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Abstract: Advances in the understanding of pathogenic mechanisms of diseases have led to the defining of new biomarkers for diagnosis, prognosis, and therapy response. In this context, flow cytometry has been positioned as one of the most useful technologies for monitoring immune-mediated diseases, such as multiple sclerosis (MS), allowing a detailed analysis of lymphocyte subpopulations in peripheral blood. The autoimmune inflammatory response in MS results in changes in lymphocyte subpopulations that might be useful as surrogate markers for the evaluation of disease activity, progression, and monitoring of therapy response. This chapter discusses the role of T-lymphocyte and B-lymphocyte subpopulations in MS pathogenesis, the effect of MS treatments on these subsets, and their potential usefulness as biomarkers of treatment response.

Keywords: Flow cytometry; Immunomonitoring; Lymphocyte subpopulations; Multiple sclerosis; Response to treatment

Introduction

There is evidence of patients with the same disease responding differently to the same treatment. Thus, it is necessary to define biomarkers to stratify patients, monitor the course of the disease, and predict response to treatment. Peripheral blood leukocytes play an important role in the pathogenesis of autoimmune diseases. It has been demonstrated that immunomodulatory treatments decrease the percentage of these cell populations, alter the expression of their surface markers, and modify their functionality (i.e., cytokine production, proliferation, and induction of apoptosis). For these reasons, it has been hypothesized that systematic analyses of peripheral blood immune cells could serve as surrogate biomarkers of activity of the disease and/or response to therapy, leading to the development of personalized medicine (1–4).

FLOW CYTOMETRY, A TOOL FOR IMMUNE-MONITORING

Flow cytometry enables the analysis of a panel of surface molecules at single-cell level that not only determines the percentages of peripheral lymphocytes but also their differentiation stage. In addition, the activation state of peripheral lymphocytes and their memory or effector functions can be measured. Recent advances in the development of multiparametric flow cytometry have made detailed characterization of lymphocyte subsets possible in whole blood or isolated peripheral blood mononuclear cells (PBMC) of healthy donors and patients, and it has been presented as a powerful tool for immunomonitoring of response to treatment (5, 6). Concurrent to this development, several international consortia have been created to standardize immune-monitoring using flow cytometry for immune-mediated diseases, transplantation, and hematological diseases, for potential use in clinical settings (7–9).

Pathogenic Mechanisms of Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, inflammatory demyelinating disease of the CNS, characterized by infiltration of T-lymphocytes, B-lymphocytes, macrophages, NK cells, demyelination, and axonal damage (10–12). The etiology of MS remains unknown; however, it has been proposed that there is a selective autoimmune response against myelin autoantigens causing damage to the CNS. However, like the majority of autoimmune diseases, the triggers of this response are unknown. Both environmental and genetic factors have been postulated. A 40% concordance in monozygotic twins as well as association with HLA-DRB1*1501 and DQB1*0602 alleles have been described (11, 13). GWAS studies in MS patients have shown the involvement of several loci related to the immune system, of which the HLA locus presents the highest association (14–16).

The existing evidence on the induction and perpetuation of the disease points to an important role of autoreactive CD4⁺ T-cells (2). Studies in the animal model of MS, experimental autoimmune encephalomyelitis (EAE), have shown that the effector CD4⁺ T-subpopulations, Th1 and Th17, play an important role in the pathogenesis of the disease. These subpopulations have been found increased in the CNS of patients with MS, mainly in CSF and the perivascular space (3, 4). In addition, oligoclonal expansions of activated CD8⁺ T-cells in CNS lesions of MS patients have been described, indicating their participation in CNS damage (5, 6). The involvement of B-lymphocytes in the pathogenesis of MS is better understood: they produce autoantibodies; induce, maintain, and reactivate CD4⁺ T-cells; act as antigen-presenting cells; and produce pro-inflammatory cytokines (7). Impairment in the immunoregulatory function of NK cells in MS patients has also been decribed (12). A schematic overview of the roles of immune cells in MS pathogenesis is represented in Figure 1.

Figure 1 Pathogenic mechanisms of multiple sclerosis. Autoreactive T-cells and B-cells are activated in peripheral lymph nodes where they are differentiated into effector cells, CD8+ T-cells, and CD4+ T-cells (Th1 and/or Th17). Activated cells migrate through the blood–brain barrier (BBB) where they are further activated by local antigen-presenting cells. These processes induce cytokine and chemokine production, facilitating the entry of other cell types from peripheral blood. At the central nervous system (CNS), macrophages and activated T-cells attack myelin components and release cytokines that activate B-cells which mature to antibody-producing plasma cells. This increases the inflammatory response and causes demyelination and axonal damage.

Lymphocyte Subpopulations in MS

The autoimmune inflammatory response in MS results in changes in lymphocyte subpopulations of peripheral blood (17–20). These changes might be useful surrogate markers for the evaluation of disease activity, progression, and monitoring of therapy response.

T-CELL SUBPOPULATIONS

T-cell subpopulations can be divided into naïve, central memory, effector memory, and other minor effector subsets such as terminally differentiated effector cells (T_EMRA), based on the expression of CD45RA, CCR7, and CD27 (7, 21). Studies published until now regarding T-cell subpopulations in MS patients are discrepant. Differences among studies might be due to different genetic backgrounds, stages of the disease, analysis of small groups of patients, and also different monoclonal antibodies used to define T-cell subpopulations. These discrepancies are particularly relevant in studies regarding CD8⁺ T-subpopulations. Whereas some authors report an increase of effector CD8⁺ T-cells (22, 23), other authors describe a decrease in effector memory and T_EMRA CD8⁺ T-cells in peripheral blood (24). Analysis of the cellularity of the CNS infiltrates show enrichment in the number of effector memory and T_EMRA CD8⁺ T-cells in patients with MS and other inflammatory neurological diseases (25, 26). In these studies, the increase in central memory and effector memory CD8⁺ T-cells in peripheral blood, and in CSF, were related to active disease or early-stage disease. In contrast, in patients with less active disease, no changes in central memory CD8⁺ T-cells or the percentages of CD8⁺ early effector memory in peripheral blood were found, although a decrease in absolute counts of CD8⁺ early effector memory T-cells could be observed, which would suggest that in MS patients these cells migrate to the CNS (17).

TH17 AND TREG SUBPOPULATIONS

The increased percentage of Th17 in the peripheral blood of RRMS patients has been widely reported and a pathogenic role for these cells postulated (27, 28). Moreover, Th17Th1 cells, a subpopulation which secretes both IL-17 and IFN-γ, have also been related to MS pathogenesis (29). Regarding Treg subpopulations, most of the reports found a similar percentage of Tregs in MS patients compared with healthy donors, although a functional impairment has been found in in vitro assays (30–32). In this context, an increase of the Th17/Treg balance has been associated with higher disease activity and severity (20, 33).

