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Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention
Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471106/ https://www.ncbi.nlm.nih.gov/pubmed/37724297 http://dx.doi.org/10.1515/mr-2021-0025 |
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author | Wang, Yuzhuo Zhu, Meng Ma, Hongxia Shen, Hongbing |
author_facet | Wang, Yuzhuo Zhu, Meng Ma, Hongxia Shen, Hongbing |
author_sort | Wang, Yuzhuo |
collection | PubMed |
description | Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual’s genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed. |
format | Online Article Text |
id | pubmed-10471106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-104711062023-09-18 Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention Wang, Yuzhuo Zhu, Meng Ma, Hongxia Shen, Hongbing Med Rev (Berl) Review Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual’s genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed. De Gruyter 2022-02-14 /pmc/articles/PMC10471106/ /pubmed/37724297 http://dx.doi.org/10.1515/mr-2021-0025 Text en © 2021 Yuzhuo Wang et al., published by De Gruyter, Berlin/Boston https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Review Wang, Yuzhuo Zhu, Meng Ma, Hongxia Shen, Hongbing Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title | Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title_full | Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title_fullStr | Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title_full_unstemmed | Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title_short | Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
title_sort | polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471106/ https://www.ncbi.nlm.nih.gov/pubmed/37724297 http://dx.doi.org/10.1515/mr-2021-0025 |
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