Hindawi Mediators of Inflammation Volume 2019, Article ID 8147803, 9 pages https://doi.org/10.1155/2019/8147803 Research Article Th1Th17CM Lymphocyte Subpopulation as a Predictive Biomarker of Disease Activity in Multiple Sclerosis Patients under Dimethyl Fumarate or Fingolimod Treatment Bibiana Quirant-Sánchez ,1,2 Silvia Presas-Rodriguez,3 María José Mansilla,1,2 Aina Teniente-Serra,1,2 José V. Hervás-García,3 Luis Brieva,4 Ester Moral-Torres,5 Antonio Cano,6 Elvira Munteis,7 Juan Navarro-Barriuso,1,2 Eva M. Martínez-Cáceres ,1,2 and Cristina Ramo-Tello 3 1 Immunology Division, LCMN, Hospital Universitari Germans Trias i Pujol and Research Institute, Campus Can Ruti, Badalona, Barcelona, Spain 2 Department of Cellular Biology, Physiology and Immunology, Universitat Autònoma de Barcelona, Spain 3 Multiple Sclerosis Unit, Department of Neurosciences, Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain 4 Neurology Department of Hospital Arnau Vilanova, Lleida, Spain 5 Neurology Department of Hospital San Joan Despi Moises Broggi, Barcelona, Spain 6 Neurology Department of Hospital de Mataró, Mataró, Barcelona, Spain 7 Neurology Department of Hospital del Mar, Barcelona, Spain Correspondence should be addressed to Eva M. Martínez-Cáceres; evmcaceres@gmail.com and Cristina Ramo-Tello; cramot@gmail.com Received 31 October 2018; Revised 14 February 2019; Accepted 10 March 2019; Published 26 June 2019 Academic Editor: Kerstin Wolk Copyright © 2019 Bibiana Quirant-Sánchez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Peripheral blood biomarkers able to predict disease activity in multiple sclerosis (MS) patients have not been identified yet. Here, we analyzed the immune phenotype of T lymphocyte subpopulations in peripheral blood samples from 66 RRMS patients under DMF (n = 22) or fingolimod (n = 44) treatment, by flow cytometry. A correlation study between the percentage and absolute cell number of each lymphocyte subpopulation with the presence of relapses or new MRI lesions during 12-month follow-up was performed. Patients who had undergone relapses showed at baseline higher percentage of Th1CM cells (relapsed: 11 60 ± 4 17%vs. nonrelapsed: 9 25 ± 3 17%, p < 0 05) and Th1Th17CM cells (relapsed: 15 65 ± 6 15%vs. nonrelapsed: 10 14 ± 4 05%, p < 0 01) before initiating DMF or fingolimod treatment. Kaplan-Meier analysis revealed that patients with Th1Th17CM (CD4+CCR7+CD45RA-CCR6+CXCR3+) cells > 11 48% had a 50% relapse-free survival compared to patients with Th1Th17CMcells < 11 48% whose relapse-free survival was 88% (p = 0 013, log-rank test). Additionally, a high percentage of Th1Th17CM cells was also found in patients with MRI activity (MRI activity: 14 02 ± 5 87%vs. no MRI activity: 9 82 ± 4 06%, p < 0 01). Our results suggest that the percentage of Th1Th17CM lymphocytes at baseline is a predictive biomarker of activity during the first 12 months of treatment, regardless of the treatment. 1. Introduction The CD4+ T-helper (Th) lymphocytes are the most studied cell subpopulation in MS. Different authors have Multiple sclerosis (MS) is a chronic autoimmune inflamma- demonstrated that T-helper 1 (Th1), T-helper 17 (Th17), tory disease of the central nervous system (CNS), character- and T-helper 1/17 (Th1Th17; also referred as Th1-like Th17 ized by immune cell infiltration, demyelination, axonal in the literature) CD4+ T cells promote or contribute to the degeneration, and astrogliosis [1, 2]. autoimmune inflammatory process of MS patients and its 2 Mediators of Inflammation mouse model, the experimental autoimmune encephalomy- classified into active or nonactive according to relapses and elitis (EAE) [3–7]. Th1Th17 cells are characterized by the pro- MRI activity (Table 1) over a follow-up period of 12 months. duction of proinflammatory cytokines such as IFN-γ (Th1) Patients who had progressive forms of MS or RRMS patients and IL-17 (Th17). Additionally, in