B-CELL SUBPOPULATIONS

Although the involvement of B-lymphocytes in the pathogenesis of MS has been a focus in recent years, a full characterization of B-cell subpopulations in peripheral blood of MS patients is still lacking (34, 35). Most of the studies on B-cells are focused on their changes in response to treatments (36, 37).

Current Therapies for MS and Their Effect on Lymphocyte Subpopulations

Even though a number of new drugs have been developed to treat MS, a treatment that can cure the disease has not been developed as yet. Approved treatments reduce the frequency of relapses and decrease inflammation but fall short of stopping CNS degeneration. Current treatments can be divided basically into two groups: those that treat acute relapses (megadoses of metilprednisolone) and disease-modifying therapies (DMTs). DMTs include classic injectable drugs (interferon-β and glatiramer acetate (GA)), oral substances (fingolimod, terifunamide, and dimethyl fumarate (DMF)), and monoclonal antibodies—anti-CD49d (natalizumab) and anti-CD52 (alemtuzumab). Other monoclonal antibodies such as anti-CD25 (daclizumab) and anti-CD20 (ocrelizumab) that cause depletion of B-cells are expected to be in the clinics soon. DMT treatments have broad immune-modulatory/immunosuppressive effects affecting peripheral blood subpopulations (38–41). The major changes in lymphocyte subpopulations in response to DMT treatments are summarized in Table 1.

TABLE 1 Main changes in lymphocyte subpopulations induced by DMT treatments

Drug	ACL	T-cells	CD4+ T-cells	CD8+ T-cells	T-Cells Memory Subsets	RTEs	Th17	Tregs	B-Cells	B-Cells Memory Subsets	B Transitional/Immature	Bregs
Interferon	↓	↓			↓ memory and activated	NC/↓	↓	↑			↑
Glatiramer acetate					↑ Th2			↑
Natalizumab	↑	↑	↑	↑	NC	↑	=	NC	↑	↓ naive ↓ memory	↑
Fingolimod	↓	↓	↓	↑	↓ naive/CM ↑ EM/TEMRA	↑	NC	↑	↓	NC	↑	↑
Dimethyl fumarate	↓				↑naive ↓EM ↑Th2			=/↑			↑	↑
Alemtuzumab	↓	↓	↓	↓	↑ EM ↑ TEMRA		=	↑	↑
Teriflunomide	↓				↓ activated*				↓	↓ activated*

ACL = absolute count lymphocytes, CM = central memory, EM = effector memory, TEMRA = terminally differentiated effector cells, RTEs = recent thymic emigrants; NC = nonconclusive.

* Inhibition synthesis of rapidly dividing lymphocytes.

INTERFERON β (1A AND 1B)

Interferon β (IFN-β) was the first treatment approved for MS. It decreases the number of relapses, progression of disability, and disease activity (measured by MRI). The mechanism of action of IFN-β, although extensively studied, is not fully understood. The known mechanisms include a decrease in lymphocytes activation and proliferation, a reduction in pro-inflammatory cytokines production, and an increase in anti-inflammatory cytokines. IFN-β has a nonspecific immuno-modulatory effect on various immune cells, and it has been demonstrated that it interferes with the transmigration of leukocytes through the blood–brain barrier (BBB). This treatment induces a weak leukopenia, an increase of IL-10 that has been associated with an increase of both CD4⁺ and CD8⁺ T regulatory cells, and CD56^bright NK cells (42–44). Moreover, some studies described a decrease of IL-17 production, and Th17 cells, in peripheral blood in MS patients under IFN-β treatment (45, 46). It has also been described that the effect of IFN-β causes a decrease of activated and memory T-cells (44, 47); on the other hand, it induces an increase of B-cells production—an increase in transitional (immature) Bccells and k-deleting recombination excision circles (KRECs), thereby supporting its use for increasing B-cell release from bone marrow (17, 48). Its effect on thymic egress of recent thymic emigrants (RTEs) is still unclear, but it seems that IFN-β may induce a decrease of RTEs and TCR recombination excision circles (TRECs) in peripheral blood (48, 49).

GA OR COPOLYMER-1

It is a polymer composed of the most frequent aminoacids in the myelin basic protein (L-tyrosine, L-glutamate, L-alanine, and L-lysine) (13). Its mechanism of action is poorly understood, but it is postulated that GA acts by binding the major histocompatibility complex class II molecules, competing with other antigens as myelin basic protein, and inhibiting the activation of myelin basic protein-specific T-cells (50, 51). GA has a nonspecific effect on the immune system because no specific changes have been described in peripheral blood of patients under treatment. Some studies describe that GA induces a shift in the CD4 T-cells’ response to a Th2 profile. Moreover, it has been proposed that it induces an increase in Treg subpopulation (50, 52).

DIMETHYL FUMARATE

DMF is an oral drug of the fumaric acid ester. It induces activation of the transcription factors Nfr2 (decreasing inflammation) and NF-κB (modifying cytokines production), and diminishes neuroinflammation by promoting the cytoprotection of CNS cells against oxidative stress (41). DMF induces a pronounced lymphopenia that has been associated with the occurrence of rare and fatal cases of progressive multifocal leukoencephalopathy (PML) associated with JC virus infection (53, 54). DMF reduces the number of lymphocytes with a decrease of B-cells and CD4⁺ and CD8⁺ T-cells. A decrease of central and effector memory T-cells with a concomitant expansion of naïve T-cells in peripheral blood of patients under treatment with DMF have been reported. Moreover, a shift in T helper (Th) subpopulations (a decrease in Th1 and Th17, and an increase in Th2 and regulatory T-cells) has been reported (55–58). Regarding B-cell subpopulations, an increase of a subset of B-cells with regulatory capacity has been described (59).

TERIFLUNOMIDE

Teriflunomide is an active metabolite of leflunomide, an approved treatment for other autoimmune diseases. It inhibits dihydroorotate dehydrogenase, blocking the de novo pyrimidine synthesis that is required by rapidly dividing lymphocytes, resulting in a reversible cytostatic effect that limits the expansion of stimulated T-cells and B-cells. It is administered orally (60–62). Teriflunomide impairs the production of activated lymphocytes (inhibiting their proliferation). Specific changes in lymphocyte subpopulations have not been reported.

