A specific micro-RNA can predict the disease course. Interestingly, they also found a connection (again) to EBV infection.
Common genetic variation within miR-146a predicts disease onset and relapse in multiple sclerosis
https://link.springer.com/article/10.10 ... 017-3177-1
Abstract
Despite extensive studies focusing on the changes in expression of microRNAs (miRNAs) in multiple sclerosis (MS) compared to healthy controls, few studies have evaluated the association of genetic variants of miRNAs with MS clinical course.
We investigated whether a functional polymorphism in the MS associated miR-146a gene predicted clinical course (hazard of conversion to MS and of relapse, and annualized change in disability), using a longitudinal cohort study of persons with a first demyelinating event followed up to their 5-year review.
We found the genotype (GC+CC) of rs2910164 predicted relapse compared with the GG genotype (HR=2.09 (95% CI 1.42, 3.06), p=0.0001), as well as a near-significant (p=0.07) association with MS conversion risk. Moreover, we found a significant additive interaction between rs2910164 and baseline anti-EBNA-1 IgG titers predicting risk of conversion to MS (relative excess risk due to interaction [RERI] 2.39, p=0.00002) and of relapse (RERI 1.20, p=0.006).
Supporting these results, similar results were seen for the other EBV-correlated variables: anti-EBNA-2 IgG titers and past history of infectious mononucleosis. There was no association of rs2910164 genotype for disability progression. Our findings provide evidence for miR-146a and EBV infection in modulating MS clinical course.
And also interesting:
Association of circulating anti-CD64 IgM levels with favourable long-term clinical outcomes in MS patients
https://www.sciencedirect.com/science/a ... 2818305484
Highlights
•Circulating IgM anti-CD64 levels fluctuate in multiple sclerosis.
•Circulating IgM anti-CD64 levels contribute to reduce disease activity and disability.
•Circulating IgM anti-CD64 levels are candidate predictive biomarkers of benign course.
Biomarkers for disease course.
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