Endomyocardial Biopsy Diagnosis of Cardiac Allograft Rejection

2001 ◽  
pp. 177-196
Author(s):  
Barbara Czerska ◽  
Mary E. Keohane ◽  
Edward F. Philbin
Keyword(s):  
Endomyocardial Biopsy ◽  
Allograft Rejection ◽  
Cardiac Allograft ◽  
Cardiac Allograft Rejection ◽  
Biopsy Diagnosis

Abstract 19055: MicroRNA Gene Expression of Heart Transplant Endomyocardial Biopsy

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Eleanor Chang ◽  
Gregory Fishbein ◽  
Maral Bakir ◽  
Galyna Bondar ◽  
Nicholas Jackson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endomyocardial Biopsy ◽  
Allograft Rejection ◽  
Empirical Bayes ◽  
Expression Profiles ◽  
Target Prediction ◽  
Cardiac Allograft ◽  
Protein Kinase Activity ◽  
Cardiac Allograft Rejection ◽  
Clinical Phenotypes

Introduction Endomyocardial biopsy is the standard surveillance method to detect cardiac allograft rejection. While microRNAs (miRNA) play a major role in regulating mRNA, their nature and role in the biology is not well understood. We hypothesized that specific mRNA-miRNA networks can be identified underlying the clinical phenotypes of different forms of cardiac allograft rejection. Method Twenty one tissue samples from 14 post-HTx patients were subjected to genome wide miRNA sequencing. A non-parametric empirical Bayes framework removed batch effect and filtered genes with low variability. Weighted Gene Correlation Network Analysis (WGCNA) clustered genes into related eigengene modules based on their gene expression. Identified miRNAs were subjected to target prediction and compared with mRNA expression profiles previously identified on the same biopsies. Gene Ontology (GO) was used for biological interpretation of selected genes. Results 1270 miRNAs were used to construct 9 eigengene modules. Module-Trait relationship were then investigated as shown in Figure. The top ten miRNA probe sets filtered by the highest intra-module correlation and statistical significance were hsa-miR-141-3p, hsa-miR-150-5p, hsa-miR-605, hsa-miR-582-5p, hsa-miR-3150b-3p, hsa-miR-508-3p, hsa-miR-652-5p, hsa-miR-26a-1-3p, hsa-miR-3667-3p and hsa-miR-3911. Target prediction analysis resulted in 724 gene targets. GO analysis revealed 184 categories enriched by these genes including regulation of protein kinase activity, cardiac muscle cell differentiation and epithelial cell migration among others. Compared to mRNA previously identified in the same heart biopsies showed 685 overlapping gene targets. Conclusion WGCNA identified miRNA modules correlated with different clinical phenotypes of rejection. MRNA-miRNA pairs were identified to help understand the biology of rejection and as interesting candidates for diagnostic or therapeutic applications.

Somatostatin receptor scintigraphy predicts impending cardiac allograft rejection before endomyocardial biopsy

2000 ◽  
Vol 27 (12) ◽  
pp. 1754-1759 ◽  
Author(s):  
Carina Marí Aparici ◽  
Jagat Narula ◽  
Mireia Puig ◽  
Marta Camprecios ◽  
Juan C. Martín ◽  
...  
Keyword(s):  
Endomyocardial Biopsy ◽  
Allograft Rejection ◽  
Somatostatin Receptor ◽  
Cardiac Allograft ◽  
Somatostatin Receptor Scintigraphy ◽  
Cardiac Allograft Rejection ◽  
Receptor Scintigraphy

Correlation of noninvasive markers of cardiac allograft rejection with endomyocardial biopsy: A case report

Heart & Lung ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 518-521 ◽  
Author(s):  
Marian Manankil ◽  
Ashim Aggarwal ◽  
Sunil Pauwaa ◽  
Geetha Bhat
Keyword(s):  
Case Report ◽  
Endomyocardial Biopsy ◽  
Allograft Rejection ◽  
Cardiac Allograft ◽  
Cardiac Allograft Rejection ◽  
Noninvasive Markers

scholarly journals Surveillance Endomyocardial Biopsy in the Modern Era Produces Low Diagnostic Yield for Cardiac Allograft Rejection

2015 ◽  
Vol 99 (8) ◽  
pp. e75-e80 ◽  
Author(s):  
Keyur B. Shah ◽  
Maureen P. Flattery ◽  
Melissa C. Smallfield ◽  
Grace Merinar ◽  
Daniel G. Tang ◽  
...  
Keyword(s):  
Endomyocardial Biopsy ◽  
Allograft Rejection ◽  
Diagnostic Yield ◽  
Cardiac Allograft ◽  
Cardiac Allograft Rejection ◽  
Modern Era

Abstract 2312: Limitations of Molecular Expression Profiling ( Allomap Score ) in Predicting Endomyocardial Biopsy Findings in Cardiac Allograft Recipients: Two Year Follow-Up Surveillance Study

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Lazaros A Nikolaidis ◽  
Benham Borzognia ◽  
Alfred A Bove
Keyword(s):  
Endomyocardial Biopsy ◽  
Predictive Value ◽  
Allograft Rejection ◽  
Molecular Profiling ◽  
Cardiac Allograft ◽  
High Dose ◽  
Cardiac Allograft Rejection ◽  
Entire Cohort ◽  
Non Invasive ◽  
Non Gaussian

Background: Molecular profiling of immune pathways implicated in cardiac allograft rejection has led to the development of a composite score (Allomap, range: 0 – 40) recently approved for clinical use. The potential for non-invasive monitoring in lieu of invasive biopsies and its reported high negative (NPV) predictive value are offset by low positive predictive value (PPV) and controversy about the threshold score (≥ 30 vs. ≥ 35) consistent with rejection. Nevertheless, the score has not been extensively validated in clinical practice. Methods : We obtained blood samples from cardiac allograft recipients (n=242 samples over 2 years) for determination of Allomap8 score at the time of endomyocardial biopsy. We excluded patients with recent transplant, on high dose steroids or recently treated for rejection. Pathologists blinded to AlloMap score interpreted all biopsies. Results: The mean Allomap score in the entire cohort was 29.9±0.4 (median: 31). The distribution was non-Gaussian with the majority of samples in the upper quartile [< 24: n=43 (18 %), 25–29: n=49 (20%), 30 –34: n=98 (40 %), > 35: n=52 (22 %)] Only 9 biopsy specimens (3.7%) were consistent with severe rejection (ISHLT 3A/3B or ≥ 2R per amended classification). Scores were not significantly different across the spectrum of ISHLT grades. Allomap scores of non-rejectors (ISHLT 0), mild rejectors (1-R) and significant rejectors (≥ 2R) were not significantly different (29.3±0.6 vs. 30.2±0.5 vs. 30.1±2.2, respectively). In predicting clinically significant (ISHLT ≥ 3A or 2-R) rejection, the NPV of Allomap was 95 %, yet PPV was < 10 %. Sensitivity (30 –55%) and specificity (37–78%) were highly dependent on the threshold used (≥30 vs. ≥35), thus ROC performance was suboptimal. Conclusions: Although molecular profiling of candidate genes to predict cardiac allograft rejection remains an attractive, non-invasive and physiologically sound concept, the clinical application of the present assay is still limited

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