FINGOLIMOD

Fingolimod is the first oral drug approved for MS treatment. It is a structural analogue of sphingosine and its phosphorylated metabolite, sphingosine 1-phosphate (S1P). S1P and its receptor (S1P₁) mediate the circulation of T-cells and B-cells between blood and lymph nodes (LNs). In physiological conditions, the interaction between S1P and S1P₁ promotes their egress from LNs by overcoming retention signals as the chemokine receptor CCR7. Naive and central memory T-cells as well as B-cells express CCR7. In contrast, effector memory T-cells and terminally differentiated effector T-cells (T_EMRA) are CCR7^- and may egress from LNs independently of S1P₁ receptor. Fingolimod binds to four of the five subtypes of S1P receptors, causing the internalization and degradation of these receptors, and consequently blocking the egress of CCR7⁺ lymphocytes from LNs (21, 63, 64). The main effect of fingolimod is a decrease of CCR7⁺ cells in peripheral blood, specifically of naïve and central memory T-cells (65–68). In contrast to T-cells, B-cell subsets have not been extensively studied in patients under fingolimod treatment. Literature on the effect of fingolimod in naïve and memory subset subpopulations is scarce and equivocal (69–71). An increase in immature and transitional B-cells (71, 72) and Treg cells has been reported in peripheral blood of MS patients under fingolimod treatment (67, 70, 73–76), supporting the conclusion that fingolimod can exert an alternative immunomodulatory mechanism inducing the production of Treg cells, as previously suggested by in vitro and ex vivo experiments (77–79). Results regarding the effect of fingolimod on Th17 cells are inconclusive and contradictory (67, 72, 75, 80). This is probably a consequence of the diversity in surface markers used to define this T-cell subset. Specifically, CCR7 (a clue marker for cells homing to LNs) can differentiate effector Th17 cells (CCR7^-) from central memory or pre-Th17 cells (CCR7⁺). In a longitudinal study (72), we detected an increase in the percentages of effector Th17 cells, defined as CD4⁺CCR7^-CCR6⁺CCR4⁺ following the international consensus of 2008 (21), in accordance with other studies (67). In contrast, Mehling et al. observed, in a cross-sectional study, that Th17 lymphocytes of MS patients were predominantly central memory Th17 and that their percentages were decreased in patients under fingolimod treatment compared with untreated MS patients and healthy donors. These authors did not analyze the effector Th17 subpopulation (80).

ALEMTUZUMAB

It is a humanized monoclonal antibody against CD52, recently approved for MS treatment (previously approved and widely used in the treatment of leukemia). It is administered via intravenous route (13, 41). As CD52 is a panleucocitary molecule, it promotes a rapid, marked, and sustained depletion of T-lymphocytes and B-lymphocytes, NK cells, monocytes, and some granulocytes. Studies performed in a transgenic mouse model postulated that the mechanism of lymphocyte depletion is predominantly antibody-dependent cytolysis (81). A decrease in the percentage of T-cell subpopulations at day 7 posttreatment with the onset of reconstitution 1 month after treatment has been described (82). Although CD4⁺ and CD8⁺ T-cell depletion lasts for months after treatment, there is a selective delayed reconstitution of some CD4⁺ T-cells subsets that remain decreased for up to 24 months after treatment (82, 83). In contrast, there is an increase in the percentages of Tregs with an increase of suppressive activity. No differences in Th1 and Th17 percentages have been reported after reconstitution of the CD4⁺ T-cell pool (83).

CD8⁺ T-cell pool reconstitution is faster than CD4⁺, normalized at the third month after treatment with the dominance of effector subsets (T_EMRA) for at least 24 months (82, 84). These results indicate that T-cell recovery is due to homeostatic expansion. In contrast to T-cells, the repopulation of CD19⁺ B-cells reaches percentages above baseline in the first 12 months of treatment (85). Interestingly, in B-cell reconstitution, there is an output from bone marrow reflected in a significant frequency of immature B-cells in the first months after treatment. The B-cell pool is dominated by memory B-cells at 12 months after treatment; however, they remain below the baseline levels (86). The efficacy of alemtuzumab has been found to last longer than the lymphocyte depletion, probably due to the fact that after treatment there is a reconstitution with a different lymphocyte repertoire (87). Furthermore, the selectively delayed CD4⁺ T-cell repopulation can contribute to the suppression of the disease activity (82). The main adverse effect of alemtuzumab is autoimmunity, the most frequent being thyroid autoimmunity, that appears in 30% of patients after treatment (84, 85, 87). The development of autoimmunity could be explained by the homeostatic expansion that occurs in the T-cell pool reconstitution (84).

NATALIZUMAB

Natalizumab is a humanized monoclonal antibody against CD49d (subunit α4 of VLA-4 integrin). The strong adhesion between VLA-4 of lymphocytes and VCAM-1 of the endothelium is very important for the migration of leucocytes through the BBB and entry to the CNS. Natalizumab is administered intravenously, and it binds to CD49d, blocking the transmigration of leucocytes through the BBB. This treatment decreases the occurrence of relapses by up to 90%, inducing a decrease of disease progression and MRI activity. The main side effect of natalizumab is the risk of developing PML caused by JC virus infection, which is associated with high mortality. As natalizumab blocks the transmigration of leukocytes through the BBB, in the peripheral blood of MS patients under treatment with natalizumab, there is an increase in the absolute numbers of B, T CD4⁺, T CD8⁺ (without alterations in CD4/CD8 ratio), and NK cells (88–90). The effect of natalizumab on lymphocyte subpopulations is not fully defined, although it has been described that memory T-cells would be increased in peripheral blood and would induce changes in memory B-cells (90–92). Moreover, natalizumab treatment interferes with the mechanisms of bone marrow egress of hematopoietic stem cells, inducing an increase of CD34⁺ cells in peripheral blood, specifically lymphoid progenitors, transitional B-cells, and RTEs (17, 91, 93–97).

Changes in Lymphocyte Subpopulations as Biomarkers of Therapy Response

Immunomonitoring of peripheral lymphocyte subpopulations may be useful to assess treatment response. In DMF treatment, patients with stable disease had lower numbers of CD4⁺, CD8⁺ T, and B-cells than those with active disease (98). Moreover, percentages of CD8⁺ T-cells and B-cells at 6 months after treatment could predict response to treatment (98). Regarding response to fingolimod treatment, Song et al proposed that percentages of central memory CD4⁺ T-cells could predict relapse (76). In a pilot study, our group described that the baseline percentage of RTEs and transitional B-cells are lower in responder patients. Therefore, immunomonitoring their percentages could be a tool for predicting which patients would be good candidates to receive fingolimod treatment. Moreover, the percentage of late effector memory CD4⁺ T-cells and RTEs could provide information on the response to therapy as early as 1 month after starting this therapy (72). Using quantitative flow cytometry as a tool for immune-monitoring, a method for immunomonitoring CD49d receptor occupancy in MS patients under natalizumab therapy has been reported. Using this method, it is possible to determine the percentage of CD49d molecules bound to natalizumab and identify those patients with low receptor occupancy (suboptimal doses), which in a long-term sustained therapy context would show a decrease in treatment efficacy (99).

