Palak Shah1, Sean Agbor-Enoh2, Pramita Bagchi3, Christopher R deFilippi4, Angela Mercado5, Gouqing Diao6, Dave Jp Morales7, Keyur B Shah8, Samer S Najjar9, Erika Feller10, Steven Hsu11, Maria E Rodrigo8, Sabra C Lewsey11, Moon Kyoo Jang12, Charles Marboe13, Gerald J Berry14, Kiran K Khush14, Hannah A Valantine15. 1. Heart Failure, Mechanical Circulatory Support & Transplant, Inova Heart and Vascular Institute, Falls Church, Virginia; Genomic Research Alliance for Transplantation (GRAfT), Bethesda, Maryland. Electronic address: palak.shah@inova.org. 2. Genomic Research Alliance for Transplantation (GRAfT), Bethesda, Maryland; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland; Applied Precision Genomics, National Heart, Lung and Blood Institute, Bethesda, Maryland. 3. Volgenau School of Engineering, George Mason University, Fairfax, Virginia. 4. Cardiovascular Medicine, Inova Heart and Vascular Institute, Falls Church, Virginia. 5. Heart Failure, Mechanical Circulatory Support & Transplant, Inova Heart and Vascular Institute, Falls Church, Virginia. 6. Milken Institute School of Public Health, The George Washington University, Washington, District of Columbia. 7. Heart Failure & Transplantation, Stanford University, Palo Alto, California. 8. The Pauley Heart Center, Virginia Commonwealth University, Richmond, Virginia. 9. Advanced Heart Failure Program, Medstar Heart and Vascular Institute, Washington Hospital Center, Washington, District of Columbia. 10. Heart Failure & Transplantation, University of Maryland, Baltimore, Maryland. 11. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland. 12. Genomic Research Alliance for Transplantation (GRAfT), Bethesda, Maryland; Applied Precision Genomics, National Heart, Lung and Blood Institute, Bethesda, Maryland. 13. Department of Pathology, New York Presbyterian University Hospital of Cornell and Columbia, New York, New York, New York. 14. Stanford University School of Medicine, Palo Alto, California. 15. Genomic Research Alliance for Transplantation (GRAfT), Bethesda, Maryland; Stanford University School of Medicine, Palo Alto, California.
Abstract
BACKGROUND: Noninvasive monitoring of heart allograft health is important to improve clinical outcomes. MicroRNAs (miRs) are promising biomarkers of cardiovascular disease and limited studies suggest they can be used to noninvasively diagnose acute heart transplant rejection. METHODS: The Genomic Research Alliance for Transplantation (GRAfT) is a multicenter prospective cohort study that phenotyped heart transplant patients from 5 mid-Atlantic centers. Patients who had no history of rejection after transplant were compared to patients with acute cellular rejection (ACR) or antibody-mediated rejection (AMR). Small RNA sequencing was performed on plasma samples collected at the time of an endomyocardial biopsy. Differential miR expression was performed with adjustment for clinical covariates. Regression was used to develop miR panels with high diagnostic accuracy for ACR and AMR. These panels were then validated in independent samples from GRAfT and Stanford University. Receiver operating characteristic curves were generated and area under the curve (AUC) statistics calculated. Distinct ACR and AMR clinical scores were developed to translate miR expression data for clinical use. RESULTS: The GRAfT cohort had a median age of 52 years, with 35% females and 45% Black patients. Between GRAfT and Stanford, we included 157 heart transplant patients: 108 controls and 49 with rejection (50 ACR and 38 AMR episodes). After differential miR expression and regression analysis, we identified 12 miRs that accurately discriminate ACR and 17 miRs in AMR. Independent validation of the miR panels within GRAfT led to an ACR AUC 0.92 (95% confidence interval [CI]: 0.86-0.98) and AMR AUC 0.82 (95% CI: 0.74-0.90). The externally validated ACR AUC was 0.72 (95% CI: 0.59-0.82). We developed distinct ACR and AMR miR clinical scores (range 0-100), a score ≥ 65, identified ACR with 86% sensitivity, 76% specificity, and 98% negative predictive value, for AMR score performance was 82%, 84% and 97%, respectively. CONCLUSIONS: We identified novel miRs that had excellent performance to noninvasively diagnose acute rejection after heart transplantation. Once rigorously validated, the unique clinical ACR and AMR scores usher in an era whereby genomic biomarkers can be used to screen and diagnose the subtype of rejection. These novel biomarkers may potentially alleviate the need for an endomyocardial biopsy while facilitating the initiation of targeted therapy based on the noninvasive diagnosis of ACR or AMR.
