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

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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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Data availability

The datasets presented in the current study can be found in online repositories. The experimental data are available from the corresponding author upon reasonable request.

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Acknowledgements

We acknowledge the GEO database and Nephroseq database contributors for sharing the meaningful data to the general public.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No: 81860161), the science and technology fund projects of Guizhou health committee [gzwjkj2020-1–003], the funding for provincial key medical discipline construction project of Health Commission of Guizhou Province from 2023 to 2024, and Guizhou Provincial Science and Technology Department Project (Grant No: qian ke he jichu-ZK[2022]yiban 448).

Author information

Authors and Affiliations

  1. Department of Endocrinology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China

    Yuanshuo Fan, Juan He, Lixin Shi, Miao Zhang & Na Han

  2. Department of Nephrology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China

    Ye Chen

  3. Department of Pathology, Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China

    Lifen Xu

  4. Guizhou Provincial People’s Hospital, Guiyang, 550002, China

    Yuecheng Jiang

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  1. Yuanshuo Fan
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Contributions

JH designed the study. YF performed the bioinformatics, experiment, data gathering, and draft writing. JH executed the data processing and statistical analysis. LS revised the manuscript and executed supervision throughout the process. MZ gave advice on the data analysis. LX made suggestions on sample selection. YC, NH and YJ coordinated the experiment and data gathering. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Juan He or Lixin Shi.

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Conflict of interest

The authors declare no conflict of interest.

Ethical approval

The study involving human participants was performed in accordance with the 1964 Helsinki Declaration and its later amendments, and approved by the Ethics Committee of the Affiliated Hospital of Guizhou Medical University (approval No. 2023-328).

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The patients/participants provided their written informed consent to participate in this study.

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Fan, Y., He, J., Shi, L. et al. Identification of potential key lipid metabolism-related genes involved in tubular injury in diabetic kidney disease by bioinformatics analysis. Acta Diabetol (2024). https://doi.org/10.1007/s00592-024-02278-1

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