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

BACKGROUND: 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. METHODS: Based on the GSE736...

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Autores principales: Hong, Sen-Yuan, Xia, Qi-Dong, Xu, Jin-Zhou, Liu, Chen-Qian, Sun, Jian-Xuan, Xun, Yang, Wang, Shao-Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751247/
https://www.ncbi.nlm.nih.gov/pubmed/35016690
http://dx.doi.org/10.1186/s12920-022-01157-4
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author Hong, Sen-Yuan
Xia, Qi-Dong
Xu, Jin-Zhou
Liu, Chen-Qian
Sun, Jian-Xuan
Xun, Yang
Wang, Shao-Gang
author_facet Hong, Sen-Yuan
Xia, Qi-Dong
Xu, Jin-Zhou
Liu, Chen-Qian
Sun, Jian-Xuan
Xun, Yang
Wang, Shao-Gang
author_sort Hong, Sen-Yuan
collection PubMed
description BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01157-4.
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spelling pubmed-87512472022-01-11 Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis Hong, Sen-Yuan Xia, Qi-Dong Xu, Jin-Zhou Liu, Chen-Qian Sun, Jian-Xuan Xun, Yang Wang, Shao-Gang BMC Med Genomics Research BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-022-01157-4. BioMed Central 2022-01-11 /pmc/articles/PMC8751247/ /pubmed/35016690 http://dx.doi.org/10.1186/s12920-022-01157-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hong, Sen-Yuan
Xia, Qi-Dong
Xu, Jin-Zhou
Liu, Chen-Qian
Sun, Jian-Xuan
Xun, Yang
Wang, Shao-Gang
Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title_full Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title_fullStr Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title_full_unstemmed Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title_short Identification of the pivotal role of SPP1 in kidney stone disease based on multiple bioinformatics analysis
title_sort identification of the pivotal role of spp1 in kidney stone disease based on multiple bioinformatics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751247/
https://www.ncbi.nlm.nih.gov/pubmed/35016690
http://dx.doi.org/10.1186/s12920-022-01157-4
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