Conclusion

DMTs induce changes in lymphocyte subpopulations that can be detected in peripheral blood using flow cytometry. Treatment with monoclonal antibodies (natalizumab and alemtuzumab), fingolimod, and DMF induces a clear effect on different peripheral blood lymphocyte subpopulations. In contrast, IFN-β, GA, and teriflunomide produce nonspecific changes. Immunomonitoring lymphocyte subpopulations allows to define biomarkers of therapy response and opens up the opportunity to initiate a personalized therapy in MS treatments, enabling clinicians to choose the best treatment for each patient and predict which patients are the most suitable for receiving a specific therapy.

Acknowledgment: This work was supported by project PI14/01175, integrated in the Plan Nacional de I+D+I and co-supported by the ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER).

Conflict of interest: The authors declare no potential conflicts of interest with respect to research, authorship, and/or publication of this chapter.

Copyright and permission statement: To the best of our knowledge, the materials included in this chapter do not violate copyright laws. All original sources have been appropriately acknowledged and/or referenced. Where relevant, appropriate permissions have been obtained from the original copyright holder(s).

REFERENCES

1. Roep BO, Buckner J, Sawcer S, Toes R, Zipp F. The problems and promises of research into human immunology and autoimmune disease. Nat Med. 2012 Jan;18(1):48–53. http://dx.doi.org/10.1038/nm.2626
2. Willis JC, Lord GM. Immune biomarkers: The promises and pitfalls of personalized medicine. Nat Rev Immunol. 2015 May;15(5):323–9. http://dx.doi.org/10.1038/nri3820
3. Hernandez-Fuentes MP, Lechler RI. A “biomarker signature” for tolerance in transplantation. Nat Rev Nephrol. 2010 Oct;6(10):606–13. http://dx.doi.org/10.1038/nrneph.2010.112
4. Maecker HT, Nolan GP, Fathman CG. New technologies for autoimmune disease monitoring. Curr Opin Endocrinol Diabetes Obes. 2010 Aug;17(4):322–8. http://dx.doi.org/10.1097/MED.0b013e32833ada91
5. Chattopadhyay PK, Roederer M. Cytometry: Today’s technology and tomorrow’s horizons. Methods. 2012 Jul;57(3):251–8. http://dx.doi.org/10.1016/j.ymeth.2012.02.009
6. Jaye DL, Bray RA, Gebel HM, Harris WA, Waller EK. Translational applications of flow cytometry in clinical practice. J Immunol. 2012 May 15;188(10):4715–19. http://dx.doi.org/10.4049/jimmunol.1290017
7. Maecker HT, McCoy JP, Nussenblatt R. Standardizing immunophenotyping for the Human Immunology Project. Nat Rev Immunol. 2012 Mar;12(3):191–200.
8. Popadic D, Anegon I, Baeten D, Eibel H, Giese T, Marits P, et al. Predictive immunomonitoring—The COST ENTIRE initiative. Clin Immunol. 2013 Apr;147(1):23–6. http://dx.doi.org/10.1016/j.clim.2013.01.013
9. Streitz M, Miloud T, Kapinsky M, Reed MR, Magari R, Geissler EK, et al. Standardization of whole blood immune phenotype monitoring for clinical trials: Panels and methods from the ONE study. Transplant Res. 2013;2(1):17. http://dx.doi.org/10.1186/2047-1440-2-17
10. Bruck W, Stadelmann C. The spectrum of multiple sclerosis: New lessons from pathology. Curr Opin Neurol. 2005 Jun;18(3):221–4. http://dx.doi.org/10.1097/01.wco.0000169736.60922.20
11. Dendrou CA, Fugger L, Friese MA. Immunopathology of multiple sclerosis. Nat Rev Immunol. 2015 Sep 15;15(9):545–58. http://dx.doi.org/10.1038/nri3871
12. Gross CC, Schulte-Mecklenbeck A, Runzi A, Kuhlmann T, Posevitz-Fejfar A, Schwab N, et al. Impaired NK-mediated regulation of T-cell activity in multiple sclerosis is reconstituted by IL-2 receptor modulation. Proc Natl Acad Sci U S A. 2016 May 24;113(21):E2973–82. http://dx.doi.org/10.1073/pnas.1524924113
13. Loma I, Heyman R. Multiple sclerosis: Pathogenesis and treatment. Curr Neuropharmacol. 2011 Sep;9(3):409–16. http://dx.doi.org/10.2174/157015911796557911
14. Ricano-Ponce I, Wijmenga C. Mapping of immune-mediated disease genes. Annu Rev Genomics Hum Genet. 2013;14:325–53. http://dx.doi.org/10.1146/annurev-genom-091212-153450
15. Bush WS, Sawcer SJ, de Jager PL, Oksenberg JR, McCauley JL, Pericak-Vance MA, et al. Evidence for polygenic susceptibility to multiple sclerosis—The shape of things to come. Am J Hum Genet. 2010 Apr 09;86(4):621–5. http://dx.doi.org/10.1016/j.ajhg.2010.02.027
16. Sawcer S, Hellenthal G, Pirinen M, Spencer CC, Patsopoulos NA, Moutsianas L, et al. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis. Nature. 2011 Aug 10;476(7359):214–19. http://dx.doi.org/10.1038/nature10251
17. Teniente-Serra A, Grau-Lopez L, Mansilla MJ, Fernandez-Sanmartin M, Ester Condins A, Ramo-Tello C, et al. Multiparametric flow cytometric analysis of whole blood reveals changes in minor lymphocyte subpopulations of multiple sclerosis patients. Autoimmunity. 2016 Jun;49(4):219–28. http://dx.doi.org/10.3109/08916934.2016.1138271
18. Fletcher JM, Lalor SJ, Sweeney CM, Tubridy N, Mills KH. T cells in multiple sclerosis and experimental autoimmune encephalomyelitis. Clin Exp Immunol. 2010 Oct;162(1):1–11. http://dx.doi.org/10.1111/j.1365-2249.2010.04143.x
19. Friese MA, Fugger L. Pathogenic CD8(+) T cells in multiple sclerosis. Ann Neurol. 2009 Aug;66(2):132–41. http://dx.doi.org/10.1002/ana.21744