vitro studies showed that receiving interferon beta (IFN-β) or glatiramer acetate (GA) human Th1Th17 lymphocytes with memory phenotype within the previous 24 h, or fingolimod in the previous 15 (CD4+CD45RO+IL-17A+) migrate more avidly across the days, or natalizumab (NTZ), teriflunomide, diazoxide, or blood-brain barrier than Th1 cells [4]. These results were also methylprednisolone within the previous 30 days prior to confirmed in vivo, by immunohistofluorescence studies of the the start of the DMF or fingolimod treatment were excluded CNS lesions of mice with EAE, indicating that Th1Th17 cells from the study. are more pathogenic than Th1 lymphocytes, although both Relapses were defined as new or worsening neurological Th1 and Th17 are required for EAE induction [5]. deficit lasting 24 h or more in the absence of fever or infec- Effective prevention of MS relapses partially reduces tion. The annualized relapse rate (ARR) was defined as the accumulation of neurological disability [8]. Nowadays, total number of relapses divided by the number of patients- disease-modifying therapies (DMTs) are the standard treat- year assessed in the 12 months prior the initiation of treat- ment for patients with RRMS and these treatments are postu- ment (baseline) and after 12-month follow-up. lated to reduce clinical relapses and radiological activity, MRI activity was measured by any new or enlarging T2 through the reduction of the activation, migration, or differ- lesions and/or gadolinium enhancement T1 lesions (Gd+) entiation of different lymphocyte subpopulations [8, 9]. in brain MRI. A 1.5 or 3.0 Tesla MRI scans were used to eval- Despite these beneficial effects, clinical and radiological out- uate the number of lesions before and after 12 months of comes remain highly variable among patients. Thereby, there treatment. The same equipment was used in each patient. is an unmet need to identify objective and accessible bio- The number of lesions was determined visually comparing markers of activity in MS patients [10, 11]. the first and second MRI scans. Dimethyl fumarate (DMF) is an oral treatment for Disability progression was defined as worsening of 1 RRMS, able to reduce the relapse rate and the number of point or more on the expanded disability status scale (EDSS) new or enlarging MRI lesions [12]. Although its mechanisms score over the baseline. of action is not yet well understood, it is postulated that DMF induces a switch toward a Th2 cytokine profile and a reduc- 2.2. Flow Cytometry Analysis. Blood samples were collected tion in the migratory capacity of the immune cells by the prior to the first administration of the treatment (baseline) inhibition of nuclear factor kappa B (NF-κB) [13]. In and processed by a centralized laboratory within the first addition, it induces activation of nuclear factor erythroid 24 h after their collection. Samples of whole blood were ana- 2-related factor 2 (Nrf-2), with neuroprotective and anti- lyzed by flow cytometry to determine the percentage and oxidant properties [14]. absolute number of T lymphocyte subpopulations using the Another oral treatment for RRMS patients is fingolimod, following combination of monoclonal antibodies per panel: a sphingosine 1-phosphate receptor modulator that reduces CD3-V450, CD4 PerCP-Cy5.5, CD45RA PE-Cy7, CCR7 the egress of lymphocytes from lymph nodes and, conse- PE, CD38 APC, CD8 APC-H7, HLA-DR V500 (BD Biosci- quently, the infiltration of potentially autoreactive lympho- ences), CD183 AF488, CD196 BV605, and CD45 AF700 cytes into the CNS [15]. (BioLegend, San Diego, CA, USA). The absolute cell number The effect of both treatments on lymphocyte subpopula- quantification was performed as previously reported [16]. tions has been described, showing relevant changes of these Samples were acquired on a LSR II Fortessa flow cytometer cells in peripheral blood of patients treated with