Chronic kidney disease (CKD) is characterized by mild to severe anemia with severe pathological consequences. Treatment of anemia in CKD patients by intravenous injection of iron and erythropoietin (Epo) in combination with dialysis, significantly improves results. Optimal treatment is hampered by the lack of quantitative information on iron and Epo dosage, and by the high cost of recombinant Epo. Moreover, excess iron exposes the patient to cardiac injury, presumably by iron-induced, free radical oxidative damage. The long- term goal of our research program is to develop a predictive model of whole-body iron metabolism that will take advantage of recent and continuing advances in understanding the genetics and cell biology of iron transport mechanisms. The model is expected to provide quantitative, mechanism-based guidance for personalized treatment of patients with CKD to maximize efficacy and minimize injurious side-effects of iron supplements. We will take a systems biology approach in which mathematical modeling and simulation is used in the design and analysis of experiments. Our approach spans diverse research areas and necessitates an experienced research team with expertise in experimental biology, computational modeling, and medicine. We have assembled a unique multidisciplinary team of recognized experts in all major aspects of this application. The team is led by a cell and molecular biologist (Paul Fox, Ph.D., P.I.) and by a biomedical engineer with specific expertise in mathematical modeling of complex biological systems (Gerald Saidel, Ph.D. Co-I). They share long-standing interest in experimental and computational/modeling aspects of iron metabolism. The other essential members of our team are: Saul Nurko, M.D., a nephrologist with expertise in treatment of CKD anemia, Linda Graham, M.D., a vascular surgeon who has improved the surgical model of CKD in the mouse, Alan Lichtin, M.D. and Roy Silverstein, M.D., hematologists with expertise in treatment of hematopoietic disease and cell biology, respectively, and Marc Penn, M.D., Ph.D., a cardiologist with expertise in heart physiology and failure. Our team is highly integrated with multiple interactions among the participants. Our model will uniquely take advantage of the kinetic characteristics of iron transport proteins as opposed to previous diffusion-based models. The whole-body model will be used to develop optimal treatment regimens for the anemia of CKD. The regimens will be tested in vivo in a surgical model of CKD in mice. Adverse effects on the heart will be measured as cardiac iron accumulation and cardiac function and hypertrophy. The potential impact of this work is very high. A predictive, mechanism-based mathematical model of whole-body iron metabolism will provide testable insights into the interactions between the key iron homeostatic systems - the small intestine, bone marrow, liver, and marrow. Moreover, this model can provide future clinicians with a tool for personalized treatment of CKD (and potentially other anemias) that can optimize erythropoiesis, minimize cost, and most importantly, reduce adverse side-effects such as cardiac hypertrophy and failure.
Chronic kidney disease (CKD) patients are generally afflicted with mild to severe anemia, which can lead to heart failure and other cardiovascular disorders. The anemia-related symptoms of kidney disease are improved by treatment with the hormone erythropoietin and iron, but their beneficial effect on heart disease is controversial, and recent studies show increased risk of heart disease upon over-treatment. We have assemble a unique multidisciplinary research team of scientists and clinicians, with expertise in kidney and heart disease, cell biology, iron metabolism, systems biology, and mathematical modeling. Our goal is to investigate the mechanisms regulating iron homeostasis during of CKD, and devise regimens for personalized treatment that will improve health and minimize risk.
|Schonberg, David L; Miller, Tyler E; Wu, Qiulian et al. (2015) Preferential Iron Trafficking Characterizes Glioblastoma Stem-like Cells. Cancer Cell 28:441-455|
|Bakhautdin, Bakytzhan; Goksoy Bakhautdin, Esen; Fox, Paul L (2014) Ceruloplasmin has two nearly identical sites that bind myeloperoxidase. Biochem Biophys Res Commun 453:722-7|
|Yao, Peng; Poruri, Kiran; Martinis, Susan A et al. (2014) Non-catalytic regulation of gene expression by aminoacyl-tRNA synthetases. Top Curr Chem 344:167-87|
|Eswarappa, Sandeepa M; Potdar, Alka A; Koch, William J et al. (2014) Programmed translational readthrough generates antiangiogenic VEGF-Ax. Cell 157:1605-18|
|Bakhautdin, Bakytzhan; Febbraio, Maria; Goksoy, Esen et al. (2013) Protective role of macrophage-derived ceruloplasmin in inflammatory bowel disease. Gut 62:209-19|
|Yao, Peng; Fox, Paul L (2013) Aminoacyl-tRNA synthetases in medicine and disease. EMBO Mol Med 5:332-43|
|Yao, Peng; Potdar, Alka A; Ray, Partho Sarothi et al. (2013) The HILDA complex coordinates a conditional switch in the 3'-untranslated region of the VEGFA mRNA. PLoS Biol 11:e1001635|
|Tang, W H Wilson; Wu, Yuping; Hartiala, Jaana et al. (2012) Clinical and genetic association of serum ceruloplasmin with cardiovascular risk. Arterioscler Thromb Vasc Biol 32:516-22|
|Yao, Peng; Potdar, Alka A; Arif, Abul et al. (2012) Coding region polyadenylation generates a truncated tRNA synthetase that counters translation repression. Cell 149:88-100|