We have applied rigorous statistical methods to unbiased analyses of cytometric data from healthy subjects and subjects with inflammatory demyelinating diseases; these analyses implicate one cell population in this family of diseases and uncover the architecture of our population of untreated subjects with RRMS or CIS. Specifically, we have validated the role of the CD8low cell population that is reduced to the same extent in CIS and RRMS subjects when they are compared to healthy control subjects. We also present evidence suggesting that these two categories of demyelinating disease share a similar population structure: both CIS and RRMS subjects appear to be distributed amongst three distinct clusters of subjects defined by different immunologic profiles.
The reduced proportion of CD8low cells in subjects with MS was discovered by multiple independent assessments in our initial screen of whole blood stained for cytometric analysis. This finding was then confirmed by both (1) an extension of the original analysis and (2) replication in an independent set of data generated from subjects in CLIMB. Furthermore, the same observation is made when healthy control subjects are compared to subjects with CIS. Thus, this decrease in CD8low cells is an early event in demyelinating diseases and is not an artifact of the way cells were stained in the MS Registry project. The observed difference, while statistically robust, is modest and is not sufficient to serve as a biomarker by itself (). Nonetheless, because it can be effectively captured using two common antibodies (anti-CD4 and anti-CD8) that are used routinely in clinical laboratories, it could become a relatively simple and valuable component of diagnostic algorithm containing other clinical and radiologic information for use by neurologists. In the future, as part of a broader diagnostic algorithm, this biomarker may be particularly useful to study individuals “at risk” of developing MS (such as first degree relatives) in the future, if a reduction in this cell population predates the onset of the disease process.
The primary goal of the MS Registry, biomarker discovery, was therefore successfully accomplished; a measurement of the frequency of the CD8low
cell population in peripheral blood shows promise in possible future clinical application. However, this result is also important in what it reveals about the immunology of demyelinating diseases: it targets the CD8low
cell population for future exploration. In particular, it is intriguing that the same CD8low
cell population was found to be increased in frequency after treatment with daclizumab (anti-IL2Ra) in a recent phase II trial (Bielekova et al., 2006
). In this daclizumab trial, the expansion of the CD8low
cell population after treatment correlated with decreased brain inflammation and decreased survival of activated T cells. Thus, correction of the deficit in CD8low
cells that we find to be robustly associated with untreated RRMS and CIS subjects may be an important and early target for treatment in demyelinating diseases.
In our secondary analysis, we demonstrate that it is the CD56+
subset of CD8low
cells that appears to drive the observation of reduced frequency in this population; in the daclizumab trial, it is also this CD8low
subset of cells that appears to increase in frequency in response to treatment. This combination of markers suggests that these are NK cells that may have regulatory properties (Freud and Caligiuri, 2006
). Further investigation will now be targeted at better characterizing the phenotype and function of these CD8low
cells to see which subset of NK cells may be implicated and how dysfunctional they may be in subjects with a demyelinating disease. Using different marker combinations, many investigators have assessed the role of NK cells in MS, and, while some early studies were negative, the propensity of the evidence available to date suggests that NK cell frequency is reduced in MS and that they may be dysfunctional (Segal, 2007
). Comparisons of our data with these other studies are challenging at this point given the limited NK markers that we had in our panel and the heterogeneity of NK cell populations. Nonetheless, a CD56bright
NK cell population has also been reported to be elevated in frequency during the last trimester of pregnancy, a time of reduced MS relapses, in women with MS (Airas et al., 2008
). Similarly, an increased proportion of circulating CD56bright
NK cells has been noted in subjects with RRMS following treatment initiation with IFNb (Saraste et al., 2007
). Finally, in vitro
data suggest that CD56+
NK cells may help to regulate the activation of MBP-reactive T cells from subjects with (Takahashi et al., 2004
). These small studies reinforce the suggestion that the frequency of CD56+
NK cells may have a role in MS. Thus, our novel description of a robust association between reduced CD8low
cell population frequency and a diagnosis of RRMS or CIS may be mediated at least in part by a deficit in CD56+
NK suppressive function that increases the likelihood of an autoimmune reaction.
Looking beyond the CD8low cell population, similarities between CIS and RRMS may extend to broader phenotypic profiles defined by our cytometric data; the underlying population structure identified by our consensus clustering method may be similar among CIS and RRMS subjects. The three subsets of subjects observed in both sets of samples suggest that population structure in inflammatory demyelinating diseases may be related to very early events in the pathophysiology of central nervous system inflammation: different triggers and/or immune dysfunction that occur early may eventually produce similar clinical manifestations that we define as RRMS. Since none of the included subjects displayed clinical manifestations of CIS or RRMS at the time of sampling, the subsets of subjects described here do not appear to be related to clinically evident episodes of inflammation.
The consensus clustering analysis that we present here suggests that collecting large immunological profiles may be one method with which to classify subjects with demyelinating diseases. However, independent replication of this observation is needed; further experimental work in larger sets of samples is required both to validate this approach and to select the optimal array of markers to be included in the profile. Our sample size, while substantial for this form of data, remains relatively small to powerfully explore the question of which cell populations are critical in defining each MS subset. In particular, technology and costs limit the number or different markers and marker combinations that we can assess: only 50 different antigens were assessed in 55 combinations of four antibodies in this project. Thus, while we have uncovered evidence of population structure in MS, we have not defined the key markers of each subset. In addition, our best estimate, based on our data, is that three major subsets of subjects exist in our dataset, but much larger datasets will be more accurate in estimating the full distribution of subject subsets and in perhaps revealing rarer subsets. Such large studies would also refine the analysis of clinical variables that may be associated with different subsets of subjects. In general, immunologic profiling appears to be one platform that will contribute significantly to the process of biomarker development, a process that must eventually integrate other forms of data such as imaging and genetic data in the development of effective diagnostic and prognostic models for MS and CIS.
In summary, our analyses direct us in three different directions: (1) to the exploration the use of the CD8low cell population in diagnostic and prognostic algorithms, (2) to more detailed phenotypic categorization of CD8low cells in CIS and RRMS and (3) to the validation and refined characterization of population structure in subjects with demyelinating diseases. Our data suggest that the next phase of studies must be much larger to powerfully assess this population structure, must target subjects early in their disease when they may have a clearer immunological profile, and must also contain new markers and new combinations of markers so that we may refine the cytometric signature of each subject subset.