University of Michigan researchers have identified a simple test to identify patients at risk for chronic kidney disease and end-stage renal disease, by measuring epidermal growth factor in a routine urine sample.

“Early identification of patients more likely to experience end-stage kidney disease is an urgent, unmet clinical need,” said lead author and nephrologist Matthias Kretzler, MD. “Right now, kidney biopsy, which involves removing a tiny sample of kidney tissue, is the standard technique used to assess kidney disease. This procedure is costly, carries a low, but significant health risk, and has limited ability to predict the future course of kidney disease.”

The U-M team worked with the European Renal cDNA Bank and the Joint Institute for Translational and Clinical Research (a collaboration between Peking University Health Sciences Center and U-M).

The international research team, led by Kretzler, renal systems biologist Wenjun Ju, PhD, MS, and bioinformatician Viji Nair, MS, identified epidermal growth factor as a molecule of interest in kidney disease while analyzing kidney tissue biopsies from chronic kidney disease patients across Europe and the U.S. The researchers then validated the findings in urine samples from more than 940 patients in North America, Europe and China.

The research, published in Science Translational Medicine, linked decreased epidermal growth factor levels in urine to worsening kidney disease. In fact, patients with low urinary epidermal growth factor were four times more likely to worsen than those who retained epidermal growth factor function in their kidneys.

“Urinary epidermal growth factor can help patients in two very important ways,” Kretzler says. “First, in clinical practice, it could be used to prioritize care to those patients most at risk of losing their kidney function. Second and more immediately, using urinary epidermal growth factor levels will improve and speed up clinical trials. Enrolling only those likely to develop specific disease endpoints can reduce the number of people needing study and ensure the trial achieves an optimal mix of patients.”