Interferon-beta (IFN-beta) is the major treatment for multiple sclerosis. However, this treatment is not always effective. Here we have found congruence in outcome between responses to IFN-beta in experimental autoimmune encephalomyelitis (EAE) and relapsing-remitting multiple sclerosis (RRMS). IFN-beta was effective in reducing EAE symptoms induced by T helper type 1 (T(H)1) cells but exacerbated disease induced by T(H)17 cells. Effective treatment in T(H)1-induced EAE correlated with increased interleukin-10 (IL-10) production by splenocytes. In T(H)17-induced disease, the amount of IL-10 was unaltered by treatment, although, unexpectedly, IFN-beta treatment still reduced IL-17 production without benefit. Both inhibition of IL-17 and induction of IL-10 depended on IFN-gamma. In the absence of IFN-gamma signaling, IFN-beta therapy was ineffective in EAE. In RRMS patients, IFN-beta nonresponders had higher IL-17F concentrations in serum compared to responders. Nonresponders had worse disease with more steroid usage and more relapses than did responders. Hence, IFN-beta is proinflammatory in T(H)17-induced EAE. Moreover, a high IL-17F concentration in the serum of people with RRMS is associated with nonresponsiveness to therapy with IFN-beta.
Results: Median pretreatment and post-treatment serum IL-17F levels were not statistically significantly different between GR and PR, and serum IL-7/IL-17F ratios were also not predictive of response status. Replicate aliquots from the Stanford study showed good correlation to their original cohort (r = 0.77).
The original study was performed on 26 samples and found a signficant difference and this new study was performed on 118 samples and found no difference at all. It is amazing that the first study produced the results it did, which would have occurred with just a 1 in 500 chance, so in 499/500 cases it would have not produced a significant result, as found in this more exhaustive study so a real case of type 1 statistical error (Believed there was a difference when there was not). I do not think it is a Pharma conspiracy to discredit the original data, but it shows that data does need to be replicated otherwise, we would believe everything we read in science comics.
It would be interesting to know how much other stuff never gets repeated, I would bet alot, especially as there would be a publication bias against the negative study seeing the light of day.