Bioinformatics analysis reveals novel hub gene pathways associated with IgA nephropathy

IgA nephropathy (IgAN), the most prevalent type of glomerulonephritis in humans, is characterized by mesangial cell proliferation, the expansion of the glomerular mesangial matrix. Nearly 25–30% of affected patients develop end-stage renal disease. Presently, several clinical biomarkers have been identified to be associated with IgAN progression, such as proteinuria, serum creatinine, hypertension and advanced histological involvement [1]. In 2011 [2], Suzuki et al. hypothesized that the pathogenesis of IgAN is based on four hits: first, the occurrence of an abnormal IgA1 glycosylation process leading to galactose-deficient IgA1 (Gd-IgA1); second, the formation of antiglycan antibodies against Gd-IgA1; third, the formation of nephrogenic circulating immune complexes; fourth, the deposition of these complexes in the mesangium of glomeruli, leading to renal injury with variable clinical expression. However, the exact pathogenesis is not very clear.

Many studies have also shown a genetic predisposition to IgAN [3]. Serino et al. found six significantly upregulated miRNAs, two of which modulate the O-glycosylation process of IgA1. Specifically, let-7b regulates the gene GALNT2 and miR-148 modulates the gene target C1GALT1, which has been considered an underlying biomarker to predict the probability of IgAN [4, 5]. Wang et al. found that low urinary levels of miR-29b and miR-29c are correlated with proteinuria and renal function. High levels of miR-93 were correlated with glomerular scarring. miR-200a, miR-200b, and miR-429 have also been suggested as potential biomarkers to monitor the progression of the disease at the renal level in IgAN patients [6]. However, due to the lack of large-scale studies, the limitation of animal models and current low-throughput genetic studies, the crucial genes involved in the development and effective treatment of IgAN have remained elusive.

Bioinformatics studies have been widely performed in various fields to extract potential information and reveal the underlying mechanics of various diseases. Recently, bioinformatics analysis has gradually provided insight into the molecular mechanisms of kidney disease. For example, PSMB8, as a novel hub gene, plays a significant role in the occurrence of membrane nephropathy [7]. In lupus, bioinformatics analysis revealed that CD38 and CCL2 are hub macrophage-related genes [8]. Additionally, EST1 may be a drug target for diabetic nephropathy treatment [9]. Currently, only a few bioinformatics analyses have been performed on IgAN; its critical associated genes and interactions have not been thoroughly investigated.

In the present study, two original microarray datasets were selected from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed genes (DEGs) in IgAN patients and control group, we employed the Database for Annotation, Visualization and Integration Discovery (DAVID) to identify the functions of the identified DEGs and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein–protein interaction (PPI) network was generated using the STRING database, and hub genes and the most significant module among the PPI networks were identified using cytoHubba and the Molecular Complex Detection (MCODE) plug-in.

The present study aimed to identify potential novel candidate hub genes to diagnose and treat IgAN.

Bioinformatics analysis plays an important role in disease studies, facilitating the understanding of pathogenesis by integrating data at the genome level with systematic bioinformatics methods. In the present study, 148 DEGs were identified from microarray data by reanalyzing the datasets that could distinguish between the IgAN and healthy controls. Previous studies have shown a significant association of IgAN development and prognosis with the inflammatory reaction, and activation of TGF-β signaling is closely related to fibrosis in IgAN [16, 17]. In our study, enrichment analysis revealed that the DEGs were significantly enriched in response to cAMP, cellular response to fibroblast growth factor stimulus and inflammatory response, a finding that is consistent with that in a previous study.

Infection plays an important role in the onset of IgAN, and nearly 30% of patients have a clear history of disease exacerbation after upper respiratory or gastrointestinal infections. Novak et al. reported that viruses (e.g., Epstein–Barr virus) or bacteria (e.g., Streptococcus) expressing GalNAc-containing moieties induce the development of IgG antiglycan autoantibodies, which might subsequently cross-react with glycans on IgA1, resulting in the formation of IgA1–IgG complexes [18]. This ‘molecular mimicry’ could also explain the association of macroscopic hematuria with upper respiratory tract infections. Yamamoto Y reported that the antigens of Haemophilus parainfluenzae are detected in the renal tissue of patients with IgAN [19]. In our study, KEGG analysis revealed that the DEGs were mainly enriched in pertussis and Staphylococcus aureus infection, a finding that coincides with the above studies.

