- Email: [email protected]
Analysis of apoptosis-related genes in patients with clinically isolated syndrome and their association with conversion to multiple sclerosis
Journal of Neuroimmunology 280 (2015) 43–48
Contents lists available at ScienceDirect
Journal of Neuroimmunology journal homepage: www.elsevier.com/locate/jneuroim
Analysis of apoptosis-related genes in patients with clinically isolated syndrome and their association with conversion to multiple sclerosis Sanna Hagman a,⁎, Marcin Kolasa a, Pabitra Basnyat a, Mika Helminen b, Mika Kähönen c, Prasun Dastidar d, Terho Lehtimäki e, Irina Elovaara a,f a
Neuroimmunology Unit, Medical School, University of Tampere and Tampere University Hospital, Tampere, Finland Science Centre, Pirkanmaa Hospital District and School of Health Sciences, University of Tampere, Finland Department of Clinical Physiology, Tampere University Hospital and University of Tampere Medical School, Finland d Medical Imaging Centre, Department of Diagnostic Radiology, Tampere University Hospital, Tampere, Finland e Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine University of Tampere, Tampere, Finland f Department of Neurology, Tampere University Hospital, Tampere, Finland b c
a r t i c l e
i n f o
Article history: Received 23 October 2014 Received in revised form 16 February 2015 Accepted 23 February 2015 Available online xxxx Keywords: Multiple sclerosis Clinically isolated syndrome Apoptosis Biomarkers BCL-2
a b s t r a c t To analyse whether the expression of apoptotic transcripts is associated with the conversion from clinically isolated syndrome (CIS) to multiple sclerosis (MS). Eleven candidate transcripts belonging to the death receptor pathway, BCL-2, the inflammasome complex and NF-ΚB family were studied in the nonconverting and converting CIS patients during the four-year follow-up period. Conversion to MS was associated with marked variability in the expression of proapoptotic genes that were linked to TGF-B1 gene levels. The predominant expression of proapoptotic genes in patients with CIS suggests an increased potential to undergo apoptosis with the goal of terminating immune responses and regulating immune system homeostasis. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Multiple sclerosis (MS) is the most common neurological disease and is characterised by inflammation, demyelination and axonal loss leading to the development of brain atrophy and neurological disability. During the recent years, treatment options with different mechanisms of action enabling better control for MS have increased markedly (Bruck et al., 2013; Freedman, 2013). The identification of patients with clinically isolated syndrome (CIS) who are at high risk for developing MS is a prerequisite for the early initiation of such therapy. However, due to the heterogeneous genetic and immunopathogenic background of MS, therapeutic responses differ in the individual patient, and hence the selection of optimal treatment for patients is challenging. Due to these reasons, there is a high need for the identification of biomarkers with the potential to predict disease course/activity, identify different phenotypes of MS as well as monitor therapeutic responses. MS pathogenesis is mediated by activated autoreactive CD4 + T helper 1 (Th1) and Th17 cells, as well as other immune cells, such as CD8+, natural killer cells and B cells, which contribute to neural damage (Comabella and Khoury, 2012; Chanvillard et al., 2013). Multiple ⁎ Corresponding author at: University of Tampere, School of Medicine, Neuroimmunology Unit, Biokatu 10, Finn-Medi 3 building, 33014 Finland. E-mail address: sanna.hagman@uta.fi (S. Hagman).
http://dx.doi.org/10.1016/j.jneuroim.2015.02.006 0165-5728/© 2015 Elsevier B.V. All rights reserved.
cellular mechanisms have been noted in MS pathogenesis, such as the dysregulation of T-cell survival and apoptosis and the altered expression of apoptotic molecules in the mitochondria and the extrinsic pathway (Comi et al., 2012; Moreno et al., 2014). Apoptosis plays a conflicting role with the two opposite effects in MS (Reichardt and Luhder, 2012). On one hand it mediates the death of oligodendrocytes and neurons in the central nervous system (CNS), while on the other hand it also terminates immune responses and regulates immune system homeostasis by eliminating autoreactive immune cells. In fact, the molecular mechanisms of several immunomodulatory and immunosuppressive agents are partly mediated through the apoptotic pathways (Fox and Rhoades, 2012). Factors inducing the dysregulation of T cell survival and apoptosis need to be clarified because these molecules may represent novel biomarkers as well as therapeutic targets. The predominance of the antiapoptotic BCL-2 family members and inhibitor of apoptosis proteins (IAP) has been observed in mitogen-activated T lymphocytes from patients with clinically active MS (Sharief and Semra, 2001; Semra et al., 2002a, 2002b; Sharief et al., 2002, 2003; Mandel et al., 2012). Elevated serum levels of antiapoptotic sFas have been associated with worsening disability and the accumulation of hypointense lesions seen upon magnetic resonance imaging (Hagman et al., 2011). Recently, increased gene expression levels of the proapoptotic adaptor protein FADD were observed in RRMS (Reuss et al., 2014). All of these data indicate the involvement
44
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
of apoptotic processes in the pathogenesis of MS, but there are still no studies reporting on the use of apoptotic molecules as biomarkers for the disease. In the present study, our aim was to examine whether the apoptotic changes are already detectable after the first demyelination event and determine their potential to predict the conversion from CIS to MS. 2. Patients and methods 2.1. Study design Gene expression analyses from peripheral blood mononuclear cells (PBMCs) were conducted with two separate cohorts. First, the expressions of 96 apoptosis-related genes were analysed from the blood samples of 12 relapsing–remitting MS (RRMS) patients and seven healthy controls (Cohort 1). Thereafter, 11 transcripts, which appeared to be upregulated in patients with RRMS, were analysed in 11 converting and nine nonconverting clinically isolated syndrome (CIS) patients over the four-year follow-up (baseline, two years and four years after the baseline visit) and 11 healthy controls at the baseline (Cohort 2). 2.2. Subjects The study included 49 subjects: 12 untreated patients with RRMS, 19 patients with CIS and 18 healthy controls. CIS patients underwent neurological and magnetic resonance imaging (MRI) examination at baseline and two years and four years after baseline, while RRMS patients were studied only at the baseline. The diagnosis of MS was based on revised McDonald Criteria (McDonald et al., 2001; Polman et al., 2005) and all diagnoses were definite. CIS patients were defined as patients who had their first demyelinating event suggestive of MS (Miller et al., 2012). The clinical evaluation included the determination of expanded disability status scale (EDSS) score (Kurtzke, 1983) and disease activity as expressed by the number of relapses in the preceding two years. The control group consisted of 18 healthy subjects (Cohort 1 (n = 7): age 34.4 ± 11.4 years; 6 females, 1 male; Cohort 2 (n = 11): age 33.6 ± 11.0 years; 10 females, 1 male, mean ± SD). The study was approved by the Ethics Committee of Tampere University Hospital, and all subjects gave informed consent. Demographics of the RRMS and CIS groups are shown in Table 1. 2.3. MRI image segmentation and volumetric analysis All examinations were performed on a 1.5 Tesla MRI Unit (Siemens Avanto, Erlangen, Germany). The MRI protocol for this examination included a T1-weighted header followed by an axial T1-weighted magnetisation prepared rapid gradient echo (MP-RAGE), and a T2weighted turbo spin echo (TSE), fluid attenuation inversion recovery (FLAIR), magnetisation transfer contrasts (MTC), diffusion weighted imaging (DWI), and gadolinium-enhanced T1-weighted MP-RAGE sequences. In this study, T1-weighted MP-RAGE, FLAIR and T2-weighted TSE images were used for volumetric analysis. For MP-RAGE, the imaging parameters were as follows: repetition time (TR) = 1160 ms; echo time (TE) = 4.24 ms; inversion time (TI) = 600 ms; slice thickness = 0.9 mm; and in-plane resolution = 0.45 ∗ 0.45 mm. In FLAIR, the following parameters were used: TR = 8500 ms; TE = 100 ms; TI = 2500 ms; slice thickness = 5.0 mm; and in-plane resolution = 0.45 ∗ 0.45 mm. In TSE, the following imaging scheme was used: TR = 750 ms; TE = 115 ms; slice thickness = 3.0 mm; and in-plane resolution = 0.90 ∗ 0.90 mm. Volumetric segmentation of plaques in the brain was performed using semiautomatic Anatomatic™ software operating in a Windows environment, and the images were analysed blindly. RRMS patients underwent examination only at the baseline, but in the CIS group MRI examinations were performed at the baseline and at two and four years after the baseline visit followed by neurological examination on the same day.
