Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy

O-glycosylation of IgA1 and the pathogenesis of an autoimmune disease IgA nephropathy

IgA nephropathy is a kidney disease characterized by deposition of immune complexes containing abnormally O-glycosylated IgA1 in the glomeruli. Specifically, some O-glycans are missing galactose that is normally β1,3-linked to N-acetylgalactosamine of the core 1 glycans. These galactose-deficient IgA1 glycoforms are produced by IgA1-secreting cells due to a dysregulated expression and activity of several glycosyltransferases. Galactose-deficient IgA1 in the circulation of patients with IgA nephropathy is bound by IgG autoantibodies and the resultant immune complexes can contain additional proteins, such as complement C3. These complexes, if not removed from the circulation, can enter the glomerular mesangium, activate the resident mesangial cells, and induce glomerular injury. In this review, we briefly summarize clinical and pathological features of IgA nephropathy, review normal and aberrant IgA1 O-glycosylation pathways, and discuss the origins and potential significance of natural anti-glycan antibodies, namely those recognizing N-acetylgalactosamine. We also discuss the features of autoantibodies specific for galactose-deficient IgA1 and the characteristics of pathogenic immune complexes containing IgA1 and IgG. In IgA nephropathy, kidneys are injured by IgA1-containing immune complexes as innocent bystanders. Most patients with IgA nephropathy progress to kidney failure and require dialysis or transplantation. Moreover, most patients after transplantation experience a recurrent disease. Thus, a better understanding of the pathogenetic mechanisms is needed to develop new disease-specific treatments.

Cross-species single-cell analysis uncovers the immunopathological mechanisms associated with IgA nephropathy progression

IgA nephropathy (IgAN) represents the main cause of renal failure, while the precise pathogenetic mechanisms have not been fully determined. Herein, we conducted a cross-species single-cell survey on human IgAN and mouse and rat IgAN models to explore the pathogenic programs. Cross-species single-cell RNA sequencing (scRNA-Seq) revealed that the IgAN mesangial cells (MCs) expressed high levels of inflammatory signatures CXCL12, CCL2, CSF1, and IL-34 and specifically interacted with IgAN macrophages via the CXCL12/CXCR4, CSF1/IL-34/CSF1 receptor, and integrin subunit alpha X/integrin subunit alpha M/complement C3 (C3) axes. IgAN macrophages expressed high levels of CXCR4, PDGFB, triggering receptor expressed on myeloid cells 2, TNF, and C3, and the trajectory analysis suggested that these cells derived from the differentiation of infiltrating blood monocytes. Additionally, protein profiling of 21 progression and 28 nonprogression IgAN samples revealed that proteins CXCL12, C3, mannose receptor C-type 1, and CD163 were negatively correlated with estimated glomerular filtration rate (eGFR) value and poor prognosis (30% eGFR as composite end point). Last, a functional experiment revealed that specific blockade of the Cxcl12/Cxcr4 pathway substantially attenuated the glomerulus and tubule inflammatory injury, fibrosis, and renal function decline in the mouse IgAN model. This study provides insights into IgAN progression and may aid in the refinement of IgAN diagnosis and the optimization of treatment strategies.

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Glomerular spatial transcriptomics of IgA nephropathy according to the presence of mesangial proliferation

Mesangial proliferation is a diagnostic feature and a prognostic predictor of immunoglobulin A nephropathy (IgAN). We aimed to investigate the gene expression profiles of IgAN glomerulus according to the presence of mesangial proliferation. We performed spatial-specific transcriptomic profiling on kidney biopsy tissues using the GeoMx Digital Spatial Profiler. Twelve cases with three glomeruli for each case were profiled using direct pathologic classification (4 M1-IgAN, 4 M0-IgAN, and 4 donor controls). The results of enriched glom-specific genes demonstrated that M1-IgAN could be distinguished from controls (77 upregulated and 55 downregulated DEGs), while some DEGs were identified between M1-IgAN and M0-IgAN cases (24 upregulated and 8 downregulated DEGs) or between M0 and controls (1 upregulated and 16 downregulated DEGs). TCF21, an early podocyte damage marker, was the only differentially expressed gene (DEG) consistently upregulated in both M1-IgAN and M0-IgAN patients, whereas ATF3, EGR1, DUSP1, FOS, JUNB, KLF2, NR4A1, RHOB, and ZFP36 were consistently downregulated in IgAN cases. Glomeruli from M1-IgAN cases were significantly enriched for cell surface/adhesion molecules and gene expressions associated with vascular development or the extracellular matrix. Spatial transcriptomic analysis may contribute to dissecting structure-specific pathophysiology and molecular changes in IgAN.

Adjustment of p-value expression to ontology using machine learning for genetic prediction, prioritization, interaction, and its validation in glomerular disease

The results of gene expression analysis based on p-value can be extracted and sorted by their absolute statistical significance and then applied to multiple similarity scores of their gene ontology (GO) terms to promote the combination and adjustment of these scores as essential predictive tasks for understanding biological/clinical pathways. The latter allows the possibility to assess whether certain aspects of gene function may be associated with other varieties of genes, to evaluate regulation, and to link them into networks that prioritize candidate genes for classification by applying machine learning techniques. We then detect significant genetic interactions based on our algorithm to validate the results. Finally, based on specifically selected tissues according to their normalized gene expression and frequencies of occurrence from their different biological and clinical inputs, a reported classification of genes under the subject category has validated the abstract (glomerular diseases) as a case study.

The role of the mesangium in glomerular function

When discussing glomerular function, one cell type is often left out, the mesangial cell (MC), probably since it is not a part of the filtration barrier per se. The MCs are instead found between the glomerular capillaries, embedded in their mesangial matrix. They are in direct contact with the endothelial cells and in close contact with the podocytes and together they form the glomerulus. The MCs can produce and react to a multitude of growth factors, cytokines, and other signaling molecules and are in the perfect position to be a central hub for crosstalk communication between the cells in the glomerulus. In certain glomerular diseases, for example, in diabetic kidney disease or IgA nephropathy, the MCs become activated resulting in mesangial expansion. The expansion is normally due to matrix expansion in combination with either proliferation or hypertrophy. With time, this expansion can lead to fibrosis and decreased glomerular function. In addition, signs of complement activation are often seen in biopsies from patients with glomerular disease affecting the mesangium. This review aims to give a better understanding of the MCs in health and disease and their role in glomerular crosstalk and inflammation.

Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine

Artificial intelligence (AI) has opened new medical avenues and revolutionized diagnostic and therapeutic practices, allowing healthcare providers to overcome significant challenges associated with cost, disease management, accessibility, and treatment optimization. Prominent AI technologies such as machine learning (ML) and deep learning (DL) have immensely influenced diagnostics, patient monitoring, novel pharmaceutical discoveries, drug development, and telemedicine. Significant innovations and improvements in disease identification and early intervention have been made using AI-generated algorithms for clinical decision support systems and disease prediction models. AI has remarkably impacted clinical drug trials by amplifying research into drug efficacy, adverse events, and candidate molecular design. AI's precision and analysis regarding patients' genetic, environmental, and lifestyle factors have led to individualized treatment strategies. During the COVID-19 pandemic, AI-assisted telemedicine set a precedent for remote healthcare delivery and patient follow-up. Moreover, AI-generated applications and wearable devices have allowed ambulatory monitoring of vital signs. However, apart from being immensely transformative, AI's contribution to healthcare is subject to ethical and regulatory concerns. AI-backed data protection and algorithm transparency should be strictly adherent to ethical principles. Vigorous governance frameworks should be in place before incorporating AI in mental health interventions through AI-operated chatbots, medical education enhancements, and virtual reality-based training. The role of AI in medical decision-making has certain limitations, necessitating the importance of hands-on experience. Therefore, reaching an optimal balance between AI's capabilities and ethical considerations to ensure impartial and neutral performance in healthcare applications is crucial. This narrative review focuses on AI's impact on healthcare and the importance of ethical and balanced incorporation to make use of its full potential.

