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C3G signal in native and allograft

ABSTRACT: C3 glomerulopathy (C3G), which encompasses C3 glomerulonephritis (C3GN) and dense deposit disease (DDD), results from dysregulation of the alternative complement pathway. Data on disease recurrence after kidney transplantation is limited, and details on histologic features of recurrent C3G are scarce. We aimed to evaluate C3G recurrence in the allograft, with a focus on histologic presentation and progression. We retrospectively analyzed 18 patients with native kidney failure attributed to C3G (12 C3GN and 6 DDD) who received a kidney transplant from January 2016 to January 2023. Demographic, genetic, clinical, and histologic data were studied. The Nanostring 770 genes immune profiling panel was used for transcriptomic analysis. Disease recurrence was the primary outcome. During a median follow-up period of 37 (18, 56) months, C3G recurrence occurred in 16 (89%) of patients (11 with C3GN and 5 with DDD), at a median of 33 (13, 141) days post-transplantation. Over a third (38%) of recurrent cases were detected in protocol biopsies, and only 31% of patients presented with >300 mg/g of proteinuria. Recurrence in index biopsies was mainly established through a combination of immunofluorescence and electron microscopy findings, while it showed only subtle histologic alterations and no characteristic transcriptomic signals. Over time, histologic chronicity indices increased, but all allografts were functioning at the end of follow-up. Patients with recurrence of C3GN and DDD showed overlapping immunofluorescence and electron microscopy findings and had similar recurrence rate and time to recurrence. The majority of patients with native kidney failure attributed to C3G developed disease recurrence very early after kidney transplantation, usually with minimal proteinuria, mild histologic alterations, and favorable short-term allograft survival. Immunofluorescence and electron microscopy played crucial role in detecting early, sub-clinical recurrence of C3GN and DDD, which showed significant overlapping features. To identify transcriptomic signals that may distinguish recurrent C3G, we utilized the 770 genes PanCancer Immune Profiling Panel in a discovery cohort of native kidney biopsies followed by a testing cohort of allograft biopsies. For the discovery cohort, we residual tissue from formalin-fixed paraffin-embedded samples (FFPE) was used from 18 native kidney biopsies with C3G (11 C3GN and 7 DDD) and 36 native biopsies with other glomerular diseases (GD controls: 15 IgA nephropathy, 14 membranous nephropathy, 7 diffuse podocytopathy). For the testing cohort, we ass essedresidual FFPE tissue was used from 13 index allograft biopsies with recurrent C3G (combining 10 from our study with enough residual tissue and 3 additional cases that were added to increase sample size) and 41 allograft glomerular disease (GD) controls. Since recurrent GD is overall more commonly encountered than de novo GD although the frequency of latter might be underestimated20, the GD controls were selected to roughly reflect this notion [15 de novo GD (5 membranous nephropathy, 6 immune complex-mediated glomerulonephritis not otherwise specified, 3 IgA nephropathy, 1 HCV-associated glomerulonephritis) and 26 recurrent GD (10 membranous nephropathy, 8 IgA nephropathy, 7 diffuse podocytopathy, 1 HCV-associated glomerulonephritis)].

ORGANISM(S): Homo sapiens

PROVIDER: GSE261305 | GEO | 2024/03/18

REPOSITORIES: GEO

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Project description:Proteinuria is the most important predictor of outcome in glomerulonephritis and experimental data suggest that the tubular cell response to proteinuria is an important determinant of progressive fibrosis in the kidney. However, it is unclear whether proteinuria is a marker of disease severity or has a direct effect on tubular cells in the kidneys of patients with glomerulonephritis. Accordingly we studied an in vitro model of proteinuria, and identified 231 albumin-regulated genes differentially expressed by primary human kidney tubular epithelial cells exposed to albumin. We translated these findings to human disease by studying mRNA levels of these genes in the tubulo-interstitial compartment of kidney biopsies from patients with IgA nephropathy using microarrays. Biopsies from patients with IgAN (n=25) could be distinguished from those of control subjects (n=6) based solely upon the expression of these 231 albumin-regulated genes. The expression of an 11-transcript subset related to the degree of proteinuria, and this 11-mRNA subset was also sufficient to distinguish biopsies of subjects with IgAN from control biopsies. We tested if these findings could be extrapolated to other proteinuric diseases beyond IgAN and found that the all forms of primary glomerulonephritis (n=33) can be distinguished from controls (n=21) based solely on the expression levels of these 11 genes derived from our in vitro proteinuria model. Pathway analysis suggests common regulatory elements shared by these 11 transcripts. In conclusion, we have identified an albumin-regulated 11-gene signature shared between all forms of primary glomerulonephritis. Our findings support the hypothesis that albuminuria may directly promote injury in the tubulo-interstitial compartment of the kidney in patients with glomerulonephritis. We used microarrays to analyze the transcriptome of microdissected renal biopsies from patients with IgA nephropathy (IgAN) RNA from tubulointerstitial compartments was extracted and processed for hybridization on Affymetrix HG-U133A microarrays.

Project description:Background: Biopsy-based diagnosis is essential for maintaining renal allograft longevity by ensuring prompt treatment for graft complications. Although histologic assessment remains the gold standard, it carries significant limitations such as subjective interpretation, suboptimal reproducibility, and imprecise quantitation of disease burden. It is hoped that molecular diagnostics could enhance the efficiency, accuracy, and reproducibility of traditional histologic methods. Methods: Quantitative label-free mass spectrometry analysis was performed on a set of formalin-fixed, paraffin-embedded (FFPE) biopsies from renal transplant patients, comprising five biopsies with the diagnosis of T-cell-mediated rejection (TCMR), five biopsies for polyomavirus BK nephropathy (BKPyVN), and normal kidney control tissue (STA). Using the differential protein expression result as a classifier, three different machine learning algorithms were tested to build a molecular diagnostic model for TCMR. Results: The label-free proteomics method yielded 800-1350 proteins that could be quantified with high confidence per sample by single-shot measurements. Among these candidate proteins, 329 and 467 proteins were defined as differentially expressed proteins (DEPs) for TCMR in comparison with STA and BKPyVN, respectively. Comparing the FFPE quantitative proteomics data set obtained in this study using label-free method with a data set we previously reported using isobaric labeling technology, a classifier pool comprised of features from DEPs commonly quantified in both data sets, was generated for TCMR prediction. Leave-one-out cross-validation result demonstrated that the random forest (RF)-based model achieved the best predictive power. In a follow-up blind test using an independent sample set, the RF-based model yields 80% accuracy for TCMR and 100% for STA. When applying the established RF-based model to two public transcriptome datasets, 78.1%-82.9% sensitivity and 58.7%-64.4% specificity was achieved respectively. Conclusions: This proof-of-principle study demonstrates the clinical feasibility of proteomics profiling for FFPE biopsies using an accurate, efficient, and cost-effective platform integrated of quantitative label-free mass spectrometry analysis with a machine learning-derived diagnostic model. It costs less than 10 dollars per test.

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C3G signal in native and allograft

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