2.4. Total RNA isolation from peripheral blood mononuclear cells PBMCs were separated in a Vacutainer CPT cell preparation tube (Becton Dickinson and Company, Franklin Lakes, NJ, USA) according to the manufacturer's protocol. Total RNA was isolated from stored cell lysate with a Qiagen RNeasy plus mini kit (QIAGEN GmbH, Hilden, Germany) according to the manufacturer's instructions. The total RNA was eluted with nuclease-free water, and samples were stored at −80 °C for further analyses. The concentration and purity of RNA was determined before cDNA synthesis using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA). 2.5. Quantitative real-time PCR of apoptosis-related genes in mononuclear cells Total RNA (1 μg) was reverse transcribed to cDNA using a High Capacity cDNA reverse transcription kit (Applied Biosystems, Foster City, CA, USA) with the standard protocol. Gene expression analyses were carried out with a TaqMan low-density array (LDA) (Applied Biosystems) using a 7900HT Real-time PCR system (Applied Biosystems). A human apoptosis array was used to determine the expression of 93 apoptosis-related genes and three housekeeping genes from the PBMCs of RRMS patients (Cohort 1). A custom Taqman array (format 23) was used to analyse selected apoptosis-related molecules (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25, IKBKE, NFKBID, CASP1, PYCARD) and cytokines (IL23A, IL12A, IL4, TGFB1, IL6, IL21, IL10, IFNG, IL17A) from CIS patients (Cohort 2). Arrays were loaded with 4 μl undiluted cDNA, 42 μl H2O, and 50 μl PCR Universal master mix and run according to the manufacturer's instructions. Samples were run in duplicate. The expression data were analysed with RQ manager software (Applied Biosystems) using the comparative Ct method (ΔΔCt). To normalise the results, the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used, and two healthy control samples were used as calibrators in the data analysis. 2.6. Statistical analyses Statistical analyses were performed using SPSS version 16.0 for Windows (SPSS Inc., Chicago, IL, USA) and R software (software environment for statistical computing and graphics, version 2.13.0, the R Table 1 Clinical characteristics in different groups. Characteristics
Agea Gender (M/F)b Age at onseta Time since first symptoms (years)a Duration of disease (years)a EDSS score at baselinea EDSS score increase over follow-upb Number of relapses, baselineb,c 0 1 or more Number of relapses over follow-upb 0 1 T1 (cm3)a FLAIR (cm3)a
Cohort 1
Cohort 2
RRMS n = 12
Converting n = 10
Nonconverting n=9
37 (30–45) 3/9 26 (24–30) 8.3 (2.2–14.4)
33 (29–36) 1/9 29 (25–34) 1.0 (0.7–4.1)
37 (31–43) 1/8 33 (28–42) 1.3 (0.8–1.7)
1.0 (0–6.5) 1.0 (0.8–2.0) –
– 0 (0–0) 3
– 0 (0–0) 0
4 8
4 6
1 8
– – 1.4 (0.8–2.1) 4.6 (2.5–7.8)
6 4 0.6 (0.2–1.3) 2.0 (0.8–7.1)
0 0 0.01 (0.0–0.2) 0.5 (0.0–0.8)
CIS clinically isolated syndrome; RRMS relapsing–remitting MS; EDSS expanded disability status scale; FLAIR fluid-attenuated inversion recovery. a Median (interquartile range). b Number of patients. c All relapses preceding two years.
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
Foundation for Statistical Computing). The Mann–Whitney U test was used to analyse the differences between the groups in the clinical parameters and volumes of T1 and FLAIR. The Wilcoxon signed-rank test was used to analyse differences in the longitudinal clinical and MRI data separately in both groups. In the gene expression analyses of the RRMS patients, the significance levels of the genes were calculated using the Mann–Whitney U test. The genes were considered to be expressed differentially if the pvalue was smaller than 0.05 and the fold-change in expression was lower than 0.6 or higher than 1.4. In the longitudinal cohort, linear mixed-effect models (with different molecules as the dependent variable) were fitted using the lme function in R software. The random intercept was used together with the independent random errors. The association between the expression of apoptosis-related genes and MRI parameters and the gene expression of cytokines was studied using Spearman's correlation analyses. Due to multiple testing, results were interpreted only at the group level and not limited to a single correlation. 3. Results 3.1. Four-year clinical and volumetric follow-up of CIS patients Over the four-year follow-up period, 10 out of 19 CIS patients fulfilled the McDonald diagnostic criteria for RRMS. The mean time from the appearance of first symptoms to diagnosis was 4.7 (range 1.5–8.8) years. After diagnosis, immunomodulatory therapy was initiated in three out of nine patients, while the rest of the patients were not willing to start medication due to inactive disease. The volumetric analysis of T1 and FLAIR lesions in the CIS groups was performed at baseline and two and four years after baseline (Table 2). The volumes of T1 and FLAIR lesions were higher in the converting patients compared to nonconverting patients at all-time points (p b 0.05, Mann–Whitney U test). Longitudinal analysis of the converting group revealed an increase in the volumes of T1 lesions from baseline up to four years (p b 0.01, Wilcoxon signed-rank test), while statistically significant changes were not detected in the nonconverting patients (p N 0.05). The volumes of FLAIR lesions fluctuated during the followup period; the highest levels were seen in the second year but thereafter the levels were in similar magnitude as those at baseline. 3.2. Aberrant expression of apoptosis- and inflammation-related genes in RRMS Expression analysis of apoptosis-related genes in RRMS patients and healthy controls revealed that 88 out of 93 transcripts were detectable in both MS patients and controls (Table 3). Half of these genes (41/88 transcripts) were differentially expressed in RRMS patients in comparison to healthy controls (p b 0.05), and 11 out of 44 transcripts showed a 1.4-fold or greater change in expression. These 11 transcripts belong to the BCL-2 family (BAD, BCLG, BIK, BOK, PUMA), the death receptor
45
pathway (FADD, TNFRSF25), the NF-κB family (IKBKE, NFKBID) and the inflammasome complex (CASP1, PYCARD). Because the balance between the expression of pro- and antiapoptotic genes of Bcl-2 family members determines the death or survival of the cells, the ratios between the cellular expression of proapoptotic genes (BID, BAD, BIK, BIM, NOXA, PUMA) and that of antiapoptotic (BCL2 and BCLXL) genes were calculated. In comparison to the controls, the following ratios were increased in RRMS patients: BAD/BCLXL, PUMA/BCLXL, BAD/BCL2, BIK/BCL2 and PUMA/BCL2, suggesting the increased potential for apoptosis in mononuclear cells (Fig. 1). 3.3. Predictive potential of apoptosis-related genes in CIS patients over the four-year follow-up period Eleven transcripts (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25, IKBKE, NFKBID, CASP1, PYCARD) that were significantly upregulated in RRMS patients were further studied in the CIS groups to elucidate the role of these transcripts in predicting conversion to RRMS. Comparisons between the CIS groups and controls showed no changes in the patients who progressed to RRMS, but higher gene expression levels of TNFRSF25, IKBKE and NFKBID were detected in the nonconverting CIS group (Table 3). Comparison between the converting and nonconverting CIS groups showed the downregulation of the TNFRSF25 gene in the converting patients. No changes were detected in the gene expression levels at the end of the study in any of the groups. The gene expression levels in the CIS groups at various time points were analysed with linear mixed-effect models. The longitudinal analysis of subjects with CIS showed marked intra- and inter-individual variabilities in the gene expression levels, even though none of the transcripts was associated with the conversion from CIS to MS (Supplementary Table 1). 3.4. Association of gene expression with the volumes of FLAIR and T1 lesions The baseline expression levels of apoptosis-related genes were associated with the volumes of T1 and FLAIR lesions over the follow-up period (Table 4). In converting patients, three genes (BAD, TNFRSF25, NFKBID) correlated positively with the volumes of FLAIR and T1 lesions. In the nonconverting group, two genes (NFKBID, TNFRSF25) correlated positively with the volumes of FLAIR lesions. 3.5. The expression of cytokines and their correlation to apoptosis-related genes To assess whether the expression of apoptosis-related genes is associated with peripheral immune activation, cytokine gene expression was analysed longitudinally (Supplementary Table 2) and correlated to the expression of apoptotic molecules. It appeared that all of the cytokines except IL17A and IL4 were detectable both in the CIS and control groups. Correlations between the baseline expression levels of
Table 2 The volumes of T1 and FLAIR lesions over the follow-up period in converting and nonconverting CIS patients. Converting
n T1 (cm3) FLAIR (cm3)
Nonconverting
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
10 0.6 (0.2–1.3)a 2.0 (0.8–7.1)b
9 0.7 (0.3–1.3)b⁎⁎ 3.6 (2.2–4.0)a⁎⁎,⁎⁎⁎
9 0.7 (0.3–1.3)b⁎⁎ 2.3 (0.7–2.5)b
9 0.01 (0.0–0.2)a 0.5 (0.0–0.8)b
9 0.04 (0.0–0.4)b 1.0 (0.2–1.2)a⁎⁎,⁎⁎⁎
6 0.05 (0.0–0.1)b 0.3 (0.08–0.70)b
BL baseline, yrs years; EDSS expanded disability status scale; FLAIR fluid-attenuated inversion recovery. a Comparison between converting and nonconverting CIS patients, the Mann–Whitney U test, p b 0.01. b Comparison between converting and nonconverting CIS patients, the Mann–Whitney U test, p b 0.05. ⁎⁎ Compared to baseline values, Wilcoxon test p b 0.01. ⁎ p b 0.05. ⁎⁎⁎ Compared to four-year values, Wilcoxon test, p b 0.05.
