Molecular characterization of m6A RNA methylation regulators with features of immune dysregulation in IgA nephropathy.

The role of RNA N6-methyladenosine (m6A) modification in immunity is being elucidated. This study aimed to explore the potential association between m6A regulators and the immune microenvironment in IgA nephropathy (IgAN). The expression profiles of 24 m6A regulators in 107 IgAN patients were obtained from the Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis were utilized to construct a model for distinguishing IgAN from control samples. Based on the expression levels of m6A regulators, unsupervised clustering was used to identify m6A-induced molecular clusters in IgAN. Gene set enrichment analysis (GSEA) and immunocyte infiltration among different clusters were examined. The gene modules with the highest correlation for each of the three clusters were identified by weighted gene co-expression network analysis (WGCNA). A model containing 10 m6A regulators was developed using LASSO and logistic regression analyses. Three molecular clusters were determined using consensus clustering of 24 m6A regulators. A decrease in the expression level of YTHDF2 in IgAN samples was significantly negatively correlated with an increase in resting natural killer (NK) cell infiltration and was positively correlated with the abundance of M2 macrophage infiltration. The risk scores calculated by the nomogram were significantly higher for cluster-3, and the expression levels of m6A regulators in this cluster were generally low. Immunocyte infiltration and pathway enrichment results for cluster-3 differed significantly from those for the other two clusters. Finally, the expression of YTHDF2 was significantly decreased in IgAN based on immunohistochemical staining. This study demonstrated that m6A methylation regulators play a significant role in the regulation of the immune microenvironment in IgAN. Based on m6A regulator expression patterns, IgAN can be classified into multiple subtypes, which might provide additional insights into novel therapeutic methods for IgAN.

Genome-wide analysis of long noncoding RNAs as cis-acting regulators of transcription factor-encoding genes in IgA nephropathy.

BACKGROUND: IgA nephropathy (IgAN) is the most common form of primary glomerulonephritis in the world, but the disease pathogenesis noncoding is yet to be elucidated. Previous studies have revealed regulatory functions for long noncoding RNA (lncRNA) in various diseases; however, the roles of lncRNA in IgAN and regulation of transcription factors (TFs) have been scarcely investigated. METHODS: Renal tissue samples (n = 5) from patients with IgAN and control samples (n = 4) were collected and RNA sequencing (RNA-seq) was performed. Four software programs were employed for lncRNA prediction. GO (Gene Ontology)/KEGG (Kyoto Encyclopedia of Genes and Genomes) were employed for analysis of the identified differentially expressed genes (DEGs). A regulatory network model of DE lncRNA-TF-DEG was developed, and the levels of expression of key lncRNAs, TFs, and corresponding target genes were assessed using qRT-PCR and immunofluorescence. RESULTS: The current study identified 674 upregulated and 1,011 downregulated DE mRNAs and 260 upregulated and 232 downregulated DE lncRNAs in IgAN samples compared with control samples. The upregulated DE mRNAs showed enrichment in cell adhesion and collagen glial fiber organization pathways. The DE lncRNAs-DE mRNAs showing co-expression are associated with transmembrane transport. A novel regulatory network model of lncRNA-TF-DEG has been developed. This study identified seven TFs that are cis-regulated by 6 DE lncRNAs, and show co-expression with 132 DEGs (correlation coefficient ≥ 0.8, P ≤ 0.01), generating 158 pairs that showed co-expression. The lncRNAs NQO1-DT and RP5-1057120.6 were found to be highly expressed in IgAN samples. The TFs vitamin D Receptor (VDR) and NFAT5, along with their target genes were also aberrantly expressed. CONCLUSION: Key lncRNAs and TFs centrally associated with IgAN have been identified in this study. A regulatory network model of lncRNA-TF-mRNA was constructed. Further studies on the genes identified herewith could provide insight into the pathogenesis of IgAN.

[Current status and prospects of genetic research on IgA nephropathy].

IgA nephropathy is the most common primary glomerulonephritis worldwide, and genetic factors may play an important role in its pathogenesis. Following candidate gene association analysis and genome-wide linkage study, genome-wide association studies (GWAS) have found multiple susceptibility genes related to the pathogenesis and clinical phenotype of IgA nephropathy. Meanwhile, structural variation and epigenetic changes are also closely related to IgA nephropathy. Genetic variants have been found to explain about 11% of its heritability. In the current era of genomic medicine, how to find more susceptible genes/loci, whole genome sequencing studies (WGS) provide clues to further understand the genetic variation of IgA nephropathy. How to find the cell type-specific susceptibility genes associated with IgA nephropathy, multi-omics studies will conduct comprehensive analysis via single-cell sequencing, expression quantitative trait locus (eQTL) and genomics to find the pathogenic genes and offer insights into the development of targeted drugs, which will be the trend and direction of future research.

