A novel donor-derived cell-free DNA assay for the detection of acute rejection in heart transplantation

Kim, Paul J.; Olymbios, Michael; Siu, Alfonso; Wever-Pinzon, Omar; Adler, Eric; Liang, Nathan L.; Swenerton, Ryan; Sternberg, Jonathan; Kaur, Neeraj; Ahmed, Ebad; Chen, Yen-An; Fehringer, Gordon; Demko, Zachary; Billings, Paul R.; Stehlik, Josef

doi:10.1016/j.healun.2022.04.002

Cited by 33 publications

(36 citation statements)

References 38 publications

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“…Most of these methods have a lower limit of quantification of ~0.15% dd-cfDNA and an imprecision (CV) of 3%-12% (Oellerich et al, 2020). Studies in heart transplant recipients reported also lower baseline levels of 0.02% (Agbor-Enoh et al, 2021a), 0.04% (Kim et al, 2022) and 0.07% (Khush et al, 2019). In kidney transplantation a lower limit of 0.08% has recently be published (Halloran et al, 2022).…”

Section: Methods For Donor-derived Cell-free Dna Determinationmentioning

confidence: 98%

“…Dd-cfDNA fraction was also significantly elevated for CLAD (De Vlaminck et al, 2015). The high negative predictive value of 97% in heart transplant recipients (Khush et al, 2019;Kim et al, 2022;Knuettgen et al, 2022) has the potential to reduce the number of endomyocardial biopsies that have a serious complication rate of 0.5%-1% (Miller et al, 2013;Knuettgen et al, 2022).…”

Section: Clinical Validity Of Donor-derived Cell-free Dna In Transpla...mentioning

confidence: 96%

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Donor-derived cell-free DNA as a diagnostic tool in transplantation

et al. 2022

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There is a need to improve personalized immunosuppression in organ transplantation to reduce premature graft loss. Biomarkers are needed to better detect rejection, asymptomatic graft injury, and under-immunosuppression. Assessment of minimal necessary exposure to guide tapering and prevent immune activation is also important. There is robust clinical evidence from a large number of published studies supporting the role of dd-cfDNA for monitoring graft integrity and detection or exclusion of rejection. Dd-cfDNA indicates graft cell death without being rejection specific. It can be determined in plasma through droplet digital PCR using preselected SNPs or next generation sequencing. Changes in recipient cfDNA (e.g., by infection) can affect the results of dd-cfDNA fractional determination. This limitation can be overcome using absolute dd-cfDNA quantification. The combination of fractional and absolute determination including total cfDNA is recommended for meaningful interpretation of the results. The value proposition for the patient includes earlier transplant injury detection and intervention, less full blown rejection risk, an alternative to invasive biopsies, and personalized immunosuppression with potential for improved long-term outcome. Transplant physicians benefit from better immunosuppressive guidance and having an alternative when biopsies are refused or contraindicated. Further advantages are improved biopsy interpretation, less trial and error changes in immunosuppression, and less time dealing with complications. The laboratory medicine specialist can provide more effective services. Hospital management and insurance companies could benefit from more cost-effective surveillance of transplant recipients. Potential cost savings would result from fewer biopsies as a result of the tests’ high negative predictive value, fewer re-transplantations, and less organ failure with return to dialysis. A pathway to implementation and metrics is suggested to measure the effectiveness of dd-cfDNA testing.

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Section: Methods For Donor-derived Cell-free Dna Determinationmentioning

confidence: 98%

Section: Clinical Validity Of Donor-derived Cell-free Dna In Transpla...mentioning

confidence: 96%

Donor-derived cell-free DNA as a diagnostic tool in transplantation

et al. 2022

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“… 8 Non-published results described by the manufacturer of these tests also list AUC values of 0.68, 0.77, and 0.81 for GEP, dd-cfDNA and a combination of both tests, respectively. 29 Three small studies evaluating the utility of dd-cfDNA to detect all forms of cardiac allograft rejection (ACR and AMR combined) among 65, 171, and 223 patients showed an AUC of 0.83, 30 0.92 31 and 0.86 32 respectively. The AUCs from these studies are notably higher than prior studies likely because the outcome of interest was different as these studies included detection of both ACR and AMR.…”

Section: Discussionmentioning

confidence: 99%

Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model

Adedinsewo

Hardway

Morales-Lara

et al. 2023

European Heart Journal - Digital Health

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Background and aims Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG). Methods and Results Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7,590 unique ECG-biopsy pairs, belonging to 1,427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (n = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 (95% CI: 0.78-0.90) and 95% (19/20; 95% CI: 75%-100%) sensitivity. A prospective proof-of-concept screening study (n = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16%-100%) sensitivity. Conclusion An AI-ECG model is effective for detection of moderate to severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.

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“…In an initial 2-center case-control evaluation of this assay, there was a sensitivity of 78.5, specificity of 76.9, PPV of 25.1%, NPV of 97.3%, and AUC of 0.86 for the detection of ACR grade ≥2R or pAMR grade ≥1. 22 dd-cfDNA tests are optimally used to avoid biopsies when there is low pretest probability and clinical suspicion for ACR and AMR.…”

Section: Donor-derived Cell-free Dnamentioning

confidence: 99%

Selection and Interpretation of Molecular Diagnostics in Heart Transplantation

Goldberg,

Truby,

Agbor-Enoh

et al. 2023

Circulation

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The number of heart transplants performed annually in the United States and worldwide continues to increase, but there has been little change in graft longevity and patient survival over the past 2 decades. The reference standard for diagnosis of acute cellular and antibody-mediated rejection includes histologic and immunofluorescence evaluation of endomyocardial biopsy samples, despite invasiveness and high interrater variability for grading histologic rejection. Circulating biomarkers and molecular diagnostics have shown substantial predictive value in rejection monitoring, and emerging data support their use in diagnosing other posttransplant complications. The use of genomic (cell-free DNA), transcriptomic (mRNA and microRNA profiling), and proteomic (protein expression quantitation) methodologies in diagnosis of these posttransplant outcomes has been evaluated with varying levels of evidence. In parallel, growing knowledge about the genetically mediated immune response leading to rejection (immunogenetics) has enhanced understanding of antibody-mediated rejection, associated graft dysfunction, and death. Antibodies to donor human leukocyte antigens and the technology available to evaluate these antibodies continues to evolve. This review aims to provide an overview of biomarker and immunologic tests used to diagnose posttransplant complications. This includes a discussion of pediatric heart transplantation and the disparate rates of rejection and death experienced by Black patients receiving a heart transplant. This review describes diagnostic modalities that are available and used after transplant and the landscape of future investigations needed to enhance patient outcomes after heart transplantation.

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A novel donor-derived cell-free DNA assay for the detection of acute rejection in heart transplantation

Cited by 33 publications

References 38 publications

Donor-derived cell-free DNA as a diagnostic tool in transplantation

Donor-derived cell-free DNA as a diagnostic tool in transplantation

Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model

Selection and Interpretation of Molecular Diagnostics in Heart Transplantation

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