Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis

• Published in: BMC medical genomics Vol. 15; no. 1; pp. 7 - 13
• Main Authors: Hong, Sen-Yuan, Xia, Qi-Dong, Xu, Jin-Zhou, Liu, Chen-Qian, Sun, Jian-Xuan, Xun, Yang, Wang, Shao-Gang
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 11.01.2022; BioMed Central; BMC
• Subjects: Aldosterone; Analysis; Arachidonic acid; Bioinformatics; Calculi; Care and treatment; Cell adhesion molecules; Computational Biology; Datasets; Diagnosis; Disease; Extracellular matrix; Gene expression; Gene Expression Profiling; Gene Ontology; Gene Regulatory Networks; Genetic factors; Genomes; Hub genes; Humans; Identification; IL-1β; Infiltration; Kidney Calculi - genetics; Kidney stone disease; Kidney stones; Kidneys; Macrophages; Matrilysin; Nephrolithiasis; Osteopontin - genetics; Protein Interaction Maps - genetics; Protein-protein interactions; Proteins; Reabsorption; Risk factors; Sodium channels; Software; SPP1; Therapeutic applications; Therapeutic targets; Weighted gene co-expression network analysis; Japan; SPP1; Hub genes; Macrophages; Kidney stone disease; Weighted gene co-expression network analysis
• DOI: 10.1186/s12920-022-01157-4
• ISSN: 1755-8794

Kidney stone disease (KSD) is a multifactorial disease involving both environmental and genetic factors, whose pathogenesis remains unclear. This study aims to explore the hub genes related to stone formation that could serve as potential therapeutic targets. Based on the GSE73680 dataset with 62 samples, differentially expressed genes (DEGs) between Randall's plaque (RP) tissues and normal tissues were screened and weighted gene co-expression network analysis (WGCNA) was applied to identify key modules associated with KSD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological functions. The protein-protein interaction (PPI) network was constructed to identify hub genes. Meanwhile, CIBERSORT and ssGSEA analysis were used to estimate the infiltration level of the immune cells. The correlations between hub genes and immune infiltration levels were also investigated. Finally, the top hub gene was selected for further GSEA analysis. A total of 116 DEGs, including 73 up-regulated and 43 down-regulated genes, were screened in the dataset. The red module was identified as the key module correlated with KSD. 53 genes were obtained for functional enrichment analysis by taking the intersection of DEGs and genes in the red module. GO analysis showed that these genes were mainly involved in extracellular matrix organization (ECM) and extracellular structure organization, and others. KEGG analysis revealed that the pathways of aldosterone-regulated sodium reabsorption, cell adhesion molecules, arachidonic acid (AA) metabolism, and ECM-receptor interaction were enriched. Through PPI network construction, 30 hub genes were identified. CIBERSORT analysis revealed a significantly increased proportion of M0 macrophages, while ssGSEA revealed no significant differences. Among these hub genes, SPP1, LCN2, MMP7, MUC1, SCNN1A, CLU, SLP1, LAMC2, and CYSLTR2 were positively correlated with macrophages infiltration. GSEA analysis found that positive regulation of JNK activity was enriched in RP tissues with high SPP1 expression, while negative regulation of IL-1β production was enriched in the low-SPP1 subgroup. There are 30 hub genes associated with KSD, among which SPP1 is the top hub gene with the most extensive links with other hub genes. SPP1 might play a pivotal role in the pathogenesis of KSD, which is expected to become a potential therapeutic target, while its interaction with macrophages in KSD needs further investigation.