Abstract Background IgA nephropathy (IgAN) is one of the most common forms of chronic glomerulonephritis, but the aetiology and pathogenesis remain unclear. Cuproptosis is a newly identified form of cell death that plays an important role in many diseases. Researchers have not clearly determined whether the expression of cuproptosis-related genes (CRGs) is involved in the pathogenesis of IgAN. Methods The [29]GSE93798, [30]GSE50469 and [31]GSE37460 datasets containing microarray data from patients with IgAN (63) and healthy controls (31) were downloaded from the GEO database. Immune cells and immune-related functions were analysed in patients with IgAN and controls, and genes were identified that may be related to cuproptosis. A logistic regression model was established according to the results, and then GO and KEGG enrichment analyses were performed. Finally, possible drugs were selected using the DSigDB database. Results The subjects in the different groups showed significantly different fractions of immune cells and immune-related functions, and 11 genes related to cuproptosis may be involved in these processes. Based on these 11 genes, the ROC curve was plotted, and the AUC value was calculated (0.898, 95% CI: 0.839–0.958). The result revealed good predictability. Then, genes with P < 0.05 (lipoyltransferase 1, LIPT1) were selected to plot an ROC curve, and the AUC value was calculated (0.729, 95% CI: 0.636–0.821). Enrichment analyses showed that the TCA cycle and multiple metabolic pathways may also be involved in the occurrence of IgAN. Finally, 293 potential drugs that may be used to treat IgAN were identified based on these genes. Conclusion In this study, we identified some novel CRGs that may be involved in IgAN, among which LIPT1 was significantly differentially expressed. It may predict the risk of IgAN and provides a possible target for the treatment of IgAN. Further experimental studies are needed to explore how these CRGs mediate the occurrence and development of IgAN. Keywords: IgA nephropathy, Cuproptosis, Immune activity, Bioinformatics analysis Introduction Immunoglobulin A nephropathy (IgAN) was initially described in 1968 by a French pathologist, Dr. Jean Berger, and his colleague, Dr. Nicole Hinglais (an electron microscopist), as a kidney disease with glomerular “intercapillary deposits of IgA-IgG” [[32]1]. IgAN is characterized by dominant IgA glomerular deposits in renal biopsy that are usually accompanied by local cellular proliferation and matrix expansion [[33]2]. It is also one of most common types of primary glomerulonephritis worldwide and remains a leading cause of chronic kidney disease and renal failure [[34]3, [35]4]. An epidemiological survey of the global prevalence of IgAN in 2018 showed that the incidence of IgAN in Asian countries was significantly higher than that in Europe, the Americas and Africa. Among Asian countries, and the incidence rates in China and Japan were significantly higher than those in South Korea, India and other countries [[36]5]. The clinical markers of the severity of kidney disease, including proteinuria, hypertension and impaired renal function, are nonspecific and only present when severe kidney injury occurs. Therefore, studies exploring the new possible pathogenic mechanisms of IgAN and identifying potential therapeutic targets are very important. Copper (Cu) is an essential element required for the maintenance of the precise activities of eukaryotes, similar to iron (Fe) and zinc (Zn). Cu plays an important role in our body; on the one hand, Cu is a vital component of many mitochondrial enzymes, such as cytochrome c oxidase (COX) and superoxide dismutase (SOD1) [[37]6, [38]7]. On the other hand, mitochondria are central for Cu metabolism [[39]8]. The term “cuproptosis” was proposed by Tsvetkov et al [[40]9]. They defined it as a Cu-elesclomol-triggered, ferredoxin-dependent form of cell death distinct from other modalities of cell death, such as apoptosis, ferroptosis, necroptosis, and pyroptosis [[41]9, [42]10]. Recently, cuproptosis has been recognized as a possibly new mechanism in some diseases [[43]9]. However, researchers have not determined whether cuproptosis is involved in the development of IgAN. At present no studies have examined whether cuproptosis is involved in the pathogenesis of IgAN. In this study, we screened the pyroptosis-related genes (CRGs) that may be involved in IgAN according to the data in three GEO databases, established models and screened some possible therapeutic drugs. Materials and methods Acquisition and preprocessing of public data Three microarray datasets of IgAN ([44]GSE93798, [45]GSE50469 and [46]GSE37460) were downloaded from the GEO database ([47]http://www.ncbi.nlm.nih.gov/geo/) using “IgAN” as the search term. Ninety-four samples were obtained from glomerular tissue, including 63 from patients with IgAN and 31 from healthy people. Since cuproptosis is a new concept and no relevant database is available, cuproptosis-related genes were selected according to the article by Peter Tsvetkov et al. [[48]9]. Thirteen CRGs were identified. The immune matrix was downloaded from GESA ([49]http://www.gsea-msigdb.org/) and divided into immune cell- and immune-related functions. Data processing and construction of the heatmap The “limma”, “ggpubr” and “reshape2” R packages were used to combine IgAN, cuproptosis and immune matrix. The “Pheatmap” R package was used to plot an immune heatmap. The “corrplot” R package was used to analyse and plot the correlation of the immune matrix. Differences in immune activity between the IgAN and control groups The “ggpubr” and “reshape2” R packages were used to determine the differences in immune cells and functions between the IgAN and control groups, and P < 0.05 was considered statistically significant. Selection of CRGs associated with IgAN The “psych” and “ggcorrplot” R packages were installed to analyse the correlation between the cuproptosis-related gene matrix and IgAN immune matrix, and a heatmap was drawn. Model building and analysis According to the mean value of gene expression, the data in the matrix were divided into low expression and high expression. The “rms” R package was used to build a logit model and establish a nomogram. The c-index was calculated, and the ROC curve was plotted using the “ROCR” R package. The nonadherence nomogram was subjected to bootstrapping validation (50 bootstrap resamples) to calculate a relatively corrected C-index. Functional enrichment analyses and screening of possible drugs Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using R software. Possible drugs for the treatment of IgAN were analysed using the DSigDB database ([50]https://maayanlab.cloud/Enrichr/). Statistical analysis All statistical analyses and preparation of figures were implemented using R 4.2.0 (R Foundation, Vienna, Austria). A 95% confidence interval (CI) was evaluated by performing univariable and multivariate logistic regression analyses. If not specified above, p < 0.05 was considered statistically significant. Results The immune activity of patients with IgAN has changed significantly As described above, we selected 13 CRGs for study (Fig. [51]1A). We analysed the data to explore the changes in immune cells and immune-related functions of CRGs in patients with IgAN. Significant changes in immune activity occurred in patients with IgAN, and many immune cells and immune-related functions were changed (Fig. [52]1B). In addition, we plotted correlation heatmaps to understand the correlations between immune cells and immune-related functions (Fig. [53]1C, D). The results showed correlations between them, and the numbers in the heatmap represent the correlation coefficient. Fig. 1. [54]Fig. 1 [55]Open in a new tab CRGs and immune heatmap. A CRGs selected from references. B Heatmap