Insight into obesity associated hyperoxaluria: identifying the shared biomarkers and pathways in kidney stones and obesity by integrative bioinformatic and in vivo studies.

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.