ArticleBiomedicines2022
Osteopontin-A Potential Biomarker for IgA Nephropathy: Machine Learning Application.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 9 citations in OpenAlex.
- Multi-Modal, Machine Learning-Driven Framework Integrating Multi-Omics for Personalized Chronic Kidney Disease Management.Journal of clinical medicine · 2026Review
- Identification of exosomal miRNA-based predictive signatures for gestational diabetes mellitus via multi-algorithm machine learning.BMC pregnancy and childbirth · 2026Article
- Early detection of contrast-associated acute kidney injury after coronary angiography: A predictive value of osteopontin.World journal of nephrology · 2026Article
- Inflammation-induced osteogenic signaling promotes calcium phosphate crystal formation in kidneys via MAPK, NF-κB, and smad pathways.Frontiers in cell and developmental biology · 2026Article
- Correlation Between Urinary Osteopontin Concentration and the Mineral Content and Composition of Kidney Stones.Journal of clinical medicine · 2025Article
- Serum Peroxiredoxins Reflect Oxidative Stress and Predict Renal Outcomes in Patients with Glomerulonephritis.International journal of molecular sciences · 2025Article
- Meprin β regulates osteopontin-signaling in ischemia/reperfusion-induced kidney injury.BMC nephrology · 2025Article
- Multiomics Analysis Reveals Therapeutic Targets for Chronic Kidney Disease With Sarcopenia.Journal of cachexia, sarcopenia and muscle · 2025Article
- Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex-An Approach with Machine Learning Algorithms.Diagnostics (Basel, Switzerland) · 2024Article
- Beyond the Biomarker: Unveiling the Multifaceted Role of Osteopontin in Both Physiological and Pathological Processes.Biomedicines · 2024Article
- Osteopontin as a Biomarker in Chronic Kidney Disease.Biomedicines · 2023Review
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Many potential biomarkers in nephrology have been studied, but few are currently used in clinical practice. One is osteopontin (OPN). We compared urinary OPN concentrations in 80 participants: 67 patients with various biopsy-proven glomerulopathies (GNs)-immunoglobulin A nephropathy (IgAN, 29), membranous nephropathy (MN, 20) and lupus nephritis (LN, 18) and 13 with no GN. Follow-up included 48 participants. Machine learning was used to correlate OPN with other factors to classify patients by GN type. The resulting algorithm had an accuracy of 87% in differentiating IgAN from other GNs using urinary OPN levels only. A lesser effect for discriminating MN and LN was observed. However, the lower number of patients and the phenotypic heterogeneity of MN and LN might have affected those results. OPN was significantly higher in IgAN at baseline than in other GNs and therefore might be useful for identifying patients with IgAN. That observation did not apply to either patients with IgAN at follow-up or to patients with other GNs. OPN seems to be a valuable biomarker and should be validated in future studies. Machine learning is a powerful tool that, compared with traditional statistical methods, can be also applied to smaller datasets.
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Registered trials
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