New Approaches to the Diagnosis of Rejection and Prediction of Tolerance in Liver Transplantation. Issue 10 (16th May 2022)

• Record Type: Journal Article
• Authors: Taner, Timucin; Bruner, Julia; Emamaullee, Juliet; Bonaccorsi-Riani, Eliano; Zarrinpar, Ali
• Is Part Of: Transplantation. Volume 106:Issue 10(2022)
• Page Start: 1952
• Page End: 1962
• Publication Date: 2022-05-16
• Subjects: Transplantation of organs, tissues, etc -- Periodicals; Transplantation immunology -- Periodicals; 617.95
• DOI: 10.1097/TP.0000000000004160
• Languages: English
• ISSNs: 0041-1337

Abstract

Abstract : Immunosuppression after liver transplantation is essential for preventing allograft rejection. However, long-term drug toxicity and associated complications necessitate investigation of immunosuppression minimization and withdrawal protocols. Development of such protocols is hindered by reliance on current paradigms for monitoring allograft function and rejection status. The current standard of care for diagnosis of rejection is histopathologic assessment and grading of liver biopsies in accordance with the Banff Rejection Activity Index. However, this method is limited by cost, sampling variability, and interobserver variation. Moreover, the invasive nature of biopsy increases the risk of patient complications. Incorporating noninvasive techniques may supplement existing methods through improved understanding of rejection causes, hepatic spatial architecture, and the role of idiopathic fibroinflammatory regions. These techniques may also aid in quantification and help integrate emerging -omics analyses with current assessments. Alternatively, emerging noninvasive methods show potential to detect and distinguish between different types of rejection while minimizing risk of adverse advents. Although biomarkers have yet to replace biopsy, preliminary studies suggest that several classes of analytes may be used to detect rejection with greater sensitivity and in earlier stages than traditional methods, possibly when coupled with artificial intelligence. Here, we provide an overview of the latest efforts in optimizing the diagnosis of rejection in liver transplantation.