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Implementation of individualised polygenic risk score analysis: a test case of a family of four
BACKGROUND: Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demon...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531350/ https://www.ncbi.nlm.nih.gov/pubmed/36192731 http://dx.doi.org/10.1186/s12920-022-01331-8 |
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author | Corpas, Manuel Megy, Karyn Metastasio, Antonio Lehmann, Edmund |
author_facet | Corpas, Manuel Megy, Karyn Metastasio, Antonio Lehmann, Edmund |
author_sort | Corpas, Manuel |
collection | PubMed |
description | BACKGROUND: Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level. CASE PRESENTATION: We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here. CONCLUSIONS: Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics. |
format | Online Article Text |
id | pubmed-9531350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95313502022-10-05 Implementation of individualised polygenic risk score analysis: a test case of a family of four Corpas, Manuel Megy, Karyn Metastasio, Antonio Lehmann, Edmund BMC Med Genomics Case Study BACKGROUND: Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level. CASE PRESENTATION: We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here. CONCLUSIONS: Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics. BioMed Central 2022-10-03 /pmc/articles/PMC9531350/ /pubmed/36192731 http://dx.doi.org/10.1186/s12920-022-01331-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Case Study Corpas, Manuel Megy, Karyn Metastasio, Antonio Lehmann, Edmund Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title | Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title_full | Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title_fullStr | Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title_full_unstemmed | Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title_short | Implementation of individualised polygenic risk score analysis: a test case of a family of four |
title_sort | implementation of individualised polygenic risk score analysis: a test case of a family of four |
topic | Case Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9531350/ https://www.ncbi.nlm.nih.gov/pubmed/36192731 http://dx.doi.org/10.1186/s12920-022-01331-8 |
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