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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.
Afiliação
  • Liang Y; Graduate School of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
  • Liang Z; The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
  • Huang J; Graduate School of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
  • Jia M; Guangdong Provincial Hospital of Integrated Traditional Chinese and Western Medicine Affiliated to Guangzhou University of Chinese Medicine, Foshan, China.
  • Liu D; Graduate School of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
  • Zhang P; The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
  • Fang Z; Graduate School of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
  • Hu X; The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
  • Li H; Department of Endocrinology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China.
Front Med (Lausanne) ; 10: 1158166, 2023.
Article em En | MEDLINE | ID: mdl-37404805
ABSTRACT

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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article