these drugs (BD Biosciences, San José, CA, USA). [16–21]. While fingolimod mainly reduces CCR7+ cells—- The following T cell subpopulations were analyzed: CD4+ naïve and central memory T cells—which are regulated by naïve, CD4+ TCM, Th1CM, Th1Th17CM, Th2CM, Th17CM, homing signals to lymph nodes [22], DMF induces a reduc- CD4+ TEMRA, CD4+ TEM, Th1EM, Th1Th17EM, Th2EM, tion of effector T cells, as well as a decrease of CD4+ T Th17EM, CD8+ naïve, CD8+ TCM, CD8+ TEMRA, CD8+ TEM, cells that express interferon-γ (IFN-γ) and interleukin-17 double positive (CD4+CD8+), and double negative (IL-17) [23, 24]. (CD4-CD8-) T cells. Analysis was performed using the There are no studies relating the basal levels of lympho- FACSDiva software (BD Biosciences). The gating strategy cyte subpopulations with the risk to develop relapses or for the subpopulations analyzed in whole blood is shown MRI lesions during treatment. In our study, we analyzed in Figure 1 and previously described by Quirant-Sánchez peripheral blood T cell subpopulations in RRMS patients at et al. [22]. baseline by flow cytometry and correlated their levels to out- come parameters (relapses and MRI activity) appearing 2.3. Statistical Analysis. The comparisons of the clinical char- during the first 12 months of DMF or fingolimod treatment. acteristics of patients were carried out using the Wilcoxon test to compare two groups in the case of paired data. The 2. Methods Kruskal-Wallis test was used to compare more than three groups in the case of independent data. For the analysis of 2.1. Patients. Sixty-six RRMS patients fulfilling the 2010 the relapse and MRI activity groups, mean baseline values McDonald’s criteria [25] who started DMF (n = 22) or fingo- of each group were compared using the nonparametric limod (n = 44) treatment were included. Patients were unpaired t-test (Mann-Whitney test). Predictive values of Mediators of Inflammation 3 Table 1: Clinical and demographic characteristics of MS patients included in the study. Total cohort Relapsed (R) Nonrelapsed (NR) DMF cohort FNG cohort (n = 66) (n = 21) (n = 45) (n = 22) (n = 44) Female sex (no. of patients (%)) 42 (63) 12 (57) 30 (67) 15 (68) 26 (59) Age (years), mean (SD) 35 29 ± 8 5 32 62 ± 7 66 36 5 ± 8 67 36 7 ± 7 4 34 9 ± 8 9 First symptoms (years), mean (SD) 4 72 ± 5 47 4 51 ± 6 08 4 81 ± 5 25 4 18 ± 4 72 4 7±5 9 33 naïve 11 naïve 22 naïve 15 naïve 18 naïve 16 IFN-β 4 IFN-β 12 IFN-β 4 IFN-β 12 IFN-β 3 GA∗ 1 GA∗ 2 GA∗ 3 GA∗ 10 NTZ∗ 3 NTZ∗ 7 NTZ∗ 10 NTZ∗ Previous immunomodulatory drugs 1 diazoxide 1 diazoxide 1 diazoxide 1 teriflunomide 1 teriflunomide 1 fingolimod 1 fingolimod 1 others∗ 1 others∗ Number of previous treatments (years), 1±1 1±1 3 0 5±0 8 0 83 ± 0 96 0 83 ± 0 98 mean (SD) 0 treatment 33 13 20 15 18 1 treatment 16 4 12 4 12 2 treatments 12 5 7 1 11 ≥3 treatments 5 2 3 2 3 ARR∗ previous year Total patients 1.53 (1.1) 1.53 (1.2) 1.52 (0.8) 1.14 (0.7) 1.53 (1.13) Naïve patients 1.54 (0.9) 1.55 (1.1) 1.6 (0.8) 1.6 (0.8) 1.61 (1.20) Treated patients 1.5 (1.3) 1.6 (1.5) 1.3 (1) 1.3 (1) 1.52 (1.21) ∗ DMF: dimethyl fumarate; FNG: fingolimod; IFN-β: interferon beta; GA: glatiramer acetate; NTZ: natalizumab; others: clinical trial of cell therapies; ARR: annualized relapse rate; SD: standard deviation. the percentages and absolute number of lymphocyte subpop- patients) presented a relapse in the first three months after ulations were investigated through receiver operating charac- starting treatment. teristic (ROC) curves. Based on these curves, cut-off values Although most of the patients did not receive any DMT for relapse prediction were assessed for each potential bio- previously (33 naïve patients), patients treated with previous marker. For these biomarkers, Kaplan-Meier curves with immunomodulatory treatments were included in our study. the log-rank test were used to test differences of survival The distribution of a previous treatment