Every day, our kidneys filter more than 30 gallons of blood to allow excretion of molecules that can harm us if they build up as waste. But, for more than 20 million Americans and a growing number of people around the world, this important function is compromised by chronic kidney disease (CKD) . Some CKD patients are at high risk of progressing to actual kidney failure, treatable only by dialysis or kidney transplants, while others remain generally healthy with stable kidney function for many years with minimal treatment.
The dilemma is that, even when CKD is diagnosed early, there’s been no good way to predict which individuals are at high risk for rapid progression. Those individuals would potentially benefit from more intensive measures to slow or prevent kidney failure, such as drug regimens that tightly control blood pressure and/or blood glucose. So, I’m pleased to report that NIH-funded researchers have made some progress toward developing more precise strategies for identifying individuals at high risk for kidney failure. In recent findings published in Science Translational Medicine , an international research team has identified a protein, easily detectable in urine, which appears to serve as an early warning sign of CKD progression.
A wide range of conditions, from diabetes to hypertension to the autoimmune disease lupus, can contribute to the gradual loss of kidney function seen in people with CKD. But research suggests that once kidney damage reaches a critical threshold, it veers off to follow a common downhill course, driven by shared cell signaling pathways and almost independent of the conditions causing it. If there was an easy, reliable way to determine when a CKD patient’s kidneys are approaching this threshold, it could open the door to better strategies for protecting them from kidney failure.
With this need in mind, a team, led by Matthias Kretzler and Wenjun Ju of the University of Michigan, began analyzing gene activity in kidney biopsy samples donated by 164 CKD patients and stored in the European Renal cDNA Bank. Specifically, the researchers looked for patterns of gene activity that corresponded with the patients’ estimated glomerular filtration rates, an indicator of renal function frequently calculated as part of a routine blood workup. Their first pass produced a list of 72 genes that displayed varying levels of activity that corresponded to differences in the patients’ estimated glomerular filtration rates. Importantly, the activity of many of those genes is also increased in cell signaling pathways thought to drive CKD progression.
Further study in two more groups of CKD patients, one from the United States and another from Europe, whittled the list down to three genes that best predicted kidney function. The researchers then zeroed in on the gene that codes for epidermal growth factor (EGF), a protein that, within the kidney, seems to be produced specifically in tubules, which are key components of the waste filtration system. Because EGF appears to enhance tubular repair after injury, researchers had a hunch that it might serve as a positive biomarker of tubular function that could be combined with existing tests of glomerular filtration to detect progression of CKD at an earlier stage.
In groups of CKD patients from the United States and China, the researchers went on to find that the amount of EGF in the urine provides an accurate measure of the protein’s activity in the kidney, making it a promising candidate for a simple urine test. In fact, CKD patients with low levels of EGF in their urine were four times more likely than those with higher EGF levels to have their kidney function worsen within a few years.
These lines of evidence suggest that, if these findings are replicated in additional studies, it may be possible to develop a simple EGF urine test to help identify which individuals with CKD would benefit the most from aggressive disease management and clinical follow-up. Researchers also plan to explore the possibility that such a urine test might prove useful in the early diagnosis of CKD, before there are any other indications of kidney disease. These are very promising new findings, but much remains to be done before we can think of applying these results as standard of care in the clinic. For example, the EGF work needs to be replicated in larger groups of CKD patients, as well as CKD patients with diabetes.
Beyond their implications for CKD, these results demonstrate the power of identifying new biologically important indicators directly from patients and then testing them in large, diverse cohorts of people. I look forward to the day when these sorts of studies will become possible on an even larger scale through our U.S. Precision Medicine Initiative Cohort.
 National Chronic Kidney Disease Fact Sheet, 2014. Centers for Disease Control and Prevention.
 Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Ju W, Nair V, Smith S, Zhu L, Shedden K, Song PX, Mariani LH, Eichinger FH, Berthier CC, Randolph A, Lai JY, Zhou Y, Hawkins JJ, Bitzer M, Sampson MG, Thier M, Solier C, Duran-Pacheco GC, Duchateau-Nguyen G, Essioux L, Schott B, Formentini I, Magnone MC, Bobadilla M, Cohen CD, Bagnasco SM, Barisoni L, Lv J, Zhang H, Wang HY, Brosius FC, Gadegbeku CA, Kretzler M; ERCB, C-PROBE, NEPTUNE, and PKU-IgAN Consortium. Sci Transl Med. 2015 Dec 2;7(316):316ra193.
Chronic Kidney Disease: What Does it Mean to Me? (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)
Personalized Molecular Nephrology Research Laboratory (University of Michigan)
C-Probe (University of Michigan)
NIH Support: National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases
Tags: C-PROBE, chronic kidney disease, CKD, diabetes, dialysis, EGF, epidermal growth factor, ERCB, glomerular filtration rate, glomeruli, hypertension, kidney, kidney damage, kidney disease, kidney failure, kidney transplantation, kidney tubules, lupus, nephrology, NEPTUNE, personalized nephrology, PKU-IgAN Consortium, precision medicine, Precision Medicine Initiative Cohort Program, transcriptomics, urine test