Using STRING and MCODE, we selected the most important module, which comprised 15 nodes and 89 edges, including CSF1R, IL10RA, ITGB2, HCK, NCF2, C3AR1, CYBB, HCLS1, CD48, C1QA, VSIG4, LAPTM5, FCER1G, CD53 and TYROBP. Further GO analysis revealed that the BP was mainly enriched in the innate immune response, integrin-mediated signaling pathway and inflammatory response. Previous studies have shown a significant association of IgAN development and prognosis with the inflammatory reaction and innate immune response. Toll-like receptors (TLRs) are the key components of the mammalian innate immune system and mediate immune and inflammatory responses through binding PAMPs and/or DAMPs [20]. Many studies have confirmed the elevated expression of TLR4 mRNA in IgAN rats. In an in vitro coculture system of IgA and mesangial cells, TLR4 mediates MAPK activation and MCP-1 secretion, indicating that TLR4 is engaged in glomerular mesangium damage by inducing inflammatory cytokines in IgAN [21]. TLR4 is also involved in the activation of NF-κB, triggering the transcription of mRNA encoding many inflammatory mediators, such as cytokines, chemokines, and fibrinogen and contributing significantly to the effects of the innate and adaptive immune responses [22].

We further implemented the MCC method and selected 10 hub genes, all of which overlapped with the important module selected by MCODE. Hierarchical clustering of the hub genes showed that these hub genes could well distinguish the IgAN and control groups completely. We further introduced these genes into blood samples for testing, and the results showed that the genes also played a crucial role in differentiating disease from control in the blood tissue.

Hck is a member of the highly conserved Src family of cytoplasmic protein tyrosine kinases that transduce various extracellular signals. Hck has been reported to be significantly upregulated in diabetic nephropathy, IgA nephropathy, and lupus nephritis, and is a key mediator of renal fibrosis via its effects on inflammation, fibroblast cell proliferation, and regulation of TGF-β signaling [23].

LAPTM5, which is preferentially expressed in hematopoietic cells and localized to the lysosome, was initially isolated by a subtractive hybridization strategy between hematopoietic and nonhematopoietic cells. A recent study showed that LAPTM5 is a positive regulator of proinflammatory signaling pathways by facilitating NF-κB and MAPK signaling, as well as proinflammatory cytokine production in macrophages [24, 25]. CYBB is also responsive to several inflammatory cytokines such as IFN-γ, LPS, and TNF-α [26]. CD53 codes for cluster of differentiation 53, a leukocyte surface antigen. Many studies have indicated that CD53 plays a substantial role in cellular stability and the inflammatory response to adverse conditions [27]. The inflammatory response plays an important role in IgAN, and the above hub genes were all identified to be involved in the pathogenesis of IgAN.

FCER1G is a protein coding gene that interacts with other factors and participates in various nuclear pathways [28]. Specifically, FCER1G is a constitutive component of the high-affinity immunoglobulin E receptor and interleukin-3 receptor complex and is mainly involved in mediating the allergic inflammatory signaling of mast cells, selectively mediating the production of interleukin 4 by basophils, and initiating the transfer from T cells to the effector T-helper 2 subset [29]. Additionally, FCER1G is associated with the progression of clear-cell renal cell carcinoma and may improve prognosis by affecting immune-related pathways. Furthermore, FCER1G is a critical molecule in signaling pathways and is widely involved in various immune responses and cell types [30]. Until now, no study has reported the association of FCER1G with IgAN.

ITGB2 is a protein coding gene that encodes an integrin beta chain, which combines with multiple different alpha chains to form different integrin heterodimers. Integrins are integral cell-surface proteins that participate in cell adhesion as well as cell surface-mediated signaling. The encoded protein plays an important role in the immune response, and defects in this gene cause leukocyte adhesion deficiency. ITGB2 was reported to be involved in cellular adhesion and ECM remodeling in patients with renal cancer [31]. Furthermore, ITGB2 was identified to be closely associated with apoptosis in patients with Alzheimer’s disease [32]. Bioinformatics analysis in CKD patients showed that ITGB2, CTSS and CCL5 are correlated negatively with the eGFR of CKD patients [33].

In our study, FCER1G and ITGB2 were the first- and second-ranked hub genes, respectively, and BiNGO analysis confirmed that FCER1G is directly involved in the innate immune response. Further analysis uncovered that, except for IgAN, both hub genes exhibit higher expression in other primary glomerulonephritis types (FSGS, MCD, MN TMD). The latter finding indicates that these hub genes may also be associated with the pathogenesis of other primary glomerulonephritis types. Although these two genes have the highest expression in IgAN compared with other primary glomerulonephritis types, they may play an important role in IgAN but are not specific for the disease. Presently, limited research has reported the association between ITGB2 or FCER1G and IgAN. Further investigation of these two genes is warranted.

Through bioinformatics analysis, we identified hub genes involved in the pathological changes of IgAN. These genes not only can be used in tissue samples, but also play important roles in blood samples. The present study is the first to apply an integrated bioinformatics analysis to investigate novel candidate genes and mechanisms involved in the pathogenesis of IgAN. Among the genes, ITGB2 and FCER1G may play important roles in the development of IgAN and act as potential candidate molecular targets that deserve further research.