20. Jamshidian A, Shaygannejad V, Pourazar A, Zarkesh-Esfahani SH, Gharagozloo M. Biased Treg/Th17 balance away from regulatory toward inflammatory phenotype in relapsed multiple sclerosis and its correlation with severity of symptoms. J Neuroimmunol. 2013 Sep 15;262(1–2):106–12. http://dx.doi.org/10.1016/j.jneuroim.2013.06.007
21. Appay V, van Lier RA, Sallusto F, Roederer M. Phenotype and function of human T lymphocyte subsets: Consensus and issues. Cytometry A. 2008 Nov;73(11):975–83. http://dx.doi.org/10.1002/cyto.a.20643
22. Haegele KF, Stueckle CA, Malin JP, Sindern E. Increase of CD8+ T-effector memory cells in peripheral blood of patients with relapsing-remitting multiple sclerosis compared to healthy controls. J Neuroimmunol. 2007 Feb;183(1–2):168–74. http://dx.doi.org/10.1016/j.jneuroim.2006.09.008
23. Liu GZ, Fang LB, Hjelmstrom P, Gao XG. Increased CD8+ central memory T cells in patients with multiple sclerosis. Mult Scler. 2007 Mar;13(2):149–55. http://dx.doi.org/10.1177/1352458506069246
24. Pender MP, Csurhes PA, Pfluger CM, Burrows SR. Deficiency of CD8+ effector memory T cells is an early and persistent feature of multiple sclerosis. Mult Scler. 2014 Dec;20(14):1825–32. http://dx.doi.org/10.1177/1352458514536252
25. Jilek S, Schluep M, Rossetti AO, Guignard L, Le Goff G, Pantaleo G, et al. CSF enrichment of highly differentiated CD8+ T cells in early multiple sclerosis. Clin Immunol. 2007 Apr;123(1):105–13. http://dx.doi.org/10.1016/j.clim.2006.11.004
26. Mullen KM, Gocke AR, Allie R, Ntranos A, Grishkan IV, Pardo C, et al. Expression of CCR7 and CD45RA in CD4+ and CD8+ subsets in cerebrospinal fluid of 134 patients with inflammatory and non-inflammatory neurological diseases. J Neuroimmunol. 2012 Aug 15;249(1–2):86–92. http://dx.doi.org/10.1016/j.jneuroim.2012.04.017
27. Kebir H, Kreymborg K, Ifergan I, Dodelet-Devillers A, Cayrol R, Bernard M, et al. Human TH17 lymphocytes promote blood-brain barrier disruption and central nervous system inflammation. Nat Med. 2007 Oct;13(10):1173–5. http://dx.doi.org/10.1038/nm1651
28. Brucklacher-Waldert V, Stuerner K, Kolster M, Wolthausen J, Tolosa E. Phenotypical and functional characterization of T helper 17 cells in multiple sclerosis. Brain. 2009 Dec;132(Pt 12):3329–41. http://dx.doi.org/10.1093/brain/awp289
29. Kebir H, Ifergan I, Alvarez JI, Bernard M, Poirier J, Arbour N, et al. Preferential recruitment of interferon-gamma-expressing TH17 cells in multiple sclerosis. Ann Neurol. 2009 Sep;66(3):390–402. http://dx.doi.org/10.1002/ana.21748
30. Venken K, Hellings N, Thewissen M, Somers V, Hensen K, Rummens JL, et al. Compromised CD4+ CD25(high) regulatory T-cell function in patients with relapsing-remitting multiple sclerosis is correlated with a reduced frequency of FOXP3-positive cells and reduced FOXP3 expression at the single-cell level. Immunology. 2008 Jan;123(1):79-89. http://dx.doi.org/10.1111/j.1365-2567.2007.02690.x
31. Feger U, Luther C, Poeschel S, Melms A, Tolosa E, Wiendl H. Increased frequency of CD4+ CD25+ regulatory T cells in the cerebrospinal fluid but not in the blood of multiple sclerosis patients. Clin Exp Immunol. 2007 Mar;147(3):412–18. http://dx.doi.org/10.1111/j.1365-2249.2006.03271.x
32. Haas J, Hug A, Viehover A, Fritzsching B, Falk CS, Filser A, et al. Reduced suppressive effect of CD4+CD25high regulatory T cells on the T cell immune response against myelin oligodendrocyte glycoprotein in patients with multiple sclerosis. Eur J Immunol. 2005 Nov;35(11):3343–52. http://dx.doi.org/10.1002/eji.200526065
33. Peelen E, Damoiseaux J, Smolders J, Knippenberg S, Menheere P, Tervaert JW, et al. Th17 expansion in MS patients is counterbalanced by an expanded CD39+ regulatory T cell population during remission but not during relapse. J Neuroimmunol. 2011 Dec 15;240–241:97–103. http://dx.doi.org/10.1016/j.jneuroim.2011.09.013
34. Niino M, Hirotani M, Miyazaki Y, Sasaki H. Memory and naive B-cell subsets in patients with multiple sclerosis. Neurosci Lett. 2009 Oct 16;464(1):74–8. http://dx.doi.org/10.1016/j.neulet.2009.08.010
35. Kuerten S, Pommerschein G, Barth SK, Hohmann C, Milles B, Sammer FW, et al. Identification of a B cell-dependent subpopulation of multiple sclerosis by measurements of brain-reactive B cells in the blood. Clin Immunol. 2014 May-Jun;152(1–2):20–4. http://dx.doi.org/10.1016/j.clim.2014.02.014
36. Claes N, Fraussen J, Stinissen P, Hupperts R, Somers V. B Cells are multifunctional players in multiple sclerosis pathogenesis: Insights from therapeutic interventions. Front Immunol. 2015;6:642. http://dx.doi.org/10.3389/fimmu.2015.00642
37. Dooley J, Pauwels I, Franckaert D, Smets I, Garcia-Perez JE, Hilven K, et al. Immunologic profiles of multiple sclerosis treatments reveal shared early B cell alterations. Neurol Neuroimmunol Neuroinflamm. 2016 Aug;3(4):e240. http://dx.doi.org/10.1212/NXI.0000000000000240
38. Perumal J, Khan O. Emerging disease-modifying therapies in multiple sclerosis. Curr Treat Options Neurol. 2012 Jun;14(3):256-63. http://dx.doi.org/10.1007/s11940-012-0173-x
39. Buck D, Hemmer B. Treatment of multiple sclerosis: Current concepts and future perspectives. J Neurol. 2011 Oct;258(10):1747–62. http://dx.doi.org/10.1007/s00415-011-6101-2
