Predictive value of single-nucleotide polymorphism signature for nephrolithiasis recurrence: a 5-year prospective study

Author:

Zhu Wei1,Zhang Xin1,Zhou Zhen1,Sun Yin12,Zhang Guangyuan3,Duan Xiaolu1,Huang Zhicong1,Ai Guoyao1,Liu Yang1,Zhao Zhijian1,Zhong Wen1,Zeng Guohua1

Affiliation:

1. Guangdong Key Laboratory of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University , Guangzhou, Guangdong , China

2. Department of Radiation Oncology, University of Rochester Medical Center , Rochester, NY , USA

3. Department of Urology, Zhongda Hospital Southeast University , Nanjing, Jiangsu , China

Abstract

ABSTRACT 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.

Funder

National Natural Science Foundation of China

Guangzhou Science, Technology and Innovation Commission

National Key Research and Development Program of China

Publisher

Oxford University Press (OUP)

Subject

Transplantation,Nephrology

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