Date: Sunday, May 3, 2015
Session Time: 5:30pm-6:30pm
Presentation Time: 5:30pm-6:30pm
Location: Exhibit Hall E
Introduction: Inability to effectively monitor transplant injuries leads to immune and non-immune mediated graft dysfunction. A non-invasive tool to monitor such injuries is an unmet need.
Method:Quantitative analysis of the urinary proteome was performed using iTRAQ based LC-MS, on a set of 264 biobanked urine samples with matched biopsies that included 70 acute rejection (AR); 70 stable graft (STA); 70 transplant glomerulopathy (TG), 35 BK virus nephropathy (BKVN); 10 patients with nephrotic syndrome (NS), and 9 normal healthy controls (HC). Potential biomarker proteins from the initial discovery were analyzed for validation by mass spectrometry (MS) based selected reaction monitoring method (SRM) on two set of independent cohorts of 71 (20 AR, 20 STA, 15 TG, 16 BKVN ) biopsy matched urine samples. The respective peptides were synthesized with heavy label and mass spectrometry data was transformed and normalized against urine creatinine.
Result: We were able to successfully optimize and detect urinary peptides from 67 proteins including 36 AR-specific, 8 BKVN specific and 23 TG specific. From the first validation set of 20 AR, 20 STA, 15 TG, 16 BKVN we have validated significant increase of 16 AR-specific, 12 TG-specific and 6 BK specific proteins with a criteria of p<0.01. In the first phase, we selected four proteins for ELISA validation, FGB, FGG, SUMO2, and HLA-DRB1 based on their relevance in AR. Urinary FBB in AR was significantly higher vs STA (p=0.04), vs CAI (p=0.05), and vs BKV (p=0.03). The increased urine protein level of FBG in AR (p=0.04), vs CAI (p=0.05), and vs BKV (p=0.02). The urine protein level of HLA-DRB1 was significantly higher in AR vs STA (p=0.001), vs CAI) (p=0.003), and vs BKV (p=0.04). Urine SUMO2 level was significantly higher in AR vs STA urine (p=0.005), and vs BKVN urine (p=0.04). An ROC analysis to identify AR from the rest of the phenotypes (CAI, BK, and STA) on the data from three urine proteins (FBB, FGG, and HLA-DRB1) yielded an AUC of 0.8.
Conclusion: We have demonstrated that mass spectrometry based proteomic discovery can identify potential biomarkers further validation of these in a larger sample set of a clinical trial is underway which will further validate and facilitate in developing a non-invasive diagnostic tool for transplant injury surveillance.
To cite this abstract in AMA style:Sigdel T, Salomonis N, Nicora C, He J, Qian W-J, Camp D, Sarwal M. Potential Urine Protein Biomarkers for Kidney Transplantation Dysfunction Through Quantitative Proteomics [abstract]. Am J Transplant. 2015; 15 (suppl 3). https://atcmeetingabstracts.com/abstract/potential-urine-protein-biomarkers-for-kidney-transplantation-dysfunction-through-quantitative-proteomics/. Accessed September 19, 2021.
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