Cuproptosis gene characterizes the immune microenvironment of diabetic nephropathy.

BACKGROUND

The cuproptosis is an intracellular copper (Cu) accumulation triggering the aggregation of mitochondrial lipoylated proteins and destabilization of iron‑sulfur (FeS) cluster proteins, leading to cell death. This copper-triggered modality of mitochondrial cell death has been associated with cuproptosis-related signature key genes (CRGs). Our study focused on the relationship between the cuproptosis CRGs and diabetic nephropathy (DN) to understand how such immune microenvironment may influence DN.

METHODS

We downloaded and compared RNA sequencing data sets of DN glomerular tissue samples vs. normal renal tissue samples (GSE142025, GSE30528, and GSE96804) from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between DN and control samples were screened. Immune cell subtypes infiltration and immune score were figured out via different algorithms. Consensus clustering was performed by the Ward's method to determine different phenotypes of DN. CRG key genes between two phenotypes were identified via machine learning algorithm. Logistic regression analysis was applied to establish a nomogram for assessing the risk of DN.

RESULTS

In DN samples, two genes NLRP3 and CDKN2A were positively correlated to the immune score. In contrast, six genes NFE2L2, LIAS, LIPT1, DLD, DBT and DLST were negatively correlated to the immune score. Via Consensus clustering based on cuproptosis CRG key genes, the DN samples were divided into cluster C1 and cluster C2. The cluster C1 was characterized by low cuproptosis CRG genes expression, high immune cell subtypes infiltration, and high enrichment of immune-related pathways. Cluster C2 was on the contrary, the Dicarbonyl/l-xylulose reductase (DCXR) and heat-responsive protein 12 (HRSP12) genes were related to clinical traits and the immune microenvironment, negatively correlated with most immune cell subtypes. The nomogram was constructed based on DCXR and HRSP12 showing good efficiency for the DN diagnosis.

CONCLUSION

We conclude that the immune microenvironment imbalance and metabolic disorders lead to the occurrence of DN. The signature cuproptosis genes, regulating the immune microenvironment and metabolism, represented the DN disease clustering to describe the heterogeneity and characterize immune microenvironment. Both HRSP12 and DCXR key genes are related to DN disease phenotypes and immune microenvironment characteristic and may help in DN diagnosis.