Transcripts associated with chronic lung allograft dysfunction in transbronchial biopsies of lung transplants
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ABSTRACT:
PROVIDER: PRJNA795148 | ENA |
REPOSITORIES: ENA
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Project description:Transplanted lungs suffer worse outcomes than other organ transplants with many developing chronic lung allograft dysfunction (CLAD), diagnosed by physiologic changes. Histology of transbronchial biopsies (TBB) yields little insight, and the molecular basis of CLAD is not defined. We hypothesized that gene expression in TBBs would reveal the nature of CLAD and distinguish CLAD from changes due simply to time posttransplant. Time was associated with increased expression of inflammation genes e.g. CD1E and immunoglobulins. After correcting for time, CLAD manifested not as inflammation but as parenchymal response-to-wounding, with increased expression of genes such as HIF1A, SERPINE2, and IGF1 that are increased in many injury and disease states and cancers, associated with development, angiogenesis, and epithelial response-to-wounding in pathway analysis. Fibrillar collagen genes were increased in CLAD, indicating matrix changes, and normal transcripts were decreased – dedifferentiation. Gene-based classifiers predicted CLAD with AUC 0.70 (no time-correction) and 0.87 (time-corrected). CLAD-related gene sets and classifiers were strongly prognostic for graft failure and correlated with CLAD stage. Thus, in TBBs molecular changes indicate that CLAD primarily reflects severe parenchymal injury-induced changes and dedifferentiation.
2022-01-09 | GSE193150 | GEO
Project description:Kidney transplants that develop dysfunction or proteinuria after one year post transplant are at considerable risk for progression to renal failure. Identifying the molecules associated with graft failure could potentially lead to interventions that would slow the progression of organ failure. We analyzed the relationship between gene expression in late biopsies for cause in human kidney transplants and subsequent graft loss, and assessed the predictive value of gene expression. We evaluated the performance of these genes in an independent , and in a population of early biopsies that have a very low risk of subsequent graft failure.
2010-05-24 | GSE21374 | 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:In lung transplantation, antibody-mediated rejection (AMR) diagnosed by ISHLT criteria is uncommon compared to other organs, and previous studies failed to find molecular AMR (ABMR) in lung biopsies. However, understanding of ABMR has changed with the recognition that ABMR in kidney transplants is often DSA-negative and associated with NK cell transcripts. After optimizing rejection-selective transcript sets (RSTS) in a training set (n = 488), the resulting algorithms separated an NK cell-enriched rejection-like state (NKRL) from TCMR/Mixed in a test set (n = 488). Applying this approach to all 896 TBBs distinguished three groups - No rejection; TCMR/Mixed; and NKRL. Like TCMR/Mixed, NKRL had increased expression of all-rejection transcripts, but NKRL had increased expression of NK cell transcripts, whereas TCMR/Mixed had increased effector T cell and activated macrophage transcripts. NKRL was usually DSA-negative and not recognized as AMR clinically. TCMR/Mixed was associated with CLAD, reduced FEV1, and short-term graft failure, but NKRL was not. Thus, some lung transplants manifest a molecular state similar to DSA-negative ABMR in kidney and heart transplants, but its clinical significance must be established.
2025-07-24 | GSE303535 | GEO
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
Project description:Microarray analysis of human kidneys with acute kidney injury (AKI) has been limited because such kidneys are seldom biopsied. However, all kidney transplants experience AKI, and early kidney transplants without rejection are an excellent model for human AKI: they are screened to exclude chronic kidney disease, frequently biopsied, and have extensive follow-up. We used histopathology and microarrays to compare indication biopsies from 28 transplants with AKI to 11 pristine protocol biopsies of stable transplants. Kidneys with AKI showed increased expression of 394 injury-repair response associated transcripts, including many known epithelial injury molecules (e.g. ITGB6, LCN2), tissue remodeling molecules (e.g. VCAN), and inflammation molecules (S100A8, ITGB3). Many other genes also predict the phenotype, depending on statistical filtering rules, including AKI biomarkers as HAVCR1 and IL18. Most mouse orthologs of the top injury-repair transcripts were increased in published mouse AKI models. Pathway analysis of the injury-repair transcripts revealed similarities to cancer, development, and cell movement. The injury-repair transcript score AKI kidneys correlated with reduced function, future recovery, brain death, and need for dialysis, but not future graft loss. In contrast, histologic features of "acute tubular injury" did not correlate with function or with the molecular changes. Thus the injury-repair associated transcripts represent a massive coordinate injury-repair response of kidney parenchyma to AKI, similar to mouse AKI models, and provide an objective measure for assessing the severity of AKI in kidney biopsies and validation for the use of many AKI biomarkers.
2012-02-21 | GSE30718 | GEO
Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hôpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hôpital Bicêtre, Paris, Hôpital Pellegrin, Bordeaux, and Hôpital Dupuytren, Limoges, plus control normal kidney samples from Hôpital Tenon, Paris, France (first batch). We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis
2009-02-24 | GSE9489 | GEO
Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set here comprises a small validation batch of renal allograft biopsies for clinical indications plus control normal kidney samples from patients at Hôpital Tenon, Paris (second batch) that complements the first batch of 60 samples. We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis
2009-02-24 | GSE9492 | GEO
Project description:Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set here comprises a small validation batch of renal allograft biopsies for clinical indications plus control normal kidney samples from patients at Hôpital Tenon, Paris (second batch) that complements the first batch of 60 samples. We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN. Keywords: disease state analysis 4 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to Banff'97 criteria and 2 normal kidney samples.
2009-02-24 | E-GEOD-9492 | biostudies-arrayexpress