APOC1 exacerbates renal fibrosis through the activation of the NF-κB signaling pathway in IgAN

Introduction: IgA nephropathy (IgAN) is the most common disease leading to end-stage renal disease, and tubular fibrosis represents an important risk factor for disease progression. However, research on early molecular diagnostic indicators of tubular fibrosis and the mechanisms underlying disease progression is still lacking. Methods: The GSE93798 dataset was downloaded from the GEO database. DEGs were screened and analyzed for GO and KEGG enrichment in IgAN. The least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms were applied to screen for hub secretory genes. The expression and diagnostic efficacy of hub genes were confirmed by the GSE35487 dataset. ELISA was applied to detect the expression of APOC1 in serum. The expression and localization of hub genes in IgAN were verified by the expression of IHC and IF in human kidney tissues, and the correlation of expression with clinical data was verified in the Nephroseq database. Finally, cellular experiments clarified the role of hub genes in the signaling pathway. Results: A total of 339 DEGs were identified in IgAN, of which 237 were upregulated and 102 downregulated. The KEGG signaling pathway is enriched in the ECM-receptor interaction and AGE-RAGE signaling pathway. APOC1, ALB, CCL8, CXCL2, SRPX2, and TGFBI identified six hub secretory genes using the LASSO and SVM-RFE algorithms. In vivo and in vitro experiments demonstrated that APOC1 expression was elevated in IgAN. The serum concentration of APOC1 was 1.232 ± 0.1812 μg/ml in IgAN patients, whereas it was 0.3956 ± 0.1233 μg/ml in healthy individuals. APOC1 exhibited high diagnostic efficacy for IgAN (AUC of 99.091%, specificity of 95.455%, and sensitivity of 99.141%) in the GSE93798 dataset. APOC1 expression negatively correlated with eGFR (R ² = 0.2285, p = 0.0385) and positively correlated with serum creatinine (R ² = 0.41, p = 0.000567) in IgAN. APOC1 exacerbated renal fibrosis, possibly in part by activating the NF-κB pathway in IgAN. Conclusion: APOC1 was identified as the core secretory gene of IgAN, which was closely associated with blood creatinine and eGFR and had significant efficacy in the diagnosis of IgAN. Mechanistic studies revealed that the knockdown of APOC1 could improve IgAN renal fibrosis by inhibiting the NF pathway, which may be a potential therapeutic target for improving renal fibrosis in IgAN.

Proteomic profiling of IgA nephropathy reveals distinct molecular prognostic subtypes

IgA nephropathy (IgAN) is a heterogeneous disease, which poses a series of challenges to accurate diagnosis and personalized therapy. Herein, we constructed a systematic quantitative proteome atlas from 59 IgAN and 19 normal control donors. Consensus sub-clustering of proteomic profiles divided IgAN into three subtypes (IgAN-C1, C2, and C3). IgAN-C2 had similar proteome expression patterns with normal control, while IgAN-C1/C3 exhibited higher level of complement activation, more severe mitochondrial injury, and significant extracellular matrix accumulation. Interestingly, the complement mitochondrial extracellular matrix (CME) pathway enrichment score achieved a high diagnostic power to distinguish IgAN-C2 from IgAN-C1/C3 (AUC>0.9). In addition, the proteins related to mesangial cells, endothelial cells, and tubular interstitial fibrosis were highly expressed in IgAN-C1/C3. Most critically, IgAN-C1/C3 had a worse prognosis compared to IgAN-C2 (30% eGFR decline, p = 0.02). Altogether, we proposed a molecular subtyping and prognostic system which could help to understand IgAN heterogeneity and improve the treatment in the clinic.

Integration of three machine learning algorithms identifies characteristic RNA binding proteins linked with diagnosis, immunity and pyroptosis of IgA nephropathy

Objective: RNA-binding proteins (RBPs) are essential for most post-transcriptional regulatory events, which exert critical roles in nearly all aspects of cell biology. Here, characteristic RBPs of IgA nephropathy were determined with multiple machine learning algorithms.

Methods: Our study included three gene expression datasets of IgA nephropathy (GSE37460, GSE73953, GSE93798). Differential expression of RBPs between IgA nephropathy and normal samples was analyzed via limma, and hub RBPs were determined through MCODE. Afterwards, three machine learning algorithms (LASSO, SVM-RFE, random forest) were integrated to determine characteristic RBPs, which were verified in the Nephroseq database. Immune cell infiltrations were estimated through CIBERSORT. Utilizing ConsensusClusterPlus, IgA nephropathy were classified based on hub RBPs. The potential upstream miRNAs were predicted.

Results: Among 388 RBPs with differential expression, 43 hub RBPs were determined. After integration of three machine learning algorithms, three characteristic RBPs were finally identified (DDX27, RCL1, and TFB2M). All of them were down-regulated in IgA nephropathy than normal specimens, with the excellent diagnostic efficacy. Additionally, they were significantly linked to immune cell infiltrations, immune checkpoints, and pyroptosis-relevant genes. Based on hub RBPs, IgA nephropathy was stably classified as two subtypes (cluster 1 and 2). Cluster 1 exhibited the relatively high expression of pyroptosis-relevant genes and characteristic RBPs. MiR-501-3p, miR-760, miR-502-3p, miR-1224-5p, and miR-107 were potential upstream miRNAs of hub RBPs.

Conclusion: Collectively, our findings determine three characteristic RBPs in IgA nephropathy and two RBPs-based subtypes, and thus provide a certain basis for further research on the diagnosis and pathogenesis of IgA nephropathy.

Downregulation of PPARα mediates FABP1 expression, contributing to IgA nephropathy by stimulating ferroptosis in human mesangial cells

Immunoglobulin A nephropathy (IgAN) is the commonest primary glomerulonephritis, and a major cause of end-stage renal disease; however, its pathogenesis requires elucidation. Here, a hub gene, FABP1, and signaling pathway, PPARα, were selected as key in IgAN pathogenesis by combined weighted gene correlation network analysis of clinical traits and identification of differentially expressed genes from three datasets. FABP1 and PPARα levels were lower in IgAN than control kidney, and linearly positively correlated with one another, while FABP1 levels were negatively correlated with urinary albumin-to-creatinine ratio, and GPX4 levels were significantly decreased in IgAN. In human mesangial cells (HMCs), PPARα and FABP1 levels were significantly decreased after Gd-IgA1 stimulation and mitochondria appeared structurally damaged, while reactive oxygen species (ROS) and malondialdehyde (MDA) were significantly increased, and glutathione and GPX4 decreased, relative to controls. GPX4 levels were decreased, and those of ACSL4 increased on siPPARα and siFABP1 siRNA treatment. In PPARα lentivirus-transfected HMCs stimulated by Gd-IgA1, ROS, MDA, and ACSL4 were decreased; glutathione and GPX4, and immunofluorescence colocalization of PPARα and GPX4, increased; and damaged mitochondria reduced. Hence, PPARα pathway downregulation can reduce FABP1 expression, affecting GPX4 and ACSL4 levels, causing HMC ferroptosis, and contributing to IgAN pathogenesis.

