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- Kuhle, J., et al.
(author)
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Conversion from clinically isolated syndrome to multiple sclerosis: A large multicentre study
- 2015
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In: Multiple Sclerosis Journal. - : SAGE Publications. - 1352-4585 .- 1477-0970. ; 21:8, s. 1013-1024
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Journal article (peer-reviewed)abstract
- Background and objective: We explored which clinical and biochemical variables predict conversion from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) in a large international cohort. Methods: Thirty-three centres provided serum samples from 1047 CIS cases with at least two years' follow-up. Age, sex, clinical presentation, T2-hyperintense lesions, cerebrospinal fluid (CSF) oligoclonal bands (OCBs), CSF IgG index, CSF cell count, serum 25-hydroxyvitamin D3 (25-OH-D), cotinine and IgG titres against Epstein-Barr nuclear antigen 1 (EBNA-1) and cytomegalovirus were tested for association with risk of CDMS. Results: At median follow-up of 4.31 years, 623 CIS cases converted to CDMS. Predictors of conversion in multivariable analyses were OCB (HR = 2.18, 95% CI = 1.71-2.77, p < 0.001), number of T2 lesions (two to nine lesions vs 0/1 lesions: HR = 1.97, 95% CI = 1.52-2.55, p < 0.001; >9 lesions vs 0/1 lesions: HR = 2.74, 95% CI = 2.04-3.68, p < 0.001) and age at CIS (HR per year inversely increase = 0.98, 95% CI = 0.98-0.99, p < 0.001). Lower 25-OH-D levels were associated with CDMS in univariable analysis, but this was attenuated in the multivariable model. OCB positivity was associated with higher EBNA-1 IgG titres. Conclusions: We validated MRI lesion load, OCB and age at CIS as the strongest independent predictors of conversion to CDMS in this multicentre setting. A role for vitamin D is suggested but requires further investigation.
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- Kotelnikova, E, et al.
(author)
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Signaling networks in MS: a systems-based approach to developing new pharmacological therapies
- 2015
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In: Multiple sclerosis (Houndmills, Basingstoke, England). - : SAGE Publications. - 1477-0970 .- 1352-4585. ; 21:2, s. 138-146
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Journal article (peer-reviewed)abstract
- The pathogenesis of multiple sclerosis (MS) involves alterations to multiple pathways and processes, which represent a significant challenge for developing more-effective therapies. Systems biology approaches that study pathway dysregulation should offer benefits by integrating molecular networks and dynamic models with current biological knowledge for understanding disease heterogeneity and response to therapy. In MS, abnormalities have been identified in several cytokine-signaling pathways, as well as those of other immune receptors. Among the downstream molecules implicated are Jak/Stat, NF-Kb, ERK1/3, p38 or Jun/Fos. Together, these data suggest that MS is likely to be associated with abnormalities in apoptosis/cell death, microglia activation, blood-brain barrier functioning, immune responses, cytokine production, and/or oxidative stress, although which pathways contribute to the cascade of damage and can be modulated remains an open question. While current MS drugs target some of these pathways, others remain untouched. Here, we propose a pragmatic systems analysis approach that involves the large-scale extraction of processes and pathways relevant to MS. These data serve as a scaffold on which computational modeling can be performed to identify disease subgroups based on the contribution of different processes. Such an analysis, targeting these relevant MS-signaling pathways, offers the opportunity to accelerate the development of novel individual or combination therapies.
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