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Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study
BACKGROUND: Genetic variations are linked to kidney stone formation. However, the association of single nucleotide polymorphism (SNPs) and stone recurrence has not been well studied. This study aims to identify genetic variants associated with kidney stone recurrences and to construct a predictive n...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616432/ https://www.ncbi.nlm.nih.gov/pubmed/37915892 http://dx.doi.org/10.1093/ckj/sfad119 |
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author | Zhu, Wei Zhang, Xin Zhou, Zhen Sun, Yin Zhang, Guangyuan Duan, Xiaolu Huang, Zhicong Ai, Guoyao Liu, Yang Zhao, Zhijian Zhong, Wen Zeng, Guohua |
author_facet | Zhu, Wei Zhang, Xin Zhou, Zhen Sun, Yin Zhang, Guangyuan Duan, Xiaolu Huang, Zhicong Ai, Guoyao Liu, Yang Zhao, Zhijian Zhong, Wen Zeng, Guohua |
author_sort | Zhu, Wei |
collection | PubMed |
description | BACKGROUND: Genetic variations are linked to kidney stone formation. However, the association of single nucleotide polymorphism (SNPs) and stone recurrence has not been well studied. This study aims to identify genetic variants associated with kidney stone recurrences and to construct a predictive nomogram model using SNPs and clinical features to predict the recurrence risk of kidney stones. METHODS: We genotyped 49 SNPs in 1001 patients who received surgical stone removal between Jan 1 and Dec 31 of 2012. All patients were confirmed stone-free by CT scan and then received follow-up at least 5 years. SNP associations with stone recurrence were analyzed by Cox proportion hazard model. A predictive nomogram model using SNPs and clinical features to predict the recurrence risk of kidney stones was developed by use of LASSO Cox regression. RESULTS: The recurrence rate at 3, 5, 7 years were 46.8%, 71.2%, and 78.4%, respectively. 5 SNPs were identified that had association with kidney stone recurrence risk. We used computer-generated random numbers to assign 500 of these patients to the training cohort and 501 patients to the validation cohort. A nomogram that combined the 14-SNPs-based classifier with the clinical risk factors was constructed. The areas under the curve (AUCs) at 3, 5 and 7 years of this nomogram was 0.645, 0.723, and 0.75 in training cohort, and was 0.631, 0.708, and 0.727 in validation cohort, respectively. Results show that the nomogram presented a higher predictive accuracy than those of the SNP classifier or clinical factors alone. CONCLUSION: SNPs are significantly associated with kidney stone recurrence and should add prognostic value to the traditional clinical risk factors used to assess the kidney stone recurrence. A nomogram using clinical and genetic variables to predict kidney stone recurrence has revealed its potential in the future as an assessment tool during the follow-up of kidney stone patients. |
format | Online Article Text |
id | pubmed-10616432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-106164322023-11-01 Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study Zhu, Wei Zhang, Xin Zhou, Zhen Sun, Yin Zhang, Guangyuan Duan, Xiaolu Huang, Zhicong Ai, Guoyao Liu, Yang Zhao, Zhijian Zhong, Wen Zeng, Guohua Clin Kidney J Original Article BACKGROUND: Genetic variations are linked to kidney stone formation. However, the association of single nucleotide polymorphism (SNPs) and stone recurrence has not been well studied. This study aims to identify genetic variants associated with kidney stone recurrences and to construct a predictive nomogram model using SNPs and clinical features to predict the recurrence risk of kidney stones. METHODS: We genotyped 49 SNPs in 1001 patients who received surgical stone removal between Jan 1 and Dec 31 of 2012. All patients were confirmed stone-free by CT scan and then received follow-up at least 5 years. SNP associations with stone recurrence were analyzed by Cox proportion hazard model. A predictive nomogram model using SNPs and clinical features to predict the recurrence risk of kidney stones was developed by use of LASSO Cox regression. RESULTS: The recurrence rate at 3, 5, 7 years were 46.8%, 71.2%, and 78.4%, respectively. 5 SNPs were identified that had association with kidney stone recurrence risk. We used computer-generated random numbers to assign 500 of these patients to the training cohort and 501 patients to the validation cohort. A nomogram that combined the 14-SNPs-based classifier with the clinical risk factors was constructed. The areas under the curve (AUCs) at 3, 5 and 7 years of this nomogram was 0.645, 0.723, and 0.75 in training cohort, and was 0.631, 0.708, and 0.727 in validation cohort, respectively. Results show that the nomogram presented a higher predictive accuracy than those of the SNP classifier or clinical factors alone. CONCLUSION: SNPs are significantly associated with kidney stone recurrence and should add prognostic value to the traditional clinical risk factors used to assess the kidney stone recurrence. A nomogram using clinical and genetic variables to predict kidney stone recurrence has revealed its potential in the future as an assessment tool during the follow-up of kidney stone patients. Oxford University Press 2023-05-25 /pmc/articles/PMC10616432/ /pubmed/37915892 http://dx.doi.org/10.1093/ckj/sfad119 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the ERA. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Zhu, Wei Zhang, Xin Zhou, Zhen Sun, Yin Zhang, Guangyuan Duan, Xiaolu Huang, Zhicong Ai, Guoyao Liu, Yang Zhao, Zhijian Zhong, Wen Zeng, Guohua Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title | Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title_full | Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title_fullStr | Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title_full_unstemmed | Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title_short | Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
title_sort | predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616432/ https://www.ncbi.nlm.nih.gov/pubmed/37915892 http://dx.doi.org/10.1093/ckj/sfad119 |
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