Identifying potential biomarkers for the diagnosis and treatment of IgA nephropathy based on bioinformatics analysis

Abstract

Background: IgA nephropathy (IgAN) has become the leading cause of end-stage renal disease in young adults. Nevertheless, the current diagnosis exclusively relies on invasive renal biopsy, and specific treatment is deficient. Thus, our study aims to identify potential crucial genes, thereby providing novel biomarkers for the diagnosis and therapy of IgAN.

Methods: Three microarray datasets were downloaded from GEO official website. Differentially expressed genes (DEGs) were identified by limma package. GO and KEGG analysis were conducted. Tissue/organ-specific DEGs were distinguished via BioGPS. GSEA was utilized to elucidate the predominant enrichment pathways. The PPI network of DEGs was established, and hub genes were mined through Cytoscape. The CTD database was employed to determine the association between hub genes and IgAN. Infiltrating immune cells and their relationship to hub genes were evaluated based on CIBERSORT. Furthermore, the diagnostic effectiveness of hub markers was subsequently predicted using the ROC curves. The CMap database was applied to investigate potential therapeutic drugs. The expression level and diagnostic accuracy of TYROBP was validated in the cell model of IgAN and different renal pathologies.

Results: A total of 113 DEGs were screened, which were mostly enriched in peptidase regulator activity, regulation of cytokine production, and collagen-containing extracellular matrix. Among these DEGs, 67 genes manifested pronounced tissue and organ specificity. GSEA analysis revealed that the most significant enriched gene sets were involved in proteasome pathway. Ten hub genes (KNG1, FN1, ALB, PLG, IGF1, EGF, HRG, TYROBP, CSF1R, and ITGB2) were recognized. CTD showed a close connection between ALB, IGF, FN1 and IgAN. Immune infiltration analysis elucidated that IGF1, EGF, HRG, FN1, ITGB2, and TYROBP were closely associated with infiltrating immune cells. ROC curves reflected that all hub genes, especially TYROBP, exhibited a good diagnostic value for IgAN. Verteporfin, moxonidine, and procaine were the most significant three therapeutic drugs. Further exploration proved that TYROBP was not only highly expressed in IgAN, but exhibited high specificity for the diagnosis of IgAN.

Conclusions: This study may offer novel insights into the mechanisms involved in IgAN occurrence and progression and the selection of diagnostic markers and therapeutic targets for IgAN.

Keywords: Bioinformatics analysis; Biomarkers; Diagnosis; Hub genes; IgA nephropathy; Therapeutics.

Fig. 1

Flow chart to demonstrate the process of data analysis and experimental validation

Fig. 2

Identification of DEGs in renal glomerular tissue from IgAN patients compared with control samples samples. (A) Heatmap of the top 10 upregulated genes and the top 10 downregulated genes. Red rectangles indicate upregulated genes and blue rectangles indicate downregulated genes. (B) Volcano plot of identified DEGs. Red dots indicate upregulated genes and blue dots indicate downregulated genes. DEG: differentially expressed gene; IgAN: IgA nephropathy

Fig. 3

GO terms and KEGG pathways enrichment analyses of DEGs. (A-C) The bubble diagram of GO terms enrichment analyse. (A) BP terms. (B) CC terms. (C) MF terms. The x-axis indicates the gene ratio and the y-axis indicates GO terms. Distinct point shapes indicate distinct different categories and bubble size indicates gene count. Coloring indicates -log₁₀(p value) with higher in red and lower in green. (D)The bubble plot of KEGG pathway analyse [–20]. The x‐axis represents gene ratio and the y‐axis represents KEGG pathway. Bubble size indicates gene count and color indicates –log₁₀(p value) with higher in red and lower in green