40. Grigoriadis N, van Pesch V. A basic overview of multiple sclerosis immunopathology. Eur J Neurol. 2015 Oct;22 Suppl 2:3–13. http://dx.doi.org/10.1111/ene.12798
41. Winkelmann A, Loebermann M, Reisinger EC, Hartung HP, Zettl UK. Disease-modifying therapies and infectious risks in multiple sclerosis. Nat Rev Neurol. 2016 Apr;12(4):217–33. http://dx.doi.org/10.1038/nrneurol.2016.21
42. Kasper LH, Reder AT. Immunomodulatory activity of interferon-beta. Ann Clin Transl Neurol. 2014 Aug;1(8):622–31. http://dx.doi.org/10.1002/acn3.84
43. Kieseier BC. The mechanism of action of interferon-beta in relapsing multiple sclerosis. CNS Drugs. 2011 Jun 1;25(6):491–502. http://dx.doi.org/10.2165/11591110-000000000-00000
44. Aristimuno C, de Andres C, Bartolome M, de las Heras V, Martinez-Gines ML, Arroyo R, et al. IFNbeta-1a therapy for multiple sclerosis expands regulatory CD8+ T cells and decreases memory CD8+ subset: A longitudinal 1-year study. Clin Immunol. 2010 Feb;134(2):148-57. http://dx.doi.org/10.1016/j.clim.2009.09.008
45. Durelli L, Conti L, Clerico M, Boselli D, Contessa G, Ripellino P, et al. T-helper 17 cells expand in multiple sclerosis and are inhibited by interferon-beta. Ann Neurol. 2009 May;65(5):499–509. http://dx.doi.org/10.1002/ana.21652
46. Zhang X, Markovic-Plese S. Interferon beta inhibits the Th17 cell-mediated autoimmune response in patients with relapsing-remitting multiple sclerosis. Clin Neurol Neurosurg. 2010 Sep;112(7):641–5. http://dx.doi.org/10.1016/j.clineuro.2010.04.020
47. Jensen J, Langkilde AR, Frederiksen JL, Sellebjerg F. CD8+ T cell activation correlates with disease activity in clinically isolated syndromes and is regulated by interferon-beta treatment. J Neuroimmunol. 2006 Oct;179(1–2):163–72. http://dx.doi.org/10.1016/j.jneuroim.2006.06.024
48. Zanotti C, Chiarini M, Serana F, Capra R, Rottoli M, Rovaris M, et al. Opposite effects of interferon-beta on new B and T cell release from production sites in multiple sclerosis patients. J Neuroimmunol. 2011 Dec 15;240–241:147–50. http://dx.doi.org/10.1016/j.jneuroim.2011.10.007
49. Puissant-Lubrano B, Viala F, Winterton P, Abbal M, Clanet M, Blancher A. Thymic output and peripheral T lymphocyte subsets in relapsing—Remitting multiple sclerosis patients treated or not by IFN-beta. J Neuroimmunol. 2008 Jan;193(1–2):188–94. http://dx.doi.org/10.1016/j.jneuroim.2007.10.027
50. Lalive PH, Neuhaus O, Benkhoucha M, Burger D, Hohlfeld R, Zamvil SS, et al. Glatiramer acetate in the treatment of multiple sclerosis: Emerging concepts regarding its mechanism of action. CNS Drugs. 2011 May;25(5):401–14. http://dx.doi.org/10.2165/11588120-000000000-00000
51. Fridkis-Hareli M, Teitelbaum D, Gurevich E, Pecht I, Brautbar C, Kwon OJ, et al. Direct binding of myelin basic protein and synthetic copolymer 1 to class II major histocompatibility complex molecules on living antigen-presenting cells—Specificity and promiscuity. Proc Natl Acad Sci U S A. 1994 May 24;91(11):4872–6. http://dx.doi.org/10.1073/pnas.91.11.4872
52. Duda PW, Schmied MC, Cook SL, Krieger JI, Hafler DA. Glatiramer acetate (Copaxone) induces degenerate, Th2-polarized immune responses in patients with multiple sclerosis. J Clin Invest. 2000 Apr;105(7):967–76. http://dx.doi.org/10.1172/JCI8970
53. Lehmann-Horn K, Penkert H, Grein P, Leppmeier U, Teuber-Hanselmann S, Hemmer B, et al. PML during dimethyl fumarate treatment of multiple sclerosis: How does lymphopenia matter? Neurology. 2016 Jul 26;87(4):440–1. http://dx.doi.org/10.1212/WNL.0000000000002900
54. Khatri BO, Garland J, Berger J, Kramer J, Sershon L, Olapo T, et al. The effect of dimethyl fumarate (Tecfidera) on lymphocyte counts: A potential contributor to progressive multifocal leukoencephalopathy risk. Mult Scler Relat Disord. 2015 Jul;4(4):377-9. http://dx.doi.org/10.1016/j.msard.2015.05.003
55. Gross CC, Schulte-Mecklenbeck A, Klinsing S, Posevitz-Fejfar A, Wiendl H, Klotz L. Dimethyl fumarate treatment alters circulating T helper cell subsets in multiple sclerosis. Neurol Neuroimmunol Neuroinflamm. 2016 Feb;3(1):e183. http://dx.doi.org/10.1212/NXI.0000000000000183
56. Longbrake EE, Ramsbottom MJ, Cantoni C, Ghezzi L, Cross AH, Piccio L. Dimethyl fumarate selectively reduces memory T cells in multiple sclerosis patients. Mult Scler. 2016 Jul;22(8):1061–70. http://dx.doi.org/10.1177/1352458515608961
57. Schloder J, Berges C, Luessi F, Jonuleit H. Dimethyl fumarate therapy significantly improves the responsiveness of T cells in multiple sclerosis patients for immunoregulation by regulatory T cells. Int J Mol Sci. 2017 Jan 28;18(2):pii: E271. http://dx.doi.org/10.3390/ijms18020271
58. Wu Q, Wang Q, Mao G, Dowling CA, Lundy SK, Mao-Draayer Y. Dimethyl fumarate selectively reduces memory T cells and shifts the balance between Th1/Th17 and Th2 in multiple sclerosis patients. J Immunol. 2017 Apr 15;198(8):3069–80. http://dx.doi.org/10.4049/jimmunol.1601532
59. Lundy SK, Wu Q, Wang Q, Dowling CA, Taitano SH, Mao G, et al. Dimethyl fumarate treatment of relapsing-remitting multiple sclerosis influences B-cell subsets. Neurol Neuroimmunol Neuroinflamm. 2016 Apr;3(2):e211. http://dx.doi.org/10.1212/NXI.0000000000000211
