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Acta Diabetologica

01-05-2024 | Original Article

Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis

Authors: Yuanshuo Fan, Juan He, Lixin Shi, Miao Zhang, Ye Chen, Lifen Xu, Na Han, Yuecheng Jiang

Published in: Acta Diabetologica

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Abstract

Aims

Accumulating evidences indicate that abnormalities in tubular lipid metabolism play a crucial role in the development of diabetic kidney disease (DKD). We aim to identify novel lipid metabolism-related genes associated with tubular injury in DKD by utilizing bioinformatics approaches.

Methods

Differentially expressed genes (DEGs) between control and DKD tubular tissue samples were screened from the Gene Expression Omnibus (GEO) database, and then were intersected with lipid metabolism-related genes. Hub genes were further determined by combined weighted gene correlation network analysis (WGCNA) and protein–protein interaction (PPI) network. We performed enrichment analysis, immune analysis, clustering analysis, and constructed networks between hub genes and miRNAs, transcription factors and small molecule drugs. Receiver operating characteristic (ROC) curves were employed to evaluate the diagnostic efficacy of hub genes. We validated the relationships between hub genes and DKD with external datasets and our own clinical samples.

Results

There were 5 of 37 lipid metabolism-related DEGs identified as hub genes. Enrichment analysis demonstrated that lipid metabolism-related DEGs were enriched in pathways such as peroxisome proliferator-activated receptors (PPAR) signaling and pyruvate metabolism. Hub genes had potential regulatory relationships with a variety of miRNAs, transcription factors and small molecule drugs, and had high diagnostic efficacy. Immune infiltration analysis revealed that 13 immune cells were altered in DKD, and hub genes exhibited significant correlations with a variety of immune cells. Through clustering analysis, DKD patients could be classified into 3 immune subtypes and 2 lipid metabolism subtypes, respectively. The tubular expression of hub genes in DKD was further verified by other external datasets, and immunohistochemistry (IHC) staining showed that except ACACB, the other 4 hub genes (LPL, AHR, ME1 and ALOX5) exhibited the same results as the bioinformatics analysis.

Conclusion

Our study identified several key lipid metabolism-related genes (LPL, AHR, ME1 and ALOX5) that might be involved in tubular injury in DKD, which provide new insights and perspectives for exploring the pathogenesis and potential therapeutic targets of DKD.
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Metadata
Title
Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis
Authors
Yuanshuo Fan
Juan He
Lixin Shi
Miao Zhang
Ye Chen
Lifen Xu
Na Han
Yuecheng Jiang
Publication date
01-05-2024
Publisher
Springer Milan
Published in
Acta Diabetologica
Print ISSN: 0940-5429
Electronic ISSN: 1432-5233
DOI
https://doi.org/10.1007/s00592-024-02278-1
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Keynote webinar | Spotlight on medication adherence

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