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London – A landmark study by researchers at The University of Manchester has identified biological signals that may revolutionize how doctors predict the course of chronic kidney disease (CKD). The findings, published in the American Journal of Nephrology, could pave the way for more personalized and effective treatment strategies, potentially preventing thousands of cases of kidney failure and mortality.
The research team, which analyzed blood and urine samples from thousands of non-dialysis CKD patients, discovered that a specific marker of kidney damage known as Kidney Injury Molecule-1 (KIM-1) is strongly linked to a heightened risk of kidney failure and death. Unlike traditional, more generic tests, these newly identified biomarkers provide a deeper look into the underlying biological processes driving the disease’s progression.
Dr. Thomas McDonnell, the study’s lead author, highlighted the significance of the findings. “This discovery could enable the development of simple blood or urine tests to better predict a patient’s risk,” he stated. “With this information, doctors could identify high-risk patients for more aggressive and targeted interventions, while simultaneously avoiding over-treatment in those at a lower risk.”
The team measured 21 different markers in the samples, which reflect key processes related to kidney disease, inflammation, and heart disease. This comprehensive approach allowed them to pinpoint the most critical signals. The ability to forecast disease progression with greater accuracy offers a new paradigm for managing CKD, moving from a reactive to a proactive model of care. The ultimate goal is to improve patient outcomes and quality of life by tailoring treatment to individual risk profiles.
Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always consult with a qualified healthcare professional for diagnosis and treatment of any medical condition.
Reference:
- Mid-Day. “Researchers find biological signals that may help predict course of chronic kidney disease.” https://www.mid-day.com/lifestyle/health-and-fitness/article/researchers-find-biological-signals-that-may-help-predict-course-of-chronic-kidney-disease-23589665. Accessed August 16, 2025.