Inflammation in kidney repair: Mechanism and therapeutic potential

The kidney has a remarkable ability of repair after acute kidney injury (AKI). However, when injury is severe or persistent, the repair is incomplete or maladaptive and may lead to chronic kidney disease (CKD). Maladaptive kidney repair involves multiple cell types and multifactorial processes, of which inflammation is a key component. In the process of inflammation, there is a bidirectional interplay between kidney parenchymal cells and the immune system. The extensive and complex crosstalk between renal tubular epithelial cells and interstitial cells, including immune cells, fibroblasts, and endothelial cells, governs the repair and recovery of the injured kidney. Further research in this field is imperative for the discovery of biomarkers and promising therapeutic targets for kidney repair. In this review, we summarize the latest progress in the immune response and inflammation during maladaptive kidney repair, analyzing the interaction between immune cells and intrinsic kidney cells, pointing out the potentialities of inflammation-related pathways as therapeutic targets, and discussing the challenges and future research prospects in this field.

Identification of key candidate genes for IgA nephropathy using machine learning and statistics based bioinformatics models

Immunoglobulin-A-nephropathy (IgAN) is a kidney disease caused by the accumulation of IgAN deposits in the kidneys, which causes inflammation and damage to the kidney tissues. Various bioinformatics analysis-based approaches are widely used to predict novel candidate genes and pathways associated with IgAN. However, there is still some scope to clearly explore the molecular mechanisms and causes of IgAN development and progression. Therefore, the present study aimed to identify key candidate genes for IgAN using machine learning (ML) and statistics-based bioinformatics models. First, differentially expressed genes (DEGs) were identified using limma, and then enrichment analysis was performed on DEGs using DAVID. Protein-protein interaction (PPI) was constructed using STRING and Cytoscape was used to determine hub genes based on connectivity and hub modules based on MCODE scores and their associated genes from DEGs. Furthermore, ML-based algorithms, namely support vector machine (SVM), least absolute shrinkage and selection operator (LASSO), and partial least square discriminant analysis (PLS-DA) were applied to identify the discriminative genes of IgAN from DEGs. Finally, the key candidate genes (FOS, JUN, EGR1, FOSB, and DUSP1) were identified as overlapping genes among the selected hub genes, hub module genes, and discriminative genes from SVM, LASSO, and PLS-DA, respectively which can be used for the diagnosis and treatment of IgAN.

The promise of artificial intelligence for kidney pathophysiology

PURPOSE OF REVIEW

We seek to determine recent advances in kidney pathophysiology that have been enabled or enhanced by artificial intelligence. We describe some of the challenges in the field as well as future directions.

RECENT FINDINGS

We first provide an overview of artificial intelligence terminologies and methodologies. We then describe the use of artificial intelligence in kidney diseases to discover risk factors from clinical data for disease progression, annotate whole slide imaging and decipher multiomics data. We delineate key examples of risk stratification and prognostication in acute kidney injury (AKI) and chronic kidney disease (CKD). We contextualize these applications in kidney disease oncology, one of the subfields to benefit demonstrably from artificial intelligence using all if these approaches. We conclude by elucidating technical challenges and ethical considerations and briefly considering future directions.

SUMMARY

The integration of clinical data, patient derived data, histology and proteomics and genomics can enhance the work of clinicians in providing more accurate diagnoses and elevating understanding of disease progression. Implementation research needs to be performed to translate these algorithms to the clinical setting.

Cytokines and Production of Aberrantly O-Glycosylated IgA1, the Main Autoantigen in IgA Nephropathy

Immunoglobulin A (IgA) nephropathy is the most common primary glomerulonephritis worldwide, with no disease-specific treatment and up to 40% of patients progressing to kidney failure. IgA nephropathy (IgAN), characterized by IgA1-containing immunodeposits in the glomeruli, is considered to be an autoimmune disease in which the kidneys are injured as innocent bystanders. Glomerular immunodeposits are thought to originate from the circulating immune complexes that contain aberrantly O-glycosylated IgA1, the main autoantigen in IgAN, bound by IgG autoantibodies. A common clinical manifestation associated with IgAN includes synpharyngitic hematuria at disease onset or during disease activity. This observation suggests a connection of disease pathogenesis with an activated mucosal immune system of the upper-respiratory and/or gastrointestinal tract and IgA1 glycosylation. In fact, some cytokines can enhance production of aberrantly O-glycosylated IgA1. This process involves abnormal cytokine signaling in IgA1-producing cells from patients with IgAN. In this article, we present our view of pathogenesis of IgAN and review how some cytokines can contribute to the disease process by enhancing production of aberrantly glycosylated IgA1. We also review current clinical trials of IgAN based on cytokine-targeting therapeutic approaches.

Identification of Hub Genes and Therapeutic Agents for IgA Nephropathy Through Bioinformatics Analysis and Experimental Validation

Background

IgA nephropathy (IgAN) is the most common primary glomerular disease and the leading cause of the end-stage renal disease in the world. The pathogenesis of IgAN has not been well elucidated, and yet treatment is limited. High-throughput microarray has been applied for elucidating molecular biomarkers and potential mechanisms involved in IgAN. This study aimed to identify the potential key genes and therapeutics associated with IgAN using integrative bioinformatics and transcriptome-based computational drug repurposing approach.

Methods

Three datasets of mRNA expression profile were obtained from the gene expression omnibus database and differentially expressed genes (DEGs) between IgAN glomeruli and normal tissue were identified by integrated analysis. Gene ontology and pathway enrichment analyses of the DEGs were performed by R software, and protein-protein interaction networks were constructed using the STRING online search tool. External dataset and immunohistochemical assessment of kidney biopsy specimens were used for hub gene validation. Potential compounds for IgAN therapy were obtained by Connectivity Map (CMap) analysis and preliminarily verified in vitro. Stimulated human mesangial cells were collected for cell proliferation and cell cycle analysis using cell counting kit 8 and flow cytometry, respectively.

Results

134 DEGs genes were differentially expressed across kidney transcriptomic data from IgAN patients and healthy living donors. Enrichment analysis showed that the glomerular compartments underwent a wide range of interesting pathological changes during kidney injury, focused on anion transmembrane transporter activity and protein digestion and absorption mostly. Hub genes (ITGB2, FCER1G, CSF1R) were identified and verified to be significantly upregulated in IgAN patients, and associated with severity of renal lesions. Computational drug repurposing with the CMap identified tetrandrine as a candidate treatment to reverse IgAN hub gene expression. Tetrandrine administration significantly reversed mesangial cell proliferation and cell cycle transition.

Conclusion

The identification of DEGs and related therapeutic strategies of IgAN through this integrated bioinformatics analysis provides a valuable resource of therapeutic targets and agents of IgAN. Especially, our findings suggest that tetrandrine might be beneficial for IgAN, which deserves future research.

Computational Analysis Reveals the Characteristics of Immune Cells in Glomerular and Tubulointerstitial Compartments in IgA Nephropathy Patients

Objective: The commonalities and differences regarding immune states between glomerular and tubulointerstitial compartments of IgA nephropathy (IgAN) remains largely undetermined. We aim to perform bioinformatic analysis for providing a comprehensive insight into the characteristics of immune cells and associated molecular mechanisms in IgAN.

Materials and Methods: We performed integrated bioinformatic analyses by using IgAN-related datasets from the Gene Expression Omnibus database. First, the differentially expressed genes (DEGs) were identified and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Then, CIBERSORT was employed to determine the landscape of infiltrating immune cells in both glomerular and tubulointerstitial compartments of IgAN patients, followed by Pearson’s correlation analysis and principal component analysis (PCA). Finally, commonly shared DEGs between glomerular and tubulointerstitial entities were recognized, followed by correlation analyses to identify the dominant commonly shared DEGs associated with immune cell infiltration in IgAN.

