Study: Plasma and urine biomarkers may help identify AKI
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Key takeaways:
- Investigators found two molecularly distinct AKI subgroups associated with differing risk profiles.
- Future identification of AKI subphenotypes may help link therapies to underlying pathophysiology.
Investigators proposed a way to classify subgroups of patients with AKI using plasma and urine biomarkers, according to research published in the American Journal of Kidney Diseases.
Investigators found two molecularly distinct AKI subgroups associated with differing risk profiles. Image: Adobe Stock.
While effective medical interventions can be elusive for this population, researchers said biomarker measurements may help pair specific therapies to certain patient groups in the same way distinct biomarkers inform treatments for patients with other ailments.
“The way that we diagnose acute kidney injury today relies on a simple blood test of kidney function or a change in urine output,” Jonathan Himmelfarb, MD, a study author, professor of medicine, adjunct professor of bioengineering and the Joseph W. Eschbach Endowed Chair in Kidney Research at the University of Washington, said in a press release. “These relatively crude diagnostic tools don’t detect the specific cause of injury or predict which individuals will be more likely to respond to a treatment or recover kidney function.”
The causes of AKI are nuanced, according to researchers. For example, sepsis, medication and inadequate blood supply in someone undergoing cardiac bypass are potential risks. Additionally, the causes of AKI vary, and sepsis, medication and inadequate blood supply in patients undergoing cardiac bypass are potential causes of kidney injury, according to the release.
To look at options for the treatment of AKI, researchers retrospectively analyzed data for 769 patients with AKI and 769 without the condition, following them for 5 years after hospital discharge. Participants were matched by demographic traits, hospital factors and baseline kidney function.
The study used 29 clinical, plasma and urinary biomarker parameters to identify AKI subphenotypes. Associations between AKI subphenotypes and major adverse kidney events were analyzed using Kaplan-Meier curves and Cox proportional hazard models.
Researchers found two molecularly distinct AKI subgroups associated with differing risk profiles and long-term outcomes. Patients in class 1 had higher rates of congestive heart failure, while those in class 2 showed higher rates of CKD and sepsis. According to the study, patients in the second group also had a 40% higher risk for major adverse kidney events 5 years later, compared with the first group.
Age, sex, rate of diabetes, or major surgical procedure as the cause of AKI was not different across subgroups, the authors wrote in the study, suggesting common clinical factors may not predict AKI subgroups.
“We’re attempting to better understand the clinical factors and molecular drivers of acute kidney injury so that, in the long run, we can better treat the different ways that people experience this disease process,” Himmelfarb said in the release. “We want to better understand the individual characteristics of people who get acute kidney injury so we can establish common characteristics of subgroup populations of these patients to know whose risk is relatively higher or lower, and work toward treatments specific to their needs.”
Reference:
- Biomarkers may help ID treatment of acute kidney injury. https://www.newswise.com/articles/biomarkers-may-help-id-treatment-of-acute-kidney-injury. Accessed June 2, 223.
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Bhatraju PK, et al. Am J Kidney Dis. 2023;doi:10.1053/j.ajkd.2023.01.449
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