Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.

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Looker, Helen C 
Colombo, Marco 
Hess, Sibylle 
Brosnan, Mary J 
Farran, Bassam 

Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.

Aged, Aged, 80 and over, Area Under Curve, Biomarkers, Case-Control Studies, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Disease Progression, Female, Glomerular Filtration Rate, Humans, Kidney, Logistic Models, Male, Odds Ratio, Predictive Value of Tests, Prospective Studies, ROC Curve, Renal Insufficiency, Chronic, Reproducibility of Results, Risk Factors, Scotland, Time Factors
Journal Title
Kidney Int
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Elsevier BV
Diabetes UK (None)
Diabetes UK (None)
Diabetes UK (06/0003341)
We acknowledge all the SUMMIT partners ( for their assistance with this project. This work was funded by the Innovative Medicine Initiative under grant agreement no. IMI/115006 (the SUMMIT consortium) and the Go-DARTS cohort was funded by the Chief Scientists Office Scotland.