Results: GO and KEGG enrichment analyses showed apparently distinct biological processes in the glomerular and tubulointerstitial compartments of IgAN. In addition, CIBERSORT analyses revealed a clear trend of increasing proportions of M1 macrophage and M2 macrophage in the glomerular compartment while noticeably higher proportions of resting CD4⁺ memory T cells and M2 macrophages in the tubulointerstitial compartments. The PCA analyses showed that the varying composition of immune cells in both glomerular and tubulointerstitial entities was compelling to distinguish IgAN patients from healthy living controls. In addition, 21 commonly shared DEGs between glomerular and tubulointerstitial entities were recognized as key regulators in the pathogenesis of IgAN, among which the enhanced hemoglobin subunit beta (HBB) gene expression was found to be positively associated with M2 macrophage in the glomerular compartment and resting CD4⁺ memory T cells in the tubulointerstitial compartment. Most importantly, FBJ murine osteosarcoma viral oncogene homolog B (FOSB) gene deficiency was recognized as the dominant alteration in promoting M2 macrophage infiltration in the glomerular compartment of IgAN.

Conclusion: The findings from our current study for the first time reveal commonalities and differences regarding immune states between glomerular and tubulointerstitial compartments, as well as decode the essential role of M2 macrophages and associated molecular patterns within the microenvironments of IgAN.

Identification of blood-based key biomarker and immune infiltration in Immunoglobulin A nephropathy by comprehensive bioinformatics analysis and a cohort validation

Background

To identify the critical genes in the onset and progression of Immunoglobulin A nephropathy (IgAN) and to explore its immune cell infiltration feature.

Methods

Differentially expressed genes (DEGs) were firstly screened from 1 blood-derived dataset GSE73953 and a glomerulus derived dataset GSE93798 through limma analysis, overlap genes omitting and weighted gene correlation network analysis (WGCNA) and further reduced according to expression pattern and correlation with the clinical features: eGFR and proteinuria, followed by external validation using the GSE37460 dataset and an IgAN cohort. In addition, the CIBERSORT tool for immune cell infiltration analysis, ceRNA network construction and Connectivity Map (CMAP) were also performed.

Results

A total of 195 DEGs were found, and among them, 3 upregulated (ORMDL2, NRP1, and COL4A1) and 3 downregulated genes (ST13, HSPA8 and PKP4) are verified to correlate clinically, and finally ORMDL2, NRP1 and COL4A1 were validated in patient cohort and with the ability of IgAN discrimination (highest AUC was COL4A1: 97.14%). The immune cell infiltration results revealed that significant differences could be found on resting memory CD4 T cells, activated NK cells, and M2 macrophages between control and IgAN.

Conclusions

Our results demonstrated here that significantly upregulated DEGs: ORMDL2, NRP1 and COL4A1, could be served as the diagnostic marker for IgAN, and dysregulated immune cell infiltration hinted possible the immune system intervention point in the setting of IgAN.

STXBP6 and B3GNT6 Genes are Associated With Selective IgA Deficiency

Immunoglobulin A Deficiency (IgAD) is a polygenic primary immune deficiency, with a strong genetic association to the human leukocyte antigen (HLA) region. Previous genome-wide association studies (GWAS) have identified five non-HLA risk loci (IFIH1, PVT1, ATG13-AMBRA1, AHI1 and CLEC16A). In this study, we investigated the genetic interactions between different HLA susceptibility haplotypes and non-MHC genes in IgAD. To do this, we stratified IgAD subjects and healthy controls based on HLA haplotypes (N = 10,993), and then performed GWAS to identify novel genetic regions contributing to IgAD susceptibility. After replicating previously published HLA risk haplotypes, we compared individuals carrying at least one HLA risk allele (HLA-B*08:01-DRB1*03:01-DQB1*02:01 or HLA-DRB1*07:01-DQB1*02:02 or HLA-DRB1*01-DQB1*05:01) with individuals lacking an HLA risk allele. Subsequently, we stratified subjects based on the susceptibility alleles/haplotypes and performed gene-based association analysis using 572,856 SNPs and 24,125 genes. A significant genome-wide association in STXBP6 (rs4097492; p = 7.63 × 10^-9) was observed in the cohort carrying at least one MHC risk allele. We also identified a significant gene-based association for B3GNT6 (P _Gene = 2.1 × 10^-6) in patients not carrying known HLA susceptibility alleles. Our findings indicate that the etiology of IgAD differs depending on the genetic background of HLA susceptibility haplotypes.

Identification of miRNA-mRNA network and immune-related gene signatures in IgA nephropathy by integrated bioinformatics analysis

BACKGROUND

IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis worldwide, and its diagnosis depends mainly on renal biopsy. However, there is no specific treatment for IgAN. Moreover, its causes and underlying molecular events require further exploration.

METHODS

The expression profiles of GSE64306 and GSE93798 were downloaded from the Gene Expression Omnibus (GEO) database and used to identify the differential expression of miRNAs and genes, respectively. The StarBase and TransmiR databases were employed to predict target genes and transcription factors of the differentially expressed miRNAs (DE-miRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to predict biological functions. A comprehensive analysis of the miRNA-mRNA regulatory network was constructed, and protein-protein interaction (PPI) networks and hub genes were identified. CIBERSORT was used to examine the immune cells in IgAN, and correlation analyses were performed between the hub genes and infiltrating immune cells.

RESULTS

Four downregulated miRNAs and 16 upregulated miRNAs were identified. Forty-five and twelve target genes were identified for the upregulated and downregulated DE-miRNAs, respectively. CDKN1A, CDC23, EGR1, HIF1A, and TRIM28 were the hub genes with the highest degrees of connectivity. CIBERSORT revealed increases in the numbers of activated NK cells, M1 and M2 macrophages, CD4 naive T cells, and regulatory T cells in IgAN. Additionally, HIF1A, CDC23, TRIM28, and CDKN1A in IgAN patients were associated with immune cell infiltration.

CONCLUSIONS

A potential miRNA-mRNA regulatory network contributing to IgAN onset and progression was successfully established. The results of the present study may facilitate the diagnosis and treatment of IgAN by targeting established miRNA-mRNA interaction networks. Infiltrating immune cells may play significant roles in IgAN pathogenesis. Future studies on these immune cells may help guide immunotherapy for IgAN patients.

The molecular mechanisms of inflammation and scarring in the kidneys of immunoglobulin A nephropathy : Gene involvement in the mechanisms of inflammation and scarring in kidney biopsy of IgAN patients

Kidney biopsy is the cornerstone for the diagnosis of immunoglobulin A nephropathy (IgAN). The immunofluorescence technique evidences the IgA deposits in the glomeruli; the routine histology shows degree of active and chronic renal lesions. The spectrum of renal lesions is highly variable, ranging from minor or no detectable lesions to diffuse proliferative or crescentic lesions. Over the past three decades, renal transcriptomic studies have been performed on fresh or frozen renal tissue, and formalin-fixed paraffin-embedded kidney tissue specimens obtained from archival histological repositories. This paper aims to describe (1) the transcriptomic profiles of the kidney biopsy and (2) the potential urinary biomarkers that can be used to monitor the follow-up of IgAN patients. The use of quantitative Real-Time Polymerase Chain Reaction (qRT-PCR), microarrays and RNA-sequencing (RNA-seq) techniques on renal tissue and separated compartments of the nephron such as glomeruli and tubule-interstitium has clarified many aspects of the renal damage in IgAN. Recently, the introduction of the single-cell RNA-seq techniques has overcome the limitations of the previous methods, making that it is possible to study the whole renal tissue without the dissection of the nephron segments; it also allows better analysis of the cell-specific gene expression involved in cell differentiation. These gene products could represent effective candidates for urinary biomarkers for clinical decision making. Finally, some of these molecules may be the targets of old drugs, such as corticosteroids, renin-angiotensin-aldosterone blockers, and new drugs such as monoclonal antibodies. In the era of personalized medicine and precision therapy, high-throughput technologies may better characterize different renal patterns of IgAN and deliver targeted treatments to individual patients.