From genomic insights to clinical hope: Targeting NEU1 in IgA nephropathy.

BACKGROUND: IgA Nephropathy (IgAN), the primary form of glomerulonephritis, presents significant clinical challenges due to its obscure pathogenesis and lack of targeted treatments. We conducted a proteome-wide Mendelian randomization (MR) study to identify therapeutic targets for IgAN. METHODS: Utilizing a plasma proteome dataset comprising 4907 blood plasma proteins as the exposure variable, and renal biopsy-confirmed IgAN cases as the outcome, this study employed MR to pinpoint proteins potentially pathogenic to IgAN. The robustness of our findings was affirmed through external dataset validation, reverse causation testing, and Bayesian colocalization analysis. Additionally, we conducted phenotypic scanning and analyzed downstream metabolites to investigate candidate proteins's biological function. RESULTS: In our study, a significant association was identified between an increase in neuraminidase 1 (NEU1) expression and the risk of IgAN. Specifically, a one standard deviation increase in NEU1 expression was associated with an odds ratio of 11.80 for the development of IgAN (95% confidence interval: 4.03-34.54). This association was substantiated across various statistical models and external validations. Colocalization analysis indicated a shared causal variant between NEU1 expression and IgAN. Furthermore, an increased influenza risk associated with NEU1 was observed, supporting the therapeutic potential of NEU1 inhibitors for IgAN. However, our study found no significant role for neuraminic acid-related metabolites in IgAN's development, suggesting an independent pathway for NEU1's influence. CONCLUSION: This study identifies NEU1 as a promising therapeutic target for IgAN, backed by robust genetic evidence. Future research should explore NEU1's therapeutic potential in diverse populations and clinical scenarios, further establishing its role in IgAN.

Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy.

The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.

The gut microbiota posttranslationally modifies IgA1 in autoimmune glomerulonephritis.

Mechanisms underlying the disruption of self-tolerance in acquired autoimmunity remain unclear. Immunoglobulin A (IgA) nephropathy is an acquired autoimmune disease where deglycosylated IgA1 (IgA subclass 1) auto-antigens are recognized by IgG auto-antibodies, forming immune complexes that are deposited in the kidneys, leading to glomerulonephritis. In the intestinal microbiota of patients with IgA nephropathy, there was increased relative abundance of mucin-degrading bacteria, including Akkermansia muciniphila. IgA1 was deglycosylated by A. muciniphila both in vitro and in the intestinal lumen of mice. This generated neo-epitopes that were recognized by autoreactive IgG from the sera of patients with IgA nephropathy. Mice expressing human IgA1 and the human Fc α receptor I (α1KI-CD89tg) that underwent intestinal colonization by A. muciniphila developed an aggravated IgA nephropathy phenotype. After deglycosylation of IgA1 by A. muciniphila in the mouse gut lumen, IgA1 crossed the intestinal epithelium into the circulation by retrotranscytosis and became deposited in the glomeruli of mouse kidneys. Human α-defensins-a risk locus for IgA nephropathy-inhibited growth of A. muciniphila in vitro. A negative correlation observed between stool concentration of α-defensin 6 and quantity of A. muciniphila in the guts of control participants was lost in patients with IgA nephropathy. This study demonstrates that gut microbiota dysbiosis contributes to generation of auto-antigens in patients with IgA nephropathy and in a mouse model of this disease.

Sparsentan ameliorates glomerular hypercellularity and inflammatory-gene networks induced by IgA1-IgG immune complexes in a mouse model of IgA nephropathy.

