Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Molecular T-cell mediated rejection in transbronchial and mucosal lung transplant biopsies

ABSTRACT: We previously developed molecular assessment systems for lung transplant transbronchial biopsies (TBBs) with high surfactant and bronchial mucosal biopsies (3BMBs). Unsupervised machine learning identified T cell-mediated rejection (TCMR) based on expression of validated rejection-associated transcripts (RATs). The relationship to patient outcomes is not known. We aimed to establish whether molecular TCMR in TBBs and 3BMBs has implications for future graft loss. Molecular TCMR scores assigned in all TBBs or high surfactant TBBs agreed closely, indicating that variation in alveolar content in TBBs does not prevent detection of TCMR. Molecular assessments of 3BMB-3BMB pairs showed less variation than TBB-TBB pairs. TBB TCMR scores correlated with those in 3BMB. In both formats, molecular TCMR was associated with increased risk of graft loss whereas the presence of histologic rejection or donor-specific antibodies was not. Molecular TCMR can be detected in TBBs or 3BMBs and is associated with future risk of graft loss. TCMR emerges as a n important contributor to risk of failure. ClinicalTrials.gov NCT02812290.

ORGANISM(S): Homo sapiens

PROVIDER: GSE150156 | GEO | 2020/10/07

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Molecular Assessment of Rejection and Injury in Lung Transplant Biopsies

Project description:Improved understanding of lung transplant disease states is essential because failure rates are high, often due to chronic lung allograft dysfunction. However, histologic assessment of lung transplant transbronchial biopsies (TBBs) is difficult and often uninterpretable even with 10 pieces. All 242 single-piece TBBs produced reliable transcript measurements. Paired TBB pieces available from 12 patients showed significant similarity but also showed some sampling variance. Alveolar content, as estimated by surfactant transcript expression, was a source of sampling variance. To offset sampling variation, for analysis we selected 152 single-piece TBBs with high surfactant transcripts. Unsupervised archetypal analysis identified four idealized phenotypes (archetypes) and scored biopsies for their similarity to each: normal, T cell-mediated rejection (TCMR; T cell transcripts), antibody-mediated rejection (ABMR)-like (endothelial transcripts), and injury (macrophage transcripts). Molecular TCMR correlated with histologic TCMR. The relationship of molecular scores to histologic ABMR could not be assessed because of the paucity of ABMR in this population. Molecular assessment of single-piece TBBs can be used to classify lung transplant biopsies and correlated with rejection histology. Two or three pieces for each TBB will probably be needed to offset sampling variance.

2019-08-16 | GSE125478 | GEO

Many heart transplant biopsies currently diagnosed as no rejection have mild molecular antibody-mediated rejection-related changes

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

Assessing rejection-related disease in kidney transplant biopsies based on archetypal analysis of molecular phenotypes

Project description:Molecular phenotyping of biopsies affords opportunities for increased precision and improved disease classification to address the limitations of conventional histologic diagnostic systems. We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. Seven machine learning-generated cross-validated classifier scores per biopsy were used as input for the archetypal analysis. Six archetypes representing extreme phenotypes were generated: no rejection; T cell-mediated rejection (TCMR); three phenotypes associated with antibody-mediated rejection (ABMR) - early-stage, fully-developed, and late-stage; and mixed rejection (TCMR plus early-stage ABMR). Each biopsy was assigned six scores, one for each archetype, that together represent a probabilistic assessment of that biopsy based on its rejection-related molecular properties. Viewed as clusters, the archetypes were similar to existing histologic Banff categories, but there was 32% disagreement, much of it probably reflecting the “noise” in the current histologic assessment system. Graft survival was worst for fully-developed and late-stage ABMR and was better predicted by molecular archetype scores than histologic diagnoses. The results provide a system for precision molecular assessment of biopsies and a new standard for recalibrating conventional diagnostic systems. (ClinicalTrials.gov NTC1299168) We applied archetypal analysis, an unsupervised method similar to cluster analysis, to microarray data from 1208 prospectively collected kidney transplant biopsies from 13 centers. This dataset is part of the TransQST collection.

2017-07-10 | E-GEOD-98320 | biostudies-arrayexpress

Assessing rejection-related disease in kidney transplant biopsies based on archetypal analysis of molecular phenotypes

2017-07-10 | GSE98320 | GEO

Redefining the molecular rejection states in 3230 heart transplant biopsies: relationships to parenchymal injury and graft survival