LncRNA PTTG3P induced aberrant glycosylated IgA1 production and B cell growth in IgA nephropathy

Growing evidences suggested that lncRNAs played functional role in several cell functions such as cell growth, invasion, migration, metabolize, apoptosis, and differentiation. However, roles of lncRNA in the development and progression of IgAN remain unknown. In this reference, we indicated that PTTG3P level was overexpressed in IgAN samples compared to healthy subject. PTTG3P expression was also higher in urinary of IgAN cases than in urinary of healthy control. Furthermore, the urinary expression of PTTG3P was correlated with PTTG3P expression in intra-renal of IgAN cases. PTTG3P overexpression induced B cell growth and enhanced cyclin D1 and ki-67 expression. Overexpression of PTTG3P induced IL-1β and IL-8 production. miR-383 level was decreased in IgAN samples compared to healthy subject. In addition, miR-383 expression was also lower in urinary of IgAN cases than in urinary of healthy control. Elevated miR-383 expression decreased luciferase intensity regulated with PTTG3P, while overexpression of miR-383 had no effect on luciferase intensity of the mutant PTTG3P. PTTG3P overexpression suppressed miR-383 expression in B cells. Ectopic miR-383 expression suppressed B cell growth and IL-1β and IL-8 production. Finally, we showed that overexpression of PTTG3P promoted B cell growth and IL-1β and IL-8 production via regulating miR-383. There results proved that PTTG3P played crucial role in progression of IgAN.

Kidney organoid systems for studies of immune-mediated kidney diseases: challenges and opportunities

Acute and chronic kidney diseases are major contributors to morbidity and mortality in the global population. Many nephropathies are considered to be immune-mediated with dysregulated immune responses playing an important role in the pathogenesis. At present, targeted approaches for many kidney diseases are still lacking, as the underlying mechanisms remain insufficiently understood. With the recent development of organoids—a three-dimensional, multicellular culture system, which recapitulates important aspects of human tissues—new opportunities to investigate interactions between renal cells and immune cells in the pathogenesis of kidney diseases arise. To date, kidney organoid systems, which reflect the structure and closer resemble critical aspects of the organ, have been established. Here, we highlight the recent advances in the development of kidney organoid models, including pluripotent stem cell-derived kidney organoids and primary epithelial cell-based tubuloids. The employment and further required advances of current organoid models are discussed to investigate the role of the immune system in renal tissue development, regeneration, and inflammation to identify targets for the development of novel therapeutic approaches of immune-mediated kidney diseases.

Retinoic acid receptor responder1 promotes development of glomerular diseases via the Nuclear Factor-κB signaling pathway

Inflammatory pathways are activated in most glomerular diseases but molecular mechanisms driving them in kidney tissue are poorly known. We identified retinoic acid receptor responder 1 (Rarres1) as a highly podocyte-enriched protein in healthy kidneys. Studies in podocyte-specific knockout animals indicated that Rarres1 was not needed for the normal development or maintenance of the glomerulus filtration barrier and did not modulate the outcome of kidney disease in a model of glomerulonephritis. Interestingly, we detected an induction of Rarres1 expression in glomerular and peritubular capillary endothelial cells in IgA and diabetic kidney disease, as well as in ANCA-associated vasculitis. Analysis of publicly available RNA data sets showed that the induction of Rarres1 expression was a common molecular mechanism in chronic kidney diseases. A conditional knock-in mouse line, overexpressing Rarres1 specifically in endothelial cells, did not show any obvious kidney phenotype. However, the overexpression promoted the progression of kidney damage in a model of glomerulonephritis. In line with this, conditional knock-out mice, lacking Rarres1 in endothelial cells, were partially protected in the disease model. Mechanistically, Rarres1 promoted inflammation and fibrosis via transcription factor Nuclear Factor-κB signaling pathway by activating receptor tyrosine kinase Axl. Thus, induction of Rarres1 expression in endothelial cells is a prevalent molecular mechanism in human glomerulopathies and this seems to have a pathogenic role in driving inflammation and fibrosis via the Nuclear Factor-κB signaling pathway.

A Partial Picture of the Single-Cell Transcriptomics of Human IgA Nephropathy

The molecular mechanisms underlying renal damage of IgA nephropathy (IgAN) remain incompletely defined. Here, single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from IgAN and control subjects to define the transcriptomic landscape at single-cell resolution. We presented a comprehensive scRNA-seq analysis of human renal biopsies from IgAN. We showed for the first time that IgAN mesangial cells displayed increased expression of several novel genes including MALAT1, GADD45B, SOX4, and EDIL3, which were related to cell proliferation and matrix accumulation. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling, and NOD-like receptor signaling. Furthermore, we compared the results of 4 IgAN patients with the published scRNA-Seq data of healthy kidney tissues of three human donors in order to further validate the findings in our study. The results also verified that the overexpressed genes in tubule cells from IgAN patients were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling, and NOD-like receptor signaling. The receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. IgAN patients with overt proteinuria displayed elevated genes participating in several signaling pathways compared with microproteinuria group. It needs to be mentioned that based on number of mesangial cells and other kidney cells analyzed in this study, the results of our study are preliminary and needs to be confirmed on larger number of cells from larger number of patients and controls in future studies. Therefore, these results offer new insight into pathogenesis and identify new therapeutic targets for IgAN.

[New technologies for renal pathology: Transcriptomics on paraffin-embedded fixed tissue]

The development of new high-throughput technologies in genomics and then in transcriptomics has modified clinical approach in nephrology. At the interface between high-throughput technologies (microarray, new generation sequencing «NGS») and few mRNA analysis (reverse transcriptase quantitative PCR [RT-qPCR]), the nCounter® of NanoString® offers a new and complementary approach. Capable of analyzing formalin-fixed paraffin-embedded samples, this technology is a credible candidate for implanting transcriptomics in clinical routine.

Complement and kidney disease, new insights

PURPOSE OF REVIEW

In this review, we discuss recent studies showing the importance of the complement pathway in kidney disease.

RECENT FINDINGS

Recent findings in C3 glomerulopathy (C3G) include: acute postinfectious glomerulonephritis is characterised by the presence of antifactor B antibodies; human leukocyte antigen type, but not rare complement gene variation, is associated with primary immunoglobulin-associated membranoproliferative GN and C3G. Immunohistochemistry in C3G shows that factor H related protein 5 (FHR5) is the most prevalent complement protein and correlates with kidney function. A multicentre study supported the use of mycophenolate mofetil (MMF) in C3G even after a propensity matching analysis. In immunoglobulin A nephropathy (IgAN) several studies have emphasised the importance of complement. Imbalances of circulating FH and FHR1 and FHR5, which interfere with the regulatory functions of FH, associate with IgAN. Immunohistochemistry has shown associations between glomerular FHR5 deposition and C3 activation; glomerular FHR5 associated with clinical markers of IgAN severity. Data also suggest the lectin complement pathway contributes to IgAN severity. We also discuss complement activation in thrombotic microangiopathy and other kidney diseases.

SUMMARY

Complement activity can be detected in a wide range of kidney diseases and this provides pathogenic insight and potential for therapy with the ongoing development of several drugs directed at complement activation.

Experimental evidence of pathogenic role of IgG autoantibodies in IgA nephropathy

BACKGROUND

IgA nephropathy is thought to be an autoimmune disease wherein galactose-deficient IgA1 (Gd-IgA1) is recognized by IgG autoantibodies, resulting in formation and renal accumulation of nephritogenic immune complexes. Although this hypothesis is supported by recent findings that, in renal immunodeposits of IgA nephropathy patients, IgG is enriched for Gd-IgA1-specific autoantibodies, experimental proof is still lacking.

METHODS

IgG isolated from sera of IgA nephropathy patients or produced as a recombinant IgG (rIgG) was mixed with human Gd-IgA1 to form immune complexes. IgG from healthy individuals served as a control. Nude and SCID mice were injected with human IgG and Gd-IgA1, in immune complexes or individually, and their presence in kidneys was ascertained by immunofluorescence. Pathologic changes in the glomeruli were evaluated by quantitative morphometry and exploratory transcriptomic profiling was performed by RNA-Seq.

