Hsi Ryan S, Zhang Siwei, Triozzi Jefferson L, Hung Adriana M, Xu Yaomin, Bejan Cosmin A
Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
Eur Urol Open Sci. 2024 Jul 24;67:38-44. doi: 10.1016/j.euros.2024.07.109. eCollection 2024 Sep.
Previous studies have reported a strong genetic contribution to kidney stone risk. This study aims to identify genetic associations of kidney stone disease within a large-scale electronic health record system.
We performed genome-wide association studies (GWASs) for nephrolithiasis from genotyped samples of 5571 cases and 83 692 controls. This analysis included a primary GWAS focused on nephrolithiasis and subsequent subgroup GWASs stratified by stone composition types. For significant risk variants, we performed association analyses with stone composition and first-time 24-h urine parameters. To assess disease severity, we investigated the associations with age at first stone diagnosis, age at first stone-related procedure, and time between first and second stone-related procedures.
The primary GWAS analysis identified ten significant loci, all located on chromosome 16 within coding regions of the gene. The strongest signal was rs28544423 (odds ratio 1.17, 95% confidence interval 1.11-1.23, = 2.7 × 10). In subgroup GWASs stratified by six kidney stone composition subtypes, 19 significant loci were identified including two loci in coding regions (brushite; , rs79970906 and rs4725104). The single nucleotide polymorphism rs28544423 was associated with differences in 24-h excretion of urinary analytes, and the minor allele was positively associated with calcium oxalate dihydrate stone composition < 0.05). No associations were found between variants and disease severity. Limitations include an omitted variable bias and a misclassification bias.
We replicated germline variants associated with kidney stone disease risk at and reported novel variants associated with stone composition Genetic variants of are associated with differences in 24-h urine parameters and stone composition, but not disease severity.
We identify genetic variants linked to kidney stone disease within an electronic health record (EHR) system. These findings suggest a role for the EHR to enable a precision-medicine approach for stone disease.
既往研究报道遗传因素对肾结石风险有很大影响。本研究旨在在大规模电子健康记录系统中确定肾结石疾病的遗传关联。
我们对5571例病例和83692例对照的基因分型样本进行了肾结石的全基因组关联研究（GWAS）。该分析包括一项针对肾结石的主要GWAS以及随后按结石成分类型分层的亚组GWAS。对于显著的风险变异，我们进行了与结石成分和首次24小时尿液参数的关联分析。为了评估疾病严重程度，我们研究了与首次结石诊断年龄、首次结石相关手术年龄以及首次和第二次结石相关手术之间时间的关联。
主要GWAS分析确定了10个显著位点，均位于16号染色体上该基因的编码区域内。最强信号为rs28544423（优势比1.17，95%置信区间1.11 - 1.23，P = 2.7×10）。在按六种肾结石成分亚型分层的亚组GWAS中，确定了19个显著位点，包括编码区域内的两个位点（透钙磷石；，rs79970906和rs4725104）。单核苷酸多态性rs28544423与尿分析物24小时排泄量的差异相关，次要等位基因与二水合草酸钙结石成分呈正相关（P < 0.05）。未发现基因变异与疾病严重程度之间存在关联。局限性包括遗漏变量偏差和错误分类偏差。
我们在[具体基因名称]复制了与肾结石疾病风险相关的种系变异，并报告了与结石成分相关的新变异。[具体基因名称]的基因变异与24小时尿液参数和结石成分的差异相关，但与疾病严重程度无关。
我们在电子健康记录（EHR）系统中确定了与肾结石疾病相关的基因变异。这些发现表明EHR在实现针对结石疾病的精准医疗方法中发挥作用。
