Erythropoietin (EPO) and erythropoiesis-stimulating agents (ESAs) are used to treat the anemia of chronic renal disease in greater than 90% of all in-center hemodialysis patients at a cost of approximately 2 billion dollars per year. Despite protocols for anemia management in the end stage renal disease (ESRD) population, a large proportion of patients do not respond predictably to typical doses of EPO. Several recent randomized controlled trials looking to increase hemoglobin (Hb) in patients with the anemia of renal disease have uncovered many questions about the treatment of anemia with ESAs not previously addressed in new drug applications or in subsequent research. A call has been made for the establishment of the optimal Hb target, dosing algorithm, and monitoring approach for patients with anemia from chronic renal disease. We suggest that our poor understanding of the mechanisms leading to EPO resistance prevents the ability to objectively predict and design dosing algorithms for anemia management. We propose that this problem is best addressed with a semi-empirical method which uses surrogate markers of EPO responsiveness and computer-directed algorithms to achieve a specific Hb target range and to exaggerated oscillations in Hb levels. The broad-based long term goals of our research are to address a critical barrier to the progress with personalization of anemia management by developing more objective, patient specific approaches to EPO dosing in ESRD populations. Data developed in our labs suggests that the abundances of specific serum proteins and protein fragments correlate with EPO responsiveness in ESRD patients receiving dialysis therapy. These data suggest these proteins and protein fragments classify EPO response with more sensitivity and specificity than C-reactive protein and hepcidin. We hypothesize that specific serum proteins and peptides are candidate surrogate biomarkers for EPO responsiveness and can be used to improve existing algorithms for predictive EPO response indexing. We propose 2 aims.
Aim 1 - We propose to validate selected candidate surrogate biomarkers in a larger population of ESRD patients enrolled from three geographically distinct centers. Within this aim we will address the null hypothesis that EPO resistance is characterized by altered expression of Th1- and Th2-cytokines, and address the hypothesis that serum peptides and proteins can predict EPO responsiveness.
In Aim 2 - We propose to investigate the contribution of our surrogate biomarkers to dosage prediction in long-term administration of EPO and compare models base on these new biomarkers to established models. Using a novel Model Predictive Control (MPC) tool that we have previously published and demonstrated to be superior to standard EPO dosing techniques, we will access and incorporate the validated surrogate biomarkers to develop a refined clinical tool for dosing of ESAs.

Public Health Relevance

The empirical treatment of anemia with erythropoiesis stimulating agents does not achieve optimal results in a significant number of end-stage renal disease patients receiving hemodialysis. Our laboratories have independently identified candidate surrogate serum biomarkers of erythropoiesis in end-stage renal disease hemodialysis patients that are associated with treatment outcome and have led the development and testing of computation methods for dosing of erythropoiesis stimulating agents. We propose to merge these two novel advances and determine their combined utility to improve erythropoiesis stimulating agent dosing in end-stage renal disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK091584-04
Application #
8721943
Study Section
Special Emphasis Panel (ZDK1)
Program Officer
Abbott, Kevin C
Project Start
2011-09-20
Project End
2016-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
4
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Louisville
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
City
Louisville
State
KY
Country
United States
Zip Code
40202
Merchant, Michael L; Rood, Ilse M; Deegens, Jeroen K J et al. (2017) Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery. Nat Rev Nephrol 13:731-749
Ketchem, Corey J; Conner, Clayton D; Murray, Rebecca D et al. (2016) Low dose ouabain stimulates NaK ATPase ?1 subunit association with angiotensin II type 1 receptor in renal proximal tubule cells. Biochim Biophys Acta 1863:2624-2636
Merchant, Michael L (2015) Can the Urinary Peptidome Outperform Creatinine and Albumin to Predict Renal Function Decline? J Am Soc Nephrol 26:1760-1
McLeish, Kenneth R; Merchant, Michael L; Klein, Jon B et al. (2013) Technical note: proteomic approaches to fundamental questions about neutrophil biology. J Leukoc Biol 94:683-92
Siew, Edward D; Himmelfarb, Jonathan (2013) The inexorable rise of AKI: can we bend the growth curve? J Am Soc Nephrol 24:3-5
Merchant, Michael L; Niewczas, Monika A; Ficociello, Linda H et al. (2013) Plasma kininogen and kininogen fragments are biomarkers of progressive renal decline in type 1 diabetes. Kidney Int 83:1177-84