RESULTS

Immunodeficient mice injected with Gd-IgA1 mixed with IgG autoantibodies from patients with IgA nephropathy, but not Gd-IgA1 mixed with IgG from healthy individuals, displayed IgA, IgG, and mouse complement C3 glomerular deposits and mesangioproliferative glomerular injury with hematuria and proteinuria. Un-complexed Gd-IgA1 or IgG did not induce pathological changes. Moreover, Gd-IgA1-rIgG immune complexes injected into immunodeficient mice induced histopathological changes characteristic of human disease. Exploratory transcriptome profiling of mouse kidney tissues indicated that these immune complexes altered gene expression of multiple pathways, in concordance with the changes observed in kidney biopsies of patients with IgA nephropathy.

CONCLUSIONS

This study provides the first in vivo evidence for a pathogenic role of IgG autoantibodies specific for Gd-IgA1 in the pathogenesis of IgA nephropathy.

Periostin Contributes to Immunoglobulin a Nephropathy by Promoting the Proliferation of Mesangial Cells: A Weighted Gene Correlation Network Analysis

Immunoglobulin A nephropathy (IgAN) is a known cause of end-stage kidney disease, but the pathogenesis and factors affecting prognosis are not fully understood. In the present study, we carried out weighted gene correlation network analysis (WGCNA) to identify hub genes related to the occurrence of IgAN and validated candidate genes in experiments using mouse mesangial cells (MMCs) and clinical specimens (kidney tissue from IgAN patients and healthy controls). We screened the GSE37460 and GSE104948 differentially expressed genes common to both datasets and identified periostin (POSTN) as one of the five key genes using the cytoHubba plugin of Cytoscape software and by receiver-operating characteristic curve analysis. The top 25% of genes in the GSE93798 dataset showing variable expression between IgAN and healthy tissue were assessed by WGCNA. The royalblue module in WGCNA was closely related to creatinine and estimated glomerular filtration rate (eGFR) in IgAN patients. POSTN had very high module membership and gene significance values for creatinine (0.82 and 0.66, respectively) and eGFR (0.82 and -0.67, respectively), indicating that it is a co-hub gene. In MMCs, POSTN was upregulated by transforming growth factor β1, and stimulation of MMCs with recombinant POSTN protein resulted in an increase in the level of proliferating cell nuclear antigen (PCNA) and a decrease in that of B cell lymphoma-associated X protein, which were accompanied by enhanced MMC proliferation. POSTN gene knockdown had the opposite effects. Immunohistochemical analysis of kidney tissue specimens showed that POSTN and PCNA levels were elevated, whereas the rate of apoptosis was reduced in IgAN patients relative to healthy controls. POSTN level in the kidney tissue of IgAN patients was positively correlated with creatinine level and negatively correlated with eGFR. Thus, POSTN promotes the proliferation of MCs to promote renal dysfunction in IgAN.

Differentiating Staphylococcus infection-associated glomerulonephritis and primary IgA nephropathy: a mass spectrometry-based exploratory study

Staphylococcus infection-associated glomerulonephritis (SAGN) and primary IgA nephropathy (IgAN) are separate disease entities requiring different treatment approaches. However, overlapping histologic features may cause a diagnostic dilemma. An exploratory proteomic study to identify potential distinguishing biomarkers was performed on formalin fixed paraffin embedded kidney biopsy tissue, using mass spectrometry (HPLC–MS/MS) (n = 27) and immunohistochemistry (IHC) (n = 64), on four main diagnostic groups—SAGN, primary IgAN, acute tubular necrosis (ATN) and normal kidney (baseline transplant biopsies). Spectral counts modeled as a negative binomial distribution were used for statistical comparisons and in silico pathway analysis. Analysis of variance techniques were used to compare groups and the ROC curve to evaluate classification algorithms. The glomerular proteomes of SAGN and IgAN showed remarkable similarities, except for significantly higher levels of monocyte/macrophage proteins in SAGN—mainly lysozyme and S100A9. This finding was confirmed by IHC. In contrast, the tubulointerstitial proteomes were markedly different in IgAN and SAGN, with a lower abundance of metabolic pathway proteins and a higher abundance of extracellular matrix proteins in SAGN. The stress protein transglutaminase-2 (TGM2) was also significantly higher in SAGN. IHC of differentially-expressed glomerular and tubulointerstitial proteins can be used to help discriminate between SAGN and IgAN in ambiguous cases.

RNA-Seq profiling of microdissected glomeruli identifies potential biomarkers for human IgA nephropathy

Few studies have examined gene expression changes occurring in the glomeruli of IgA nephropathy (IgAN) using a sensitive transcriptomic profiling method such as RNA sequencing (RNA-Seq). We collected glomeruli from biopsy specimens from patients with IgAN with relatively preserved kidney function (estimated glomerular filtration rate ≥ 60 mL·min^-1·1.73 m^-2 and urine protein-to-creatinine ratio < 3 g/g) and from normal kidney cortexes by hand microdissection and performed RNA-Seq. Differentially expressed genes were identified, and gene ontology term annotation and pathway analysis were performed. Immunohistochemical labeling and primary mesangial cell cultures were performed to confirm the findings of RNA-Seq analysis. Fourteen patients with IgAN and ten controls were included in this study. Glomerulus-specific genes were highly abundant. Principal component analysis showed clear separation between the IgAN and control groups. There were 2,497 differentially expressed genes, of which 1,380 were upregulated and 1,117 were downregulated (false discovery rate < 0.01). The enriched gene ontology terms included motility/migration, protein/vesicle transport, and immune system, and kinase binding was the molecular function overrepresented in IgAN. B cell signaling, chemokine signal transduction, and Fcγ receptor-mediated phagocytosis were the canonical pathways overrepresented. In vitro experiments confirmed that spleen tyrosine kinase (SYK), reported as upregulated in the IgAN transcriptome, was also upregulated in glomeruli from an independent set of patients with IgAN and that treatment with patient-derived IgA1 increased the expression of SYK in mesangial cells. In conclusion, transcriptomic profiling of the IgAN glomerulus provides insights in the intraglomerular pathophysiology of IgAN before it reaches profound kidney dysfunction. SYK may have a pathogenetic role in IgAN.

ST6Gal1 is up-regulated and associated with aberrant IgA1 glycosylation in IgA nephropathy: An integrated analysis of the transcriptome

Galactose-deficient IgA1 (Gd-IgA1) plays a crucial role in the development of Immunoglobulin A nephropathy (IgAN), however, the underlying pathogenic mechanisms driving Gd-IgA1 production in B cells are not well understood. In this study, RNA-seq analysis identified 337 down-regulated and 405 up-regulated genes in B cells from 17 patients with IgAN and 6 healthy controls. Among them, ST6Gal1, which was associated with IgAN in a previous genome-wide association study (GWAS), was up-regulated in IgAN and significantly positive correlated with elevated Gd-IgA1. In addition, we identified increased plasma ST6Gal1 levels in 100 patients with IgAN, which were associated with higher levels of proteinuria, plasma IgA, Gd-IgA1 levels, greater degrees of systemic complement activation including C3a, Bb, C4d, MAC and a lower proportion classified as C2 grade (crescent proportion ≥25%). Interesting, in vitro, recombinant ST6Gal1 (rST6Gal1) exposure reduced the production of Gd-IgA1 in cultured peripheral blood mononuclear cells from IgAN patients. rST6Gal1 stimuli also increased expression of C1GALT1, which were well-known proportional to the decrease in galactose deficiency of IgA1. In conclusions, we identified increased plasma ST6Gal1 levels and the association of ST6Gal1 with disease severity of IgAN. Additionally, rST6Gal1 administration in vitro increased expression of C1GALT1 and reduced the production of Gd-IgA1.