46
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
Table 3 Significantly upregulated genes in RRMS and CIS at baseline. Gene expression values in Cohort 1 a
Baseline gene expression values in Cohort 2a
Controls n=7
Fold changeb
Converting n = 10
Nonconverting n=9
Controls n = 11
BCL-2 family members BAD 1.20 (0.93–3.51) BCLG 1.66 (1.14–2.36) BIK 1.67 (1.20–2.03) BOK 2.03 (1.23–2.62) PUMA 1.14 (0.83–1.68)
0.84 (0.75–1.00)⁎ 1.00 (0.34–1.18)⁎⁎ 1.00 (0.93–1.58)⁎ 1.00 (0.89–1.44)⁎ 0.80 (0.52–1.00)⁎
1.4 1.7 1.7 2.0 1.4
2.08 (1.99–3.23) 1.63 (1.15–2.00) 1.61 (1.39–2.47) 0.77 (0.43–3.57) 4.82 (1.80–6.77)
2.7 (2.06–2.84) 1.57 (1.23–1.87) 2.47 (2.27–2.69) 0.92 (0.35–1.20) 3.59 (2.83–4.79)
2.73 (2.02–3.92) 1.36 (0.82–4.13) 1.98 (1.67–2.12) 1.12 (0.76–2.21) 3.19 (2.38–4.41)
Death receptor pathway FADD 1.13 (0.78–2.44) TNFRSF25 2.68 (1.88–3.79)
0.74 (0.45–1.00)⁎ 1.16 (1.00–1.49)⁎⁎
1.5 2.3
1.83 (0.59–2.36) 1.17 (0.69–2.09)⁎⁎⁎
1.32 (0.98–2.27) 2.37 (1.87–2.97)⁎⁎
1.40 (0.93–1.51) 1.14 (0.74–1.57)
Nuclear factor-kappa B family IKBKE 1.47 (1.12–1.72) NFKBID 1.74 (1.39–2.52)
1.00 (0.95–1.14)⁎ 1.00 (0.92–1.30)⁎⁎
1.5 1.7
1.55 (1.37–1.81) 1.38 (1.04–1.67)
1.67 (1.53–2.00)⁎ 1.67 (1.35–1.94)⁎
1.37 (1.15–1.52) 1.18 (0.91–1.48)
Inflammasome complex CASP1 1.10 (0.78–1.32) PYCARD 1.12 (0.93–2.08)
0.78 (0.65–1.00)⁎ 0.78 (0.65–1.00)⁎
1.4 1.4
1.48 (1.38–1.77) 1.90 (1.43–2.33)
1.43 (1.36–1.90) 1.65 (1.45–2.28)
1.68 (1.22–1.79) 1.87 (1.22–2.34)
RRMS n = 12
RRMS relapsing–remitting multiple sclerosis; CIS clinically isolated syndrome; BAD BCL2-associated agonist of cell death; BCLG BCL2-like 14 (apoptosis facilitator); BIK BCL2-interacting killer (apoptosis-inducing); BOK BCL2-related ovarian killer; PUMA BCL2 Binding Component 3; FADD Fas (TNFRSF6)-associated via death domain; TNFRSF25 tumour necrosis factor receptor superfamily, member 25; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta; CASP1 caspase 1, apoptosis-related cysteine peptidase; PYCARD PYD and CARD domain containing protein. a The expression values are medians (interquartile range). b Fold changes were calculated by comparing the median gene expression values between the patients and controls. ⁎ Compared to controls p b 0.05. ⁎⁎ Compared to controls p b 0.01. ⁎⁎⁎ Compared to nonconverting CIS patients p b 0.01.
apoptosis-related genes and cytokines were found in both CIS groups and the controls, but these correlations were more notable in the healthy controls (Table 5, Supplementary Table 3). Amongst the seven tested cytokines, IL23A and TGFB1 correlated more significantly with apoptosis-related genes. TGFB1 was correlated with the baseline gene expression of apoptotic molecules (BAD, BOK, PUMA, FADD, TNFRSF25, NFKBID, PYCARD) in the converting group, while IL23A correlated with the baseline gene expression of apoptotic molecules in the nonconverting group (BIK, TNFRSF25, IKBKE, NFKBID) and healthy controls (BAD, BOK, TNFRSF25, FADD, IKBKE). Correlation analyses amongst apoptosisrelated transcripts and cytokines showed that correlations were most notable in all groups except converting patients (Table 6A and B).
4. Discussion MS is a heterogeneous disease in which tissue injury is mediated by multiple immunological and neurobiological mediators, including
cytokines, antibodies, glutamate and reactive oxygen species (Ellwardt and Zipp, 2014). Dysregulation in the cell death mechanisms of T cells leading to prolonged activation of autoreactive T cells is also considered to play an important role in MS (Ellwardt and Zipp, 2014). Amongst the multiple apoptotic mechanisms, extrinsic and intrinsic pathways are the most well-known processes that induce immune cell death leading to decreased inflammation. The intrinsic pathway is mediated by interplay between pro- and antiapoptotic BCL-2 family members that regulate the permeabilization of the mitochondrial outer membrane, and the extrinsic pathway is initiated upon death receptor and ligand interactions at the cell surface that eventually activate the caspase cascade (Reichardt and Luhder, 2012). Some of the death receptors, such as tumour necrosis factor receptors 1 and 25, have dual roles and they transmit both death signals via caspase activation and a survival signal via the activation of nuclear factor-kappa B (NF-ΚB) transcription factor. The NF-ΚB pathway regulates the expression of several immunoregulatory factors, including cytokines, chemokines, adhesion molecules, cell cycle regulators and cell survival factors and therefore plays an
Fig. 1. The expression ratios of BCL-2 family genes in RRMS patients and healthy controls. Median (25th–75th percentiles). **p b 0.01, *p b 0.05.
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
47
Table 4 Correlation analyses of baseline expression levels of apoptosis-related genes to baseline volumes of T1 and FLAIR lesions over the follow-up period in converting and nonconverting CIS patients. Converting
Nonconverting
T1
BAD TNFRSF25 IKBKE NFKBID
FLAIR
T1
FLAIR
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
0.72⁎ 0.88⁎⁎ – 0.77⁎
– 0.83⁎ – 0.76⁎
– 0.81⁎ – 0.72⁎
0.80⁎ 0.83⁎⁎ – 0.81⁎⁎
0.76⁎ 0.88⁎⁎ – 0.81⁎
0.76⁎ 0.88⁎⁎ – 0.81⁎
– – – –
– – – –
– – 0.89⁎ –
– 0.67⁎ – 0.68⁎
– 0.67⁎ – –
– – 0.89⁎ –
BL baseline; yrs years; FLAIR fluid-attenuated inversion recovery; BAD BCL2-associated agonist of cell death; TNFRSF25 tumour necrosis factor receptor superfamily, member 25; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta. – not significant. Spearman's rank correlation test *p b 0.05; **p b 0.001.
