Single-cell transcriptomics of mouse kidney transplants reveals a potentially novel myeloid cell pathway for transplant rejection
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA660771 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12565000.fastq.gz | Fastqsanger.gz | |||
| SRR12565001.fastq.gz | Fastqsanger.gz | |||
| SRR12565002.fastq.gz | Fastqsanger.gz | |||
| SRR12565003.fastq.gz | Fastqsanger.gz | |||
| SRR12565004.fastq.gz | Fastqsanger.gz |
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Project description:We used a murine kidney transplantation model and single-cell transcriptomics to dissect the contribution of myeloid cell subsets and their potential signaling pathways to kidney transplant rejection. Using a variety of bioinformatic techniques including machine learning, we demonstrated that kidney allograft-infiltrating myeloid cells followed a trajectory of differentiating from monocytes to pro-inflammatory macrophages, and exhibited distinct interactions with kidney allograft parenchymal cells. While this process correlated with a unique pattern of myeloid cell transcripts, a top gene identified was Axl, a member of the receptor tyrosine kinase familyTAM(Tyro3/Axl/Mertk).
2020-09-02 | GSE157292 | GEO
Project description:Most kidney transplant patients who undergo biopsies are classified as having no rejection based on consensus thresholds. However, we hypothesized that because these patients have normal adaptive immune systems, T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) may exist as subthreshold activity in some transplants currently classified as no rejection. Subthreshold molecular TCMR and/or ABMR activity molecular activity was detectable as elevated classifier scores in many biopsies classified as no rejection, with ABMR activity in many TCMR biopsies and TCMR activity in many ABMR biopsies. In biopsies classified as no rejection histologically and molecularly, molecular TCMR classifier scores correlated with increases in histologic TCMR features and molecular injury, lower eGFR, and higher risk of graft loss, and molecular ABMR activity correlated with increased glomerulitis and donor-specific antibody. No rejection biopsies with high subthreshold TCMR or ABMR activity had a higher probability of having TCMR or ABMR respectively diagnosed in a future biopsy. We conclude that many kidney transplant recipients have unrecognized subthreshold TCMR or ABMR activity, with significant implications for future problems.
2024-09-04 | GSE275126 | GEO
Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other. This dataset is part of the TransQST collection.
2004-07-14 | E-GEOD-1563 | biostudies-arrayexpress
Project description:We used DNA microarrays (HG-U95Av2 GeneChips) to determine gene expression profiles for kidney biopsies and peripheral blood lymphocytes (PBLs) in transplant patients. Sample classes include kidney biopsies and PBLs from patients with 1) healthy normal donor kidneys, 2) well-functioning transplants with no clinical evidence of rejection, 3) kidneys undergoing acute rejection, and 4) transplants with renal dysfunction without rejection. Nomenclature for samples is as follows: 1) all sample names include either BX or PBL to indicate that they were derived from biopsies or PBLs respectively, 2) C indicates samples from healthy normal donors, 3) TX indicates samples from patients with well-functioning transplants with no clinical evidence of rejection, 3) AR indicates samples from transplant patients with kidneys undergoing acute rejection, 4) NR indicates samples from transplant patients with renal dysfunction without rejection. Abbreviations used to describe patient samples include the following: BX - Biopsy; PBL- Peripheral Blood Lymphocytes; CsA -Cyclosporine; MMF - Mycophenolate Mofetil; P - Prednisone; FK - Tacrolimus; SRL - Sirolimus; CAD -Cadaveric; LD - Live Donor; Scr - Serum Creatinine; ATN - Acute Tubular Necrosis CNI - Calcineurin Inhibitor; FSGS - Focal Segmental Glomerulosclerosis several array data sets did not pass quality control and were not analyzed. These include AR1PBL, NR4BX, and NR6PBL Keywords = DNA microarrays, gene expression, kidney, rejection, transplant Keywords: other
2004-07-14 | GSE1563 | GEO
Project description:Background: Initial analysis of liver transplant biopsies in the INTERLIVER study (#NCT03193151) using rejection-associated transcripts failed to find an antibody-mediated rejection state (i.e. rich in NK cells and with interferon-gamma effects). We recently developed an optimization strategy in lung transplants that isolated an NK cell-enriched rejection-like state (NKRL) that was molecularly distinct from T cell-mediated rejection (TCMR). Here we apply the same strategy to a liver transplant biopsy population. Results: The full model classified 765 biopsies into the following molecular phenotypes, characterized by their gene expression: No-rejection (NR) 54%; TCMR 16%; NKRL 13%; and Injury 16%. Top TCMR transcripts were expressed in effector T cells; top NKRL transcripts were almost exclusively expressed in NK cells; and both had increased IFNG-inducible transcripts, which were more pronounced in TCMR. Most TCMR biopsies had significant parenchymal injury, molecular fibrosis, and abnormal biochemistry. NKRL biopsies had no excess of injury, fibrosis, or biochemistry abnormalities. Conclusions: Optimized rejection algorithms indicate that some liver transplants manifest an NKRL state that is well-tolerated in the short-term postbiopsy and with minimal injury and relatively normal biochemistry, while also underscoring the potential of TCMR to produce extensive parenchymal injury.
