Abstract
Objective To investigate whether vitamin D, smoking, and anti-Epstein-Barr virus (EBV) antibody concentrations predict long-term cognitive status and neuroaxonal injury in multiple sclerosis (MS). Methods This study was conducted among 278 patients with clinically isolated syndrome who participated in the clinical trial BENEFIT (Betaferon/Betaseron in Newly Emerging Multiple Sclerosis for Initial Treatment) and completed the 11-year assessment (BENEFIT-11). We measured serum 25-hydroxyvitamin-D (25(OH)D), cotinine (smoking biomarker), and anti-Epstein-Barr virus nuclear antigen 1 (EBNA-1) immunoglobulin G (IgG) at baseline and at months 6, 12, and 24 and examined whether these biomarkers contributed to predict Paced Auditory Serial Addition Test (PASAT)-3 scores and serum neurofilament light chain (NfL) concentrations at 11 years. Linear and logistic regression models were adjusted for sex, baseline age, treatment allocation, steroid treatment, multifocal symptoms, T2 lesions, and body mass index. Results Higher vitamin D predicted better, whereas smoking predicted worse cognitive performance. A 50-nmol/L higher mean 25(OH)D in the first 2 years was related to 65% lower odds of poorer PASAT performance at year 11 (95% confidence intervals [95% CIs]: 0.14-0.89). Standardized PASAT scores were lower in smokers and heavy smokers than nonsmokers ( p(trend) = 0.026). Baseline anti-EBNA-1 IgG levels did not predict cognitive performance (p(trend) = 0.88). Associations with NfL concentrations at year 11 corroborated these findings-a 50-nmol/L higher mean 25(OH)D in the first 2 years was associated with 20% lower NfL (95% CI: -36% to 0%), whereas smokers had 20% higher NfL levels than nonsmokers (95% CI: 2%-40%). Anti-EBNA-1 antibodies were not associated with NfL. Conclusions Lower vitamin D and smoking after clinical onset predicted worse long-term cognitive function and neuronal integrity in patients with MS.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin > Munich Cluster for Systems Neurology (SyNergy) |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
Sprache: | Englisch |
Dokumenten ID: | 117223 |
Datum der Veröffentlichung auf Open Access LMU: | 07. Jun. 2024, 15:43 |
Letzte Änderungen: | 11. Jun. 2024, 14:05 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198 |