IgA nephropathy (IgAN) is characterized by glomerular deposition of immune complexes (ICs) consisting of IgA1 with O-glycans deficient in galactose (Gd-IgA1) and Gd-IgA1-specific IgG autoantibodies. These ICs induce kidney injury, and in the absence of disease-specific therapy, up to 40% of patients with IgAN progress to kidney failure. IgA1 with its clustered O-glycans is unique to humans, which hampered development of small-animal models of IgAN. Here, we used a model wherein engineered ICs (EICs) formed from human Gd-IgA1 and recombinant human IgG autoantibody are injected into nude mice to induce glomerular injury mimicking human IgAN. In this model, we assessed the protective effects of sparsentan, a single-molecule dual endothelin angiotensin receptor antagonist (DEARA) versus vehicle on EIC-induced glomerular proliferation and dysregulation of gene expression in the kidney. Oral administration of sparsentan (60 or 120 mg/kg daily) to mice intravenously injected with EIC attenuated the EIC-induced glomerular hypercellularity. Furthermore, analysis of changes in the whole kidney transcriptome revealed that key inflammatory and proliferative biological genes and pathways that are upregulated in this EIC model of IgAN were markedly reduced by sparsentan, including complement genes, integrin components, members of the mitogen-activated protein kinase family, and Fc receptor elements. Partial overlap between mouse and human differentially expressed genes in IgAN further supported the translational aspect of the immune and inflammatory components from our transcriptional findings. In conclusion, our data indicate that in the mouse model of IgAN, sparsentan targets immune and inflammatory processes leading to protection from mesangial hypercellularity.NEW & NOTEWORTHY The mechanisms by which deposited IgA1 immune complexes cause kidney injury during early phases of IgA nephropathy are poorly understood. We used an animal model we recently developed that involves IgA1-IgG immune complex injections and determined pathways related to the induced mesangioproliferative changes. Treatment with sparsentan, a dual inhibitor of endothelin type A and angiotensin II type 1 receptors, ameliorated the induced mesangioproliferative changes and the associated alterations in the expression of inflammatory genes and networks.

Unveiling biomarkers and therapeutic targets in IgA nephropathy through large-scale blood transcriptome analysis.

INTRODUCTION: IgA nephropathy (IgAN) is the most prevalent form of glomerulonephritis. Unfortunately, molecular biomarkers for IgAN derived from omics studies are still lacking. This research aims to identify critical genes associated with IgAN through large-scale blood transcriptome analysis. METHODS: We constructed novel blood transcriptome profiles from peripheral blood mononuclear cells (PBMCs) of 53 Chinese IgAN patients and 28 healthy individuals. Our analysis included GO, KEGG, and GSEA for biological pathways. We analyzed immune cell profiles with CIBERSORT and constructed PPI networks with STRING, visualized in Cytoscape. Key differentially expressed genes (DEGs) were identified using CytoHubba and MCODE. We assessed the correlation between gene expressions and clinical data to evaluate clinical significance and identified hub genes through machine learning, validated with an open-access dataset. Potential drugs were explored using the CMap database. RESULTS: We identified 333 DEGs between IgAN patients and healthy controls, mainly related to immune response and inflammation. Key pathways included NK cell mediated cytotoxicity, complement and coagulation cascades, antigen processing, and B cell receptor signaling. Cytoscape revealed 16 clinically significant genes (including KIR2DL1, KIR2DL3, VISIG4, C1QB, and C1QC, associated with sub-phenotype and prognosis). Machine learning identified two hub genes (KLRC1 and C1QB) for a diagnostic model of IgAN with 0.92 accuracy, validated at 1.00 against the GSE125818 dataset. Sirolimus, calcifediol, and efaproxiral were suggested as potential therapeutic agents. CONCLUSION: Key DEGs, particularly VISIG4, KLRC1, and C1QB, emerge as potential specific markers for IgAN, paving the way for future targeted personalized treatment options.

Protective effect of modified Huangqi Chifeng decoction on immunoglobulin A nephropathy through toll-like receptor 4/myeloid differentiation factor 88/nuclear factor-kappa B signaling pathway.

