Clinical transplantation · 2026
Raman Urine Fingerprinting to Predict DGF, Assess Renal Allograft Quality, and Monitor Its State of Health.
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Orlando Giuseppe, Senger Ryan S, Issa Amr Sayed, Asl Romina Seifollahi, Gutierrez Alejandra Mena, Jay Colleen C, McCracken Emily K E, Farney Alan C, Stratta Robert J, Webb Christopher J, Davis Hollie B, Doty Tracy, McPherson Gwen, Monetti Alexandra R, Savino John R, Byers Lori, Fallahzadeh Mohammad Kazem, Reeves-Daniel Amber, Sakhovskaja Natalia V, Asthana Amish, Yoza Barbara K, Bussolati Benedetta, Mikhailov Alexei V, Peveri Emma, Schaich Christopher L, Ngo Lacey, Gage Fred, Fisher Robert, Robertson John
Аннотация
OBJECTIVES: To determine whether Raman spectroscopy-based urine molecular fingerprinting (UMF) may predict delayed graft function (DGF) and assess renal allograft quality prior to transplant and monitor its state of health after transplantation.
BACKGROUND: Current methods for assessing the quality of the renal allograft at baseline and its state of health post-transplantation are inadequate.
METHODS: We conducted a pilot study in 26 patients receiving DCD allografts. UMF was performed on urine samples collected from study participants immediately before transplantation (baseline), on postoperative day 1-3, and monthly thereafter. UMF findings were correlated with clinical and laboratory data. Primary endpoint was identification of a DGF fingerprint. Secondary endpoints were identification of fingerprints for acute rejection, CMV, BK and eGFR.
RESULTS: DGF was observed in 58% of our patients. UMF fingerprints from patients with DGF were distinct from UMF fingerprints of non-DGF patients. Notably, UMF analysis of baseline urine samples from patients prior to transplantation also predicted development of DGF. A correlation of UMF with eGFR was observed, whereas we did not identify fingerprints specific for rejection, CMV or BK possibly due to the small patient population.
CONCLUSIONS: In this exploratory study, UMF predicts DGF prior to transplantation and provides information on the state of health of the allograft following transplantation.
BACKGROUND: Current methods for assessing the quality of the renal allograft at baseline and its state of health post-transplantation are inadequate.
METHODS: We conducted a pilot study in 26 patients receiving DCD allografts. UMF was performed on urine samples collected from study participants immediately before transplantation (baseline), on postoperative day 1-3, and monthly thereafter. UMF findings were correlated with clinical and laboratory data. Primary endpoint was identification of a DGF fingerprint. Secondary endpoints were identification of fingerprints for acute rejection, CMV, BK and eGFR.
RESULTS: DGF was observed in 58% of our patients. UMF fingerprints from patients with DGF were distinct from UMF fingerprints of non-DGF patients. Notably, UMF analysis of baseline urine samples from patients prior to transplantation also predicted development of DGF. A correlation of UMF with eGFR was observed, whereas we did not identify fingerprints specific for rejection, CMV or BK possibly due to the small patient population.
CONCLUSIONS: In this exploratory study, UMF predicts DGF prior to transplantation and provides information on the state of health of the allograft following transplantation.