Brian D Piening1, Alexa K Dowdell2, Mengqi Zhang3, Bao-Li Loza3, David Walls3, Hui Gao3, Maede Mohebnasab4, Yun Rose Li3, Eric Elftmann3, Eric Wei5, Divya Gandla3, Hetal Lad3, Hassan Chaib5, Nancy K Sweitzer6, Mario Deng7, Alexandre C Pereira8, Martin Cadeiras9, Abraham Shaked3, Michael P Snyder5, Brendan J Keating10. 1. Earle A. Chiles Research Institute, Providence, Portland, Oregon; Department of Genetics, Stanford University School of Medicine, Stanford, California. 2. Earle A. Chiles Research Institute, Providence, Portland, Oregon. 3. Division of Transplantation, Department of Surgery, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania. 4. Division of Transplantation, Department of Surgery, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania; Department of Pathology, Oregon Health and Sciences University, Portland, Oregon. 5. Department of Genetics, Stanford University School of Medicine, Stanford, California. 6. Division of Cardiology, University of Arizona, Tucson, Arizona. 7. Division of Cardiology, David Geffen School of Medicine, University of California, Los Angeles, California. 8. Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School Hospital, São Paulo, Brazil. 9. Division of Cardiovascular Medicine, University of California Davis, Davis, California. 10. Division of Transplantation, Department of Surgery, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: bkeating@pennmedicine.upenn.edu.
Abstract
BACKGROUND: Heart transplantation provides a significant improvement in survival and quality of life for patients with end-stage heart disease, however many recipients experience different levels of graft rejection that can be associated with significant morbidities and mortality. Current clinical standard-of-care for the evaluation of heart transplant acute rejection (AR) consists of routine endomyocardial biopsy (EMB) followed by visual assessment by histopathology for immune infiltration and cardiomyocyte damage. We assessed whether the sensitivity and/or specificity of this process could be improved upon by adding RNA sequencing (RNA-seq) of EMBs coupled with histopathological interpretation. METHODS: Up to 6 standard-of-care, or for-cause EMBs, were collected from 26 heart transplant recipients from the prospective observational Clinical Trials of Transplantation (CTOT)-03 study, during the first 12-months post-transplant and subjected to RNA-seq (n = 125 EMBs total). Differential expression and random-forest-based machine learning were applied to develop signatures for classification and prognostication. RESULTS: Leveraging the unique longitudinal nature of this study, we show that transcriptional hallmarks for significant rejection events occur months before the actual event and are not visible using traditional histopathology. Using this information, we identified a prognostic signature for 0R/1R biopsies that with 90% accuracy can predict whether the next biopsy will be 2R/3R. CONCLUSIONS: RNA-seq-based molecular characterization of EMBs shows significant promise for the early detection of cardiac allograft rejection.
BACKGROUND: Heart transplantation provides a significant improvement in survival and quality of life for patients with end-stage heart disease, however many recipients experience different levels of graft rejection that can be associated with significant morbidities and mortality. Current clinical standard-of-care for the evaluation of heart transplant acute rejection (AR) consists of routine endomyocardial biopsy (EMB) followed by visual assessment by histopathology for immune infiltration and cardiomyocyte damage. We assessed whether the sensitivity and/or specificity of this process could be improved upon by adding RNA sequencing (RNA-seq) of EMBs coupled with histopathological interpretation. METHODS: Up to 6 standard-of-care, or for-cause EMBs, were collected from 26 heart transplant recipients from the prospective observational Clinical Trials of Transplantation (CTOT)-03 study, during the first 12-months post-transplant and subjected to RNA-seq (n = 125 EMBs total). Differential expression and random-forest-based machine learning were applied to develop signatures for classification and prognostication. RESULTS: Leveraging the unique longitudinal nature of this study, we show that transcriptional hallmarks for significant rejection events occur months before the actual event and are not visible using traditional histopathology. Using this information, we identified a prognostic signature for 0R/1R biopsies that with 90% accuracy can predict whether the next biopsy will be 2R/3R. CONCLUSIONS: RNA-seq-based molecular characterization of EMBs shows significant promise for the early detection of cardiac allograft rejection.
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