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Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy

BACKGROUND: Aging and immune infiltration have essential role in the physiopathological mechanisms of diabetic nephropathy (DN), but their relationship has not been systematically elucidated. We identified aging-related characteristic genes in DN and explored their immune landscape. METHODS: Four da...

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Autores principales: Liang, Yingchao, Liang, Zhiyi, Huang, Jinxian, Jia, Mingjie, Liu, Deliang, Zhang, Pengxiang, Fang, Zebin, Hu, Xinyu, Li, Huilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316791/
https://www.ncbi.nlm.nih.gov/pubmed/37404805
http://dx.doi.org/10.3389/fmed.2023.1158166
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author Liang, Yingchao
Liang, Zhiyi
Huang, Jinxian
Jia, Mingjie
Liu, Deliang
Zhang, Pengxiang
Fang, Zebin
Hu, Xinyu
Li, Huilin
author_facet Liang, Yingchao
Liang, Zhiyi
Huang, Jinxian
Jia, Mingjie
Liu, Deliang
Zhang, Pengxiang
Fang, Zebin
Hu, Xinyu
Li, Huilin
author_sort Liang, Yingchao
collection PubMed
description BACKGROUND: Aging and immune infiltration have essential role in the physiopathological mechanisms of diabetic nephropathy (DN), but their relationship has not been systematically elucidated. We identified aging-related characteristic genes in DN and explored their immune landscape. METHODS: Four datasets from the Gene Expression Omnibus (GEO) database were screened for exploration and validation. Functional and pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Characteristic genes were obtained using a combination of Random Forest (RF) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm. We evaluated and validated the diagnostic performance of the characteristic genes using receiver operating characteristic (ROC) curve, and the expression pattern of the characteristic genes was evaluated and validated. Single-Sample Gene Set Enrichment Analysis (ssGSEA) was adopted to assess immune cell infiltration in samples. Based on the TarBase database and the JASPAR repository, potential microRNAs and transcription factors were predicted to further elucidate the molecular regulatory mechanisms of the characteristic genes. RESULTS: A total of 14 differentially expressed genes related to aging were obtained, of which 10 were up-regulated and 4 were down-regulated. Models were constructed by the RF and SVM-RFE algorithms, contracted to three signature genes: EGF-containing fibulin-like extracellular matrix (EFEMP1), Growth hormone receptor (GHR), and Vascular endothelial growth factor A (VEGFA). The three genes showed good efficacy in three tested cohorts and consistent expression patterns in the glomerular test cohorts. Most immune cells were more infiltrated in the DN samples compared to the controls, and there was a negative correlation between the characteristic genes and most immune cell infiltration. 24 microRNAs were involved in the transcriptional regulation of multiple genes simultaneously, and Endothelial transcription factor GATA-2 (GATA2) had a potential regulatory effect on both GHR and VEGFA. CONCLUSION: We identified a novel aging-related signature allowing assessment of diagnosis for DN patients, and further can be used to predict immune infiltration sensitivity.
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spelling pubmed-103167912023-07-04 Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy Liang, Yingchao Liang, Zhiyi Huang, Jinxian Jia, Mingjie Liu, Deliang Zhang, Pengxiang Fang, Zebin Hu, Xinyu Li, Huilin Front Med (Lausanne) Medicine BACKGROUND: Aging and immune infiltration have essential role in the physiopathological mechanisms of diabetic nephropathy (DN), but their relationship has not been systematically elucidated. We identified aging-related characteristic genes in DN and explored their immune landscape. METHODS: Four datasets from the Gene Expression Omnibus (GEO) database were screened for exploration and validation. Functional and pathway analysis was performed using Gene Set Enrichment Analysis (GSEA). Characteristic genes were obtained using a combination of Random Forest (RF) and Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm. We evaluated and validated the diagnostic performance of the characteristic genes using receiver operating characteristic (ROC) curve, and the expression pattern of the characteristic genes was evaluated and validated. Single-Sample Gene Set Enrichment Analysis (ssGSEA) was adopted to assess immune cell infiltration in samples. Based on the TarBase database and the JASPAR repository, potential microRNAs and transcription factors were predicted to further elucidate the molecular regulatory mechanisms of the characteristic genes. RESULTS: A total of 14 differentially expressed genes related to aging were obtained, of which 10 were up-regulated and 4 were down-regulated. Models were constructed by the RF and SVM-RFE algorithms, contracted to three signature genes: EGF-containing fibulin-like extracellular matrix (EFEMP1), Growth hormone receptor (GHR), and Vascular endothelial growth factor A (VEGFA). The three genes showed good efficacy in three tested cohorts and consistent expression patterns in the glomerular test cohorts. Most immune cells were more infiltrated in the DN samples compared to the controls, and there was a negative correlation between the characteristic genes and most immune cell infiltration. 24 microRNAs were involved in the transcriptional regulation of multiple genes simultaneously, and Endothelial transcription factor GATA-2 (GATA2) had a potential regulatory effect on both GHR and VEGFA. CONCLUSION: We identified a novel aging-related signature allowing assessment of diagnosis for DN patients, and further can be used to predict immune infiltration sensitivity. Frontiers Media S.A. 2023-06-19 /pmc/articles/PMC10316791/ /pubmed/37404805 http://dx.doi.org/10.3389/fmed.2023.1158166 Text en Copyright © 2023 Liang, Liang, Huang, Jia, Liu, Zhang, Fang, Hu 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 Medicine
Liang, Yingchao
Liang, Zhiyi
Huang, Jinxian
Jia, Mingjie
Liu, Deliang
Zhang, Pengxiang
Fang, Zebin
Hu, Xinyu
Li, Huilin
Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title_full Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title_fullStr Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title_full_unstemmed Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title_short Identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
title_sort identification and validation of aging-related gene signatures and their immune landscape in diabetic nephropathy
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10316791/
https://www.ncbi.nlm.nih.gov/pubmed/37404805
http://dx.doi.org/10.3389/fmed.2023.1158166
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