ArticlePloS one2015
A panel of novel biomarkers representing different disease pathways improves prediction of renal function decline in type 2 diabetes.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it, 67 citations in OpenAlex.
- Pooled it
- Establishment of a YKL-40 time-resolved Immunoassay and Application in Diabetic Kidney Disease.Journal of fluorescence · 2025Article
- The Potential Use of Targeted Proteomics and Metabolomics for the Identification and Monitoring of Diabetic Kidney Disease.Journal of personalized medicine · 2024Review
- Diagnostic challenges of diabetic kidney disease.Biochemia medica · 2023Review
- Identification of a New RNA and Protein Integrated Biomarker Panel Associated with Kidney Function Impairment in DKD: Translational Implications.International journal of molecular sciences · 2023Article
- Development and Validation of a Prediction Model for Future Estimated Glomerular Filtration Rate in People With Type 2 Diabetes and Chronic Kidney Disease.JAMA network open · 2023Article
- Role of MCP-1 as an inflammatory biomarker in nephropathy.Frontiers in immunology · 2023Review
- Article
- Absence of long-term changes in urine biomarkers after AKI: findings from the CRIC study.BMC nephrology · 2022Article
- Review of potential biomarkers of inflammation and kidney injury in diabetic kidney disease.Diabetes/metabolism research and reviews · 2022Review
- Associations of Plasma Biomarkers of Inflammation, Fibrosis, and Kidney Tubular Injury With Progression of Diabetic Kidney Disease: A Cohort Study.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2022Article
- High-Throughput Metabolomics and Diabetic Kidney Disease Progression: Evidence from the Chronic Renal Insufficiency (CRIC) Study.American journal of nephrology · 2022Article
- Cardiovascular disease protein biomarkers are associated with kidney function: The Framingham Heart Study.PloS one · 2022Article
- A prediction model for the decline in renal function in people with type 2 diabetes mellitus: study protocol.Diagnostic and prognostic research · 2021Article
- Vascular peroxidase 1 is independently associated with worse kidney function in patients with peripheral artery disease.Journal of nephrology · 2021Observational
- Current Challenges and Future Perspectives of Renal Tubular Dysfunction in Diabetic Kidney Disease.Frontiers in endocrinology · 2021Review
- Proteomics-Based Machine Learning Approach as an Alternative to Conventional Biomarkers for Differential Diagnosis of Chronic Kidney Diseases.International journal of molecular sciences · 2020Article
- The Role of Chemokines and Chemokine Receptors in Diabetic Nephropathy.International journal of molecular sciences · 2020Review
- Review
- Growth differentiation factor 15 (GDF-15) is a potential biomarker of both diabetic kidney disease and future cardiovascular events in cohorts of individuals with type 2 diabetes: a proteomics approach.Upsala journal of medical sciences · 2020Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to identify a novel panel of biomarkers predicting renal function decline in type 2 diabetes, using biomarkers representing different disease pathways speculated to contribute to the progression of diabetic nephropathy. RESEARCH DESIGN AND
methodsA systematic data integration approach was used to select biomarkers representing different disease pathways. Twenty-eight biomarkers were measured in 82 patients seen at an outpatient diabetes center in The Netherlands. Median follow-up was 4.0 years. We compared the cross-validated explained variation (R2) of two models to predict eGFR decline, one including only established risk markers, the other adding a novel panel of biomarkers. Least absolute shrinkage and selection operator (LASSO) was used for model estimation. The C-index was calculated to assess improvement in prediction of accelerated eGFR decline defined as <-3.0 mL/min/1.73m2/year.
resultsPatients' average age was 63.5 years and baseline eGFR was 77.9 mL/min/1.73m2. The average rate of eGFR decline was -2.0 ± 4.7 mL/min/1.73m2/year. When modeled on top of established risk markers, the biomarker panel including matrix metallopeptidases, tyrosine kinase, podocin, CTGF, TNF-receptor-1, sclerostin, CCL2, YKL-40, and NT-proCNP improved the explained variability of eGFR decline (R2 increase from 37.7% to 54.6%; p=0.018) and improved prediction of accelerated eGFR decline (C-index increase from 0.835 to 0.896; p=0.008).
conclusionsA novel panel of biomarkers representing different pathways of renal disease progression including inflammation, fibrosis, angiogenesis, and endothelial function improved prediction of eGFR decline on top of established risk markers in type 2 diabetes. These results need to be confirmed in a large prospective cohort.
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