Early effects of first-line treatment with anti-interleukin-6 receptor antibody tocilizumab for chronic active antibody-mediated rejection in kidney transplantation

INTRODUCTION

Chronic active antibody-mediated rejection (cAMR) is a major determinant of late allograft failure. Rituximab/immunoglobulins (IVIg) + plasma exchange (PLEX) showed controversial results in cAMR treatment. Tocilizumab (TCZ), a humanized anti-interleukin 6 receptor antibody, has been recently used as rescue therapy in patients non-responsive to rituximab/IVIg/PLEX with favorable outcomes. Whether TCZ acts "per se" or requires a priming effect from previous treatments is currently unknown.

METHODS

Fifteen patients with cAMR were treated with TCZ as a first-line therapy and followed for a median time of 20.7 months.

RESULTS

Despite the majority of patients experiencing advanced transplant glomerulopathy (TG) at diagnosis (60% with cg3), glomerular filtration rate and proteinuria stabilized during the follow-up, with a significant reduction in donor-specific antibodies. Protocol biopsies after 6 months demonstrated significant amelioration of microvascular inflammation and no TG, C4d deposition, or IF/TA progression. Gene-expression and immunofluorescence analysis showed upregulation of three genes (TJP-1, AKR1C3, and CASK) involved in podocyte, mesangial, and tubular restoration.

CONCLUSION

Tocilizumab adopted as a first-line approach in cAMR was associated with early serological and histological improvements and functional stabilization even in advanced TG, suggesting a role for the use of TCZ alone with the avoidance of unnecessary previous immunosuppressants.

Identification of key genes, pathways and potential therapeutic agents for IgA nephropathy using an integrated bioinformatics analysis

PURPOSE

This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment.

METHODS

Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy.

RESULTS

A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy.

CONCLUSION

Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.

Fecal microbiota characteristics of Chinese patients with primary IgA nephropathy: a cross-sectional study

BACKGROUND

Growing evidence has shown that the gut-renal connection and gut microbiota dysbiosis play a critical role in immunoglobulin A nephropathy (IgAN). However, the fecal microbiome profile in Chinese patients with IgAN remains unknown. A cross-sectional study was designed for the first time to investigate the fecal microbiota compositions in patients with primary IgAN in China and to evaluate the relationship between the fecal microbiome and IgAN clinical presentation.

METHODS

Fecal samples were collected from 17 IgAN patients and 18 age-, sex-, and body mass index-matched healthy controls, and bacterial DNA was extracted for 16S ribosomal RNA gene sequencing targeting the V3-V4 region.

RESULTS

Fecal samples from the IgAN patients and healthy controls showed differences in gut microbiota community richness and compositions. Compared to the healthy controls, IgAN patients at the phylum level had an increased abundance of Fusobacteria, but a decreased abundance of Synergistetes. The significantly increased genera in the IgAN group were Escherichia-Shigella, Hungatella, and Eggerthella, all of which possess pathogenic potential. Furthermore, the genus Escherichia-Shigella was negatively associated with the estimated glomerular filtration rate (eGFR) but was positively associated with the urinary albumin-to-creatinine ratio (uACR). However, the genus rectale_group was present in the IgAN group with a low abundance and was negatively associated with the uACR. Functional analysis disclosed that infection-related pathways were enriched in the IgAN group.

CONCLUSIONS

We demonstrate that gut microbiota dysbiosis occurs in patients with IgAN, and that changes in gut bacterial populations are closely related to IgAN clinical features, suggesting that certain specific gut microbiota may be a potential therapeutic target for IgAN.

Renal progenitor cells modulated by angiotensin II receptor blocker (ARB) medication and differentiation towards podocytes in anti-thy1.1 nephritis

Background

Mesangial proliferative glomerulonephritis (MsPGN) is an epidemic disease with increasing occurrence. As important as mesangial cells, podocytes are key innate cells for MsPGN prognosis and recovery. Renal progenitor cells, located at the urinary pole (UP) of Bowman’s capsule (BC), could alleviate kidney injury through their capacity to differentiate into podocytes.

Methods

Seventy-two male rats were categorized randomly into the sham (n=24), untreated Thy-1 (n=24) and losartan-treated (n=24) groups. We administered vehicle or losartan (50 mg/kg by gavage) daily to treat rats with anti-thy1.1 nephritis, an ideal model to simulate human MsPGN. Two weeks after the intravenous injection of antibody, urinary protein and blood samples were analyzed, pathological changes were examined, the number of podocytes was determined, and renal progenitor cells were studied.

Results

Anti-thy1.1 nephritis was significantly alleviated after losartan treatment, as reported previously and as expected. Compared with the untreated Thy-1 group, the number of podocytes in the losartan group increased, and the area of renal progenitor cells significantly increased. The protein expression of components of the p-ERK pathway was determined during the development of renal progenitor cells differentiating into podocytes.

Conclusions

The data in this paper show the direct glomerular cell action of angiotensin II receptor blocker (ARB) treatment in improving outcomes in anti-thy1.1 nephritis. The positive effects of ARB medication on anti-thy1.1 nephritis were due to an increase in the number of renal epithelial progenitor cells (defined as PECs that expressed only stem cell markers without podocyte proteins).

Characterization of glomerular extracellular matrix in IgA nephropathy by proteomic analysis of laser-captured microdissected glomeruli

Background

IgA nephropathy (IgAN) involves mesangial matrix expansion, but the proteomic composition of this matrix is unknown. The present study aimed to characterize changes in extracellular matrix in IgAN.

Methods

In the present study we used mass spectrometry-based proteomics in order to quantitatively compare protein abundance between glomeruli of patients with IgAN (n = 25) and controls with normal biopsy findings (n = 15).

Results

Using a previously published paper by Lennon et al. and cross-referencing with the Matrisome database we identified 179 extracellular matrix proteins. In the comparison between IgAN and controls, IgAN glomeruli showed significantly higher abundance of extracellular matrix structural proteins (e.g periostin, vitronectin, and extracellular matrix protein 1) and extracellular matrix associated proteins (e.g. azurocidin, myeloperoxidase, neutrophil elastase, matrix metalloproteinase-9 and matrix metalloproteinase 2). Periostin (fold change 3.3) and azurocidin (3.0) had the strongest fold change between IgAN and controls; periostin was also higher in IgAN patients who progressed to ESRD as compared to patients who did not.

Conclusion

IgAN is associated with widespread changes of the glomerular extracellular matrix proteome. Proteins important in glomerular sclerosis or inflammation seem to be most strongly increased and periostin might be an important marker of glomerular damage in IgAN.

A Functional Landscape of CKD Entities From Public Transcriptomic Data

Introduction

To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.

Methods

We integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure.

Results

We performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib.

Conclusion

These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

From expression footprints to causal pathways: contextualizing large signaling networks with CARNIVAL

While gene expression profiling is commonly used to gain an overview of cellular processes, the identification of upstream processes that drive expression changes remains a challenge. To address this issue, we introduce CARNIVAL, a causal network contextualization tool which derives network architectures from gene expression footprints. CARNIVAL (CAusal Reasoning pipeline for Network identification using Integer VALue programming) integrates different sources of prior knowledge including signed and directed protein-protein interactions, transcription factor targets, and pathway signatures. The use of prior knowledge in CARNIVAL enables capturing a broad set of upstream cellular processes and regulators, leading to a higher accuracy when benchmarked against related tools. Implementation as an integer linear programming (ILP) problem guarantees efficient computation. As a case study, we applied CARNIVAL to contextualize signaling networks from gene expression data in IgA nephropathy (IgAN), a condition that can lead to chronic kidney disease. CARNIVAL identified specific signaling pathways and associated mediators dysregulated in IgAN including Wnt and TGF-β, which we subsequently validated experimentally. These results demonstrated how CARNIVAL generates hypotheses on potential upstream alterations that propagate through signaling networks, providing insights into diseases.