important role in various biological processes (Oh and Ghosh, 2013). The NF-ΚB pathway is regulated via inhibitory kappa B (IΚB) proteins and IΚB kinases. Another activator of the NF-ΚB pathway is the proinflammatory cytokine interleukin (IL)-1B, which is activated and secreted from macrophages via an inflammasome-dependent mechanism. Several reports have suggested the involvement of inflammasomes in autoimmune diseases to maintain the ongoing inflammation (Inoue and Shinohara, 2013). In this study, we assessed whether apoptosis-related molecules are already detectable after the first demyelinating event suggestive of MS and evaluated whether their expression levels have predictive potential for the conversion from CIS to MS. Study design was based on the assumption that aberrantly expressed genes detected in RRMS patients but not in controls might indicate such predictive potential. Data showed that the gene expression profile in RRMS patients was characterised by the upregulation of proapoptotic genes (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25), inflammatory NF-ΚB family members (IKBKE, NFKBID) and inflammasome (CASP1, PYCARD) genes. Interestingly, IKBKE and NFKBID are novel NF-ΚB pathway regulators and their specific role, especially in MS, is poorly understood (Schuster et al., 2013). The involvement of the death receptor TNFRSF25 in MS has not yet been elucidated, but it is known to stimulate the NF-ΚB pathway via TRADD adaptor protein and regulate cell apoptosis via FADD adaptor protein in activated T cells (Meylan et al., 2011). Many other members of this tumour necrosis factor receptor superfamily have previously been associated with MS pathogenesis (Mc Guire et al., 2011). Half of the upregulated transcripts detected in this study were proapoptotic BCL-2 family members (BAD, BCLG, BIK, BOK, PUMA), indicating the predominance of intrinsic proapoptotic events in RRMS. This interpretation is further supported by the presence of increased expression ratios of pro- to antiapoptotic BCL-2 family members. Other authors have reported upregulated levels of antiapoptotic BCL-2 family members in active RRMS patients, indicating failure in the apoptotic pathways (Sharief et al., 2002, 2003; Achiron et al., 2007; Gurevich Table 5 Number of observed correlations between apoptosis-related genes (n = 11) and cytokines (n = 7) in different groups. Number of statistically significant correlations in different groups All samples Cytokines IFNG 2 IL6 1 IL10 1 IL12A 2 IL21 4 IL23A 6 TGFB1 1 Total 17
a
All CIS
Converting
Nonconverting
Controls
1 0 0 0 2 6 3 12
2 0 1 0 0 1 7 11
1 1 0 0 1 4 0 7
2 2 0 3 1 5 0 13
IFNG interferon-gamma; IL interleukin; TGFB1 transforming growth factor beta1. a Actual Spearman's rank correlation coefficients (r) can be found in Supplementary Table.
and Achiron, 2012; Mandel et al., 2012). The discrepancies between these studies are most likely explained by differences in the studied populations; in this study patients were relatively stable. In fact, Gurevitch and others have shown the involvement of different operating pathways during the stable and active phase of the disease (Gurevich and Achiron, 2012). They proposed that the stable phase of the disease is mediated by anti-inflammatory responses together with tight regulation of apoptosis mechanisms aiming to prevent harmful inflammatory responses, but during relapse antiapoptotic and proinflammatory responses prevail. Therefore, the upregulation of proapoptotic BCL-2 family genes found in our study may indicate that the regulatory effects of the immune system enhance apoptosis and thereby limit lymphocyte responses. The longitudinal analysis of CIS patients showed intra- and interindividual variability in the levels of BCL-2, NF-ΚB, inflammasome components and death receptor pathway transcripts consistent with peripheral immune activation already at the early stage of MS, although differences were not statistically significant. The variability in the expression of the apoptotic transcripts between the subjects is most likely Table 6 Number of observed correlations amongst apoptosis-related genes (A) and cytokines (B) in different groups. All samples
All CIS
Converting
Nonconverting
Controls
A. BAD BCLG BIK BOK PUMA FADD TNFRSF25 IKBKE NFKBID CASP1 PYCARD Total
7 3 3 1 6 6 6 4 7 5 4 52
3 0 1 0 4 4 2 1 4 0 3 22
4 2 0 2 5 2 3 1 3 0 2 24
0 0 5 1 6 5 3 3 3 3 3 32
6 0 0 2 5 4 5 6 3 1 2 34
B. IFNG IL6 IL10 IL12A IL21 IL23A TGFB1 Total
4 2 3 1 1 0 1 12
1 0 0 1 1 0 1 4
0 0 1 0 1 0 0 2
1 0 1 0 1 0 1 4
3 2 2 1 0 0 0 8
CIS clinically isolated syndrome; BAD BCL2-associated agonist of cell death; BCLG BCL2like 14 (apoptosis facilitator); BIK BCL2-interacting killer (apoptosis-inducing); BOK BCL2-related ovarian killer; PUMA BCL2 Binding Component 3; FADD Fas (TNFRSF6)-associated via death domain; TNFRSF25 tumour necrosis factor receptor superfamily. member 25; ; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta; CASP1 caspase 1, apoptosis-related cysteine peptidase PYCARD PYD and CARD domain containing protein; IFNG interferon-gamma; IL interleukin; TGFB1 transforming growth factor beta 1.
48
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
explained by the heterogeneous nature of the disease characterised by different immunological and structural patterns differing between the individual patients (Lassmann et al., 2001). Interestingly, the correlation analyses showed a positive correlation between the apoptotic transcripts BAD, NFKBID and TNFRSF25 and increased volumes of FLAIR and T1 lesions in converting patients indicating increased potential for apoptosis in such patients with more active disease. In spite of variation in the expression of apoptotic molecules and their association with the volumes of FLAIR and T1 lesions, the observed differences were not associated with the conversion to MS. At the baseline, three genes (IKBKE, NFKBID, TNFRSF25) were increased in nonconverting patients indicating the presence of peripheral immune activation in this subtype. Because the data showed marked intra- and inter-individual variability in the levels of apoptosis-related transcripts, we performed correlation analyses between the proapoptotic transcripts and pro-and anti-inflammatory cytokine transcripts to assess whether the apoptosis-related gene expression levels are associated with peripheral immune activation. It appeared that correlations were more notable in nonconverting CIS patients and controls, while correlations were most predominant between TGFB1 and apoptotic molecules in converting CIS patients. TGFB1 has a critical role in controlling the differentiation of pathogenic Th17 cells in the presence of IL-23 and IL-6, but it also plays a key role in the differentiation and function of regulatory T cells (Oh and Li, 2013). The increased expression of proapoptotic genes found in our study is related to peripheral immune activation aimed at terminating the immune response in order to maintain immune system homeostasis. These observations also suggest the involvement of different operating pathways in converting and nonconverting CIS patients, which may partially explain the accumulation of neuroinflammation in converting patients. In summary, the variability of the apoptotic transcripts in the early MS patients with clinically silent disease reflects peripheral immune activation, which seems to play a role in MS. Because only a limited number of patients were included in this exploratory study, these observations need to be confirmed in larger number of patients with a longer follow-up period in order to find biomarkers for identifying patients who are at high risk for developing MS. Acknowledgements We would like to thank Raija Caliskan for the excellent technical assistance. This study was financially supported by the Competitive State Research Financing of the Expert Responsibility Area of Tampere University Hospital (9P010), Finnish Cultural Foundation, Pirkanmaa Regional Fund (50131294, 50141553), and Eemil Aaltonen Foundation. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jneuroim.2015.02.006. References Achiron, A., Feldman, A., Mandel, M., Gurevich, M., 2007. Impaired expression of peripheral blood apoptotic-related gene transcripts in acute multiple sclerosis relapse. Ann. N. Y. Acad. Sci. 1107, 155–167.
