Background
Immunoglobulin A nephropathy (IgAN), characterized by glomerular IgA deposits on renal biopsy, is one of the most common primary glomerular disease and remains a leading cause of chronic kidney disease and end-stage kidney disease (ESKD) [
1‐
3]. The common clinical manifestations include hematuria, fever and different degree of proteinuria [
4,
5]. The estimated incidence of IgAN is about 2–10 per 100,000 person-years [
6,
7] and a higher disease burden has been reported in the East Asian countries, including China [
2]. To realize quick diagnosis using a less invasive methodology, blood-based biomarkers rather than renal biopsy that could be more preference in early indication and urgently needed in the clinical practice.
Recent advances in the microarray and transcriptomic technology allow us to obtain a landscape view of the differentially expressed genes (DEGs) in a certain kind of disease [
8‐
10]. Several studies have been performed to assess the expression profiling of the samples from IgAN. For example, Nagasawa et al. [
11] performed the microarray using 15 IgAN patients derived peripheral blood mononuclear cells (PBMCs), Liu et al. [
12] employed microarray analysis of the glomerular compartment of renal biopsy specimens from 19 IgAN patients and Guo et al. [
13] used microarrays to analyze the transcriptome of microdissected renal biopsies from 27 patients with IgAN. However, certain bias could be presented in these isolated experiments due to the complicated human genetic background and different experimental conditions. Integrative bioinformatics analysis can provide the possibility of multiple group verification of the DEGs, thereby facilitating the process of novel and reliable biomarkers identification.
In the present study, we aimed to identify the critical genes in the onset and progression of IgAN via integrative employment of blood-based microarray data and glomerular tissue-related data, thereby identifying the novel biomarkers for IgAN diagnosis. Moreover, we also explored immune cell infiltration feature using the glomerular-related data to discover the possible treatment intervention for IgAN.
Discussion
With the biomedical research entering into the big data era, steadily increased number of algorithms and analysis tools are proposed by different research groups each year; moreover, multiple types of omics data about a specific type of disease are also repeated assessed by different groups. To obtain full insights into the systemic and pathological effects of omics data, an integrative bioinformatics analysis of these datasets by using the effective algorithms or tools have become the top priority, which can facilitate the further exploration by “Wet” experiments.
In present study, we employed limma analysis, overlap genes omitting and WGCNA to obtain DEGs from 1 blood-derived dataset and a glomeruli-derived dataset, and a total of 195 DEGs were found. Then we found 3 upregulated and 3 downregulated DEGs via checking of expression pattern and clinical features correlation. Finally, through the external dataset and an IgAN cohort validation, 3 genes including ORMDL2, NRP1, and COL4A1 were confirmed with the ability of IgAN discrimination, and the highest AUC was found by COL4A1, which is 97.14%.
During the datasets screening process, we also found another 2 datasets (GSE35488 and GSE14795) related with IgAN in the GEO website. In GSE35488 [
21], RNA from tubulointerstitial compartments was extracted and processed for microarray analysis and the authors used these tissues for screening for proteinuria related DEGs. Finally, they identified an albumin-regulated 11-gene signature, which is shared in all forms of glomerulonephritits, including IgAN and membranoproliferative glomerulonephritis. Due to the poor gene clustering (Additional file
10) and inaccurate tissue derivation, this dataset was omitted. For GSE14795 [
22], the whole blood cells from 12 IgAN patients were used for analysis using a specific commercial system, and DEGs were identified using SAM method, however, the DEGs obtained by us using the same SAM method showed significant difference from those reported in the papers, and we guess that the data from this GEO dataset is incomplete.