BACKGROUND: Noninvasive monitoring of heart allograft health is important to improve clinical outcomes. MicroRNAs (miRs) are promising biomarkers of cardiovascular disease and limited studies suggest they can be used to noninvasively diagnose acute heart transplant rejection. METHODS: The Genomic Research Alliance for Transplantation (GRAfT) is a multicenter prospective cohort study that phenotyped heart transplant patients from 5 mid-Atlantic centers. Patients who had no history of rejection after transplant were compared to patients with acute cellular rejection (ACR) or antibody-mediated rejection (AMR). Small RNA sequencing was performed on plasma samples collected at the time of an endomyocardial biopsy. Differential miR expression was performed with adjustment for clinical covariates. Regression was used to develop miR panels with high diagnostic accuracy for ACR and AMR. These panels were then validated in independent samples from GRAfT and Stanford University. Receiver operating characteristic curves were generated and area under the curve (AUC) statistics calculated. Distinct ACR and AMR clinical scores were developed to translate miR expression data for clinical use. RESULTS: The GRAfT cohort had a median age of 52 years, with 35% females and 45% Black patients. Between GRAfT and Stanford, we included 157 heart transplant patients: 108 controls and 49 with rejection (50 ACR and 38 AMR episodes). After differential miR expression and regression analysis, we identified 12 miRs that accurately discriminate ACR and 17 miRs in AMR. Independent validation of the miR panels within GRAfT led to an ACR AUC 0.92 (95% confidence interval [CI]: 0.86-0.98) and AMR AUC 0.82 (95% CI: 0.74-0.90). The externally validated ACR AUC was 0.72 (95% CI: 0.59-0.82). We developed distinct ACR and AMR miR clinical scores (range 0-100), a score ≥ 65, identified ACR with 86% sensitivity, 76% specificity, and 98% negative predictive value, for AMR score performance was 82%, 84% and 97%, respectively. CONCLUSIONS: We identified novel miRs that had excellent performance to noninvasively diagnose acute rejection after heart transplantation. Once rigorously validated, the unique clinical ACR and AMR scores usher in an era whereby genomic biomarkers can be used to screen and diagnose the subtype of rejection. These novel biomarkers may potentially alleviate the need for an endomyocardial biopsy while facilitating the initiation of targeted therapy based on the noninvasive diagnosis of ACR or AMR.
Authors: Alexandre Loupy; Jean Paul Duong Van Huyen; Luis Hidalgo; Jeff Reeve; Maud Racapé; Olivier Aubert; Jeffery M Venner; Konrad Falmuski; Marie Cécile Bories; Thibaut Beuscart; Romain Guillemain; Arnaud François; Sabine Pattier; Claire Toquet; Arnaud Gay; Philippe Rouvier; Shaida Varnous; Pascal Leprince; Jean Philippe Empana; Carmen Lefaucheur; Patrick Bruneval; Xavier Jouven; Philip F Halloran Journal: Circulation Date: 2017-02-01 Impact factor: 29.690
Authors: Kiran K Khush; Jignesh Patel; Sean Pinney; Andrew Kao; Rami Alharethi; Eugene DePasquale; Gregory Ewald; Peter Berman; Manreet Kanwar; David Hiller; James P Yee; Robert N Woodward; Shelley Hall; Jon Kobashigawa Journal: Am J Transplant Date: 2019-04-08 Impact factor: 8.086