He Ziqi, Song Chao, Wang Zhong, Dong Caitao, Jiang Qinhong, Yu Xi, Shan Guang
Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China.
Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
Front Genet. 2025 Mar 18;16:1542840. doi: 10.3389/fgene.2025.1542840. eCollection 2025.
One of the most prevalent urinary illnesses is kidney stone formation, often known as nephrolithiasis. The precise processes of kidney stone remain poorly known after substantial investigation. In order to successfully prevent and cure stone formation and recurrence, additional research into the pathophysiology of stone formation is of paramount importance. Ferroptosis is linked to a variety of renal diseases and is a critical factor in the death of cells. However, little is known about how ferroptosis-related genes (FRGs) contribute to the development of kidney stones.
The Ferroptosis Database and the Gene Expression Omnibus (GEO) database provided us with information on kidney stones and FRGs, respectively (FerrDb).
Eight DE-FRGs related to kidney stones were found in total, and they were all closely related to immune response and autophagy management. Following this, among the 8 DE-FRGs, LASSO and SVM-RFE algorithms chose FZD7, STK11, SUV39H1, and LCN2 as marker genes with suitable diagnostic capabilities. These marker genes may be involved in the control of the PPAR signaling pathway, mTOR signaling system, and fatty acid production of kidney stones, according to the functional enrichment analysis that followed. Additionally, 24 drugs that target two marker genes have been found. Despite this, the ceRNA networks have gained that the regulatory relationship between marker genes is rather complex. Additionally, the findings of the CIBERSORT investigation indicated that FZD7 and SUV39H1 may be linked to variations in the immune milieu of people who have kidney stones.
We developed a diagnostic tool and provided information on the development of kidney stones. In order to confirm its diagnostic applicability for kidney stones, more studies are needed before it may be used in clinical practice.
最常见的泌尿系统疾病之一是肾结石形成，通常称为肾石症。经过大量研究，肾结石的确切形成过程仍然知之甚少。为了成功预防和治疗结石形成及复发，对结石形成的病理生理学进行更多研究至关重要。铁死亡与多种肾脏疾病相关，是细胞死亡的关键因素。然而，关于铁死亡相关基因（FRGs）如何促成肾结石的发展，人们了解甚少。
铁死亡数据库和基因表达综合数据库（GEO）分别为我们提供了有关肾结石和FRGs的信息（FerrDb）。
总共发现了8个与肾结石相关的差异表达铁死亡相关基因（DE-FRGs），它们都与免疫反应和自噬调控密切相关。在此之后，在这8个DE-FRGs中，LASSO和支持向量机递归特征消除（SVM-RFE）算法选择FZD7、STK11、SUV39H1和LCN2作为具有合适诊断能力的标记基因。随后的功能富集分析表明，这些标记基因可能参与肾结石的过氧化物酶体增殖物激活受体（PPAR）信号通路、雷帕霉素靶蛋白（mTOR）信号系统和脂肪酸生成的调控。此外，还发现了24种靶向两个标记基因的药物。尽管如此，竞争性内源RNA（ceRNA）网络显示标记基因之间的调控关系相当复杂。此外，CIBERSORT研究结果表明，FZD7和SUV39H1可能与肾结石患者免疫微环境的变化有关。
我们开发了一种诊断工具，并提供了有关肾结石发展的信息。为了确认其对肾结石的诊断适用性，在将其应用于临床实践之前还需要更多研究。