Bruck, W., Gold, R., Lund, B.T., Oreja-Guevara, C., Prat, A., Spencer, C.M., et al., 2013. Therapeutic decisions in multiple sclerosis: moving beyond efficacy. JAMA Neurol. 70 (10), 1315–1324. Chanvillard, C., Jacolik, R.F., Infante-Duarte, C., Nayak, R.C., 2013. The role of natural killer cells in multiple sclerosis and their therapeutic implications. Front. Immunol. 4, 63. Comabella, M., Khoury, S.J., 2012. Immunopathogenesis of multiple sclerosis. Clin. Immunol. 142 (1), 2–8. Comi, C., Fleetwood, T., Dianzani, U., 2012. The role of T cell apoptosis in nervous system autoimmunity. Autoimmun. Rev. 12 (2), 150–156. Ellwardt, E., Zipp, F., 2014. Molecular mechanisms linking neuroinflammation and neurodegeneration in MS. Exp. Neurol.; 262 Pt A: 8-17. Fox, E.J., Rhoades, R.W., 2012. New treatments and treatment goals for patients with relapsing–remitting multiple sclerosis. Curr. Opin. Neurol. (25 Suppl.), S11–S19. Freedman, M.S., 2013. Present and emerging therapies for multiple sclerosis. Continuum (Minneap Minn). Mult. Scler. 19 (4), 968–991. Gurevich, M., Achiron, A., 2012. The switch between relapse and remission in multiple sclerosis: continuous inflammatory response balanced by Th1 suppression and neurotrophic factors. J. Neuroimmunol. 252 (1–2), 83–88. Hagman, S., Raunio, M., Rossi, M., Dastidar, P., Elovaara, I., 2011. Disease-associated inflammatory biomarker profiles in blood in different subtypes of multiple sclerosis: prospective clinical and MRI follow-up study. J. Neuroimmunol. 234 (1–2), 141–147. Inoue, M., Shinohara, M.L., 2013. NLRP3 Inflammasome and MS/EAE. Autoimmune Dis. 2013, 859145. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33 (11), 1444–1452. Lassmann, H., Bruck, W., Lucchinetti, C., 2001. Heterogeneity of multiple sclerosis pathogenesis: implications for diagnosis and therapy. Trends Mol. Med. 7 (3), 115–121. Mandel, I., Paperna, T., Miller, A., 2012. Aberrant expression of the apoptosis-related proteins BAK and MCL1 in T cells in multiple sclerosis. J. Neuroimmunol. 244 (1–2), 51–56. Mc Guire, C., Beyaert, R., van Loo, G., 2011. Death receptor signalling in central nervous system inflammation and demyelination. Trends Neurosci. 34 (12), 619–628. McDonald, W.I., Compston, A., Edan, G., Goodkin, D., Hartung, H.P., Lublin, F.D., et al., 2001. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50 (1), 121–127. Meylan, F., Richard, A.C., Siegel, R.M., 2011. TL1A and DR3, a TNF family ligand-receptor pair that promotes lymphocyte costimulation, mucosal hyperplasia, and autoimmune inflammation. Immunol. Rev. 244 (1), 188–196. Miller, D.H., Chard, D.T., Ciccarelli, O., 2012. Clinically isolated syndromes. Lancet Neurol. 11 (2), 157–169. Moreno, M., Negrotto, L., Río, J., Moubarak, R., Martín, I., Bustamante, M.F., et al., 2014. Activation-induced cell death in T lymphocytes from multiple sclerosis patients. J. Neuroimmunol. 272 (1–2), 51–55. Oh, H., Ghosh, S., 2013. NF-kappaB: roles and regulation in different CD4(+) T-cell subsets. Immunol. Rev. 252 (1), 41–51. Oh, S.A., Li, M.O., 2013. TGF-beta: guardian of T cell function. J. Immunol. 191 (8), 3973–3979. Polman, C.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.P., Kappos, L., et al., 2005. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald criteria”. Ann. Neurol. 58 (6), 840–846. Reichardt, H.M., Luhder, F., 2012. The ambivalent role of apoptosis in experimental autoimmune encephalomyelitis and multiple sclerosis. Curr. Pharm. Des. 18 (29), 4453–4464. Reuss, R., Mistarz, M., Mirau, A., Kraus, J., Bodeker, R.H., Oschmann, P., 2014. FADD is upregulated in relapsing remitting multiple sclerosis. Neuroimmunomodulation 21 (5), 221–225. Schuster, M., Annemann, M., Plaza-Sirvent, C., Schmitz, I., 2013. Atypical IkappaB proteins — nuclear modulators of NF-kappaB signaling. Cell Commun. Signal. 11 (1), 23 (–811X-11–23). Semra, Y.K., Seidi, O.A., Sharief, M.K., 2002a. Disease activity in multiple sclerosis correlates with T lymphocyte expression of the inhibitor of apoptosis proteins. J. Neuroimmunol. 122 (1–2), 159–166. Semra, Y.K., Seidi, O.A., Sharief, M.K., 2002b. Heightened intrathecal release of axonal cytoskeletal proteins in multiple sclerosis is associated with progressive disease and clinical disability. J. Neuroimmunol. 122 (1–2), 132–139. Sharief, M.K., Semra, Y.K., 2001. Heightened expression of survivin in activated T lymphocytes from patients with multiple sclerosis. J. Neuroimmunol. 119 (2), 358–364. Sharief, M.K., Douglas, M., Noori, M., Semra, Y.K., 2002. The expression of pro- and antiapoptosis Bcl-2 family proteins in lymphocytes from patients with multiple sclerosis. J. Neuroimmunol. 125 (1–2), 155–162. Sharief, M.K., Matthews, H., Noori, M.A., 2003. Expression ratios of the Bcl-2 family proteins and disease activity in multiple sclerosis. J. Neuroimmunol. 134 (1–2), 158–165.
Contents lists available at ScienceDirect
Journal of Neuroimmunology journal homepage: www.elsevier.com/locate/jneuroim
Analysis of apoptosis-related genes in patients with clinically isolated syndrome and their association with conversion to multiple sclerosis Sanna Hagman a,⁎, Marcin Kolasa a, Pabitra Basnyat a, Mika Helminen b, Mika Kähönen c, Prasun Dastidar d, Terho Lehtimäki e, Irina Elovaara a,f a
Neuroimmunology Unit, Medical School, University of Tampere and Tampere University Hospital, Tampere, Finland Science Centre, Pirkanmaa Hospital District and School of Health Sciences, University of Tampere, Finland Department of Clinical Physiology, Tampere University Hospital and University of Tampere Medical School, Finland d Medical Imaging Centre, Department of Diagnostic Radiology, Tampere University Hospital, Tampere, Finland e Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine University of Tampere, Tampere, Finland f Department of Neurology, Tampere University Hospital, Tampere, Finland b c
a r t i c l e
i n f o
Article history: Received 23 October 2014 Received in revised form 16 February 2015 Accepted 23 February 2015 Available online xxxx Keywords: Multiple sclerosis Clinically isolated syndrome Apoptosis Biomarkers BCL-2
a b s t r a c t To analyse whether the expression of apoptotic transcripts is associated with the conversion from clinically isolated syndrome (CIS) to multiple sclerosis (MS). Eleven candidate transcripts belonging to the death receptor pathway, BCL-2, the inflammasome complex and NF-ΚB family were studied in the nonconverting and converting CIS patients during the four-year follow-up period. Conversion to MS was associated with marked variability in the expression of proapoptotic genes that were linked to TGF-B1 gene levels. The predominant expression of proapoptotic genes in patients with CIS suggests an increased potential to undergo apoptosis with the goal of terminating immune responses and regulating immune system homeostasis. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Multiple sclerosis (MS) is the most common neurological disease and is characterised by inflammation, demyelination and axonal loss leading to the development of brain atrophy and neurological disability. During the recent years, treatment options with different mechanisms of action enabling better control for MS have increased markedly (Bruck et al., 2013; Freedman, 2013). The identification of patients with clinically isolated syndrome (CIS) who are at high risk for developing MS is a prerequisite for the early initiation of such therapy. However, due to the heterogeneous genetic and immunopathogenic background of MS, therapeutic responses differ in the individual patient, and hence the selection of optimal treatment for patients is challenging. Due to these reasons, there is a high need for the identification of biomarkers with the potential to predict disease course/activity, identify different phenotypes of MS as well as monitor therapeutic responses. MS pathogenesis is mediated by activated autoreactive CD4 + T helper 1 (Th1) and Th17 cells, as well as other immune cells, such as CD8+, natural killer cells and B cells, which contribute to neural damage (Comabella and Khoury, 2012; Chanvillard et al., 2013). Multiple ⁎ Corresponding author at: University of Tampere, School of Medicine, Neuroimmunology Unit, Biokatu 10, Finn-Medi 3 building, 33014 Finland. E-mail address: sanna.hagman@uta.fi (S. Hagman).
http://dx.doi.org/10.1016/j.jneuroim.2015.02.006 0165-5728/© 2015 Elsevier B.V. All rights reserved.