In the DEGs discovery process, we found 5 genes are of clinical significance. Among them, ORMDL2 is considered as a negative regulator of sphingolipid synthesis and is predicted to be located in the endoplasmic reticulum. Clarke et al. [
23] reported that ORMDLs are able to restrain sphingolipid metabolism, thereby limiting levels of dangerous metabolic intermediates that can interfere with essential physiological processes such as myelination, whereas Bugajev et al. [
24] demonstrated that ORMDL2 deficiency could affect mast cell signaling during the systemic anaphylactic reaction. Due to an abnormal sphingolipid metabolism could contribute to various pathologic processes, including kidney diseases [
25], and activated mast cells were revealed according to the immune infiltration results, it is highly possible that ORMDL2 may an important role in IgAN. NRP1, a transmembrane receptor protein, has been reported to play an important role in several kidney diseases, including regulation of apoptosis and cytoskeleton organization of cells located in glomerular during the process of diabetic nephropathy [
26], and prediction of renal outcome in patients with lupus nephritis [
27]. COL4A1 encodes the α1 chain of collagen IV, which a major component of basement membranes and its mutation could result in glomerulocystic kidney disease [
28‐
30]. According to previous reports [
31,
32], macrophage can directly contribute to collagen generation in wound healing and other pathological conditions. They suggested that primary function of type VI collagen secreted by macrophages could be cell–cell (immune cells) and cell–matrix interactions modulation and production of type VI collagen is a marker for a nondestructive, matrix-conserving macrophage phenotype that could profoundly influence physiological and pathophysiological conditions in vivo. PKP4 is considered to play a role as a regulator of Rho activity during cytokinesis and is confirmed as one of DEGs in glomerular diseases reported by Ding et al. [
33]. Most recently, Raby found that PKP4 is presented in the urine exosome in patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD) as poor treatment responder biomarker [
34]. In our cohort validation, we found that PKP4 is also upregulated in IgAN compared to normal controls, and it is omitted due to inconsistent expression pattern between the datasets and our patient cohort. HSPA8 is a chaperone protein with important roles in various cellular processes, including autophagy [
35] and protection from reactive oxygen species (ROS) production by mitochondria during inflammatory conditions [
36]. Kim et al. [
37] reported that HSPA8 could be used as an effective and sensitive non-invasive biomarker for the assessment of nephrotoxicity, whereas Wen et al. [
38] suggested that possible the role of HSPA8 in organ fibrosis in diabetic kidney disease (DKD) patients. In a recent study by Lin et al. [
39], downregulated HSPA8 was found in IgAN patients, however, we did not find an obvious difference on HSPA8 in our discovery datasets. Therefore, further confirmation using more subjects might be carried out. No report was found on the role of ST13 in the kidney disease, whereas most of studies about ST13 are about the cancer biology [
40]. Furthermore, ST13 was found with no significant downregulation in our validation cohort. We attributed the reasons that limited patient number or possible the error in the microarray analysis.
For the immune infiltration results, we found that differentially ratio of naive B cells (p = 0.016), resting memory CD4 T cells (p < 0.001), resting and activated NK cells (p = 0.021 and < 0.001), M1 and M2 macrophages (p = 0.016 and 0.020), activated mast cells (p = 0.038), and neutrophils (p < 0.001) between control and IgAN. B cells may be involved in the production of galactose-deficient IgA1(Gd-IgA1) and its antibodies in IgA nephropathy [
41], and decreased number of naive B cell could be resulted by more of activated B cells. Moreover, Eijgenraam et al. [
42] showed previously that dendritic cells of IgAN patients have an impaired capacity to induce IgA production in naive B cells. As heterogeneous cells of the innate immune system, macrophages can fluidly modulate their phenotype in response to the local microenvironment, and macrophage polarization is found during chronic kidney disease (CKD) [
43], therefore, it is reasonable to observe elevation of M1 and M2 macrophages in IgAN. Moreover, activated mast cells mediated antibody production [
44], neutrophils caused glomerular injury [
45], NK induced hematuria [
46] and T cell-induced Gd-IgA1 synthesis elevation [
47] are reported according to previous reports during the IgAN.
In addition, according to the results from ceRNA network, miR-135a-5p and miR-135b-5p are found significantly correlated with the gene ORMDL2 found here, in the recent studies by Pawluczyk et al. [
48] and Min et al.[
49], miR-135a-5p showed differentially expressed in IgAN patients, whereas miR-135b-5p was confirmed as the differentially expressed miRNA using the urinary exosome samples from IgAN patients. Moreover, circulating miR-29a [
50] and urinary exosome derived miR-29c [
49] are also found differentially expressed in IgAN according to previous studies.
There are also some limitations in present study. First, the number of validation cohort is limited and no follow-up information is available, thereby resulting in possible the bias on the results and inability of examination of the genes in the prognosis. Second, although several immune cells were found dysregulated and the results were consistent with previous reports, the detailed function of these immune cells and the exact molecular events during the IgAN remains unknown. Therefore, further clinical validation with a large cohort of patient and experimental verification of these genes are required in near future.
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