2025-07-03 | GSE277334 | GEO
Project description:Diagnosing lung transplant rejection currently depends on histologic assessment of transbronchial biopsies (TBB) with limited reproducibility and considerable risk of complications. Mucosal biopsies are safer but not histologically interpretable. Microarray-based diagnostic systems for TBBs and other transplants suggest such systems could assess mucosal biopsies as well.
2019-11-19 | GSE125004 | GEO
Project description:We integrated three transplant rejection microarray studies examining gene expression in samples from pediatric renal, adult renal, and adult heart transplants. We performed one study ourselves and retrieved two others from the NCBI Gene Expression Omnibus (GEO)(GSE4470 and GSE1563). We identified 45 genes that were upregulated in common in acute rejection. Half were involved in one immune-related pathway. Among ten proteins we tested by serum ELISA, three successfully distinguished acute rejection from stable transplants. These were CXCL9, PECAM1, and CD44, with areas under the receiver operating characteristic curves of 0.844, 0.802, and 0.738, respectively. Immunohistochemistry showed that the PECAM1 protein was increased in acute rejection in renal, liver and heart transplants versus normal tissues. Our results show that integrating publicly-available gene expression data sets is a fast, powerful, and cost-effective way to identify serum-detectable diagnostic biomarkers.
2010-10-12 | GSE14328 | GEO
Project description:In the present work, we have used whole genome expression profiling of peripheral blood samples from 51 patients with biopsy-proven acute kidney transplant rejection and 24 patients with excellent function and biopsy-proven normal transplant histology. The results demonstrate that there are 1738 probesets on the Affymetrix HG-U133 Plus 2.0 GeneChip representing 1472 unique genes which are differentially expressed in the peripheral blood during an acute kidney transplant rejection. By ranking these results we have identified minimal sets of 50 to 150 probesets with predictive classification accuracies for AR of greater than 90% established with several different prediction tools including DLDA and PAM. We have demonstrated that a subset of peripheral blood gene expression signatures can also diagnose four different subtypes of AR (Banff Borderline, IA, IB and IIA) and the top 100 ranked classifiers have greater than 89% predictive accuracy. Finally, we have demonstrated that there are gene signatures for early and late AR defined as less than or greater than one year post-transplant with greater than 86% predictive accuracies. We also confirmed that there are 439 time-independent gene classifiers for AR. Based on these results, we conclude that peripheral blood gene expression profiling can be used to diagnose AR at any time in the first 5 years post-transplant in the setting of acute kidney transplant dysfunction not caused by BK nephropathy, other infections, drug-induced nephrotoxicity or ureteral obstruction. Keywords: kidney transplantation, peripheral blood, DNA microarrays, acute kidney rejection, biomarkers Microarray profiles of peripheral blood from 51 biopsy-proven acute kidney rejection (AR) and 24 well-functioning kidney transplants were randomized and compared using class comparisons, network and biological function analyses.
2014-03-01 | E-GEOD-15296 | biostudies-arrayexpress
Project description:Previous studies of rejection-associated transcript expression in heart transplant biopsies identified not only rejection but a group of early biopsies with injury but no rejection. The present analysis used an expanded population of biopsies to explore parenchymal injury in all biopsies, with or without rejection, and its relationship to function, and outcome. Archetypal analysis defined five injury clusters: no-injury (N=376); mild (N=526); moderate (N=110); severe (N=87); and late (N=221). The late group, 62% of which had no rejection, had molecular characteristics associated with atrophy-fibrosis, depressed LVEF, and increased graft loss independent of rejection status. In random forest analysis, low LVEF was more strongly associated with injury scores than with rejection scores. Three-year graft failure was best predicted using a combination of injury and rejection scores. In heart transplant biopsies, injury-related molecular scores correlate with dysfunction and risk of failure and identify an important new group of late heart transplants, many with no rejection, that have impaired function and a high risk of graft loss. (ClinicalTrials.gov #NCT02670408).
2021-12-28 | GSE150059 | GEO
Project description:Molecular diagnosis of rejection is emerging in kidney, heart, and lung transplant biopsies and could offer insights for liver transplant biopsies. Groups differed in median time post-transplant e.g. R3injury 99 days vs. R4late 3117 days. R2TCMR biopsies expressed typical TCMR-related transcripts e.g. intense IFNG-induced effects. R3injury displayed increased expression of parenchymal injury transcripts (e.g. hypoxia-inducible factor EGLN1). R4late biopsies showed immunoglobulin transcripts and injury-related transcripts. R2TCMR correlated with histologic rejection although with many discrepancies, and R4late with fibrosis. R2TCMR, R3injury, and R4late correlated with liver function abnormalities. Supervised classifiers trained on histologic rejection showed less agreement with histology than unsupervised R2TCMR scores. No confirmed cases of clinical ABMR were present in the population, and strategies that previously revealed antibody-mediated rejection (ABMR) in kidney and heart transplants failed to reveal a liver ABMR phenotype. In conclusion, molecular analysis of liver transplant biopsies detects rejection, has the potential to resolve ambiguities, and could assist with immunosuppressive management.
2020-05-06 | GSE145780 | GEO