Circulating microRNAs in cellular and antibody-mediated heart transplant rejection.

MedStar author(s):
Citation: Journal of Heart & Lung Transplantation. 2022 Jun 28PMID: 35872109Institution: MedStar Heart & Vascular InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: IN PROCESS -- NOT YET INDEXEDYear: 2022Local holdings: Available online from MWHC library: 1999 - present, Available in print through MWHC library:1999-2007ISSN:
  • 1053-2498
Name of journal: The Journal of heart and lung transplantation : the official publication of the International Society for Heart TransplantationAbstract: 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.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. Copyright © 2022 International Society for Heart and Lung Transplantation. All rights reserved.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.All authors: Agbor-Enoh S, Bagchi P, Berry GJ, deFilippi CR, Diao G, Feller E, GRAfT Investigators, Hsu S, Jang MK, Khush KK, Lewsey SC, Marboe C, Mercado A, Morales DJ, Najjar SS, Rodrigo ME, Shah KB, Shah P, Valantine HAFiscal year: FY2022Digital Object Identifier: Date added to catalog: 2022-09-26
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Item type Current library Collection Call number Status Date due Barcode
Journal Article MedStar Authors Catalog Article 35872109 Available 35872109

Available online from MWHC library: 1999 - present, Available in print through MWHC library:1999-2007

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.

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. Copyright © 2022 International Society for Heart and Lung Transplantation. All rights reserved.

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.

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