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Antioxidant and Anti-inflammatory Diagnostic Biomarkers in Multiple Sclerosis: A Machine Learning Study
Leda Mezzaroba1,2, Andrea Name Colado Simão2, Sayonara Rangel Oliveira2
1Laboratory of Research in Applied Immunology, University of Londrina, Paraná, Brazil.
Molecular Neurobiology
|January 24, 2020
Summary
Multiple sclerosis (MS) is linked to lower levels of key antioxidants like zinc, adiponectin, total radical-trapping antioxidant parameter (TRAP), and sulfhydryl (SH) groups. These markers, along with soluble TNF receptor 2 (sTNFR2), can accurately predict MS diagnosis.
Area of Science:
- Biochemistry
- Immunology
- Neurology
Background:
- Multiple sclerosis (MS) pathogenesis involves an imbalance between inflammatory and anti-inflammatory, as well as oxidant and antioxidant molecules.
- This imbalance contributes to demyelination and axonal damage characteristic of MS.
Purpose of the Study:
- To evaluate plasma levels of various inflammatory, oxidant, and antioxidant markers in MS patients compared to controls.
- To identify potential biomarkers for predicting MS diagnosis and understanding its pathophysiology.
Main Methods:
- Plasma levels of tumor necrosis factor (TNF)-α, soluble TNF receptors (sTNFR1, sTNFR2), adiponectin, hydroperoxides, advanced oxidation protein products (AOPP), nitric oxide metabolites, total radical-trapping antioxidant parameter (TRAP), sulfhydryl (SH) groups, and serum zinc were measured.
- 174 MS patients and 182 controls were included in the study.
- Statistical analyses, including receiver operating characteristic (ROC) curve analysis and support vector machine (SVM) with tenfold validation, were employed.
Main Results:
- MS patients exhibited significantly lower levels of zinc, adiponectin, TRAP, and SH groups, and increased AOPP levels compared to controls.
- A combination of lowered zinc, adiponectin, TRAP, and SH groups achieved a high area under the ROC curve (AUC/ROC) of 0.986 for MS prediction.
- The addition of sTNFR2 to these four antioxidants further improved prediction accuracy (AUC/ROC = 0.997).
- SVM analysis demonstrated high training (92.9%) and validation (90.6%) accuracies for predicting MS based on these antioxidant markers.
Conclusions:
- Lowered levels of zinc, adiponectin, TRAP, and SH groups are strongly associated with MS.
- These antioxidants, along with sTNFR2, serve as sensitive and specific biomarkers for MS diagnosis, outperforming TNF-α and nitro-oxidative biomarkers.
- Targeting therapies to enhance antioxidant capacity may offer new therapeutic avenues for managing MS.
