens, Christine Voortman, Trudy Kostareva, Anna Konradi, Alexandra Daly, Mark J. Artomov, Mykyta Genotype imputation and polygenic score estimation in northwestern Russian population |
title | Genotype imputation and polygenic score estimation in northwestern Russian population |
title_full | Genotype imputation and polygenic score estimation in northwestern Russian population |
title_fullStr | Genotype imputation and polygenic score estimation in northwestern Russian population |
title_full_unstemmed | Genotype imputation and polygenic score estimation in northwestern Russian population |
title_short | Genotype imputation and polygenic score estimation in northwestern Russian population |
title_sort | genotype imputation and polygenic score estimation in northwestern russian population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239469/ https://www.ncbi.nlm.nih.gov/pubmed/35763490 http://dx.doi.org/10.1371/journal.pone.0269434 |
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