cellular mechanisms have been noted in MS pathogenesis, such as the dysregulation of T-cell survival and apoptosis and the altered expression of apoptotic molecules in the mitochondria and the extrinsic pathway (Comi et al., 2012; Moreno et al., 2014). Apoptosis plays a conflicting role with the two opposite effects in MS (Reichardt and Luhder, 2012). On one hand it mediates the death of oligodendrocytes and neurons in the central nervous system (CNS), while on the other hand it also terminates immune responses and regulates immune system homeostasis by eliminating autoreactive immune cells. In fact, the molecular mechanisms of several immunomodulatory and immunosuppressive agents are partly mediated through the apoptotic pathways (Fox and Rhoades, 2012). Factors inducing the dysregulation of T cell survival and apoptosis need to be clarified because these molecules may represent novel biomarkers as well as therapeutic targets. The predominance of the antiapoptotic BCL-2 family members and inhibitor of apoptosis proteins (IAP) has been observed in mitogen-activated T lymphocytes from patients with clinically active MS (Sharief and Semra, 2001; Semra et al., 2002a, 2002b; Sharief et al., 2002, 2003; Mandel et al., 2012). Elevated serum levels of antiapoptotic sFas have been associated with worsening disability and the accumulation of hypointense lesions seen upon magnetic resonance imaging (Hagman et al., 2011). Recently, increased gene expression levels of the proapoptotic adaptor protein FADD were observed in RRMS (Reuss et al., 2014). All of these data indicate the involvement
44
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
of apoptotic processes in the pathogenesis of MS, but there are still no studies reporting on the use of apoptotic molecules as biomarkers for the disease. In the present study, our aim was to examine whether the apoptotic changes are already detectable after the first demyelination event and determine their potential to predict the conversion from CIS to MS. 2. Patients and methods 2.1. Study design Gene expression analyses from peripheral blood mononuclear cells (PBMCs) were conducted with two separate cohorts. First, the expressions of 96 apoptosis-related genes were analysed from the blood samples of 12 relapsing–remitting MS (RRMS) patients and seven healthy controls (Cohort 1). Thereafter, 11 transcripts, which appeared to be upregulated in patients with RRMS, were analysed in 11 converting and nine nonconverting clinically isolated syndrome (CIS) patients over the four-year follow-up (baseline, two years and four years after the baseline visit) and 11 healthy controls at the baseline (Cohort 2). 2.2. Subjects The study included 49 subjects: 12 untreated patients with RRMS, 19 patients with CIS and 18 healthy controls. CIS patients underwent neurological and magnetic resonance imaging (MRI) examination at baseline and two years and four years after baseline, while RRMS patients were studied only at the baseline. The diagnosis of MS was based on revised McDonald Criteria (McDonald et al., 2001; Polman et al., 2005) and all diagnoses were definite. CIS patients were defined as patients who had their first demyelinating event suggestive of MS (Miller et al., 2012). The clinical evaluation included the determination of expanded disability status scale (EDSS) score (Kurtzke, 1983) and disease activity as expressed by the number of relapses in the preceding two years. The control group consisted of 18 healthy subjects (Cohort 1 (n = 7): age 34.4 ± 11.4 years; 6 females, 1 male; Cohort 2 (n = 11): age 33.6 ± 11.0 years; 10 females, 1 male, mean ± SD). The study was approved by the Ethics Committee of Tampere University Hospital, and all subjects gave informed consent. Demographics of the RRMS and CIS groups are shown in Table 1. 2.3. MRI image segmentation and volumetric analysis All examinations were performed on a 1.5 Tesla MRI Unit (Siemens Avanto, Erlangen, Germany). The MRI protocol for this examination included a T1-weighted header followed by an axial T1-weighted magnetisation prepared rapid gradient echo (MP-RAGE), and a T2weighted turbo spin echo (TSE), fluid attenuation inversion recovery (FLAIR), magnetisation transfer contrasts (MTC), diffusion weighted imaging (DWI), and gadolinium-enhanced T1-weighted MP-RAGE sequences. In this study, T1-weighted MP-RAGE, FLAIR and T2-weighted TSE images were used for volumetric analysis. For MP-RAGE, the imaging parameters were as follows: repetition time (TR) = 1160 ms; echo time (TE) = 4.24 ms; inversion time (TI) = 600 ms; slice thickness = 0.9 mm; and in-plane resolution = 0.45 ∗ 0.45 mm. In FLAIR, the following parameters were used: TR = 8500 ms; TE = 100 ms; TI = 2500 ms; slice thickness = 5.0 mm; and in-plane resolution = 0.45 ∗ 0.45 mm. In TSE, the following imaging scheme was used: TR = 750 ms; TE = 115 ms; slice thickness = 3.0 mm; and in-plane resolution = 0.90 ∗ 0.90 mm. Volumetric segmentation of plaques in the brain was performed using semiautomatic Anatomatic™ software operating in a Windows environment, and the images were analysed blindly. RRMS patients underwent examination only at the baseline, but in the CIS group MRI examinations were performed at the baseline and at two and four years after the baseline visit followed by neurological examination on the same day.
2.4. Total RNA isolation from peripheral blood mononuclear cells PBMCs were separated in a Vacutainer CPT cell preparation tube (Becton Dickinson and Company, Franklin Lakes, NJ, USA) according to the manufacturer's protocol. Total RNA was isolated from stored cell lysate with a Qiagen RNeasy plus mini kit (QIAGEN GmbH, Hilden, Germany) according to the manufacturer's instructions. The total RNA was eluted with nuclease-free water, and samples were stored at −80 °C for further analyses. The concentration and purity of RNA was determined before cDNA synthesis using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA). 2.5. Quantitative real-time PCR of apoptosis-related genes in mononuclear cells Total RNA (1 μg) was reverse transcribed to cDNA using a High Capacity cDNA reverse transcription kit (Applied Biosystems, Foster City, CA, USA) with the standard protocol. Gene expression analyses were carried out with a TaqMan low-density array (LDA) (Applied Biosystems) using a 7900HT Real-time PCR system (Applied Biosystems). A human apoptosis array was used to determine the expression of 93 apoptosis-related genes and three housekeeping genes from the PBMCs of RRMS patients (Cohort 1). A custom Taqman array (format 23) was used to analyse selected apoptosis-related molecules (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25, IKBKE, NFKBID, CASP1, PYCARD) and cytokines (IL23A, IL12A, IL4, TGFB1, IL6, IL21, IL10, IFNG, IL17A) from CIS patients (Cohort 2). Arrays were loaded with 4 μl undiluted cDNA, 42 μl H2O, and 50 μl PCR Universal master mix and run according to the manufacturer's instructions. Samples were run in duplicate. The expression data were analysed with RQ manager software (Applied Biosystems) using the comparative Ct method (ΔΔCt). To normalise the results, the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used, and two healthy control samples were used as calibrators in the data analysis. 2.6. Statistical analyses Statistical analyses were performed using SPSS version 16.0 for Windows (SPSS Inc., Chicago, IL, USA) and R software (software environment for statistical computing and graphics, version 2.13.0, the R Table 1 Clinical characteristics in different groups. Characteristics
Agea Gender (M/F)b Age at onseta Time since first symptoms (years)a Duration of disease (years)a EDSS score at baselinea EDSS score increase over follow-upb Number of relapses, baselineb,c 0 1 or more Number of relapses over follow-upb 0 1 T1 (cm3)a FLAIR (cm3)a
Cohort 1
Cohort 2
RRMS n = 12
Converting n = 10
Nonconverting n=9
37 (30–45) 3/9 26 (24–30) 8.3 (2.2–14.4)
33 (29–36) 1/9 29 (25–34) 1.0 (0.7–4.1)
37 (31–43) 1/8 33 (28–42) 1.3 (0.8–1.7)
1.0 (0–6.5) 1.0 (0.8–2.0) –
– 0 (0–0) 3
– 0 (0–0) 0
4 8
4 6
1 8
– – 1.4 (0.8–2.1) 4.6 (2.5–7.8)
6 4 0.6 (0.2–1.3) 2.0 (0.8–7.1)
0 0 0.01 (0.0–0.2) 0.5 (0.0–0.8)
CIS clinically isolated syndrome; RRMS relapsing–remitting MS; EDSS expanded disability status scale; FLAIR fluid-attenuated inversion recovery. a Median (interquartile range). b Number of patients. c All relapses preceding two years.
