A prospective study of multiple protein biomarkers to predict progression in diabetic chronic kidney disease

作者：Rajiv Agarwal, Kevin L. Duffin, Dennis A. Laska, James R. Voelker, Matthew Douglas Breyer, Peter G. Mitchell · 发表于：Nephrology Dialysis Transplantation · 年份：2014 · DOI：10.1093/ndt/gfu255 · 被引用次数：78 · 研究领域：Chronic Kidney Disease and Diabetes、Fibroblast Growth Factor Research、Angiogenesis and VEGF in Cancer

BACKGROUND: Diabetic nephropathy imposes a substantial cardiovascular and renal burden contributing to both morbidity and excess mortality. Progression of chronic kidney disease (CKD) in diabetes mellitus is variable, and few biomarkers are available to predict progression accurately. Identification of novel predictive biomarkers may inform clinical care and assist in the design of clinical trials. We hypothesized that urinary and plasma protein biomarkers predict CKD progression independently of the known clinical markers such as albuminuria and estimated glomerular filtration rate (eGFR) in diabetic nephropathy. METHODS: We studied 67 US veterans with CKD due to type 2 diabetes mellitus and 20 age-matched controls (no CKD, hypertension or cardiovascular disease). After clinical evaluation and the collection of blood and urine specimens for 24 biomarkers, we followed subjects prospectively for the next 2-6 years. CKD progression was defined in three ways: (i) clinically by examining eGFR versus time plots for each individual (slope progression), (ii) progression to end-stage renal disease (ESRD) and (iii) a composite outcome of ESRD or death. RESULTS: Among 17 urinary and 7 plasma biomarkers evaluated, the relationship of the biomarkers with outcome was as follows: (i) for progression identified by eGFR plots, urinary C-terminal fibroblast growth factor (FGF)-23 emerged to have the strongest primary association (adjusted odds ratio [aOR] 2.08, P = 0.008); (ii) for ESRD, plas...