Our results reveal that RRMS patients show a heterogeneous pharmacological response to IFNß therapy. In some patients we demonstrate that administered exogenous IFNß induces functional activation of the IFN pathway, whereas other patients do not reveal a functional IFNß response. The latter are characterized by a biomarker profile reflecting a saturated IFN activation pathway prior to treatment. Hence the baseline expression of the biomarker profile reflecting the baseline status of the IFN activity negatively correlates with the pharmacological effects of IFNß treatment. This indicates that the baseline expression levels of the selected set of 15 IFN-induced genes can be used as a predictive marker for the responsiveness to IFNß treatment.
Thus patients with clinically defined similar disease may have intrinsic different modes of immune status. These findings make more evident the complexity of the disease and the relationship to therapy responsiveness.
Although different regimens of IFNß treatment were used in this study evidence is available that this does not affect our conclusions.
Firstly, there is accumulating evidence that there is no or little difference between different types of IFNβ in terms of their biological activity and routes of administration 
. Extent and duration of clinical and biologic effects were independent of the route of administration of IFNβ. Rebif when given s.c.
was found to be bioequivalent to Avonex 
. Moreover, there were no major differences between the results with IFNβ1a and 1b in the duration of the changes in the pharmacodynamic markers after the two routes of injection 
Secondly, we excluded a possible bias in our results due to frequency of injection by analyzing different treatment groups separately. No significant differences in the range of biological response levels between Avonex treated patients and Rebif or Betaferon treated patients were observed, and selection of the high-frequently (Rebif and Betaferon) dosed patients by excluding weekly–treated (Avonex) patients from our analyses still resulted in a negative correlation between baseline IFN levels and biological response rate.
Thirdly, in the present study we show that the observed negative correlation between biological response and baseline levels of IFN induced genes is consistently observed over time, at one, three and six months after start of the therapy.
Finally, we showed that response-rates of in vitro stimulated PBMC isolated prior to treatment are consistent with those of the ex vivo results. These results convincingly supported the conclusion that the in vivo biological response is independent of differences in treatment regimens and interfering serum proteins such as neutralizing antibodies (Nabs).
Hence, we concluded that the inter-individual variation in pharmacological response to IFNß therapy is an intrinsic property of the peripheral blood cell compartment.
Several investigators have recently reported on transcription based responses to IFNß in MS. Baranzini and colleagues 
used a pre-selected set of 70 genes and reported that (un)supervised two-way hierarchical clustering does not reveal significantly differential expressed genes between responders and non-responders. Using quadratic discriminant analysis-based integrated Bayesian inference system they found a gene triplet consisting of apoptosis-related genes as best predictive for good responder versus poor responder classification. Most of the 70 genes they selected are represented on our microarray but we didn't observe a difference for these genes using a gene-by-gene approach. However, the majority of genes that we found as predictive for responsiveness using an open survey approach were not present in the gene set selected by Baranzini and colleagues and therefore not identified in their study. A careful comparison between the different IFNβ pharmacogenomics studies 
learns that there is consistency between these reports and our data with respect to the heterogeneity of the IFNβ response. Although not explicitly mentioned in these reports, we learned that they contained evidence for inter-individual differences in response to IFNβ. Overall, despite basic differences in the designs, we confirm and extend the trends observed in these reports with respect to the heterogeneity in treatment response rates. In addition, our paired analysis method provides an ideal approach for a patient centric mode of data analysis and discloses significant differences in the expression of an IFN driven response gene set at baseline in relation to the pharmacological response. Our findings provide a perfect explanation for the inter-individual variation in the pharmacological responses mentioned above.
Our data based on paired analysis at the individual patient level clearly show that there is evidence for differences in IFNß responsiveness between patients with MS. The inter-individual differences in IFNß responsiveness may be the result of genetic variation in the IFNß biology.
Feng and colleagues 
showed that IFN-induced levels of mRNA and protein for IFN-regulatory genes (IRF-1
) and antiviral genes (MxA
and 2′, 5′-OAS
) were significantly lower in PBMC from patients with clinically active MS compared to normal controls. They demonstrated that clinical disease activity was related to decreased phosphorylation of Ser-STAT-1 and proposed that this could be a mechanism explaining a defective IFN response. Whereas these studies provided insight into the IFN responsiveness in terms of a group average the issue of inter-individual heterogeneity was not addressed. Other mechanisms that could account for differential responsiveness to IFNß include variation in activity of inhibitory transcription factors. Evidence exists that crosstalk with other cytokine-activated pathways, could cause tachyphylaxis to type I IFNs. Although type I IFNs have an essential function in mediating innate immune responses against viruses, they may already be produced at very low levels in the absence of viral infections 
in serum of a subset of MS patients. Since e.g. IFNα is known to desensitize further responses to IFNs, the presence of low endogenous IFNs could block IFNß-induced signals.
This explorative pilot study suggests a predictive value of baseline gene expression levels of IFN-induced genes. Since the molecular differences most likely reflect distinct pathophysiologic processes underlying disease, it is tempting to speculate that these differences will predict individual responsiveness to treatment. Clinical response to IFNß may be determined by disability progression and relapse rate. Because MS is a chronic disease with an unpredictable clinical course it remains difficult to assess clinical responder status at an individual patient level. A more objective method for determining disease activity is the measurement of MRI parameters, e.g. CNS atrophy measures or T1 gadolinium enhancing or the appearance of new T2 lesions.
However, using these methods it is still extremely difficult to precisely define the state of responsiveness after a short period of treatment or preferably before start of the treatment. These facts emphasize the importance of finding pharmacological predictors and/or determinants for treatment responsiveness. We realize that the design of this study does not allow any firm conclusions to be drawn concerning the clinical parameters associated with the molecular phenotype.
Hence, further studies in a large cohort of patients starting IFNß treatment are needed to validate and further investigate the predictive value of baseline IFN response gene expression levels and it is of great importance to find a correlation between clinical parameters and the biological IFN response. In future, molecular stratification of patients at baseline may be helpful in assembling homogeneous populations of patients, which will improve the likelihood of observing drug efficacy in clinical trials.