OBJECTIVE: To examine the nephroprotective mechanism of modified Huangqi Chifeng decoction (, MHCD) in immunoglobulin A nephropathy (IgAN) rats. METHODS: To establish the IgAN rat model, the bovine serum albumin, lipopolysaccharide, and carbon tetrachloride 4 method was employed. The rats were then randomly assigned to the control, model, telmisartan, and high-, medium-, and low-dose MHCD groups, and were administered the respective treatments via intragastric administration for 8 weeks. The levels of 24-h urinary protein, serum creatinine (CRE), and blood urea nitrogen (BUN) were measured in each group. Pathological alterations were detected. IgA deposition was visualized through the use of immunofluorescence staining. The ultrastructure of the kidney was observed using a transmission electron microscope. The expression levels of interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), and transforming growth factor-ß1 (TGF-ß1) were examined by immunohistochemistry and quantitative polymerase chain reaction. Levels of toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), and nuclear factor-kappa B (NF-κB) P65, were examined by immunohistochemistry, Western blotting, and quantitative polymerase chain reaction. RESULTS: The 24-h urine protein level in each group increased significantly at week 6, and worsen from then on. But this process can be reversed by treatments of telmisartan, and high-, medium-, and low-dose of MHCD, and these treatments did not affect renal function. Telmisartan, and high-, and medium-dose of MHCD reduced IgA deposition. Renal histopathology demonstrated the protective effect of high-, medium-, and low-dose of MHCD against kidney injury. The expression levels of MCP-1, IL-6, and TGF-ß1 in kidney tissues were downregulated by low, medium and high doses of MHCD treatment. Additionally, treatment of low, medium and high doses of MHCD decreased the protein and mRNA levels of TLR4, MyD88, and NF-κB. CONCLUSIONS: MHCD exerted nephroprotective effects on IgAN rats, and MHCD regulated the expressions of key targets in TLR4/MyD88/NF-κB signaling pathway, thereby alleviating renal inflammation by inhibiting MCP-1, IL-6 expressions, and ameliorating renal fibrosis by inhibiting TGF-ß1 expression.

Charting new frontiers in IgA nephropathy: a paradigm shift toward precision medicine and early intervention?

Advancements in glomerular transcriptomics offer a promising avenue toward precision medicine in IgA nephropathy. Traditional prognostic biomarkers, including proteinuria, blood pressure, and histomorphometry, fall short at capturing the complexity of IgA nephropathy and can only crudely guide therapeutic decisions. This issue needs to be addressed urgently as pathway-specific treatments become available. Glomerular transcriptomics, although technically challenging, offers an opportunity to refine prognostic precision and identify therapeutic targets, even when apparent risk of disease progression is low.

A cluster of type I interferon-regulated genes associates with disease activity and prognosis in patients with IgA nephropathy.

The exact pathogenesis of IgA nephropathy (IgAN) is complex and so far, not well defined. Since it has been shown that microbial infections could induce high levels of type I interferon (IFN-I) and there is an evident link between mucosal infection and gross hematuria in IgAN, we hypothesized that IFN-I may play a role in the pathogenic process. In this study, we investigated the type I interferon status in IgAN based on the expression of 17 IFN-regulated genes (IRGs) in whole blood from 59 IgAN patients in a cross-sectional study, of which 34 patients followed longitudinally. Analysis of the IFN-score showed that there was a significant elevated IFN-score in the IgAN patients compared with healthy controls (n = 28, p = 9.80 × 10-3), and we observed an elevated IFN-score in the group with less tubular atrophy/interstitial fibrosis (p = 1.07 × 10-2) and with a lower proportion of mesangial hypercellularity (p = 1.23 × 10-2). In the longitudinal analysis, Cox regression analysis revealed that a higher IFN level was associated with a better renal outcome in IgAN after adjustments for gender and age (hazard ratio, 0.90; 95 % confidence interval, 0.81 to 0.97; p = 4.20 × 10-2). In conclusion, our finding suggested that IFN score may represent a novel type of biomarker in IgAN, which requires further exploration on its mechanism and therapeutic targeting.

Identifying functional subtypes of IgA nephropathy based on three machine learning algorithms and WGCNA.

BACKGROUND: IgA nephropathy (IgAN) is one of the most common primary glomerulonephritis, which is a significant cause of renal failure. At present, the classification of IgAN is often limited to pathology, and its molecular mechanism has not been established. Therefore we aim to identify subtypes of IgAN at the molecular level and explore the heterogeneity of subtypes in terms of immune cell infiltration, functional level. METHODS: Two microarray datasets (GSE116626 and GSE115857) were downloaded from GEO. Differential expression genes (DEGs) for IgAN were screened with limma. Three unsupervised clustering algorithms (hclust, PAM, and ConsensusClusterPlus) were combined to develop a single-sample subtype random forest classifier (SSRC). Functional subtypes of IgAN were defined based on functional analysis and current IgAN findings. Then the correlation between IgAN subtypes and clinical features such as eGFR and proteinuria was evaluated by using Pearson method. Subsequently, subtype heterogeneity was verified by subtype-specific modules identification based on weighted gene co-expression network analysis(WGCNA) and immune cell infiltration analysis based on CIBERSORT algorithm. RESULTS: We identified 102 DEGs as marker genes for IgAN and three functional subtypes namely: viral-hormonal, bacterial-immune and mixed type. We screened seventeen genes specific to viral hormonal type (ATF3, JUN and FOS etc.), and seven genes specific to bacterial immune type (LIF, C19orf51 and SLPI etc.). The subtype-specific genes showed significantly high correlation with proteinuria and eGFR. The WGCNA modules were in keeping with functions of the IgAN subtypes where the MEcyan module was specific to the viral-hormonal type and the MElightgreen module was specific to the bacterial-immune type. The results of immune cell infiltration revealed subtype-specific cell heterogeneity which included significant differences in T follicular helper cells, resting NK cells between viral-hormone type and control group; significant differences in eosinophils, monocytes, macrophages, mast cells and other cells between bacterial-immune type and control. CONCLUSION: In this study, we identified three functional subtypes of IgAN for the first time and specific expressed genes for each subtype. Then we constructed a subtype classifier and classify IgAN patients into specific subtypes, which may be benefit for the precise treatment of IgAN patients in future.

