Sequencing of Physically Interacting Cells in Human Kidney Allograft Rejection Reveals Insights into Immune Cell Interactions
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA783343 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22703963_1.fastq.gz | Fastqsanger.gz | |||
| SRR22703963_2.fastq.gz | Fastqsanger.gz | |||
| SRR22703964_1.fastq.gz | Fastqsanger.gz | |||
| SRR22703964_2.fastq.gz | Fastqsanger.gz | |||
| SRR22703965_1.fastq.gz | Fastqsanger.gz |
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Project description:Acute rejection threatens kidney allograft longevity. Cell-free DNA (cfDNA) is a real-time marker of organ injury and immune response. DNA methylation is an epigenetic marker that regulates gene expression. We aim to elucidate differential methylation of total plasma cfDNA between pediatric kidney transplant recipients in the presence compared to the absence of acute rejection. In doing so, we hope to exploit the property of cfDNA as a real-time biomarker and build on available testing to identify genes and processes participating in acute allograft rejection pathophysiology in kidney transplantation. Twenty plasma cfDNA samples from pediatric kidney transplant recipients were collected at the time of allograft biopsy. Using whole genome bisulfite sequencing (WGBS), differentially methylated cytosines were identified in presence vs absence of acute rejection. Separate analyses were performed comparing those with borderline rejection to those with rejection, and to those without rejection. Differentially methylated cytosines were then assessed for gene associations and pathway enrichments. Acute rejection was present in 7 biopsies, borderline rejection in 4 biopsies, and no rejection in 9 biopsies. In the comparison of acute rejection to non-rejection biopsies, there were 34,356 differentially methylated cytosines corresponding to 1,269 associated genes, and 533 enriched pathways. These numbers were all substantially greater (4x-13x) than the comparisons made between acute rejection against those with borderline rejection, and between non-rejection against borderline rejection. Prominently enriched pathways between samples of individuals with and without acute rejection were related to immune cell regulation, inflammatory response, lipid metabolism, and tryptophan-kynurenine metabolism. Our data suggest methylation plays a role in development of or response to acute kidney allograft rejection. Specifically, differentially methylated pathways associated with acute rejection include those related to immune and inflammatory responses.
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Project description:To investigate the involvement of FCGR3A and FCGR2C signaling and NK cell activation during antibody-mediated rejection, we analyzed transcriptomic data obtained by bulk RNA sequencing of kidney allograft FFPE biopsies diagnosed with either antibody-mediated rejection, T-cell mediated rejection or normal biopsies.
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Project description:Acute allograft rejection is a leading cause for the failure of organ allotransplantation. Identifying the genes involved in the rejection process provides clues to study the mechanisms, and to provide specific gene targets for monitoring, predicting and preventing acute allograft rejection. Using a mice model of skin acute allograft rejection and SAGE method, we analyzed gene expression in the CD4+ T cells of the mice, the cell type known to play critical roles in acute allograft rejection. Our study identifies 402 SAGE tags significantly different from these from the control. From these SAGE tags, we identified 91 increasingly and 85 decreasingly expressed genes, and many genes have not been linked with acute allograft rejection before. Functional classification of these genes shows that apoptosis, transcription regulation, cell growth and maintenance and signal transduction are among the most frequently changed functional groups. Our study provides a genome-wide view for the genes involving acute allograft rejection in the CD4+ T cells, and indicates that acute allograft rejection involves multiple genes in different functional categories. The genes identified from the study provide candidates for further studying the mechanisms and for monitoring, predicting and preventing acute allograft rejection.
2010-03-01 | GSE14540 | GEO
Project description:The data set contains 67 array (lymphochip cDNA array), published in N Engl J Med 2003 Jul 10;349(2):125-38. PMID: 12853585. TITLE: Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. BACKGROUND: The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. METHODS: We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. : We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). CONCLUSIONS: Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: normal vs disease Keywords: disease_state_design Using regression correlation
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Project description:We sequenced the transriptomes of 31203 cells from 11 human kidney transplant biopsies. We used the CITE-seq approach to generate these single cell multiomics data. We then used a computational pipeline called PIC-seq to deconvolute the transcriptional signatures of each contributing cell in a PIC by comparing PIC gene expression to a theoretical PIC.
