Our goal in this study is to discovery of diagnostic non-invasive biomarkers in a large cohort (n=580) patient urine samples for different graft injury phenotypes in pediatric kidney transplantation. Kidney transplantation is the treatment of choice for children with end stage kidney disease. Graft survival is limited by the accrual of different injuries such as acute rejection (AR), chronic allograft nephropathy (CAN), and viral infection with the BK virus (BKV), which are indistinguishable by simply monitoring the serum creatinine and require an invasive biopsy for diagnosis of established injury. Urine is an ultrafiltrate of plasma and a direct filtrate of the kidney and provides a valuable resource for monitoring graft health and dysfunction. We propose to employ cutting-edge, comprehensive analysis of the urinary proteome by LC-MALDI based peptidomics and LC-MS/MS based soluble protein analysis of human urine. An environment of outstanding bioinformatics and the availability of a comprehensive Clinical Database will support high-throughput data analysis for selection of 50 most significant peptides and proteins for differentiating different graft injury phenotypes- AR, CAN, BKV and stable functioning grafts (STA). To enable selection of the most biologically relevant candidates, robust integrative proteogenomic data analysis will be performed using overlapping biopsy microarray data and urine proteomic data from the same patient, collected at the same time-point. Specific and sensitive non-invasive urinary biomarkers discovery for different phenotypes of graft injury will undergo pre-clinical validation by MRM on an independent set of 400 urine samples for diagnosis and prediction. The deliverable from this proposal is to enrich for ~10 urinary protein biomarkers that can be used for clinical monitoring of graft injury, replacing the invasive transplant biopsy.
In the absence of an effective noninvasive way of diagnosing acute injury, kidney biopsy is the only way to monitor the clinical progress the transplanted kidney. In this study, we propose a comprehensive search for biomarkers that could be later developed as an injury specific clinical test. We are going to use two most powerful proteomic methods to identify these biomarkers which will be first of its kind in the field of transplantation.
| Sigdel, Tara K; Gao, Yuqian; He, Jintang et al. (2016) Mining the human urine proteome for monitoring renal transplant injury. Kidney Int 89:1244-52 |
| Yang, Joshua Young Cynming; Sigdel, Tara K; Sarwal, Minnie M (2016) Self-antigens and rejection: a proteomic analysis. Curr Opin Organ Transplant 21:362-7 |
| Sigdel, Tara K; Bestard, Oriol; Salomonis, Nathan et al. (2016) Intragraft Antiviral-Specific Gene Expression as a Distinctive Transcriptional Signature for Studies in Polyomavirus-Associated Nephropathy. Transplantation 100:2062-70 |
| Nasr, Michael; Sigdel, Tara; Sarwal, Minnie (2016) Advances in diagnostics for transplant rejection. Expert Rev Mol Diagn 16:1121-1132 |
| Vitalone, Matthew J; Sigdel, Tara K; Salomonis, Nathan et al. (2015) Transcriptional Perturbations in Graft Rejection. Transplantation 99:1882-93 |
| Sigdel, Tara K; Bestard, Oriol; Tran, Tim Q et al. (2015) A Computational Gene Expression Score for Predicting Immune Injury in Renal Allografts. PLoS One 10:e0138133 |
| Delville, Marianne; Sigdel, Tara K; Wei, Changli et al. (2014) A circulating antibody panel for pretransplant prediction of FSGS recurrence after kidney transplantation. Sci Transl Med 6:256ra136 |
| Sigdel, Tara K; Salomonis, Nathan; Nicora, Carrie D et al. (2014) The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics. Mol Cell Proteomics 13:621-31 |
| Sigdel, Tara K; Sarwal, Minnie M (2013) Moving beyond HLA: a review of nHLA antibodies in organ transplantation. Hum Immunol 74:1486-90 |
| Sigdel, Tara K; Sarwal, Minnie M (2013) Discovery and customized validation of antibody targets by protein arrays and indirect ELISA. Methods Mol Biol 1034:373-84 |
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