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Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network

Background: Randall’s plaque is regarded as the precursor lesion of lithiasis. However, traditional bioinformatic analysis is limited and ignores the relationship with immune response. To investigate the underlying calculi formation mechanism, we introduced innovative algorithms to expand our unders...

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Autores principales: Yu, Lingyun, Li, Gefei, Jin, Shiyao, Su, Jiahong, Li, Shoulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931196/
https://www.ncbi.nlm.nih.gov/pubmed/36816033
http://dx.doi.org/10.3389/fgene.2023.1048919
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author Yu, Lingyun
Li, Gefei
Jin, Shiyao
Su, Jiahong
Li, Shoulin
author_facet Yu, Lingyun
Li, Gefei
Jin, Shiyao
Su, Jiahong
Li, Shoulin
author_sort Yu, Lingyun
collection PubMed
description Background: Randall’s plaque is regarded as the precursor lesion of lithiasis. However, traditional bioinformatic analysis is limited and ignores the relationship with immune response. To investigate the underlying calculi formation mechanism, we introduced innovative algorithms to expand our understanding of kidney stone disease. Methods: We downloaded the GSE73680 series matrix from the Gene Expression Omnibus (GEO) related to CaOx formation and excluded one patient, GSE116860. In the RStudio (R version 4.1.1) platform, the differentially expressed genes (DEGs) were identified with the limma package for GO/KEGG/GSEA analysis in the clusterProfiler package. Furthermore, high-correlated gene co-expression modules were confirmed by the WGCNA package to establish a protein–protein interaction (PPI) network. Finally, the CaOx samples were processed by the CIBERSORT algorithm to anchor the key immune cells group and verified in the validation series matrix GSE117518. Results: The study identified 840 upregulated and 1065 downregulated genes. The GO/KEGG results revealed fiber-related or adhesion-related terms and several pathways in addition to various diseases identified from the DO analysis. Moreover, WGCNA selected highly correlated modules to construct a PPI network. Finally, 16 types of immune cells are thought to participate in urolithiasis pathology and are related to hub genes in the PPI network that are proven significant in the validation series matrix GSE117518. Conclusion: Randall’s plaque may relate to genes DCN, LUM, and P4HA2 and M2 macrophages and resting mast immune cells. These findings could serve as potential biomarkers and provide new research directions.
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spelling pubmed-99311962023-02-16 Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network Yu, Lingyun Li, Gefei Jin, Shiyao Su, Jiahong Li, Shoulin Front Genet Genetics Background: Randall’s plaque is regarded as the precursor lesion of lithiasis. However, traditional bioinformatic analysis is limited and ignores the relationship with immune response. To investigate the underlying calculi formation mechanism, we introduced innovative algorithms to expand our understanding of kidney stone disease. Methods: We downloaded the GSE73680 series matrix from the Gene Expression Omnibus (GEO) related to CaOx formation and excluded one patient, GSE116860. In the RStudio (R version 4.1.1) platform, the differentially expressed genes (DEGs) were identified with the limma package for GO/KEGG/GSEA analysis in the clusterProfiler package. Furthermore, high-correlated gene co-expression modules were confirmed by the WGCNA package to establish a protein–protein interaction (PPI) network. Finally, the CaOx samples were processed by the CIBERSORT algorithm to anchor the key immune cells group and verified in the validation series matrix GSE117518. Results: The study identified 840 upregulated and 1065 downregulated genes. The GO/KEGG results revealed fiber-related or adhesion-related terms and several pathways in addition to various diseases identified from the DO analysis. Moreover, WGCNA selected highly correlated modules to construct a PPI network. Finally, 16 types of immune cells are thought to participate in urolithiasis pathology and are related to hub genes in the PPI network that are proven significant in the validation series matrix GSE117518. Conclusion: Randall’s plaque may relate to genes DCN, LUM, and P4HA2 and M2 macrophages and resting mast immune cells. These findings could serve as potential biomarkers and provide new research directions. Frontiers Media S.A. 2023-02-01 /pmc/articles/PMC9931196/ /pubmed/36816033 http://dx.doi.org/10.3389/fgene.2023.1048919 Text en Copyright © 2023 Yu, Li, Jin, Su and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Yu, Lingyun
Li, Gefei
Jin, Shiyao
Su, Jiahong
Li, Shoulin
Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title_full Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title_fullStr Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title_full_unstemmed Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title_short Identification of the core genes in Randall’s plaque of kidney stone and immune infiltration with WGCNA network
title_sort identification of the core genes in randall’s plaque of kidney stone and immune infiltration with wgcna network
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931196/
https://www.ncbi.nlm.nih.gov/pubmed/36816033
http://dx.doi.org/10.3389/fgene.2023.1048919
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