Fig. 4

GSEA analysis demonstrating most enriched gene sets between the healthy and IgAN group. (A) The most significant enriched gene set was proteasome pathway (ES = 0.666, NES = 1.782, p < 0.05). (B) The second significant enriched gene set was allograft rejection (ES = 0.707, NES = 1.586, p < 0.05). (C) The third significant enriched gene set was viral myocarditis (ES = 0.548, NES = 1.568, p < 0.05). (D) The fourth significant enriched gene set was graft versus host disease (ES = 0.685, NES = 1.568, p < 0.05). (E) The fifth significant enriched gene set was FCγR mediated phagocytosis (ES = 0.524, NES = 1.562, p < 0.05). (F) The sixth significant enriched gene set was natural killer cell mediated cytotoxicity. (ES = 0.543, NES = 1.534, p < 0.05). GSEA: gene set enrichment analysis; ES: enrichment score; NES: normalized enrichment score; IgAN: IgA nephropathy

Fig. 5

PPI network of DEGs, five cluster modules extracted by MCODE and identification of hub genes. (A) A network of PPI among the DEGs was established on STRING database. The highly expressed genes are illustrated by the red ellipses and lowly expressed genes by the green diamonds. Nodes represent genes, while edges represent protein-protein interaction. (B) Cluster 1 (MCODE score = 7). (C) Cluster 2 (MCODE score = 6.667). (D) Cluster 3 (MCODE score = 3). (E) Cluster 4 (MCODE score = 3). (F) Cluster 5 (MCODE score = 3). (G) Ten crucial genes were screened through MCC algorithm in Cytoscape. The higher the score, the deeper the color. (H) The GO terms enrichment analysis of the ten identified hub genes. (I) KEGG pathways analysis of identified ten hub genes. DEG: differentially expressed gene; PPI: protein-protein interaction

Fig. 6

Recognization of potential crucial genes related to IgAN by CTD database

Fig. 7

The immune landscape in IgAN and normal controls. (A) Principal components analyses (PCA) performed on all samples. (B) The difference in infiltrating immune cells between IgAN and the normal group. The IgAN group was illustrated in red color and the normal group was illustrated in blue color. (C) Correlation heatmap of all 22 immune cells. The size of the colored dots indicates the strength of the correlation. The red color stands for a positive correlation, while the blue color stands for a negative correlation. Darker color indicates a stronger correlation. *p < 0.05, **p < 0.01, ***p < 0.001. (D) Correlation heatmap between hub genes and immune cells infiltration. The color depth of the triangle below is positively correlated with the correlation coefficient. The red color indicates a negative correlation, while the blue color indicates a positive correlation. The color depth of the upper triangle indicates p value. *p < 0.05, **p < 0.01, ***p < 0.001

Fig. 8

mRNA expression of hub genes in the glomerulus of IgAN patients based on Nephroseqv5 platform. (A) The expression of KNG1 decreased in IgAN. (B) The expression of FN1 elevated in IgAN. (C) The expression of ALB downregulated in IgAN. (D) The expression of PLG reduced in IgAN. (E) The expression of IGF1 decreased in IgAN. (F) The expression of EGF descended in IgAN. (G) The expression of HRG declined in IgAN. (H) The expression of TYROBP upregulated in IgAN. (I) The expression of CSF1R enhanced in IgAN. (J) The expression of ITGB2 increased in IgAN. p < 0.05 was considered statistically significant. * p < 0.05, **p < 0.01, ***p < 0.001. IgAN: IgA nephropathy; mRNA: messenger RNA

Fig. 9

Diagnostic accuracy of hub genes. ROC: receiver operating characteristic; AUC: area under the ROC curve

Fig. 10

Ten most significant small molecules as potential drugs for IgAN treatment targetting ten hub genes. (A–H) Predicted chemical structure of targeted drugs. IgAN: IgA nephropathy

Fig. 11

The expression level and diagnostic significance of TYROBP were verified. (A) TYROBP protein expression was measured through western blotting. (B) Quantitative analysis indicated that the expression of TYROBP in aIgA1-stimulated HMCs was evidently up-regulated compared with the control group. (C) Immunohistochemical staining for TYROBP was conducted in different renal pathologies to evaluate its diagnostic accuracy in IgAN. Macroscopic and microscopic examination were presented. (D) Quantitative results of immunohistochemical staining revealed that TYROBP was markedly higher in IgAN than that in other renal pathologies. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. Data are representative of 3 independent experiments and are expressed as mean ± SD