A Novel Role for GATA3 in Mesangial Cells in Glomerular Development and Injury

BACKGROUND

GATA3 is a dual-zinc finger transcription factor that regulates gene expression in many developing tissues. In the kidney, GATA3 is essential for ureteric bud branching, and mice without it fail to develop kidneys. In humans, autosomal dominant GATA3 mutations can cause renal aplasia as part of the hypoparathyroidism, renal dysplasia, deafness (HDR) syndrome that includes mesangioproliferative GN. This suggests that GATA3 may have a previously unrecognized role in glomerular development or injury.

METHODS

To determine GATA3's role in glomerular development or injury, we assessed GATA3 expression in developing and mature kidneys from Gata3 heterozygous (⁺/-) knockout mice, as well as injured human and rodent kidneys.

RESULTS

We show that GATA3 is expressed by FOXD1 lineage stromal progenitor cells, and a subset of these cells mature into mesangial cells (MCs) that continue to express GATA3 in adult kidneys. In mice, we uncover that GATA3 is essential for normal glomerular development, and mice with haploinsufficiency of Gata3 have too few MC precursors and glomerular abnormalities. Expression of GATA3 is maintained in MCs of adult kidneys and is markedly increased in rodent models of mesangioproliferative GN and in IgA nephropathy, suggesting that GATA3 plays a critical role in the maintenance of glomerular homeostasis.

CONCLUSIONS

These results provide new insights on the role GATA3 plays in MC development and response to injury. It also shows that GATA3 may be a novel and robust nuclear marker for identifying MCs in tissue sections.

Identification of primary genes in glomeruli compartment of immunoglobulin A nephropathy by bioinformatic analysis

The current study is aimed to explore the specific genes which are responsible for the manifestation of Immunoglobulin A nephropathy (IgAN). Gene expression profiles GSE37460, GSE93798 and GSE104948 were analyzed using biological informatics methods to identify differentially expressed genes (DEGs) in IgAN glomeruli samples which were then compared to normal control samples. Subsequently, the DEGs were overlapped to explore genes with significant expression in at least two profiles. Finally, the enrichment analysis was conducted and the protein-protein interaction (PPI) network was constructed for the overlapping DEGs. A total of 28 genes were up-regulated and 10 genes were down-regulated. The up-regulated genes including CD44 and FN1 were chiefly involved in extracellular matrix receptors interaction pathway. In addition, CX3CR1 and CCL4 were associated with chemokine signaling pathway. ITGB2, PTPRC, FN1, and FCER1G were hub genes with a high degree of interaction in the PPI network. Therefore, this study identified many significant genes associated with extracellular matrix expansion and inflammatory mechanism which may be the novel biomarker and target candidates in IgAN.

GPRC5b Modulates Inflammatory Response in Glomerular Diseases via NF-κB Pathway

BACKGROUND

Inflammatory processes play an important role in the pathogenesis of glomerulopathies. Finding novel ways to suppress glomerular inflammation may offer a new way to stop disease progression. However, the molecular mechanisms that initiate and drive inflammation in the glomerulus are still poorly understood.

METHODS

We performed large-scale gene expression profiling of glomerulus-associated G protein-coupled receptors (GPCRs) to identify new potential therapeutic targets for glomerulopathies. The expression of Gprc5b in disease was analyzed using quantitative PCR and immunofluorescence, and by analyzing published microarray data sets. In vivo studies were carried out in a podocyte-specific Gprc5b knockout mouse line. Mechanistic studies were performed in cultured human podocytes.

RESULTS

We identified an orphan GPCR, Gprc5b, as a novel gene highly enriched in podocytes that was significantly upregulated in common human glomerulopathies, including diabetic nephropathy, IgA nephropathy, and lupus nephritis. Similar upregulation of Gprc5b was detected in LPS-induced nephropathy in mice. Studies in podocyte-specific Gprc5b knockout mice showed that Gprc5b was not essential for normal development of the glomerular filtration barrier. However, knockout mice were partially protected from LPS-induced proteinuria and recruitment of inflammatory cells. Mechanistically, RNA sequencing in Gprc5b knockouts mice and experiments in cultured human podocytes showed that Gpr5cb regulated inflammatory response in podocytes via NF-κB signaling.

CONCLUSIONS

GPRC5b is a novel podocyte-specific receptor that regulates inflammatory response in the glomerulus by modulating the NF-κB signaling pathway. Upregulation of Gprc5b in human glomerulopathies suggests that it may play a role in their pathogenesis.

Integrated bioinformatics analysis reveals novel hub genes closely associated with pathological mechanisms of immunoglobulin A nephropathy

Immunoglobulin A (IgA) nephropathy (IgAN) is the most common glomerular disease. The major pathological changes associated with it affect cell proliferation, fibrosis, apoptosis, inflammation and extracellular matrix (ECM) organization. However, the molecular events underlying IgAN remain to be fully elucidated. In the present study, an integrated bioinformatics analysis was applied to further explore novel potential gene targets for IgAN. The mRNA expression profile datasets GSE93798 and GSE37460 were downloaded from the Gene Expression Omnibus database. After data preprocessing, differentially expressed genes (DEGs) were identified. Gene Ontology (GO) enrichment analysis of DEGs was performed. Protein-protein interaction (PPI) networks of the DEGs were built with the STRING online search tool and visualized by using Cytoscape, and hub genes were identified through the degree of connectivity in the PPI. The hub genes were subjected to Kyoto Encyclopedia of Genes and Genomes pathway analysis, and co-expression analysis was performed. A total of 298 DEGs between IgAN and control groups were identified, and 148 and 150 of these DEGs were upregulated and downregulated, respectively. The DEGs were enriched in distinct GO terms for Biological Process, including cell growth, epithelial cell proliferation, ERK1 and ERK2 cascades, regulation of apoptotic signaling pathway and ECM organization. The top 10 hub genes were then screened from the PPI network by Cytoscape. As novel hub genes, Fos proto-oncogene, AP-1 transcription factor subunit and early growth response 1 were determined to be closely associated with apoptosis and cell proliferation in IgAN. Tumor protein 53, integrin subunit β2 and fibronectin 1 may also be involved in the occurrence and development of IgAN. Co-expression analysis suggested that these hub genes were closely linked with each other. In conclusion, the present integrated bioinformatics analysis provided novel insight into the molecular events and novel candidate gene targets of IgAN.

Inflammatory Mediators and Renal Fibrosis

Renal inflammation is the initial, healthy response to renal injury. However, prolonged inflammation promotes the fibrosis process, which leads to chronic pathology and eventually end-stage kidney disease. There are two major sources of inflammatory cells: first, bone marrow-derived leukocytes that include neutrophils, macrophages, fibrocytes and mast cells, and second, locally activated kidney cells such as mesangial cells, podocytes, tubular epithelial cells, endothelial cells and fibroblasts. These activated cells produce many profibrotic cytokines and growth factors that cause accumulation and activation of myofibroblasts, and enhance the production of the extracellular matrix. In particular, activated macrophages are key mediators that drive acute inflammation into chronic kidney disease. They produce large amounts of profibrotic factors and modify the microenvironment via a paracrine effect, and they also transdifferentiate to myofibroblasts directly, although the origin of myofibroblasts in the fibrosing kidney remains controversial. Collectively, understanding inflammatory cell functions and mechanisms during renal fibrosis is paramount to improving diagnosis and treatment of chronic kidney disease.

Artificial intelligence, physiological genomics, and precision medicine

Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.