Biomarker Panel May Predict Nephropathy in Type 2 Diabetes
By Lorraine L. Janeczko
NEW YORK (Reuters Health) - Novel biomarkers may predict rapid kidney function loss in type 2 diabetes, a study reported in a late-breaking poster June 11 at the 77th Scientific Sessions of the American Diabetes Association in San Diego.
"We have identified and validated a panel of protein biomarkers which can predict rapid decline in renal function independently of current diagnostic measures of kidney function," said lead author Dr. Kirsten E. Peters, biostatistician at Proteomics International in Perth, and research associate at the University of Western Australia in Fremantle, Western Australia.
"Our hypothesis-free approach to detect differences in protein signatures by disease severity allowed the highest chance to identify these differences. The strong independence of our biomarker panel from other clinical factors and robust performance across different definitions of renal decline was surprising," Dr. Peters told Reuters Health in an email.
"High-risk patients will be identified using PromarkerD before symptoms present, allowing a more targeted approach to patient care, including more frequent assessment of kidney function and intensification of blood glucose and/or blood pressure medications," she said.
Dr. Peters and her colleagues assessed and validated the ability of PromarkerD - a panel of novel plasma protein biomarkers - to predict rapid loss of kidney function over a four-year period in T2DM independently of clinical variables such as albuminuria and estimated glomerular filtration rate (eGFR).
The biomarkers included alipoprotein A-IV (APO4), insulin-like growth factor-binding protein (IBP3), CD5 antigen-like (CD5L), and complement C1q subcomponent subunit B (C1QB).
The researchers used mass spectrometry to measure baseline plasma biomarkers in a development cohort of 345 patients with type 2 diabetes who were participating in the longitudinal Fremantle Diabetes Study Phase II.
The authors defined onset and progression of CKD as 1) 30% or greater drop in eGFR over four years, 2) incident CKD (eGFR <60mL/min/1.73m2) at year four in patients who were above this at baseline, 3) declining eGFR trajectories, and 4) eGFR drop of 5mL/min/1.73m2/year or more.
They used multiple logistic regression to identify clinical predictors of developing nephropathy, and they evaluated the incremental predictive value of biomarkers.
They based all the prediction models on their development cohort and a validation cohort of 447 patients. Of the 345 initial participants, 30 had a 30% or greater drop in eGFR over four years.
After adjusting for the tightest model, APOA4 (odds ratio 4.85, 95% confidence interval 2.04 to 11.50) and IBP3 (OR 0.32, CI 0.13 to 0.81) independently predicted outcome and better model fit (P<0.001).
CD5L (OR 0.52, CI 0.29 to 0.93) and C1QB (OR 2.41, CI 1.14 to 5.11) independently predicted quickest eGFR drop.
Co-author Dr. Scott D. Bringans, research manager at Proteomics International in Perth, said in an email. "PromarkerD is a new approach to managing diabetic kidney disease. Early detection allows at-risk patients to make lifestyle changes such as tighter monitoring and control of blood glucose and insulin level, and to implement targeted treatments and medications. Currently, no drugs area available specifically for diabetic kidney disease, but the pharmaceutical industry is trying to change this: over 20 drugs are in late-stage clinical trials."
The technology developed for this study is being used to develop the ability to predict any form of kidney disease as well as diagnostic tests for other diseases and as an endpoint marker in clinical trials for any new drug, he said.
"The representative nature of our cohort means that our findings are applicable to the majority of patients with type 2 diabetes and are not limited by age or disease severity. PromarkerD could therefore be used to improve the statistical power of clinical trials by enrolling individuals at highest risk of renal decline and subsequent renal failure," Dr. Peters noted.
This work was funded by Proteomics International and The University of Western Australia.
American Diabetes Association 2017.
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