Expression profiling of human endomyocardial biopsies before, during and after cardiac allograft rejection
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE4315 | GEO | 2006/03/02
SECONDARY ACCESSION(S): PRJNA94853
REPOSITORIES: GEO
Similar Datasets
Project description:Cardiac allograft rejection remains a significant clinical problem in the early phase after heart transplantation and requires frequent surveillance with endomyocardial biopsy. Endomyocardial tissue samples were obtained in connection with clinical biopsies from twenty consecutive heart transplant patients followed for six months. A rejection episode was observed in 14 patients and biopsies obtained before, during and after the episode were identified. Endomyocardial RNA, from three patients, matching these three points in time were analysed with DNA microarray. Experiment Overall Design: Three subjects (subject number 1,8 and 12) Experiment Overall Design: Three timepoints (Before, during and after an rejection episode)
2007-12-12 | E-GEOD-4315 | biostudies-arrayexpress
Project description:Acute rejection in cardiac transplant patients is still a contributing factor to limited survival of the implanted heart. Currently there are no biomarkers in clinical use that can predict, at the time of transplantation, the likelihood of post-transplantation acute rejection, which would be of great importance for personalizing immunosuppressive treatment. Within the Biomarkers in Transplantation initiative, the predictive biomarker discovery focused on data and samples collected before or during transplantation such as: clinical variables, genes and proteins from the recipient, and genes from the donor. Based on this study, the best predictive biomarker panel contains genes from the recipient whole blood and from donor endomyocardial tissue and has an estimated area under the curve of 0.90. This biomarker panel provides clinically relevant prediction power and may help personalize immunosuppressive treatment and frequency of rejection monitoring.
2017-09-29 | GSE33970 | GEO
Project description:PBMC samples from heart transplant patients were profiled. Sample classification was based on endomyocardial biopsy at the time of sample collection. Keywords = Transplant Keywords = Transplantation Keywords = Heart Transplant Keywords = Graft Rejection Keywords = Rejection Keywords = PBMC Keywords = Immune Response Keywords = Peripheral Blood
2010-06-10 | E-GEOD-2445 | biostudies-arrayexpress
Project description:BACKGROUND: Assessment of gene expression in peripheral blood may provide a noninvasive screening test for allograft rejection. We hypothesized that changes in peripheral blood expression profiles would correlate with biopsy-proven rejection and would resolve after treatment of rejection episodes. METHODS AND RESULTS: We performed a case-control study nested within a cohort of 189 cardiac transplant patients who had blood samples obtained during endomyocardial biopsy (EMB). Using Affymetrix HU133A microarrays, we analyzed whole-blood expression profiles from 3 groups: (1) control samples with negative EMB (n=7); (2) samples obtained during rejection (at least International Society for Heart and Lung Transplantation grade 3A; n=7); and (3) samples obtained after rejection, after treatment and normalization of the EMB (n=7). We identified 91 transcripts differentially expressed in rejection compared with control (false discovery rate <0.10). In postrejection samples, 98% of transcripts returned toward control levels, displaying an intermediate expression profile for patients with treated rejection (P<0.0001). Cluster analysis of the 40 transcripts with >25% change in expression levels during rejection demonstrated good discrimination between control and rejection samples and verified the intermediate expression profile of postrejection samples. Quantitative real-time polymerase chain reaction confirmed significant differential expression for the predictive markers CFLAR and SOD2 (UniGene ID No. 355724 and No. 384944). CONCLUSIONS: These data demonstrate that peripheral blood expression profiles correlate with biopsy-proven allograft rejection. Intermediate expression profiles of treated rejection suggest persistent immune activation despite normalization of the EMB. If validated in larger studies, expression profiling may prove to be a more sensitive screening test for allograft rejection than EMB. Experiment Overall Design: Case- control study with three groups. Patients with rejection (r1-r7), follow-up samples after treatment of rejection (post1-7), and controls with no rejection (con1-7)
2008-06-14 | E-GEOD-5967 | biostudies-arrayexpress
Project description:PBMC samples from heart transplant patients were profiled. Sample classification was based on endomyocardial biopsy at the time of sample collection. Keywords = Transplant Keywords = Transplantation Keywords = Heart Transplant Keywords = Graft Rejection Keywords = Rejection Keywords = PBMC Keywords = Immune Response Keywords = Peripheral Blood Keywords: other
2005-09-01 | GSE2445 | GEO
