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Biomarkers, monitoring & outcomes

Tuesday September 13, 2022 - 17:35 to 18:35

Room: CF-5

344.6 QSant, a urine-based multi-analyte assay, detects and predicts acute rejection risk with high accuracy, in the first 2 weeks post-transplant

Minnie M. Sarwal, United States

Professor in Residence, Surgery, Medicine, Pediatrics
Department of Transplant
UC San Francisco


QSant, a urine-based multi-analyte assay, detects and predicts acute rejection risk with high accuracy, in the first 2 weeks post-transplant

Carla Baan1, Srinka Ghosh2, Jeroen Verhoeven1, Dennis Hesselink1, Karin Boer1, Minnie Sarwal2.

1Erasmus MC, Rotterdam, Netherlands; 2Nephrosant, San Mateo, CA, United States

Introduction: Current blood-based biomarker assays are confounded by ischemic reperfusion injury(IRI) and have an inability to detect acute rejection(AR) in the early post-transplant(tx) period. Some of these assays fail in the first 2 weeks, and others fail even in the first 90 days post-transplant. We proposed to evaluate if the urine biomarkers-based assay – QSant [Yang, STM 2020].  - could accurately detect biopsy confirmed AR in functioning allografts in the first 2 weeks post-transplant.

Methods: 27(sensitized=4, cPRA >20%) adult renal allograft recipients (69% deceased donors), on basiliximab induction and TAC/MMF/CS maintenance, with (n=18) and without (n=9) biopsy confirmed AR (BPAR), had serial urine samples (n=96) bio-banked in the first 2 weeks, at cause biopsy and at 6 months. First episode of AR occurred at 8 days(median) post-tx and 69% of the early AR were refractory requiring Alemtuzumab. QSant was run on all urine samples, and the following clinical risk categories identified: i) immunequiescence (IQ): Q-Score <32 and ii) acute rejection (AR): Q-Score >32. The latter range was further sub-divided into a dynamic alloimmune injury spectrum: 32≥QScore≤55; and a high-grade acute rejection: QScore >55 [Sarwal, JCM 2022]. Analyses comprised of:(i) Cross-sectional correlation between the Q-Score, SCr and BPAR; (ii)Longitudinal immunosuppression (IS) treatment response-correlation with QSant.

Results: BPAR occurred in 66% of patients; 11/18 cases occurring in the first week post-tx. The accuracy of QSant to detect early BPAR(< 2 weeks post-tx) was 89.3% this is in contrast to the median change in SCr by +15%. QSant detected both ABMR and TCMR. The median Q-Scores for 5 cases of ABMR were lower at 30(IQR:25-43) compared to 13 cases of TCMR at 49(IQR:29-85). In 44% of cases elevated Q-Scores >32 was observed preceding BPAR by 3 days(median), supporting the ability of QSant to predict the risk of AR across the alloimmune injury spectrum. Refractory BPAR cases (n=9) had higher Q-Scores than treatment sensitive rejections (Q-Score: 59(IQR:31-85) versus 32(IQR:19-41)). This differential was statistically significant (p=0.008) attesting to treatment sensitive rejections encompassing the alloimmune injury spectrum and refractory events being more of high-grade AR.  Repeat QSant monitoring post treatment of refractory BPAR registered a 25% decline(median) in response to IS treatment.

Conclusions: QSant trajectory tracking by serial urine analysis early post-transplant, can potentially obviate or trigger for-cause biopsies. Despite the sampling size, urinary QSant-based AR diagnosis is not confounded by early ischemia reperfusion injury and very early time post- transplant. This underscores the potential to augment clinician decision-making during the early weeks post-transplant, to diagnose AR.

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