in the cohort of fin- probability between groups of patients. Values of p < 0 05 golimod was 18 naïve patients, 12 switched from IFN-β, 10 were considered statistically significant. Results are expressed from NTZ (all for positive JC virus serostatus), 3 from GA, as means ± SEM. The Statistical Package for Social Sciences and only one patient switched from diazoxide. In the cohort (SPSS/Windows version 15.0; SPSS Inc., Chicago, IL, USA) of DMF, the following patients were included: 15 naïve and the software program GraphPad Prism (5.0 version; patients, 4 switched from IFN-β, 1 patient switched from ter- GraphPad, La Jolla, CA, USA) were used to perform iflunomide, and 1 from fingolimod. In addition, one patient statistical analyses. who had participated in a clinical trial with mesenchymal stem cells was included. No other previous treatments were included in this study (Table 1). 3. Results According to a previous treatment, the distribution of patients who did not undergo relapses during the follow-up 3.1. Patients. Clinical and demographical characteristics of was (i) 64% of 33 naïve patients, (ii) 69% of 16 IFN-β patients are shown in Table 1. No differences were found at patients, (iii) 70% of 10 NTZ patients, and (iv) 68% of 3 baseline between groups. GA patients (Table 1). From the sixty-six RRMS, 44 patients were treated with The analysis of the ARR according to the treatment fingolimod and 22 patients with DMF. After 12 months, started during the follow-up is shown in Table 2. Previous 60% of patients treated with fingolimod and 83% of patients DMTs and washout period were considered in the ARR anal- treated with DMF did not experience relapses (nonrelapsed ysis. No differences in the distribution of patients depending patients). A total of 21 patients underwent at least one on the previous treatment were found in relation to the ARR relapse during follow-up, and 57% of them (12 of 21 at baseline (Table 2). The ARR was significantly reduced 4 Mediators of Inflammation T CD4 T CD4CM 105 T CD4 EMRA T CD4 naive 105 Th1CM Th1Th17CM 104 104 CD45RA CXCR3 103 103 0 0 T CD4EM T CD4CM Th17CM –409 –329 –97 0 102 103 104 105 –1.457 0 103 104 105 CCR7 CCR6 (a) (b) Central memory Th1 (Th1CM) Central memory Th1Th17 (Th1Th17CM) 20 ⁎ ⁎⁎ CD4+CCR7+CD45RA−CCR6+ CD4+CCR7+CD45RA−CCR6− 30 15 CXCR3+ (%) CXCR3+ (%) 20 10 5 10 0 0 No relapse Relapse No relapse Relapse (c) (d) Figure 1: Distribution of lymphocyte subpopulations at baseline in MS patients who presented clinical relapses during the first year of treatment. Representative example of the flow cytometry gating strategy used to analyze the different stages of maturation CD4+ T lymphocyte subpopulations (a) and central memory Th1, Th2, Th17, and Th1Th17 lymphocytes (b). Percentage of Th1 central memory cells (Th1CM) (n = 53) (c) and percentage of Th1Th17 central memory cells (Th1Th17CM) (n = 53) (d). Each dot represents the value of an individual patient. CM = central memory; EM = effector memory. ∗ p < 0 05; ∗∗ p < 0 01. Table 2: Analysis of clinical and radiologic characteristics of the patients after 12 months of treatment. DMF cohort (n = 22) Fingolimod cohort (n = 44) Baseline +12 months p value Baseline +12 months p value ARR∗ mean (SD) Total patients 1.5 (1.01) 0.14 (0.35) p < 0 0001 1.56 (1.18) 0.61 (0.84) p < 0 0001 Naive patients 1.6 (0.8) 0.06 (0.26) p < 0 0001 1.72 (1.01) 0.83 (0.86) p < 0 01 Treated patients 1.6 (1.4) 0.28 (0.48) p < 0 05 1.4 (1.35) 0.46 (0.81) p < 0 01 Relapse-free patients (no. of patients (%)) 19 (86.4) 25 (62.5) Progression-free patients (no. of patients (%)) 21 (95) 34 (85) Free MRI activity (no. of patients (%)) 15 (79) 25 (64) ∗ DMF: dimethyl fumarate; ARR: annualized relapse rate. during the 12-month follow-up period (0 5 ± 0 8) vs. ARR from 1 6 ± 0 93 to 0 42 ± 0 75 (p < 0 001) and naïve (1 53 ± 1 1) (p < 0 001). Particularly, patients who had patients showed a reduced