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
Foundation for Statistical Computing). The Mann–Whitney U test was used to analyse the differences between the groups in the clinical parameters and volumes of T1 and FLAIR. The Wilcoxon signed-rank test was used to analyse differences in the longitudinal clinical and MRI data separately in both groups. In the gene expression analyses of the RRMS patients, the significance levels of the genes were calculated using the Mann–Whitney U test. The genes were considered to be expressed differentially if the pvalue was smaller than 0.05 and the fold-change in expression was lower than 0.6 or higher than 1.4. In the longitudinal cohort, linear mixed-effect models (with different molecules as the dependent variable) were fitted using the lme function in R software. The random intercept was used together with the independent random errors. The association between the expression of apoptosis-related genes and MRI parameters and the gene expression of cytokines was studied using Spearman's correlation analyses. Due to multiple testing, results were interpreted only at the group level and not limited to a single correlation. 3. Results 3.1. Four-year clinical and volumetric follow-up of CIS patients Over the four-year follow-up period, 10 out of 19 CIS patients fulfilled the McDonald diagnostic criteria for RRMS. The mean time from the appearance of first symptoms to diagnosis was 4.7 (range 1.5–8.8) years. After diagnosis, immunomodulatory therapy was initiated in three out of nine patients, while the rest of the patients were not willing to start medication due to inactive disease. The volumetric analysis of T1 and FLAIR lesions in the CIS groups was performed at baseline and two and four years after baseline (Table 2). The volumes of T1 and FLAIR lesions were higher in the converting patients compared to nonconverting patients at all-time points (p b 0.05, Mann–Whitney U test). Longitudinal analysis of the converting group revealed an increase in the volumes of T1 lesions from baseline up to four years (p b 0.01, Wilcoxon signed-rank test), while statistically significant changes were not detected in the nonconverting patients (p N 0.05). The volumes of FLAIR lesions fluctuated during the followup period; the highest levels were seen in the second year but thereafter the levels were in similar magnitude as those at baseline. 3.2. Aberrant expression of apoptosis- and inflammation-related genes in RRMS Expression analysis of apoptosis-related genes in RRMS patients and healthy controls revealed that 88 out of 93 transcripts were detectable in both MS patients and controls (Table 3). Half of these genes (41/88 transcripts) were differentially expressed in RRMS patients in comparison to healthy controls (p b 0.05), and 11 out of 44 transcripts showed a 1.4-fold or greater change in expression. These 11 transcripts belong to the BCL-2 family (BAD, BCLG, BIK, BOK, PUMA), the death receptor
45
pathway (FADD, TNFRSF25), the NF-κB family (IKBKE, NFKBID) and the inflammasome complex (CASP1, PYCARD). Because the balance between the expression of pro- and antiapoptotic genes of Bcl-2 family members determines the death or survival of the cells, the ratios between the cellular expression of proapoptotic genes (BID, BAD, BIK, BIM, NOXA, PUMA) and that of antiapoptotic (BCL2 and BCLXL) genes were calculated. In comparison to the controls, the following ratios were increased in RRMS patients: BAD/BCLXL, PUMA/BCLXL, BAD/BCL2, BIK/BCL2 and PUMA/BCL2, suggesting the increased potential for apoptosis in mononuclear cells (Fig. 1). 3.3. Predictive potential of apoptosis-related genes in CIS patients over the four-year follow-up period Eleven transcripts (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25, IKBKE, NFKBID, CASP1, PYCARD) that were significantly upregulated in RRMS patients were further studied in the CIS groups to elucidate the role of these transcripts in predicting conversion to RRMS. Comparisons between the CIS groups and controls showed no changes in the patients who progressed to RRMS, but higher gene expression levels of TNFRSF25, IKBKE and NFKBID were detected in the nonconverting CIS group (Table 3). Comparison between the converting and nonconverting CIS groups showed the downregulation of the TNFRSF25 gene in the converting patients. No changes were detected in the gene expression levels at the end of the study in any of the groups. The gene expression levels in the CIS groups at various time points were analysed with linear mixed-effect models. The longitudinal analysis of subjects with CIS showed marked intra- and inter-individual variabilities in the gene expression levels, even though none of the transcripts was associated with the conversion from CIS to MS (Supplementary Table 1). 3.4. Association of gene expression with the volumes of FLAIR and T1 lesions The baseline expression levels of apoptosis-related genes were associated with the volumes of T1 and FLAIR lesions over the follow-up period (Table 4). In converting patients, three genes (BAD, TNFRSF25, NFKBID) correlated positively with the volumes of FLAIR and T1 lesions. In the nonconverting group, two genes (NFKBID, TNFRSF25) correlated positively with the volumes of FLAIR lesions. 3.5. The expression of cytokines and their correlation to apoptosis-related genes To assess whether the expression of apoptosis-related genes is associated with peripheral immune activation, cytokine gene expression was analysed longitudinally (Supplementary Table 2) and correlated to the expression of apoptotic molecules. It appeared that all of the cytokines except IL17A and IL4 were detectable both in the CIS and control groups. Correlations between the baseline expression levels of
Table 2 The volumes of T1 and FLAIR lesions over the follow-up period in converting and nonconverting CIS patients. Converting
n T1 (cm3) FLAIR (cm3)
Nonconverting
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
10 0.6 (0.2–1.3)a 2.0 (0.8–7.1)b
9 0.7 (0.3–1.3)b⁎⁎ 3.6 (2.2–4.0)a⁎⁎,⁎⁎⁎
9 0.7 (0.3–1.3)b⁎⁎ 2.3 (0.7–2.5)b
9 0.01 (0.0–0.2)a 0.5 (0.0–0.8)b
9 0.04 (0.0–0.4)b 1.0 (0.2–1.2)a⁎⁎,⁎⁎⁎
6 0.05 (0.0–0.1)b 0.3 (0.08–0.70)b
BL baseline, yrs years; EDSS expanded disability status scale; FLAIR fluid-attenuated inversion recovery. a Comparison between converting and nonconverting CIS patients, the Mann–Whitney U test, p b 0.01. b Comparison between converting and nonconverting CIS patients, the Mann–Whitney U test, p b 0.05. ⁎⁎ Compared to baseline values, Wilcoxon test p b 0.01. ⁎ p b 0.05. ⁎⁎⁎ Compared to four-year values, Wilcoxon test, p b 0.05.
46
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
Table 3 Significantly upregulated genes in RRMS and CIS at baseline. Gene expression values in Cohort 1 a
Baseline gene expression values in Cohort 2a
Controls n=7
Fold changeb
Converting n = 10
Nonconverting n=9
Controls n = 11
BCL-2 family members BAD 1.20 (0.93–3.51) BCLG 1.66 (1.14–2.36) BIK 1.67 (1.20–2.03) BOK 2.03 (1.23–2.62) PUMA 1.14 (0.83–1.68)
0.84 (0.75–1.00)⁎ 1.00 (0.34–1.18)⁎⁎ 1.00 (0.93–1.58)⁎ 1.00 (0.89–1.44)⁎ 0.80 (0.52–1.00)⁎
1.4 1.7 1.7 2.0 1.4
2.08 (1.99–3.23) 1.63 (1.15–2.00) 1.61 (1.39–2.47) 0.77 (0.43–3.57) 4.82 (1.80–6.77)
2.7 (2.06–2.84) 1.57 (1.23–1.87) 2.47 (2.27–2.69) 0.92 (0.35–1.20) 3.59 (2.83–4.79)
2.73 (2.02–3.92) 1.36 (0.82–4.13) 1.98 (1.67–2.12) 1.12 (0.76–2.21) 3.19 (2.38–4.41)
Death receptor pathway FADD 1.13 (0.78–2.44) TNFRSF25 2.68 (1.88–3.79)
0.74 (0.45–1.00)⁎ 1.16 (1.00–1.49)⁎⁎
1.5 2.3
1.83 (0.59–2.36) 1.17 (0.69–2.09)⁎⁎⁎
1.32 (0.98–2.27) 2.37 (1.87–2.97)⁎⁎
1.40 (0.93–1.51) 1.14 (0.74–1.57)
Nuclear factor-kappa B family IKBKE 1.47 (1.12–1.72) NFKBID 1.74 (1.39–2.52)
1.00 (0.95–1.14)⁎ 1.00 (0.92–1.30)⁎⁎
1.5 1.7
1.55 (1.37–1.81) 1.38 (1.04–1.67)
1.67 (1.53–2.00)⁎ 1.67 (1.35–1.94)⁎
1.37 (1.15–1.52) 1.18 (0.91–1.48)
Inflammasome complex CASP1 1.10 (0.78–1.32) PYCARD 1.12 (0.93–2.08)
0.78 (0.65–1.00)⁎ 0.78 (0.65–1.00)⁎
1.4 1.4
1.48 (1.38–1.77) 1.90 (1.43–2.33)
1.43 (1.36–1.90) 1.65 (1.45–2.28)
1.68 (1.22–1.79) 1.87 (1.22–2.34)
RRMS n = 12
RRMS relapsing–remitting multiple sclerosis; CIS clinically isolated syndrome; BAD BCL2-associated agonist of cell death; BCLG BCL2-like 14 (apoptosis facilitator); BIK BCL2-interacting killer (apoptosis-inducing); BOK BCL2-related ovarian killer; PUMA BCL2 Binding Component 3; FADD Fas (TNFRSF6)-associated via death domain; TNFRSF25 tumour necrosis factor receptor superfamily, member 25; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta; CASP1 caspase 1, apoptosis-related cysteine peptidase; PYCARD PYD and CARD domain containing protein. a The expression values are medians (interquartile range). b Fold changes were calculated by comparing the median gene expression values between the patients and controls. ⁎ Compared to controls p b 0.05. ⁎⁎ Compared to controls p b 0.01. ⁎⁎⁎ Compared to nonconverting CIS patients p b 0.01.
apoptosis-related genes and cytokines were found in both CIS groups and the controls, but these correlations were more notable in the healthy controls (Table 5, Supplementary Table 3). Amongst the seven tested cytokines, IL23A and TGFB1 correlated more significantly with apoptosis-related genes. TGFB1 was correlated with the baseline gene expression of apoptotic molecules (BAD, BOK, PUMA, FADD, TNFRSF25, NFKBID, PYCARD) in the converting group, while IL23A correlated with the baseline gene expression of apoptotic molecules in the nonconverting group (BIK, TNFRSF25, IKBKE, NFKBID) and healthy controls (BAD, BOK, TNFRSF25, FADD, IKBKE). Correlation analyses amongst apoptosisrelated transcripts and cytokines showed that correlations were most notable in all groups except converting patients (Table 6A and B).
