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Evaluation of polygenic risk score for risk prediction of gastric cancer
Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic rev...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9994049/ https://www.ncbi.nlm.nih.gov/pubmed/36908320 http://dx.doi.org/10.4251/wjgo.v15.i2.276 |
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author | Wang, Xiao-Yu Wang, Li-Li Xu, Lin Liang, Shu-Zhen Yu, Meng-Chao Zhang, Qiu-Yue Dong, Quan-Jiang |
author_facet | Wang, Xiao-Yu Wang, Li-Li Xu, Lin Liang, Shu-Zhen Yu, Meng-Chao Zhang, Qiu-Yue Dong, Quan-Jiang |
author_sort | Wang, Xiao-Yu |
collection | PubMed |
description | Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated. |
format | Online Article Text |
id | pubmed-9994049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-99940492023-03-09 Evaluation of polygenic risk score for risk prediction of gastric cancer Wang, Xiao-Yu Wang, Li-Li Xu, Lin Liang, Shu-Zhen Yu, Meng-Chao Zhang, Qiu-Yue Dong, Quan-Jiang World J Gastrointest Oncol Minireviews Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated. Baishideng Publishing Group Inc 2023-02-15 2023-02-15 /pmc/articles/PMC9994049/ /pubmed/36908320 http://dx.doi.org/10.4251/wjgo.v15.i2.276 Text en ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Minireviews Wang, Xiao-Yu Wang, Li-Li Xu, Lin Liang, Shu-Zhen Yu, Meng-Chao Zhang, Qiu-Yue Dong, Quan-Jiang Evaluation of polygenic risk score for risk prediction of gastric cancer |
title | Evaluation of polygenic risk score for risk prediction of gastric cancer |
title_full | Evaluation of polygenic risk score for risk prediction of gastric cancer |
title_fullStr | Evaluation of polygenic risk score for risk prediction of gastric cancer |
title_full_unstemmed | Evaluation of polygenic risk score for risk prediction of gastric cancer |
title_short | Evaluation of polygenic risk score for risk prediction of gastric cancer |
title_sort | evaluation of polygenic risk score for risk prediction of gastric cancer |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9994049/ https://www.ncbi.nlm.nih.gov/pubmed/36908320 http://dx.doi.org/10.4251/wjgo.v15.i2.276 |
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