Identification and characterization of two immune-related subtypes in human chronic kidney disease
Copyright © 2023. Published by Elsevier B.V..
BACKGROUND: Immune response plays a vital role in the initiation and development of chronic kidney disease (CKD). Detailed mechanisms and specific immune-related biomarkers of CKD need further clarification. We aimed to identify and characterize immune-related infiltrates that are implicated in the CKD development using a bioinformatics method.
METHODS: The expression profiles of GSE66494 dataset were acquired from the Gene Expression Omnibus (GEO) database. Patients with CKD were divided into low- vs. high-immune subtypes based on their immune score. Based on such analysis, we identified differentially expressed genes (DEGs) of low- and high-immune subtypes. The weight gene co-expression network analysis (WGCNA) was used to identify immune-associated modules between two subtypes. The gene set enriched (GSEA) and variation (GSVA) analyses were correlated with their functional types using the molecular complex detection (MCODE) method. Finally, the immune infiltration landscape between subtypes was revealed using the xCell algorithm.
RESULTS: The total number of 131 differentially expressed immune-related genes (DEIRGs) were identified between low- vs. high-immune subtypes. Out of them GSEA/GSVA results identified and enriched immune- and inflammation-related pathways. In particular, GSVA results indicated that immune-related pathways were activated in high-immune subgroups. The core DEIRG genes that were identified to be involved in CKD development included: the protein tyrosine phosphatase receptor type C (PTPRC; also known as CD45) regulating cell growth and differentiation, an early activation marker (CD69), co-receptor for T cell receptor (CD8A), and T cell co-stimulatory signal (CD28). These core DEIRD genes were further verified by the GSE96804 dataset. We also found a higher proportion of immune cells infiltrating the high-immune subgroup. Furthermore, the four core genes were positively correlated with most immune cell types.
CONCLUSION: Among 131 DEIRG genes, four genes (PTPRC, CD69, CD8A, and CD28) were identified as potential biomarkers associated with the immune cell infiltration in CKD patients, which may provide a novel insight for immunotherapy for CKD.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:82 |
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| Enthalten in: |
Transplant immunology - 82(2024) vom: 25. Feb., Seite 101983 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Fang, Xiangdong [VerfasserIn] |
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| Links: |
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| Themen: |
Bioinformatics analysis |
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| Anmerkungen: |
Date Completed 29.01.2024 Date Revised 06.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.trim.2023.101983 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM366748319 |
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| 500 | |a Date Revised 06.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023. Published by Elsevier B.V. | ||
| 520 | |a BACKGROUND: Immune response plays a vital role in the initiation and development of chronic kidney disease (CKD). Detailed mechanisms and specific immune-related biomarkers of CKD need further clarification. We aimed to identify and characterize immune-related infiltrates that are implicated in the CKD development using a bioinformatics method | ||
| 520 | |a METHODS: The expression profiles of GSE66494 dataset were acquired from the Gene Expression Omnibus (GEO) database. Patients with CKD were divided into low- vs. high-immune subtypes based on their immune score. Based on such analysis, we identified differentially expressed genes (DEGs) of low- and high-immune subtypes. The weight gene co-expression network analysis (WGCNA) was used to identify immune-associated modules between two subtypes. The gene set enriched (GSEA) and variation (GSVA) analyses were correlated with their functional types using the molecular complex detection (MCODE) method. Finally, the immune infiltration landscape between subtypes was revealed using the xCell algorithm | ||
| 520 | |a RESULTS: The total number of 131 differentially expressed immune-related genes (DEIRGs) were identified between low- vs. high-immune subtypes. Out of them GSEA/GSVA results identified and enriched immune- and inflammation-related pathways. In particular, GSVA results indicated that immune-related pathways were activated in high-immune subgroups. The core DEIRG genes that were identified to be involved in CKD development included: the protein tyrosine phosphatase receptor type C (PTPRC; also known as CD45) regulating cell growth and differentiation, an early activation marker (CD69), co-receptor for T cell receptor (CD8A), and T cell co-stimulatory signal (CD28). These core DEIRD genes were further verified by the GSE96804 dataset. We also found a higher proportion of immune cells infiltrating the high-immune subgroup. Furthermore, the four core genes were positively correlated with most immune cell types | ||
| 520 | |a CONCLUSION: Among 131 DEIRG genes, four genes (PTPRC, CD69, CD8A, and CD28) were identified as potential biomarkers associated with the immune cell infiltration in CKD patients, which may provide a novel insight for immunotherapy for CKD | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Bioinformatics analysis | |
| 650 | 4 | |a Chronic kidney disease | |
| 650 | 4 | |a Immune cell infiltration | |
| 650 | 4 | |a Renal fibrosis | |
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| 700 | 1 | |a Chen, Yanxia |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Qiu, Minzi |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Jinjing |e verfasserin |4 aut | |
| 700 | 1 | |a Ke, Ben |e verfasserin |4 aut | |
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