Urinary exosomal miRNA-451a can be used as a potential noninvasive biomarker for diagnosis, reflecting tubulointerstitial damage and therapeutic response in IgA nephropathy.

To investigate the potential clinical value of urinary exosomal (uE) miR-451a as a biomarker for IgAN, urinary exosomes were isolated from 40 patients with IgAN, 30 patients with primary renal diseases without IgA as disease controls (non-IgAN group) and 21 healthy controls (HCs). The expression of miR-451a within exosomes was examined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). uE miR-451a was significantly upregulated in patients with IgAN compared to non-IgAN and HCs. The uE miR-451a level was positively correlated with the change in eGFR and negatively correlated with serum creatinine, urinary macrophage migration inhibitory factor (MIF), interleukin-6 (IL-6) and tumor necrosis factor (TNF-α). A dual-luciferase reporter assay confirmed that MIF was a direct target of miR-451a. Receiver operating characteristic (ROC) curve analysis revealed that the expression of uE miR-451a showed potential diagnostic value for IgAN. Additionally, the uE miR-451a level could distinguish patients with IgAN with mild tubular atrophy/interstitial fibrosis from those with severe tubular atrophy/interstitial fibrosis. After a mean follow-up of 14.2 months, the levels of eGFR loss (ml/min/1.73 m2/year) were negatively correlated with baseline miR-451a. The levels of baseline miR-451a in the complete remission group were significantly higher than those in the non-complete remission group. uE miR-451a expression was significantly elevated in patients with IgA nephropathy and may serve as a potential biomarker for the diagnosis of IgAN and evaluation of tubulointerstitial damage, while the baseline levels of uE miR-451a may be predictors of therapeutic efficacy and disease progression.

Molecular Pathogenic Mechanisms of IgA Nephropathy Secondary to COVID-19 mRNA Vaccination.

INTRODUCTION: Accumulating evidence has disclosed that IgA nephropathy (IgAN) could present shortly after the second dose of COVID-19 mRNA vaccine. However, the undying mechanism remains unclear and we aimed to investigate the potential molecular mechanisms. METHODS: We downloaded gene expression datasets of COVID-19 mRNA vaccination (GSE201535) and IgAN (GSE104948). Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to identify co-expression modules related to the second dose of COVID-19 mRNA vaccination and IgAN. Differentially expressed genes (DEGs) were screened, and a transcription factor (TF)-miRNA regulatory network and protein-drug interaction were constructed for the shared genes. RESULTS: WGCNA identified one module associated with the second dose of COVID-19 mRNA vaccine and four modules associated with IgAN. Gene ontology (GO) analyses revealed enrichment of cell cycle-related processes for the COVID-19 mRNA vaccine hub genes and immune effector processes for the IgAN hub genes. We identified 74 DEGs for the second dose of COVID-19 mRNA vaccine and 574 DEGs for IgAN. Intersection analysis with COVID-19 vaccine-related genes led to the identification of two shared genes, TOP2A and CEP55. The TF-miRNA network analysis showed that hsa-miR-144 and ATF1 might regulate the shared hub genes. CONCLUSIONS: This study provides insights into the common pathogenesis of COVID-19 mRNA vaccination and IgAN. The identified pivotal genes may offer new directions for further mechanistic studies of IgAN secondary to COVID-19 mRNA vaccination.

Liquid Biopsy: A New Avenue for the Diagnosis of Kidney Disease: Diabetic Kidney Disease, Renal Cancer, and IgA Nephropathy.

