Candidate: Maryam Afkarian received an MD-PhD from Washington University in St. Louis and underwent residency training in Internal Medicine at New York Presbyterian Hospital-Weill Cornell Medical Center. She is currently a Nephrology Research Fellow at the joint program of Massachusetts General Hospital and Brigham and Women's Hospital. Starting July 2010, she will be appointed as an instructor at the Nephrology Division of Massachusetts General Hospital. Mentor: Dr. Ravi Thadhani is an internationally recognized clinical and translational investigator with a strong track record of mentoring new investigators. He is, and will remain, a closely-involved mentor, committed to the success of Dr. Afkarian's training, her proposed studies and career development. Research: Diabetic nephropathy (DN) is the leading cause of end-stage kidney disease. However, with the current standards of care, we can only delay progression of this disease. This is partly due to a lack of effective therapies and partly due to absence of reliable assays for diagnosis of the early disease, before renal damage is severe or irreversible. New diagnostic and therapeutic tools are urgently needed, both of which require an improved understanding of the disease natural history, i.e. identification of new markers of onset and progression. Comparative proteomic analysis of urine (study of the urine protein composition and how it is changed in the disease state) has been used to identify markers for several kidney diseases. Dr. Thadhani (mentor)'s group has previously used this approach to identify a peptide signature that detected signs of early diabetic kidney injury up to 10 years prior to clinical diagnosis. This proposal lays out a multi-stage approach to identify the proteins that are altered in early DN. The preliminary data describes calibration and adaptation of a sensitive proteomic technology (iTRAQ: isobaric Tags for Relative and Absolute Quantitation) for application to urine.
In Aim 1 A, iTRAQ will be used to compare urine samples from patients with and without DN (cases and controls, respectively). This hypothesis-free and unbiased comparative analysis will generate a preliminary list of candidate biomarkers for early DN.
In Aim 1 B, this list will be supplemented with hypothesis-driven candidates, i.e. those with significant evidence of involvement in DN. Examples are proteins which (a) are part of pathways incriminated in DN, (b) have altered mRNA expression in DN or (c) have altered protein level in DN. This step serves to incorporate all currently available information into this biomarker discovery effort.
In Aim 3, a target-specific and quantitative assay, e.g. ELISA, is used to re-evaluate the expression of putative biomarkers from Aims 1A and 1B in an independent cohort. This step will help weed out the false positives and identify a subset of markers whose differential expression in DN is confirmed.
In Aim 4, the expression of these confirmed markers will be characterized over the course of disease. This proposal is designed to generate a group of candidate biomarkers for early DN which have been validated within the original study population. A future step would be to test these candidates in a broader and more varied population. In long term, we hope that the validated biomarkers would serve as a novel diagnostic tool for early DN and also help shed light on the disease pathophysiology.
Diabetes is the leading cause of end-stage kidney disease and dialysis in the US. The current medical tests can diagnose the disease only after significant and sometimes irreversible damage has already occurred. We plan to find urine marker proteins that can be used to detect early signs of diabetic damage to the kidneys, when it is more likely to be stopped or reversed.
|Vrana, Marc; Goodling, Anne; Afkarian, Maryam et al. (2016) An Optimized Method for Protein Extraction from OCT-Embedded Human Kidney Tissue for Protein Quantification by LC-MS/MS Proteomics. Drug Metab Dispos 44:1692-6|
|Afkarian, Maryam; Zelnick, Leila R; Hall, Yoshio N et al. (2016) Clinical Manifestations of Kidney Disease Among US Adults With Diabetes, 1988-2014. JAMA 316:602-10|
|de Boer, Ian H; Afkarian, Maryam; Tuttle, Katherine R (2016) The Surging Tide of Diabetes: Implications for Nephrology. Am J Kidney Dis 67:364-6|
|Afkarian, Maryam; Katz, Ronit; Bansal, Nisha et al. (2016) Diabetes, Kidney Disease, and Cardiovascular Outcomes in the Jackson Heart Study. Clin J Am Soc Nephrol 11:1384-91|
|Afkarian, Maryam; Zelnick, Leila R; Ruzinski, John et al. (2015) Urine matrix metalloproteinase-7 and risk of kidney disease progression and mortality in type 2 diabetes. J Diabetes Complications 29:1024-31|
|Shao, Baohai; de Boer, Ian; Tang, Chongren et al. (2015) A Cluster of Proteins Implicated in Kidney Disease Is Increased in High-Density Lipoprotein Isolated from Hemodialysis Subjects. J Proteome Res 14:2792-806|
|Afkarian, Maryam (2015) Diabetic kidney disease in children and adolescents. Pediatr Nephrol 30:65-74; quiz 70-1|
|Afkarian, Maryam; Hirsch, Irl B; Tuttle, Katherine R et al. (2014) Urinary excretion of RAS, BMP, and WNT pathway components in diabetic kidney disease. Physiol Rep 2:e12010|
|de Boer, Ian H; Afkarian, Maryam; Rue, Tessa C et al. (2014) Renal outcomes in patients with type 1 diabetes and macroalbuminuria. J Am Soc Nephrol 25:2342-50|
|Mottl, Amy K; Lauer, Abigail; Dabelea, Dana et al. (2013) Albuminuria according to status of autoimmunity and insulin sensitivity among youth with type 1 and type 2 diabetes. Diabetes Care 36:3633-8|
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