60. Miller AE. Teriflunomide: A once-daily oral medication for the treatment of relapsing forms of multiple sclerosis. Clin Ther. 2015 Oct 01;37(10):2366–80. http://dx.doi.org/10.1016/j.clinthera.2015.08.003
61. Warnke C, Stuve O, Kieseier BC. Teriflunomide for the treatment of multiple sclerosis. Clin Neurol Neurosurg. 2013 Dec;115 Suppl 1:S90–4. http://dx.doi.org/10.1016/j.clineuro.2013.09.030
62. Bar-Or A, Pachner A, Menguy-Vacheron F, Kaplan J, Wiendl H. Teriflunomide and its mechanism of action in multiple sclerosis. Drugs. 2014 Apr;74(6):659–74. http://dx.doi.org/10.1007/s40265-014-0212-x
63. Hla T, Brinkmann V. Sphingosine 1-phosphate (S1P): Physiology and the effects of S1P receptor modulation. Neurology. 2011 Feb 22;76(8 Suppl 3):S3–8. http://dx.doi.org/10.1212/WNL.0b013e31820d5ec1
64. Pinschewer DD, Brinkmann V, Merkler D. Impact of sphingosine 1-phosphate modulation on immune outcomes. Neurology. 2011 Feb 22;76(8 Suppl 3):S15–19. http://dx.doi.org/10.1212/WNL.0b013e31820d9596
65. Mehling M, Brinkmann V, Antel J, Bar-Or A, Goebels N, Vedrine C, et al. FTY720 therapy exerts differential effects on T cell subsets in multiple sclerosis. Neurology. 2008 Oct 14;71(16):1261–7. http://dx.doi.org/10.1212/01.wnl.0000327609.57688.ea
66. Mehling M, Brinkmann V, Burgener AV, Gubser P, Luster AD, Kappos L, et al. Homing frequency of human T cells inferred from peripheral blood depletion kinetics after sphingosine-1-phosphate receptor blockade. J Allergy Clin Immunol. 2013 May;131(5):1440–3 e7.
67. Sato DK, Nakashima I, Bar-Or A, Misu T, Suzuki C, Nishiyama S, et al. Changes in Th17 and regulatory T cells after fingolimod initiation to treat multiple sclerosis. J Neuroimmunol. 2014 Mar 15;268(1-2):95–8. http://dx.doi.org/10.1016/j.jneuroim.2014.01.008
68. Henault D, Galleguillos L, Moore C, Johnson T, Bar-Or A, Antel J. Basis for fluctuations in lymphocyte counts in fingolimod-treated patients with multiple sclerosis. Neurology. 2013 Nov 12;81(20): 1768–72. http://dx.doi.org/10.1212/01.wnl.0000435564.92609.2c
69. Chiarini M, Sottini A, Bertoli D, Serana F, Caimi L, Rasia S, et al. Newly produced T and B lymphocytes and T-cell receptor repertoire diversity are reduced in peripheral blood of fingolimod-treated multiple sclerosis patients. Mult Scler. 2015 May;21(6):726–34. http://dx.doi.org/10.1177/1352458514551456
70. Claes N, Dhaeze T, Fraussen J, Broux B, Van Wijmeersch B, Stinissen P, et al. Compositional changes of B and T cell subtypes during fingolimod treatment in multiple sclerosis patients: A 12-month follow-up study. PLoS One. 2014;9(10):e111115. http://dx.doi.org/10.1371/journal.pone.0111115
71. Miyazaki Y, Niino M, Fukazawa T, Takahashi E, Nonaka T, Amino I, et al. Suppressed pro-inflammatory properties of circulating B cells in patients with multiple sclerosis treated with fingolimod, based on altered proportions of B-cell subpopulations. Clin Immunol. 2014 Apr;151(2):127–35. http://dx.doi.org/10.1016/j.clim.2014.02.001
72. Teniente-Serra A, Hervas JV, Quirant-Sanchez B, Mansilla MJ, Grau-Lopez L, Ramo-Tello C, et al. Baseline differences in minor lymphocyte subpopulations may predict response to fingolimod in relapsing-remitting multiple sclerosis patients. CNS Neurosci Ther. 2016 Jul;22(7):584–92. http://dx.doi.org/10.1111/cns.12548
73. Haas J, Schwarz A, Korporal-Kunke M, Jarius S, Wiendl H, Kieseier BC, et al. Fingolimod does not impair T-cell release from the thymus and beneficially affects treg function in patients with multiple sclerosis. Mult Scler. 2015 Oct;21(12):1521–32. http://dx.doi.org/10.1177/1352458514564589
74. Muls N, Dang HA, Sindic CJ, van Pesch V. Fingolimod increases CD39-expressing regulatory T cells in multiple sclerosis patients. PLoS One. 2014;9(11):e113025. http://dx.doi.org/10.1371/journal.pone.0113025
75. Serpero LD, Filaci G, Parodi A, Battaglia F, Kalli F, Brogi D, et al. Fingolimod modulates peripheral effector and regulatory T cells in MS patients. J Neuroimmune Pharmacol. 2013 Dec;8(5):1106–13. http://dx.doi.org/10.1007/s11481-013-9465-5
76. Song ZY, Yamasaki R, Kawano Y, Sato S, Masaki K, Yoshimura S, et al. Peripheral blood T cell dynamics predict relapse in multiple sclerosis patients on fingolimod. PLoS One. 2014;10(4):e0124923. http://dx.doi.org/10.1371/journal.pone.0124923
77. Kim MG, Lee SY, Ko YS, Lee HY, Jo SK, Cho WY, et al. CD4+ CD25+ regulatory T cells partially mediate the beneficial effects of FTY720, a sphingosine-1-phosphate analogue, during ischaemia/reperfusion-induced acute kidney injury. Nephrol Dial Transplant. 2011 Jan;26(1):111–24. http://dx.doi.org/10.1093/ndt/gfq480
78. Sun Y, Wang W, Shan B, Di J, Chen L, Ren L, et al. FTY720-induced conversion of conventional Foxp3- CD4+ T cells to Foxp3+ regulatory T cells in NOD mice. Am J Reprod Immunol. 2011 Nov;66(5):349–62. http://dx.doi.org/10.1111/j.1600-0897.2011.01010.x
79. Sehrawat S, Rouse BT. Anti-inflammatory effects of FTY720 against viral-induced immunopathology: Role of drug-induced conversion of T cells to become Foxp3+ regulators. J Immunol. 2008 Jun 1;180(11):7636–47. http://dx.doi.org/10.4049/jimmunol.180.11.7636