Project description:BACKGROUND: Assessment of gene expression in peripheral blood may provide a noninvasive screening test for allograft rejection. We hypothesized that changes in peripheral blood expression profiles would correlate with biopsy-proven rejection and would resolve after treatment of rejection episodes. METHODS AND RESULTS: We performed a case-control study nested within a cohort of 189 cardiac transplant patients who had blood samples obtained during endomyocardial biopsy (EMB). Using Affymetrix HU133A microarrays, we analyzed whole-blood expression profiles from 3 groups: (1) control samples with negative EMB (n=7); (2) samples obtained during rejection (at least International Society for Heart and Lung Transplantation grade 3A; n=7); and (3) samples obtained after rejection, after treatment and normalization of the EMB (n=7). We identified 91 transcripts differentially expressed in rejection compared with control (false discovery rate <0.10). In postrejection samples, 98% of transcripts returned toward control levels, displaying an intermediate expression profile for patients with treated rejection (P<0.0001). Cluster analysis of the 40 transcripts with >25% change in expression levels during rejection demonstrated good discrimination between control and rejection samples and verified the intermediate expression profile of postrejection samples. Quantitative real-time polymerase chain reaction confirmed significant differential expression for the predictive markers CFLAR and SOD2 (UniGene ID No. 355724 and No. 384944). CONCLUSIONS: These data demonstrate that peripheral blood expression profiles correlate with biopsy-proven allograft rejection. Intermediate expression profiles of treated rejection suggest persistent immune activation despite normalization of the EMB. If validated in larger studies, expression profiling may prove to be a more sensitive screening test for allograft rejection than EMB. Keywords: human, peripheral blood, before and after therpay, untreated control
2006-10-04 | GSE5967 | GEO
Project description:Aims. Serial invasive endomyocardial biopsies (EMB) remain the gold standard for acute cellular rejection (ACR) diagnosis. However histological grading has several limitations. We aimed to explore the value of myocardial Gene Expression Profiling (GEP) for diagnosing and identifying predictive biomarkers of ACR. Methods. A case-control study nested within a retrospective heart transplant patients cohort included 126 patients with median (IQR) age 50 (41-57) years and 111 (88%) males. Among 1157 EMB performed, 467 were eligible (i.e, corresponding to either ISHLT grade 0 or â¥3A), among which 36 were selected for GEP according to the grading: 0 (CISHLT, n= 13); rejection â¥3A (RISHLT, n=13); 0 one month before ACR (BRISHLT, n=10). Results. We found 294 genes differentially expressed between CISHLT and RISHLT, mainly involved in immune activation, and inflammation. Hierarchical clustering showed a clear segregation of CISHLT and RISHLT groups and heterogeneity of GEP within RISHLT. All EMB presented immune activation, but some RISHLT EMB were strongly subject to inflammation, whereas others, closer to CISHLT, were characterized by structural modifications with lower inflammation level. We identified 15 probes significantly different between BRISHLT and CISHLT, including the gene of the muscular protein TTN. This result suggests that structural alterations precede inflammation in ACR. Linear Discriminant Analysis based on these 15 probes was able to identify the histological status of every 36 samples. Conclusion. Myocardial GEP is a helpful method to accurately diagnose ACR, and predicts rejection one month before its histological occurrence. These results should be considered in cardiac allograft recipientsâ care.
2017-03-07 | E-MTAB-5136 | biostudies-arrayexpress
Project description:Our goals were to determine whether (i) gene expression patterns in biopsies grouped by acute rejection grade (AR) would be consistent; (ii) a characteristic gene expression profile would be associated with ISHLT Grade 0, 1A & 1B (equivalent to 1R on recently revised criteria) and ISHLT grade 3A & 3B (equivalent to 2R & 3R on recently revised criteria); (iii) gene expression patterns emerging from the analysis would provide insights into mechanisms of AR. The samples used for gene expression profiling were endomyocardial biopsies (EMB) with different acute rejection gradings. The EMB (n=2726) were obtained from the right site of the interventricular septum of heart transplant recipients (n=2423) and graded according to the guidelines of the International Society for Heart and Lung Transplantation (ISHLT, grade 0, n=9; grade1A, n=5; 1B, n=5; 3A, n=4; 3B, n=43). Selection criteria for inclusion of patients in this analysis required the availability of appropriately stored EMB samples for RNA extraction; absence of any infection that required treatment with an antimicrobial drug at anytime during the posttransplant course of the patient; absence of prior AR rejection of any grade; absence of hemodynamic compromise at the time of EMB; use of standard immunosuppressive regimen; and the absence of HLA antibodies prior to transplant.
2008-10-18 | GSE9377 | 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 âmolecular Banffâ 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. Experiment Overall Design: 47 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria, and 13 normal kidney samples as controls.
2009-02-28 | E-GEOD-9489 | biostudies-arrayexpress
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