Comparison of serum and urinary biomarker panels with albumin/creatinine ratio in the prediction of renal function decline in type 1 diabetes
Open Access
- 1 April 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Diabetologia
- Vol. 63 (4), 788-798
- https://doi.org/10.1007/s00125-019-05081-8
Abstract
Aims/hypothesis We examined whether candidate biomarkers in serum or urine can improve the prediction of renal disease progression in type 1 diabetes beyond prior eGFR, comparing their performance with urinary albumin/creatinine ratio (ACR). Methods From the population-representative Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) we sampled 50% and 25% of those with starting eGFR below and above 75 ml min(-1) [1.73 m](-2), respectively (N = 1629), and with median 5.1 years of follow-up. Multiplexed ELISAs and single molecule array technology were used to measure nine serum biomarkers and 13 urine biomarkers based on our and others' prior work using large discovery and candidate studies. Associations with final eGFR and with progression to <30 ml min(-1) [1.73] m(-2), both adjusted for baseline eGFR, were tested using linear and logistic regression models. Parsimonious biomarker panels were identified using a penalised Bayesian approach, and their performance was evaluated through tenfold cross-validation and compared with using urinary ACR and other clinical record data. Results Seven serum and seven urine biomarkers were strongly associated with either final eGFR or progression to <30 ml min(-1) [1.73 m](-2), adjusting for baseline eGFR and other covariates (all at p<2.3 x 10(-3)). Of these, associations of four serum biomarkers were independent of ACR for both outcomes. The strongest associations with both final eGFR and progression to <30 ml min(-1) [1.73 m](-2) were for serum TNF receptor 1, kidney injury molecule 1, CD27 antigen, alpha-1-microglobulin and syndecan-1. These serum associations were also significant in normoalbuminuric participants for both outcomes. On top of baseline covariates, the r(2) for prediction of final eGFR increased from 0.702 to 0.743 for serum biomarkers, and from 0.702 to 0.721 for ACR alone. The area under the receiver operating characteristic curve for progression to <30 ml min(-1) [1.73 m](-2) increased from 0.876 to 0.953 for serum biomarkers, and to 0.911 for ACR alone. Other urinary biomarkers did not outperform ACR. Conclusions/interpretation A parsimonious panel of serum biomarkers easily measurable along with serum creatinine may outperform ACR for predicting renal disease progression in type 1 diabetes, potentially obviating the need for urine testing.Funding Information
- Diabetes UK (Ref. 10/0004010)
- Chief Scientist Office (Ref. ETM/47)
- Juvenile Diabetes Research Foundation (Ref. 3-SRA-2016- 332-M-R)
This publication has 25 references indexed in Scilit:
- Progressive Renal Decline: The New Paradigm of Diabetic Nephropathy in Type 1 DiabetesDiabetes Care, 2015
- Serum Concentration of Cystatin C and Risk of End-Stage Renal Disease in DiabetesDiabetes Care, 2012
- A Predictive Model for Progression of Chronic Kidney Disease to Kidney FailureJAMA, 2011
- Performance of the Cockcroft-Gault, MDRD, and New CKD-EPI Formulas in Relation to GFR, Age, and Body SizeClinical Journal of the American Society of Nephrology, 2010
- Factors other than glomerular filtration rate affect serum cystatin C levelsKidney International, 2009
- Estimating GFR Using Serum Cystatin C Alone and in Combination With Serum Creatinine: A Pooled Analysis of 3,418 Individuals With CKDAmerican Journal of Kidney Diseases, 2008
- Cystatin C as a Risk Factor for Outcomes in Chronic Kidney DiseaseAnnals of Internal Medicine, 2007
- Variable selection in qualitative models via an entropic explanatory powerJournal of Statistical Planning and Inference, 2003
- Model choice in generalised linear models: a Bayesian approach via Kullback-Leibler projectionsBiometrika, 1998
- PROGRESSION OF DIABETIC NEPHROPATHYThe Lancet, 1979