Chronic Kidney Disease
Precision modeling a common age-related disorder – Chronic Kidney Disease (CKD)
Project Leader: Ron Korstanje, Ph.D.
Collaborator: Andrzej S. Krolewski, M.D. Ph.D. (Joslin Diabetes Center, Harvard Medical School)
The overall objective of this project is to generate new animal models of Chronic Kidney Disease, by leveraging GWAS data from human patients to predict discrete gene candidates that will be tested in mouse mutants and in mutant or knockdown zebrafish. These new animal models will be examined for renal phenotypes, which will then be validated in human clinical samples to prepare for future development of better interventions and therapies.
Background & Rationale
Chronic kidney disease (CKD) is a growing medical problem in the United States. It affects more than 26 million Americans and accounted for more than $33 billion in annual Medicare costs in 2010. The number of patients progressing to end-stage renal disease has increased by 95% over the last 10 years, a trend that is expected to continue as the population ages. There are currently over half a million Americans on dialysis, a procedure that severely reduces quality of life and comes with much co-morbidity. Furthermore, the impact of CKD is not limited to impairments related to renal failure. CKD is also recognized as an important risk factor for other chronic diseases such as cardiovascular disease, including myocardial infarction, atherosclerosis, stroke, and hypertension. A critical and inevitable contributor to CKD is normal kidney aging, which is associated with a decline in glomerular filtration rate (GFR).
Genome-wide association studies for GFR have been performed in many different cohorts. Metanalysis by the the CKDGen consortium and research efforts of several laboratories identified 14 candidate genes which showed that: 1) the tubulointerstitial expression levels were significantly correlated with GFR, 2) all were expressed in the same compartment in the kidney and 3) expression correlated with GFR in renal patients independent of their specific type of disease. Our goal is to develop mouse models that allow us to study the role of these genes in the disease process and identify novel biomarkers that can help with the pre-clinical diagnosis in human patients and ultimately provide a platform for intervention studies and clinical trials.
In addition, using longitudinal data from diabetes patients, our clinical collaborator at the Joslin Diabetes Center has developed a new model of diabetic nephropathy. In this model the predominant clinical feature of both early and late stages of diabetic nephropathy is early progressive renal decline, not albuminuria. Using high throughput 'omics' platforms on blood samples of diabetes patients with and without early progressive renal decline a number of associated pathways were identified. We are developing mouse models in which we manipulate these pathways in order to mimic the early progressive renal decline and facilitate preclinical studies.