Project description:The first-generation Molecular Microscope® (MMDx) system for heart transplant endomyocardial biopsies used expression of rejection-associated transcripts (RATs) to diagnose T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR) but also detected acute injury. However, the ideal system should detect rejection without being influenced by injury, to permit analysis of the relationship between rejection and parenchymal injury. To achieve this, we developed a new rejection classification in an expanded cohort of 3230 biopsies: 1641 from INTERHEART (ClinicalTrials.gov #NCT02670408), plus 1589 service biopsies added to improve the power of the machine learning algorithms. The new system used six rejection classifiers instead of RATs and generated seven rejection archetypes: No Rejection 48%; Minor 24%; TCMR1 2.3%; TCMR2 2.7%; TCMR/Mixed 2.7%; EABMR 3.9%; and FABMR 16%. Using rejection classifiers eliminated cross-reactions with acute injury, permitting separate assessment of rejection and injury. TCMR was associated with severe recent injury and late atrophy-fibrosis and rarely had normal parenchyma. ABMR was better tolerated, seldom producing severe injury, but in later biopsies was often associated with atrophy-fibrosis, indicating long term risk. Graft survival and LVEF were reduced in hearts with TCMR, but also in hearts with severe-recent injury and atrophy-fibrosis, even without rejection.

2024-04-02 | GSE262742 | GEO

The effect of cortex/medulla proportions on molecular diagnoses in kidney transplant biopsies: rejection and injury can be assessed in medulla

Project description:Histologic assessment of kidney transplant biopsies relies on cortex rather than medulla, but for microarray studies, the proportion cortex in a biopsy is typically unknown and could affect the molecular readings. The present study aimed to develop a molecular estimate of proportion cortex in biopsies and examine its effect on molecular diagnoses. Microarrays from 26 kidney transplant biopsies divided into cortex and medulla components and processed separately showed that many of the most significant differences were in glomerular genes e.g. NPHS2, NPHS1, CLIC5, PTPRO, PLA2R1, PLCE1, PODXL and REN. Using NPHS2 (podocin) to estimate proportion cortex, we examined whether proportion cortex influenced molecular assessment in the Molecular Microscope Diagnostic System. In 1190 unselected kidney transplant indication biopsies (Clinicaltrials.govNCT01299168), only 11% had <50% cortex. Molecular scores for ABMR, TCMR, and injury were independent of proportion cortex. Rejection was diagnosed in many biopsies that were mostly or all medulla. Agreement in molecular diagnoses in paired cortex/medulla samples (23/26) was similar to biological replicates (32/37). We conclude that NPHS2 expression can estimate proportion cortex; that proportion cortex has little influence on molecular diagnosis of rejection, and that, although histology cannot assess medulla, rejection does occur in medulla as well as cortex. We studied 26 pairs of cortex/medulla biopsies from 26 patients (4 unpaired), characterizing the clinical and histological features, and defined the mRNA phenotype with Affymetrix expression microarrays. We also studied 37 pairs of biopsies from biological replicates and 12 pairs from technical replicates. This dataset is part of the TransQST collection.

2017-04-27 | E-GEOD-95611 | biostudies-arrayexpress

The Trifecta study: comparing plasma donor-derived cell-free DNA levels with the molecular phenotype of kidney transplant biopsies

Project description:Background. The Trifecta study (ClinicalTrials.gov #NCT04239703) is a prospective investigator-initiated trial to evaluate the relationship between plasma %dd-cfDNA at the time of indication biopsy and the molecular phenotype of the biopsy. Results. Median time of biopsy post-transplant was 455 days (5 days - 32 years), with case-mix similar to previous studies: 180 (60%) no rejection, 89 (30%) antibody-mediated rejection (ABMR), and 31 (10%) T cell-mediated rejection (TCMR) and mixed. In genome-wide mRNA measurements, all 20 top probesets correlating with %dd-cfDNA were previously annotated for association with ABMR and all rejection, either NK cell-expressed (e.g. GNLY, CCL4, TRDC, and S1PR5) or IFNG-inducible (e.g. PLA1A, IDO1, CXCL11, and WARS). Among gene set and classifier scores, %dd-cfDNA correlated very strongly with ABMR and all rejection, reasonably strongly with active TCMR, and weakly with inactive TCMR, kidney injury and atrophy-fibrosis. %dd-cfDNA was highest in active ABMR, mixed, and active TCMR but lower in late-stage ABMR and less active TCMR. By multivariate random forests and logistic regression, molecular rejection variables predicted %dd-cfDNA better than histologic variables. Conclusions. %dd-cfDNA at time of indication biopsy strongly correlates with active molecular rejection and has potential to reduce unnecessary biopsies.

2021-12-23 | GSE192444 | GEO

Molecular phenotyping of rejection in mucosal biopsies from lung transplant recipients

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

Potential impact of microarray diagnosis of T cell-mediated rejection in kidney transplants: the INTERCOM study

Project description:The authors report that in INTERCOM, a prospective international study of 300 kidney transplant biopsies, a microarray-based molecular score for T cell-mediated rejection changed the assessment of 26% of all biopsies, illustrating the potential of precision diagnostics to impact practice. Microarray analysis of 300 kidney transplant biopsies (non-TCMR, TCMR) and 6 nephrectomies.

2013-09-15 | E-GEOD-48581 | biostudies-arrayexpress

The molecular diagnosis of rejection in liver transplant biopsies: First results of the INTERLIVER study

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

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data