Integrative analysis of prognostic biomarkers derived from multiomics panels for the discrimination of chronic kidney disease trajectories in people with type 2 diabetes

Kammer, M. et al. (2019) Integrative analysis of prognostic biomarkers derived from multiomics panels for the discrimination of chronic kidney disease trajectories in people with type 2 diabetes. Kidney International, 96(6), pp. 1381-1388. (doi: 10.1016/j.kint.2019.07.025) (PMID:31679767)

Abstract

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of; a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor.

• Item Type: Articles
• Additional Information: This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 115974. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA with JDRF.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Mark, Professor Patrick
• Authors: Kammer, M., Heinzel, A., Willency, J., Duffin, K., Mayer, G., Simons, K., Gerl, M., Klose, C., Heinze, G., Reindl-Schwaighofer, R., Hu, K., Perco, P., Eder, S., Rosivall, L., Mark, P., Ju, W., Kretzler, M., McCarthy, M., Heerspink, H. J., Wiecek, A., Gomez, M., and Oberbauer, R.
• College/School: College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing
• Journal Name: Kidney International
• Publisher: Nature Publishing Group
• ISSN: 0085-2538
• ISSN (Online): 1523-1755
• Published Online: 30 August 2019
• Copyright Holders: Copyright © 2019 Elsevier, Inc., on behalf of the International Society of Nephrology
• First Published: First published in Kidney International 96(6):1381-1388
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher