Kirsten E Peters1,2, Wendy A Davis1, Jun Ito2, Kaye Winfield2, Thomas Stoll2, Scott D Bringans2, Richard J Lipscombe2, Timothy M E Davis3. 1. Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Fremantle, Western Australia, Australia. 2. Proteomics International, Perth, Western Australia, Australia. 3. Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Fremantle, Western Australia, Australia tim.davis@uwa.edu.au.
Abstract
OBJECTIVE: To assess the ability of plasma apolipoprotein (apo) A-IV (apoA4), apo C-III, CD5 antigen-like (CD5L), complement C1q subcomponent subunit B (C1QB), complement factor H-related protein 2, and insulin-like growth factor binding protein 3 (IBP3) to predict rapid decline in estimated glomerular filtration rate (eGFR) in type 2 diabetes. RESEARCH DESIGN AND METHODS: Mass spectrometry was used to measure baseline biomarkers in 345 community-based patients (mean age 67.0 years, 51.9% males) from the Fremantle Diabetes Study Phase II (FDS2). Multiple logistic regression was used to determine clinical predictors of rapid eGFR decline trajectory defined by semiparametric group-based modeling over a 4-year follow-up period. The incremental benefit of each biomarker was then assessed. Similar analyses were performed for a ≥30% eGFR fall, incident chronic kidney disease (eGFR <60 mL/min/1.73 m2), and eGFR decline of ≥5 mL/min/1.73 m2/year. RESULTS: Based on eGFR trajectory analysis, 35 participants (10.1%) were defined as "rapid decliners" (mean decrease 2.9 mL/min/1.73 m2/year). After adjustment for clinical predictors, apoA4, CD5L, and C1QB independently predicted rapid decline (odds ratio 2.40 [95% CI 1.24-4.61], 0.52 [0.29-0.93], and 2.41 [1.14-5.11], respectively) and improved model performance and fit (P < 0.001), discrimination (area under the curve 0.75-0.82, P = 0.039), and reclassification (net reclassification index 0.76 [0.63-0.89]; integrated discrimination improvement 6.3% [2.1-10.4%]). These biomarkers and IBP3 contributed to improved model performance in predicting other indices of rapid eGFR decline. CONCLUSIONS: The current study has identified novel plasma biomarkers (apoA4, CD5L, C1QB, and IBP3) that may improve the prediction of rapid decline in renal function independently of recognized clinical risk factors in type 2 diabetes.
OBJECTIVE: To assess the ability of plasma apolipoprotein (apo) A-IV (apoA4), apo C-III, CD5 antigen-like (CD5L), complement C1q subcomponent subunit B (C1QB), complement factor H-related protein 2, and insulin-like growth factor binding protein 3 (IBP3) to predict rapid decline in estimated glomerular filtration rate (eGFR) in type 2 diabetes. RESEARCH DESIGN AND METHODS: Mass spectrometry was used to measure baseline biomarkers in 345 community-based patients (mean age 67.0 years, 51.9% males) from the Fremantle Diabetes Study Phase II (FDS2). Multiple logistic regression was used to determine clinical predictors of rapid eGFR decline trajectory defined by semiparametric group-based modeling over a 4-year follow-up period. The incremental benefit of each biomarker was then assessed. Similar analyses were performed for a ≥30% eGFR fall, incident chronic kidney disease (eGFR <60 mL/min/1.73 m2), and eGFR decline of ≥5 mL/min/1.73 m2/year. RESULTS: Based on eGFR trajectory analysis, 35 participants (10.1%) were defined as "rapid decliners" (mean decrease 2.9 mL/min/1.73 m2/year). After adjustment for clinical predictors, apoA4, CD5L, and C1QB independently predicted rapid decline (odds ratio 2.40 [95% CI 1.24-4.61], 0.52 [0.29-0.93], and 2.41 [1.14-5.11], respectively) and improved model performance and fit (P < 0.001), discrimination (area under the curve 0.75-0.82, P = 0.039), and reclassification (net reclassification index 0.76 [0.63-0.89]; integrated discrimination improvement 6.3% [2.1-10.4%]). These biomarkers and IBP3 contributed to improved model performance in predicting other indices of rapid eGFR decline. CONCLUSIONS: The current study has identified novel plasma biomarkers (apoA4, CD5L, C1QB, and IBP3) that may improve the prediction of rapid decline in renal function independently of recognized clinical risk factors in type 2 diabetes.
Authors: Kinsuk Chauhan; Girish N Nadkarni; Fergus Fleming; James McCullough; Cijiang J He; John Quackenbush; Barbara Murphy; Michael J Donovan; Steven G Coca; Joseph V Bonventre Journal: Kidney360 Date: 2020-06-30
Authors: Jana D Braun; Diego O Pastene; Annette Breedijk; Angelica Rodriguez; Björn B Hofmann; Carsten Sticht; Elke von Ochsenstein; Heike Allgayer; Jacob van den Born; Stephan Bakker; Sibylle J Hauske; Bernhard K Krämer; Benito A Yard; Thomas Albrecht Journal: Sci Rep Date: 2019-02-04 Impact factor: 4.379