EP OWENS1,2, W HOY1,3, JS COOMBES1,4, ZH ENDRE1,5,6 G GOBE1,2
1NHMRC CKD CRE, Brisbane, Queensland; 2Diamantina Institute, The University of Queensland, Brisbane, Queensland; 3 Centre for Chronic Disease, Faculty of Medicine, The University of Queensland, Brisbane, Queensland; 4School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane; 5Department of Nephrology, Prince of Wales Hospital and Clinical School, University of New South Wales; 6Department of Medicine, University of Otago, Christchurch.
Aim: To design a multi-parameter biomarker panel to aid clinicians and investigators in identifying chronic kidney disease (CKD) patients whose kidney function is likely to significantly decline in the following 1-3 years.
Background: CKD is a major health and economic burden within Australia. Irrespective of aetiology, many patients will progress through the stages of CKD and ultimately reach end-stage kidney disease. However, several studies have determined that many CKD patients do not progress. Therefore, a better method of predicting CKD progression is needed.
Methods: Bio-specimens will be sourced from the CKD.Biobank (NHMRC CKD Centre of Research Excellence) and stratified into declining, stable, improving and healthy controls based on yearly estimated glomerular filtration rate change, proteinuria, and albumin-to-creatinine ratio measured at 0, 12, and 24 months. The concentration of circulating and urinary inflammatory, fibrotic, tissue injury, tissue repair, and oxidative stress biomarkers will be measured at 0 and 12 months. They are assessed for the capacity to predict change in kidney function over the following 12 months. The combination of biomarkers that provides the best accuracy and precision in predicting future kidney function will be selected to develop a model to predict CKD progressors.
Results: Development of a multi-parameter panel of circulating and urinary biomarkers that captures inflammation, fibrosis, tissue damage, tissue regeneration, and oxidative stress associated with CKD and accurately predicts future kidney function.
Conclusions: This biomarker panel will address major clinical and research needs for identification of CKD patients likely to lose kidney function and those who are not. This will reduced the impact of CKD on society and the health care system.