ARR from 1 42 ± 1 32 to 0 55 ± received a previous treatment had shown a reduction in the 0 77 (p < 0 01). Mediators of Inflammation 5 Table 3: Phenotype of T cell subpopulations by flow cytometry. Lymphocyte subpopulations Phenotype T cell subsets (CD3+) CD4+ naïve T cell CD4+CCR7+CD45RA+ CD8+ naïve T cell CD8+CCR7+CD45RA+ CD4+ central memory (CD4+ TCM) CD4+CCR7+CD45RA- Th1 central memory (Th1CM) CD4 CCR7+CD45RA-CCR6-CXCR3+ + Th2 central memory (Th2CM) CD4+CCR7+CD45RA-CCR6-CXCR3- Th17 central memory (Th17CM) CD4+CCR7+CD45RA-CCR6+CXCR3- Th1Th17 central memory (Th1Th17CM) CD4+CCR7+CD45RA-CCR6+CXCR3+ CD8+ central memory T cell (CD8+ TCM) CD8+CCR7+CD45RA- CD4+ effector memory T cell (CD4+ TEM) CD4+CCR7-CD45RA- Th1 effector memory (Th1EM) CD4+CCR7-CD45RA-CCR6-CXCR3+ Th2 effector memory (Th2EM) CD4+CCR7-CD45RA-CCR6-CXCR3- Th17 effector memory (Th17EM) CD4+CCR7-CD45RA-CCR6+CXCR3- Th1Th17 effector memory (Th1Th17EM) CD4+CCR7-CD45RA-CCR6+CXCR3+ CD8+ effector memory T cell (CD8+ TEM) CD8+CCR7-CD45RA- Terminal differentiated effector memory CD4+ T cell (TEMRA) CD4+CCR7-CD45RA+ Terminal differentiated effector memory CD8+ T cell (TEMRA) CD8+CCR7-CD45RA+ Double negative T cell CD4-CD8- Double positive T cell CD4+CD8+ 3.2. Increase of Th1CM and Th1Th17CM Cells in Patients That (relapsed: 41 28 ± 13 84%vs. nonrelapsed: 36 38 ± 9 83%, Presented Clinical Relapses. We compared the percentage and p = 0 034) (Table S1). No differences were found in the absolute number of T lymphocyte subpopulations (Table 3), percentage of CD4+ TCM in the DMF cohort. at baseline, of patients that experienced at least one clinical Patients in which the prior treatment was NTZ showed a relapse (n = 21) with those that remained relapse-free higher percentage of CD4+ TCM at baseline than naïve (n = 45). Although the percentage of CD4+ TCM cells did patients (NTZ-treated patients: 47 4 ± 5 6%vs. naïve patients: not show differences between groups in the total cohort of 37 56 ± 11 09%, p = 0 013). A deep analysis of CD4+ TCM cell patients (Table 4), a deep analysis of minor subpopulations subsets—Th1CM, Th17CM, and Th1Th17CM—revealed no of CD4+ TCM pointed out a significantly higher percentage differences at baseline between naïve and patients previously Th1CM cells (CD4+CCR7+CD45RA-CCR6-CXCR3+) and treated with DMT as well as no differences between naïve Th1Th17CM cells (CD4+CCR7+CD45RA-CCR6+CXCR3+) and patients that switched from NTZ (Th1CM: NTZ patients: at baseline in patients that underwent relapses (Th1: 10 39 ± 3 36%vs. naïve patients: 9 83 ± 3 35%, p = 0 64, relapsed: 11 60 ± 4 17%vs. nonrelapsed: 9 25 ± 3 17%, p Th17CM: NTZ patients: 13 65 ± 2 9%vs. naïve patients: 10 46 < 0 05, Figure 1(c); Th1Th17: relapsed: 15 65 ± 6 15%vs. ± 5 45%, p = 0 09, and Th1Th17CM: NTZ patients: 14 56 ± nonrelapsed: 10 14 ± 4 05%, p < 0 01, Figure 1(d) and 5 36%vs. naïve patients: 12 65 ± 6 42%, p = 0 39). Figure S1). Th1CM and Th1Th17CM cells from 13 patients In relation to absolute numbers of lymphocyte subpopu- were not available from the study. No statistically differences lations, no differences of Th1CM, Th17CM, and Th1Th17CM were observed in Th1CM and Th1Th17CM lymphocytes were found. In contrast, the absolute number of CD4+ TCM between patients treated with DMF or fingolimod at baseline. cells at baseline was higher in patients who experienced Only one DMF patient and three fingolimod patients relapses during the follow-up (p < 0 05) (Table 4). experienced relapses in the last 6 months of follow-up. These To determine whether elevated percentages of patients did not show differences in the percentage of Th1Th17CM cells at baseline were associated with an Th1Th17CM at baseline (relapsed in the last 6 months of fol- increased risk to develop relapses, we analyzed the outcome low-up: 14 15 ± 2 02; p = 0 2482vs. relapsed in the first 6 of patients after 12-month follow-up. We defined ROC months of follow-up: 18 33 ± 1 78) and Th1CM (relapsed in curves that enabled us to identify values of Th1Th17CM per- the last 6 months of follow-up 12 16 ± 1 42vs. relapsed in centages in our cohort of patients, predicting the risk to the first 6 months of follow-up 11 01 ± 2 9; p = 0 70) com- undergo relapses. Baseline values of Th1Th17CM > 11 48% pared to patients who experienced relapses in the first 6 indicated an increased risk to develop relapse (sensibility of months starting the treatment. 