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Prediction of clinically significant prostate cancer using polygenic risk models in Asians
PURPOSE: To develop and evaluate the performance of a polygenic risk score (PRS) constructed in a Korean male population to predict clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: Total 2,702 PCa samples and 7,485 controls were used to discover csPCa susceptible single nucleot...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Korean Urological Association
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756152/ https://www.ncbi.nlm.nih.gov/pubmed/34983122 http://dx.doi.org/10.4111/icu.20210305 |
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author | Song, Sang Hun Kim, Eunae Woo, Eunjin Kwon, Eunkyung Yoon, Sungroh Kim, Jung Kwon Lee, Hakmin Oh, Jong Jin Lee, Sangchul Hong, Sung Kyu Byun, Seok-Soo |
author_facet | Song, Sang Hun Kim, Eunae Woo, Eunjin Kwon, Eunkyung Yoon, Sungroh Kim, Jung Kwon Lee, Hakmin Oh, Jong Jin Lee, Sangchul Hong, Sung Kyu Byun, Seok-Soo |
author_sort | Song, Sang Hun |
collection | PubMed |
description | PURPOSE: To develop and evaluate the performance of a polygenic risk score (PRS) constructed in a Korean male population to predict clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: Total 2,702 PCa samples and 7,485 controls were used to discover csPCa susceptible single nucleotide polymorphisms (SNPs). Males with biopsy-proven or post-radical prostatectomy Gleason score 7 or higher were included for analysis. After genotype imputation for quality control, logistic regression models were applied to test association and calculate effect size. Extracted candidate SNPs were further tested to compare predictive performance according to number of SNPs included in the PRS. The best-fit model was validated in an independent cohort of 311 cases and 822 controls. RESULTS: Of the 83 candidate SNPs with significant PCa association reported in previous literature, rs72725879 located in PRNCR1 showed the highest significance for PCa risk (odds ratio, 0.597; 95% confidence interval [CI], 0.555–0.641; p=4.3×10(-45)). Thirty-two SNPs within 26 distinct loci were further selected for PRS construction. Best performance was found with the top 29 SNPs, with AUC found to be 0.700 (95% CI, 0.667–0.734). Males with very-high PRS (above the 95th percentile) had a 4.92-fold increased risk for csPCa. CONCLUSIONS: Ethnic-specific PRS was developed and validated in Korean males to predict csPCa susceptibility using the largest csPCa sample size in Asia. PRS can be a potential biomarker to predict individual risk. Future multi-ethnic trials are required to further validate our results. |
format | Online Article Text |
id | pubmed-8756152 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Korean Urological Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-87561522022-01-25 Prediction of clinically significant prostate cancer using polygenic risk models in Asians Song, Sang Hun Kim, Eunae Woo, Eunjin Kwon, Eunkyung Yoon, Sungroh Kim, Jung Kwon Lee, Hakmin Oh, Jong Jin Lee, Sangchul Hong, Sung Kyu Byun, Seok-Soo Investig Clin Urol Original Article PURPOSE: To develop and evaluate the performance of a polygenic risk score (PRS) constructed in a Korean male population to predict clinically significant prostate cancer (csPCa). MATERIALS AND METHODS: Total 2,702 PCa samples and 7,485 controls were used to discover csPCa susceptible single nucleotide polymorphisms (SNPs). Males with biopsy-proven or post-radical prostatectomy Gleason score 7 or higher were included for analysis. After genotype imputation for quality control, logistic regression models were applied to test association and calculate effect size. Extracted candidate SNPs were further tested to compare predictive performance according to number of SNPs included in the PRS. The best-fit model was validated in an independent cohort of 311 cases and 822 controls. RESULTS: Of the 83 candidate SNPs with significant PCa association reported in previous literature, rs72725879 located in PRNCR1 showed the highest significance for PCa risk (odds ratio, 0.597; 95% confidence interval [CI], 0.555–0.641; p=4.3×10(-45)). Thirty-two SNPs within 26 distinct loci were further selected for PRS construction. Best performance was found with the top 29 SNPs, with AUC found to be 0.700 (95% CI, 0.667–0.734). Males with very-high PRS (above the 95th percentile) had a 4.92-fold increased risk for csPCa. CONCLUSIONS: Ethnic-specific PRS was developed and validated in Korean males to predict csPCa susceptibility using the largest csPCa sample size in Asia. PRS can be a potential biomarker to predict individual risk. Future multi-ethnic trials are required to further validate our results. The Korean Urological Association 2022-01 2021-11-29 /pmc/articles/PMC8756152/ /pubmed/34983122 http://dx.doi.org/10.4111/icu.20210305 Text en © The Korean Urological Association, 2022 https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Song, Sang Hun Kim, Eunae Woo, Eunjin Kwon, Eunkyung Yoon, Sungroh Kim, Jung Kwon Lee, Hakmin Oh, Jong Jin Lee, Sangchul Hong, Sung Kyu Byun, Seok-Soo Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title | Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title_full | Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title_fullStr | Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title_full_unstemmed | Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title_short | Prediction of clinically significant prostate cancer using polygenic risk models in Asians |
title_sort | prediction of clinically significant prostate cancer using polygenic risk models in asians |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756152/ https://www.ncbi.nlm.nih.gov/pubmed/34983122 http://dx.doi.org/10.4111/icu.20210305 |
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