Hiremath Shridhar, Ganesh Rajesh N, Viswanathan Pragasam
Renal Research Laboratory, Pearl Research Park, School of Bio Sciences and Technology, Vellore Institute of Technology, #412, Vellore, 632014, Tamil Nadu, India.
Department of Pathology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Urolithiasis. 2025 Apr 11;53(1):70. doi: 10.1007/s00240-025-01744-x.
Obesity is a primary risk factor associated with kidney stones (KS), with evidence suggesting that increasing BMI, obesity, and metabolic syndrome over the past three decades correlate with an elevated risk of hyperoxaluria. However, the pathogenic mechanisms associated between obesity and kidney stones at the transcriptional level remain poorly understood. Thus, we aim to explore the hub genes related to obesity-associated hyperoxaluria (OAH) to improve the understanding of its underlying pathophysiology. To understand the gap in the underlying mechanism, we performed a comprehensive weighted gene co-expression network analysis (WGCNA) on two microarray datasets. Further, differently expressed genes (DEGs) of the kidney tissue dataset and significant key modules identified through WGCNA were analyzed to pinpoint shared biomarkers and biological pathways implicated in OAH. Subsequently, hub genes were identified by constructing Protein-protein interaction (PPI) networks. Furthermore, an in vivo animal model mimicking OAH was employed to validate the hub genes through quantitative PCR (qPCR) and histopathological evaluations. Four key modules associated with KS and obesity were identified using WGCNA. The DEGs analysis revealed 346 upregulated and 19 downregulated genes. Functional enrichment via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, combined with PPI network insights, highlighted seven potential genes shared between KS and obesity. Further, in vivo studies demonstrated gut inflammation and kidney stone formation, as confirmed by histopathological evidence. The validation through qPCR has identified five hub genes-IL-6, TLR-4, CD44, SPP-1, and CCL-2-as key contributors to OAH pathophysiology. These findings, which provide new insights into the molecular mechanisms driving OAH, underscore the need for further studies with larger sample sizes to corroborate these findings and expand on their implications.
肥胖是与肾结石（KS）相关的主要风险因素，有证据表明，在过去三十年中，体重指数（BMI）增加、肥胖和代谢综合征与高草酸尿症风险升高相关。然而，肥胖与肾结石在转录水平上的致病机制仍知之甚少。因此，我们旨在探索与肥胖相关性高草酸尿症（OAH）相关的枢纽基因，以增进对其潜在病理生理学的理解。为了解潜在机制中的差距，我们对两个微阵列数据集进行了全面的加权基因共表达网络分析（WGCNA）。此外，对肾组织数据集的差异表达基因（DEGs）以及通过WGCNA鉴定出的重要关键模块进行分析，以确定与OAH相关的共同生物标志物和生物途径。随后，通过构建蛋白质-蛋白质相互作用（PPI）网络来鉴定枢纽基因。此外，采用模拟OAH的体内动物模型，通过定量PCR（qPCR）和组织病理学评估来验证枢纽基因。使用WGCNA鉴定出与KS和肥胖相关的四个关键模块。DEGs分析显示有346个基因上调和19个基因下调。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路分析进行功能富集，并结合PPI网络分析结果，突出显示了KS和肥胖之间共有的七个潜在基因。此外，体内研究证实了肠道炎症和肾结石形成，组织病理学证据也支持这一点。通过qPCR验证已确定五个枢纽基因——白细胞介素-6（IL-6）、Toll样受体4（TLR-4）、CD44、分泌性磷蛋白1（SPP-1）和趋化因子配体2（CCL-2）——是OAH病理生理学的关键因素。这些发现为驱动OAH的分子机制提供了新见解，强调需要进行更大样本量的进一步研究来证实这些发现并扩展其意义。