75%, specificity of 62%, area under curve (AUC) of 0.74, The analysis of the percentage of CD4+ TCM in the fingo- p < 0 04). Then, the ability to predict relapse-free survival limod cohort showed a higher percentage in patients who of the potential biomarker was compared. Kaplan-Meier experienced relapses during the 12 months of treatment curves showed that patients with Th1Th17CM > 11 48% 6 Table 4: Differences in the percentage and absolute number of central memory T cell subpopulations at baseline according to the clinical outcome in dimethyl fumarate- or fingolimod- treated patients. Total cohort (n = 66) DMF (n = 22) Fingolimod (n = 44) Lymphocyte subpopulations MRI activity Relapses MRI activity Relapses MRI activity Relapses at baseline (no MRI activity, n = 40) (nonrelapsed, n = 45) (no MRI activity, n = 15) (nonrelapsed, n = 19) (no MRI activity, n = 25) (nonrelapsed, n = 25) p value p value p value p value p value p value CD4+ TCM (%) 0.147 0.154 0.057 0.561 0.609 0.034 Th1CM (%) 0.326 0.049 0.505 0.289 0.637 0.093 Th17CM (%) 0.878 0.06 0.502 0.557 0.477 0.345 Th1Th17CM (%) 0.006 0.002 0.09 0.842 0.062 0.040 CD4+ TCM (cel/μL) 0.515 0.048 0.057 0.980 0.998 0.020 Th1CM (cel/μL) 0.150 0.877 0.088 0.443 0.679 0.059 Th17CM (cel/μL) 0.156 0.746 0.440 0.391 0.235 0.134 Th1Th17CM (cel/μL) 0.168 0.190 0.192 0.540 0.512 0.052 DMF: dimethyl fumarate; CD4+ TCM: central memory CD4 T lymphocytes; Th1CM: Th1 central memory lymphocytes; Th17CM: Th17 central memory lymphocytes; Th1Th17CM: Th1Th17 central memory lymphocytes; MRI: magnetic resonance imaging. p values in bold indicate statistically significance. Mediators of Inflammation Mediators of Inflammation 7 Centeral memory Th1Th17 (Th1Th17CM) (%) The relapse process in nontreated MS patients is linked to the presence of CD4+ TCM and Th1Th17CM lymphocytes in 100 peripheral blood and CNS [5, 6, 21]. The Th1Th17 lympho- Percent relapse-free survival 80 cytes are characterized by an activated phenotype and higher migratory capacity to CNS. Actually, a recent study described 60 Th1Th17CM lymphocytes as key regulators in the onset of MS due to their predominance in the CD4+ T cell pool of 40 peripheral blood in early stages of disease [7]. Additionally, Sato et al. described an increase in Th1Th17 cells at the time 20 of the MS relapses in patients following fingolimod treatment [21]. Accordingly, our findings showed a significant higher 0 percentage of Th1CM and Th1Th17CM in peripheral blood 0 1 2 3 4 5 6 7 8 9 10 11 12 at baseline in patients who experienced relapses during the Months 12-month follow-up. In addition, we found a statistically significant association on the percentage of Th1Th17CM Figure 2: Relapse-free survival for patients within the first 12 lymphocytes with MRI activity. These results suggest an months after treatment. Groups were separated by percentage of important role of these cells in MS pathogenesis and support Th1Th17CM out of CD4+ T cells. Patients with less than 11.48% of the idea that they could be a potential predictive biomarker of Th1Th17CM (n = 26) and more than 11.48% (n = 27) (p < 0 01, disease activity. log-rank test). Most of the mechanisms of action of DMTs are addressed to reduce autoreactive and proinflammatory immune mech- (n = 27) showed a relapse-free survival of 50% compared anisms in MS and thus are used to reduce the number of to 88% for patients with Th1Th17CM < 11 48% (n = 26) relapses [12–15]. Although the immunological effect of these (p < 0 01, log-rank test) (Figure 2 and Figure S2). treatments reducing the number of lymphocytes in periph- eral blood is already detectable after the first month of treat- ment, in some patients, its efficacy is observed only after the 3.3. Th1Th17CM Lymphocytes as a Prognostic Factor for MRI third or sixth month of treatment [16–21, 26]. In this context, Activity. A total of 33% of patients had MRI activity at 12 the analysis of the percentage of Th1Th17CM and Th1CM months of follow-up under DMF or fingolimod treatment. lymphocytes at baseline from patients who experienced Almost all patients (n = 58) had a MRI available. The distri- relapses in the last 6 months of follow-up did not show bution of patients who presented MRI activity based on pre- differences compared to patients who experienced relapses vious treatments was 33% of naïve patients, 38% of IFN-β in the first 6 months starting treatment. More information patients, and 22% of NTZ. Fourteen patients under fingoli- at different time points is necessary to determine the rele- mod treatment and four patients treated with DMF showed vance of these biomarkers at the time of the relapse during MRI activity after 12-month follow-up. the treatment. Given that we previously observed a high percentage of An important issue to take into account is that the cur- Th1Th17CM cells in clinically active MS patients, we studied rently established washout periods for patients with previ- the association of MRI activity with this lymphocyte ous treatments could be insufficient to achieve a proper subpopulation. recovery of the normal immune profile. In fact, in contrast A higher percentage of Th1Th17CM cells was found in to other DMTs, patients that switched from NTZ showed patients with MRI activity (MRI activity: 14 02 ± 5 87%, higher CD4+ TCM percentages at baseline than naïve p < 0 01; no MRI activity: 9 82 ± 4 06%). No differences patients. However, those patients remained with the same were found either in the percentage of Th1CM, Th17CM, and ARR after fingolimod treatment, which has also been CD4+ TCM lymphocytes or in the absolute number of the observed by other authors [27]. For this reason, the per- lymphocyte subpopulations studied, including Th1Th17CM centage of CD4+ TCM cells would not constitute a useful lymphocytes (Table 4). biomarker in cases of patients previously treated with NTZ. Interestingly, the percentage of Th1Th17CM could 4. Discussion be used as a predictive biomarker in those patients, as the distribution of CD4+ Th1CM, Th17CM, and Th1Th17CM Patients with RRMS have a large number of treatment subsets at baseline was not affected by the effect of a previ- options available. There is a need to investigate objective ous NTZ treatment. and accessible biomarkers able to predict treatment response. Although our results showed a trend of higher percent- Predictive biomarkers of disease activity would help to ages of Th1Th17CM lymphocytes at baseline in DMF patients choose initial therapy, monitoring response to therapy and who develop at least one relapse during the first 12 months of detecting subclinical disease activity. The present study follow-up, our study presents an important limitation in the proposes that, regardless of the treatment, the increased number of DMF patients who had relapses. A large confirma- percentage of Th1Th17CM lymphocytes at baseline could be tory cohort will be necessary to validate these results. None- a predictive biomarker of relapses or MRI activity during theless, our study suggests that the analysis monitoring of the first 12 months of treatment. the Th1Th17CM subpopulation at baseline may be useful in 8 Mediators of Inflammation order to personalize therapeutic approaches and prevent References relapses in MS patients. [1] D. S. Reich, C. F. 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