80. Mehling M, Lindberg R, Raulf F, Kuhle J, Hess C, Kappos L, et al. Th17 central memory T cells are reduced by FTY720 in patients with multiple sclerosis. Neurology. 2010 Aug 3;75(5):403–10. http://dx.doi.org/10.1212/WNL.0b013e3181ebdd64
81. Hu Y, Turner MJ, Shields J, Gale MS, Hutto E, Roberts BL, et al. Investigation of the mechanism of action of alemtuzumab in a human CD52 transgenic mouse model. Immunology. 2009 Oct;128(2):260–70. http://dx.doi.org/10.1111/j.1365-2567.2009.03115.x
82. Zhang X, Tao Y, Chopra M, Ahn M, Marcus KL, Choudhary N, et al. Differential reconstitution of T cell subsets following immunodepleting treatment with alemtuzumab (anti-CD52 monoclonal antibody) in patients with relapsing-remitting multiple sclerosis. J Immunol. 2013 Dec 15;191(12): 5867–74. http://dx.doi.org/10.4049/jimmunol.1301926
83. De Mercanti S, Rolla S, Cucci A, Bardina V, Cocco E, Vladic A, et al. Alemtuzumab long-term immunologic effect: Treg suppressor function increases up to 24 months. Neurol Neuroimmunol Neuroinflamm. 2016 Feb;3(1):e194. http://dx.doi.org/10.1212/NXI.0000000000000194
84. Jones JL, Thompson SA, Loh P, Davies JL, Tuohy OC, Curry AJ, et al. Human autoimmunity after lymphocyte depletion is caused by homeostatic T-cell proliferation. Proc Natl Acad Sci U S A. 2013 Dec 10;110(50):20200–5. http://dx.doi.org/10.1073/pnas.1313654110
85. Hill-Cawthorne GA, Button T, Tuohy O, Jones JL, May K, Somerfield J, et al. Long term lymphocyte reconstitution after alemtuzumab treatment of multiple sclerosis. J Neurol Neurosurg Psychiatry. 2012 Mar;83(3):298–304. http://dx.doi.org/10.1136/jnnp-2011-300826
86. Williams T, Coles A, Azzopardi L. The outlook for alemtuzumab in multiple sclerosis. BioDrugs. 2013 Jun;27(3):181–9. http://dx.doi.org/10.1007/s40259-013-0028-3
87. Hersh CM, Cohen JA. Alemtuzumab for the treatment of relapsing-remitting multiple sclerosis. Immunotherapy. 2014;6(3):249–59. http://dx.doi.org/10.2217/imt.14.7
88. Skarica M, Eckstein C, Whartenby KA, Calabresi PA. Novel mechanisms of immune modulation of natalizumab in multiple sclerosis patients. J Neuroimmunol. 2011 Jun;235(1–2):70–6. http://dx.doi.org/10.1016/j.jneuroim.2011.02.010
89. Putzki N, Baranwal MK, Tettenborn B, Limmroth V, Kreuzfelder E. Effects of natalizumab on circulating B cells, T regulatory cells and natural killer cells. Eur Neurol. 2010;63(5):311–17. http://dx.doi.org/10.1159/000302687
90. Koudriavtseva T, Sbardella E, Trento E, Bordignon V, D’Agosto G, Cordiali-Fei P. Long-term follow-up of peripheral lymphocyte subsets in a cohort of multiple sclerosis patients treated with natalizumab. Clin Exp Immunol. 2014 Jun;176(3):320–6. http://dx.doi.org/10.1111/cei.12261
91. Planas R, Jelcic I, Schippling S, Martin R, Sospedra M. Natalizumab treatment perturbs memory- and marginal zone-like B-cell homing in secondary lymphoid organs in multiple sclerosis. Eur J Immunol. 2012 Mar;42(3):790–8. http://dx.doi.org/10.1002/eji.201142108
92. Kivisakk P, Healy BC, Viglietta V, Quintana FJ, Hootstein MA, Weiner HL, et al. Natalizumab treatment is associated with peripheral sequestration of proinflammatory T cells. Neurology. 2009 Jun 2;72(22):1922–30. http://dx.doi.org/10.1212/WNL.0b013e3181a8266f
93. Bonig H, Wundes A, Chang KH, Lucas S, Papayannopoulou T. Increased numbers of circulating hematopoietic stem/progenitor cells are chronically maintained in patients treated with the CD49d blocking antibody natalizumab. Blood. 2008 Apr 1;111(7):3439–41. http://dx.doi.org/10.1182/blood-2007-09-112052
94. Jing D, Oelschlaegel U, Ordemann R, Holig K, Ehninger G, Reichmann H, et al. CD49d blockade by natalizumab in patients with multiple sclerosis affects steady-state hematopoiesis and mobilizes progenitors with a distinct phenotype and function. Bone Marrow Transplant. 2010 Oct;45(10): 1489–96. http://dx.doi.org/10.1038/bmt.2009.381
95. Zohren F, Toutzaris D, Klarner V, Hartung HP, Kieseier B, Haas R. The monoclonal anti-VLA-4 antibody natalizumab mobilizes CD34+ hematopoietic progenitor cells in humans. Blood. 2008 Apr 1;111(7):3893–5. http://dx.doi.org/10.1182/blood-2007-10-120329
96. Zanotti C, Chiarini M, Serana F, Sottini A, Garrafa E, Torri F, et al. Peripheral accumulation of newly produced T and B lymphocytes in natalizumab-treated multiple sclerosis patients. Clin Immunol. 2012 Oct;145(1):19–26. http://dx.doi.org/10.1016/j.clim.2012.07.007
97. Krumbholz M, Meinl I, Kumpfel T, Hohlfeld R, Meinl E. Natalizumab disproportionately increases circulating pre-B and B cells in multiple sclerosis. Neurology. 2008 Oct 21;71(17):1350–4. http://dx.doi.org/10.1212/01.wnl.0000327671.91357.96
98. Fleischer V, Friedrich M, Rezk A, Buhler U, Witsch E, Uphaus T, et al. Treatment response to dimethyl fumarate is characterized by disproportionate CD8+ T cell reduction in MS. Mult Scler. 2017 Apr 01: 1352458517703799. http://dx.doi.org/10.1177/1352458517703799
99. Punet-Ortiz J, Hervas-Garcia JV, Teniente-Serra A, Cano-Orgaz A, Mansilla MJ, Quirant-Sanchez B, et al. Monitoring CD49d receptor occupancy: A method to optimize and personalize natalizumab therapy in multiple sclerosis patients. Cytometry B Clin Cytom. 2017 Apr 05. http://dx.doi.org/10.1002/cyto.b.21527