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Project description:In this proof-of-concept study, spatial transcriptomics combined with public single-cell RNA sequencing data were used to explore the potential of this technology to study kidney allograft rejection. We aimed to map gene expression patterns within diverse pathological states by examining biopsies classified across non-rejection, T cell-mediated acute rejection, and interstitial fibrosis and tubular atrophy (IFTA). Our results revealed distinct immune cell signatures, including those of T and B lymphocytes, monocytes, mast cells, and plasma cells, and their spatial organization within the renal interstitium. We also mapped chemokine receptors and ligands to study immune-cell migration and recruitment. Finally, our analysis demonstrated differential spatial enrichment of transcription signatures associated with kidney allograft rejection across various biopsy regions. Interstitium regions displayed higher enrichment scores for rejection-associated gene expression patterns than did tubular areas, which had negative scores. This implies that these signatures are primarily driven by processes unfolding in the renal interstitium. Overall, this study highlights the value of spatial transcriptomics for revealing cellular heterogeneity and immune signatures in renal transplant biopsies, and demonstrates its potential for studying the molecular and cellular mechanisms associated with rejection. However, certain limitations must be borne in mind regarding the development and future applications of this technology.
2024-05-02 | GSE245870 | GEO
Project description:Lung allograft rejection results in the accumulation of low molecular weight hyaluronic acid (LMW-HA), which further propagates inflammation and tissue injury. We have previously shown that therapeutic lymphangiogenesis in a murine model of lung allograft rejection reduced tissue LMW-HA and was associated with improved transplant outcomes. Herein we investigated the use of 4-Methylumbelliferone (4-MU), a known inhibitor of HA synthesis, to alleviate acute allograft rejection in a murine model of lung transplantation. We found that treating mice with 4-MU from day 20-30 post-transplant was sufficient to significantly improve outcomes, characterized by a reduction in T-cell mediated lung inflammation, LMW-HA content and improved pathology scores. In vitro, 4-MU directly attenuated activation, proliferation, and differentiation of naïve CD4+ T-cells into Th1 cells. As 4-MU has already been demonstrated to be safe for human use, we believe examining 4-MU for the treatment of acute lung allograft rejection may be of clinical significance.
2021-12-15 | GSE183142 | GEO
Project description:The data set contains 67 array (lymphochip cDNA array), published in N Engl J Med 2003 Jul 10;349(2):125-38. PMID: 12853585. TITLE: Molecular heterogeneity in acute renal allograft rejection identified by DNA microarray profiling. BACKGROUND: The causes and clinical course of acute rejection vary, and it is not possible to predict graft outcome reliably on the basis of available clinical, pathological, and genetic markers. We hypothesized that previously unrecognized molecular heterogeneity might underlie some of the variability in the clinical course of acute renal allograft rejection and in its response to treatment. METHODS: We used DNA microarrays in a systematic study of gene-expression patterns in biopsy samples from normal and dysfunctional renal allografts. A combination of exploratory and supervised bioinformatic methods was used to analyze these profiles. : We found consistent differences among the gene-expression patterns associated with acute rejection, nephrotoxic effects of drugs, chronic allograft nephropathy, and normal kidneys. The gene-expression patterns associated with acute rejection suggested at least three possible distinct subtypes of acute rejection that, although indistinguishable by light microscopy, were marked by differences in immune activation and cellular proliferation. Since the gene-expression patterns pointed to substantial variation in the composition of immune infiltrates, we used immunohistochemical staining to define these subtypes further. This analysis revealed a striking association between dense CD20+ B-cell infiltrates and both clinical glucocorticoid resistance (P=0.01) and graft loss (P<0.001). CONCLUSIONS: Systematic analysis of gene-expression patterns provides a window on the biology and pathogenesis of renal allograft rejection. Biopsy samples from patients with acute rejection that are indistinguishable on conventional histologic analysis reveal extensive differences in gene expression, which are associated with differences in immunologic and cellular features and clinical course. The presence of dense clusters of B cells in a biopsy sample was strongly associated with severe graft rejection, suggesting a pivotal role of infiltrating B cells in acute rejection. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Disease State: normal vs disease Keywords: disease_state_design
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Project description:Acute renal allograft rejection is an important complication in kidney transplantation. Accurate diagnosis of rejection events is necessary for timely response and treatment. We illustrate the usefulness and biological relevance of selected multivariate approaches to detect rejection from genomic and proteomic signals. The data was used to study gene expression changes using whole genome microarray analysis of peripheral blood from subjects with acute rejection (n=20) and non-rejecting controls (n=20) to obtain insight into the molecular and biological causation of acute renal allograft rejection when combined with proteomics (iTRAQ) data for the same patients/time-points.
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