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Updated: Mar 23, 2026

Comprehensive Autopsy Program for Individuals with Multiple Sclerosis
Published on: July 19, 2019
Albumin and Protein Oxidation are Predictors that Differentiate Relapsing-Remitting from Progressive Clinical Forms
Sayonara R Oliveira1, Ana Paula Kallaur1, Edna M V Reiche2
1Postgraduate Program, Health Sciences Center, University of Londrina, Av. Robert Koch, 60, 86038-440, Londrina, Paraná, Brazil.
Abstract:
The aim of the present study was to evaluate inflammatory, oxidative, and nitrosative stress (IO&NS) blood markers as possible predictors of multiple sclerosis (MS) and its clinical forms. This study included 258 MS patients (175 with relapsing-remitting MS (RRMS) and 83 with progressive MS clinical forms) and 249 healthy individuals. Peripheral blood samples were obtained to determine serum levels of albumin, ferritin, C-reactive protein (CRP), total protein, lipid hydroperoxide by tert-butyl hydroperoxide-initiated chemiluminescence (CL-LOOH), carbonyl protein content, advanced oxidation protein products (AOPP), nitric oxide metabolites (NOx), and total radical-trapping antioxidant parameter (TRAP). MS patients showed higher ferritin (p < 0.001) and CL-LOOH (p < 0.001) and lower albumin (p = 0.001), TRAP (p < 0.001), AOPP (p = 0.013), and NOx values (p < 0.001) than controls. Difference was not observed in CRP, total protein, and carbonyl proteins between patients and controls. In the logistic regression age-adjusted, ferritin and CL-LOOH showed positive association with MS and were predictors of MS development (OR: 1.006, 95 % CI: 1.003-1.009, p < 0.001 and OR: 1.029, 95 % CI: 1.007-1.052, p = 0.009, respectively). Albumin, TRAP, AOPP, and NOx were negatively associated with MS (p = 0.019, p = 0.003, p = 0.001, and p = 0.003, respectively). Moreover, other logistic regression age-adjusted showed that MS patients with progressive clinical forms had lower albumin and higher AOPP than those with RRMS (p = 0.037). In conclusion, ferritin, albumin, and biomarkers of IO&NS, such as CL-LOOH, AOPP, TRAP, and NOx were predictors of MS diagnosis, whereas albumin and AOPP were predictors that differentiated RRMS from the progressive clinical forms of MS.
Insights
Inflammatory, oxidative, and nitrosative stress (IO&NS) blood markers like ferritin and CL-LOOH predict multiple sclerosis (MS) development. Albumin and AOPP levels also differentiate MS subtypes, aiding diagnosis.
Area of Science:
- Biochemistry
- Immunology
- Neurology
Background:
- Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system.
- Understanding the role of inflammatory, oxidative, and nitrosative stress (IO&NS) in MS pathogenesis is crucial.
- Identifying reliable biomarkers for MS diagnosis and clinical form prediction is an ongoing challenge.
Purpose of the Study:
- To investigate serum levels of IO&NS markers as predictors of MS.
- To evaluate these markers in distinguishing between relapsing-remitting MS (RRMS) and progressive MS (PMS).
Main Methods:
- Cross-sectional study involving 258 MS patients and 249 healthy controls.
- Measurement of serum biomarkers including ferritin, albumin, C-reactive protein (CRP), lipid hydroperoxide (CL-LOOH), advanced oxidation protein products (AOPP), nitric oxide metabolites (NOx), and total radical-trapping antioxidant parameter (TRAP).
- Statistical analysis using logistic regression to assess predictive values of biomarkers for MS diagnosis and clinical forms.
Main Results:
- MS patients exhibited higher ferritin and CL-LOOH levels, and lower albumin, TRAP, AOPP, and NOx levels compared to controls.
- Ferritin and CL-LOOH were positively associated with MS development, while albumin, TRAP, AOPP, and NOx were negatively associated.
- Lower albumin and higher AOPP levels were observed in progressive MS patients compared to RRMS patients.
Conclusions:
- Serum ferritin, albumin, CL-LOOH, AOPP, TRAP, and NOx are significant predictors for MS diagnosis.
- Albumin and AOPP levels can help differentiate between RRMS and progressive forms of MS, offering potential for improved clinical management.

