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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...

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Autores principales: Zhu, Wei, Zhang, Xin, Zhou, Zhen, Sun, Yin, Zhang, Guangyuan, Duan, Xiaolu, Huang, Zhicong, Ai, Guoyao, Liu, Yang, Zhao, Zhijian, Zhong, Wen, Zeng, Guohua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
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.
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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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