Kidney diseases are some of the most common healthcare problems. As the population of elderly individuals with concurrent health conditions continues to rise, there will be a heightened occurrence of these diseases. Due to the renal condition being one of the longevity predictors, early diagnosis of kidney dysfunction plays a crucial role. Currently, prevalent diagnostic tools include laboratory tests and kidney tissue biopsies. New technologies, particularly liquid biopsy and new detection biomarkers, hold promise for diagnosing kidney disorders. The aim of this review is to present modern diagnostic methods for kidney diseases. The paper focuses on the advances in diagnosing three common renal disorders: diabetic kidney disease, renal cancer, and immunoglobulin A nephropathy. We highlight the significance of liquid biopsy and epigenetic changes, such as DNA methylation, microRNA, piRNAs, and lncRNAs expression, or single-cell transcriptome sequencing in the assessment of kidney diseases. This review underscores the importance of early diagnosis for the effective management of kidney diseases and investigates liquid biopsy as a promising approach.

Identification of inflammatory biomarkers in IgA nephropathy using the NanoString technology: a validation study in Caucasians.

OBJECTIVE AND DESIGN: Immunoglobulin A nephropathy (IgAN) is a kidney disease characterized by the accumulation of IgA deposits in the glomeruli of the kidney, leading to inflammation and damage to the kidney. The inflammatory markers involved in IgAN remain to be defined. Gene expression analysis platforms, such as the NanoString nCounter system, are promising screening and diagnostic tools, especially in oncology. Still, their role as a diagnostic and prognostic tool in IgAN remains scarce. In this study, we aimed to validate the use of NanoString technology to identify potential inflammatory biomarkers involved in the progression of IgAN. SUBJECTS: A total of 30 patients with biopsy-proven IgAN and 7 cases of antineutrophil cytoplasmic antibody (ANCA)-associated pauci-immune glomerulonephritis were included for gene expression measurement. For the immunofluorescence validation experiments, a total of 6 IgAN patients and 3 controls were included. METHODS: Total RNA was extracted from formalin-fixed paraffin-embedded kidney biopsy specimens, and a customized 48-plex human gene CodeSet was used to study 29 genes implicated in different biological pathways. Comparisons in gene expression were made between IgAN and ANCA-associated pauci-immune glomerulonephritis patients to delineate an expression profile specific to IgAN. Gene expression was compared between patients with low and moderate risk of progression. Genes for which RNA expression was associated with disease progression were analyzed for protein expression by immunofluorescence and compared with controls. RESULTS: IgAN patients had a distinct gene expression profile with decreased expression in genes IL-6, INFG, and C1QB compared to ANCA patients. C3 and TNFRSF1B were identified as potential biomarkers for IgAN progression in patients early in their disease course. Protein expression for those 2 candidate genes was upregulated in IgAN patients compared to controls. Expression of genes implicated in fibrosis (PTEN, CASPASE 3, TGM2, TGFB1, IL2, and TNFRSF1B) was more pronounced in IgAN patients with severe fibrosis compared to those with none. CONCLUSIONS: Our findings validate our NanoString mRNA profiling by examining protein expression levels of two candidate genes, C3 and TNFRSF1B, in IgAN patients and controls. We also identified several upregulated mRNA transcripts implicated in the development of fibrosis that may be considered fibrotic markers within IgAN patients.

Pathologic-genomic correlation identified a novel variant in FN1 and established the diagnosis of recurrent fibronectin glomerulopathy in the kidney allograft.

Fibronectin glomerulopathy is a rare inherited kidney disease, characterized by abnormal accumulation of fibronectin in the glomeruli. We report an exceptional case of recurrent fibronectin glomerulopathy first diagnosed in the kidney allograft. The presence of IgA staining in the native kidney biopsy and the reported family history of IgA nephropathy had led to initial pretransplant diagnosis of IgA nephropathy. At 4.5 years posttransplant, the patient presented with kidney insufficiency and minimal proteinuria. The allograft biopsy revealed glomerular deposits with very weak staining for immunoglobulins and vague filamentous material. Immunostaining for fibronectin was positive, and genetic studies showed a variant of unknown significance in the fibronectin 1 gene. Proteomic analyses of the glomeruli in the native kidney biopsy demonstrated large amount of fibronectin with abundant accumulation of the peptide synthesized by the detected variant. These findings established the diagnosis of recurrent fibronectin glomerulopathy secondary to a novel variant in the fibronectin 1 gene. This report sheds light on recurrent fibronectin glomerulopathy in the allograft, highlights the diagnostic pitfalls of the disease, and underscores the importance of pathologic-genomic correlation to establish the correct diagnosis.