Our goal in this study is to discover highly specific diagnostic non-invasive biomarkers by analyzing a large cohort (n=660) patient urine samples for different kidney transplant injury phenotypes in pediatric renal 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 being an ultrafiltrate of plasma and a direct filtrate of the kidney provides a valuable resource for monitoring graft health and dysfunction. In this proposal, we propose to employ a cutting-edge, comprehensive analysis of the urinary proteome by using recently developed and LC-FT MS/MS-UStags based peptidomics analysis of native urinary peptides and LC-MS/MS based soluble protein analysis of human urine. Availability of state-of-the-art proteomics facility at PNNL and an environment of outstanding bioinformatics with available comprehensive Clinical Database at Stanford will support high-throughput biomarker screening and data analysis for selection of 20 most significant peptides and proteins for differentiating different graft injury phenotypes- AR, CAN, BKV and stable functioning grafts (STA). The selection of the most biologically relevant candidates will be aided by robust integrative proteogenomic data analysis which will use overlapping biopsy microarray data and urine proteomic data from the same patients, 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 SRM on an independent set of 480 urine samples for diagnosis and prediction. The protein/peptide markers will be useful in developing ELISA assays which 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|
|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|
|Vitalone, Matthew J; Sigdel, Tara K; Salomonis, Nathan et al. (2015) Transcriptional Perturbations in Graft Rejection. Transplantation 99:1882-93|
|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|
|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; 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|
|Sigdel, Tara K; Gao, Xiaoxiao; Sarwal, Minnie M (2012) Protein and peptide biomarkers in organ transplantation. Biomark Med 6:259-71|
|Shi, Tujin; Su, Dian; Liu, Tao et al. (2012) Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics. Proteomics 12:1074-92|
|Sigdel, Tara K; Lee, Sangho; Sarwal, Minnie M (2011) Profiling the proteome in renal transplantation. Proteomics Clin Appl 5:269-80|
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