4. Discussion MS is a heterogeneous disease in which tissue injury is mediated by multiple immunological and neurobiological mediators, including
cytokines, antibodies, glutamate and reactive oxygen species (Ellwardt and Zipp, 2014). Dysregulation in the cell death mechanisms of T cells leading to prolonged activation of autoreactive T cells is also considered to play an important role in MS (Ellwardt and Zipp, 2014). Amongst the multiple apoptotic mechanisms, extrinsic and intrinsic pathways are the most well-known processes that induce immune cell death leading to decreased inflammation. The intrinsic pathway is mediated by interplay between pro- and antiapoptotic BCL-2 family members that regulate the permeabilization of the mitochondrial outer membrane, and the extrinsic pathway is initiated upon death receptor and ligand interactions at the cell surface that eventually activate the caspase cascade (Reichardt and Luhder, 2012). Some of the death receptors, such as tumour necrosis factor receptors 1 and 25, have dual roles and they transmit both death signals via caspase activation and a survival signal via the activation of nuclear factor-kappa B (NF-ΚB) transcription factor. The NF-ΚB pathway regulates the expression of several immunoregulatory factors, including cytokines, chemokines, adhesion molecules, cell cycle regulators and cell survival factors and therefore plays an
Fig. 1. The expression ratios of BCL-2 family genes in RRMS patients and healthy controls. Median (25th–75th percentiles). **p b 0.01, *p b 0.05.
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
47
Table 4 Correlation analyses of baseline expression levels of apoptosis-related genes to baseline volumes of T1 and FLAIR lesions over the follow-up period in converting and nonconverting CIS patients. Converting
Nonconverting
T1
BAD TNFRSF25 IKBKE NFKBID
FLAIR
T1
FLAIR
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
BL
2-yrs
4-yrs
0.72⁎ 0.88⁎⁎ – 0.77⁎
– 0.83⁎ – 0.76⁎
– 0.81⁎ – 0.72⁎
0.80⁎ 0.83⁎⁎ – 0.81⁎⁎
0.76⁎ 0.88⁎⁎ – 0.81⁎
0.76⁎ 0.88⁎⁎ – 0.81⁎
– – – –
– – – –
– – 0.89⁎ –
– 0.67⁎ – 0.68⁎
– 0.67⁎ – –
– – 0.89⁎ –
BL baseline; yrs years; FLAIR fluid-attenuated inversion recovery; BAD BCL2-associated agonist of cell death; TNFRSF25 tumour necrosis factor receptor superfamily, member 25; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta. – not significant. Spearman's rank correlation test *p b 0.05; **p b 0.001.
important role in various biological processes (Oh and Ghosh, 2013). The NF-ΚB pathway is regulated via inhibitory kappa B (IΚB) proteins and IΚB kinases. Another activator of the NF-ΚB pathway is the proinflammatory cytokine interleukin (IL)-1B, which is activated and secreted from macrophages via an inflammasome-dependent mechanism. Several reports have suggested the involvement of inflammasomes in autoimmune diseases to maintain the ongoing inflammation (Inoue and Shinohara, 2013). In this study, we assessed whether apoptosis-related molecules are already detectable after the first demyelinating event suggestive of MS and evaluated whether their expression levels have predictive potential for the conversion from CIS to MS. Study design was based on the assumption that aberrantly expressed genes detected in RRMS patients but not in controls might indicate such predictive potential. Data showed that the gene expression profile in RRMS patients was characterised by the upregulation of proapoptotic genes (BAD, BCLG, BIK, BOK, PUMA, FADD, TNFRSF25), inflammatory NF-ΚB family members (IKBKE, NFKBID) and inflammasome (CASP1, PYCARD) genes. Interestingly, IKBKE and NFKBID are novel NF-ΚB pathway regulators and their specific role, especially in MS, is poorly understood (Schuster et al., 2013). The involvement of the death receptor TNFRSF25 in MS has not yet been elucidated, but it is known to stimulate the NF-ΚB pathway via TRADD adaptor protein and regulate cell apoptosis via FADD adaptor protein in activated T cells (Meylan et al., 2011). Many other members of this tumour necrosis factor receptor superfamily have previously been associated with MS pathogenesis (Mc Guire et al., 2011). Half of the upregulated transcripts detected in this study were proapoptotic BCL-2 family members (BAD, BCLG, BIK, BOK, PUMA), indicating the predominance of intrinsic proapoptotic events in RRMS. This interpretation is further supported by the presence of increased expression ratios of pro- to antiapoptotic BCL-2 family members. Other authors have reported upregulated levels of antiapoptotic BCL-2 family members in active RRMS patients, indicating failure in the apoptotic pathways (Sharief et al., 2002, 2003; Achiron et al., 2007; Gurevich Table 5 Number of observed correlations between apoptosis-related genes (n = 11) and cytokines (n = 7) in different groups. Number of statistically significant correlations in different groups All samples Cytokines IFNG 2 IL6 1 IL10 1 IL12A 2 IL21 4 IL23A 6 TGFB1 1 Total 17
a
All CIS
Converting
Nonconverting
Controls
1 0 0 0 2 6 3 12
2 0 1 0 0 1 7 11
1 1 0 0 1 4 0 7
2 2 0 3 1 5 0 13
IFNG interferon-gamma; IL interleukin; TGFB1 transforming growth factor beta1. a Actual Spearman's rank correlation coefficients (r) can be found in Supplementary Table.
and Achiron, 2012; Mandel et al., 2012). The discrepancies between these studies are most likely explained by differences in the studied populations; in this study patients were relatively stable. In fact, Gurevitch and others have shown the involvement of different operating pathways during the stable and active phase of the disease (Gurevich and Achiron, 2012). They proposed that the stable phase of the disease is mediated by anti-inflammatory responses together with tight regulation of apoptosis mechanisms aiming to prevent harmful inflammatory responses, but during relapse antiapoptotic and proinflammatory responses prevail. Therefore, the upregulation of proapoptotic BCL-2 family genes found in our study may indicate that the regulatory effects of the immune system enhance apoptosis and thereby limit lymphocyte responses. The longitudinal analysis of CIS patients showed intra- and interindividual variability in the levels of BCL-2, NF-ΚB, inflammasome components and death receptor pathway transcripts consistent with peripheral immune activation already at the early stage of MS, although differences were not statistically significant. The variability in the expression of the apoptotic transcripts between the subjects is most likely Table 6 Number of observed correlations amongst apoptosis-related genes (A) and cytokines (B) in different groups. All samples
All CIS
Converting
Nonconverting
Controls
A. BAD BCLG BIK BOK PUMA FADD TNFRSF25 IKBKE NFKBID CASP1 PYCARD Total
7 3 3 1 6 6 6 4 7 5 4 52
3 0 1 0 4 4 2 1 4 0 3 22
4 2 0 2 5 2 3 1 3 0 2 24
0 0 5 1 6 5 3 3 3 3 3 32
6 0 0 2 5 4 5 6 3 1 2 34
B. IFNG IL6 IL10 IL12A IL21 IL23A TGFB1 Total
4 2 3 1 1 0 1 12
1 0 0 1 1 0 1 4
0 0 1 0 1 0 0 2
1 0 1 0 1 0 1 4
3 2 2 1 0 0 0 8
CIS clinically isolated syndrome; BAD BCL2-associated agonist of cell death; BCLG BCL2like 14 (apoptosis facilitator); BIK BCL2-interacting killer (apoptosis-inducing); BOK BCL2-related ovarian killer; PUMA BCL2 Binding Component 3; FADD Fas (TNFRSF6)-associated via death domain; TNFRSF25 tumour necrosis factor receptor superfamily. member 25; ; IKBKE inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase epsilon; NFKBID nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, delta; CASP1 caspase 1, apoptosis-related cysteine peptidase PYCARD PYD and CARD domain containing protein; IFNG interferon-gamma; IL interleukin; TGFB1 transforming growth factor beta 1.
48
S. Hagman et al. / Journal of Neuroimmunology 280 (2015) 43–48
explained by the heterogeneous nature of the disease characterised by different immunological and structural patterns differing between the individual patients (Lassmann et al., 2001). Interestingly, the correlation analyses showed a positive correlation between the apoptotic transcripts BAD, NFKBID and TNFRSF25 and increased volumes of FLAIR and T1 lesions in converting patients indicating increased potential for apoptosis in such patients with more active disease. In spite of variation in the expression of apoptotic molecules and their association with the volumes of FLAIR and T1 lesions, the observed differences were not associated with the conversion to MS. At the baseline, three genes (IKBKE, NFKBID, TNFRSF25) were increased in nonconverting patients indicating the presence of peripheral immune activation in this subtype. Because the data showed marked intra- and inter-individual variability in the levels of apoptosis-related transcripts, we performed correlation analyses between the proapoptotic transcripts and pro-and anti-inflammatory cytokine transcripts to assess whether the apoptosis-related gene expression levels are associated with peripheral immune activation. It appeared that correlations were more notable in nonconverting CIS patients and controls, while correlations were most predominant between TGFB1 and apoptotic molecules in converting CIS patients. TGFB1 has a critical role in controlling the differentiation of pathogenic Th17 cells in the presence of IL-23 and IL-6, but it also plays a key role in the differentiation and function of regulatory T cells (Oh and Li, 2013). The increased expression of proapoptotic genes found in our study is related to peripheral immune activation aimed at terminating the immune response in order to maintain immune system homeostasis. These observations also suggest the involvement of different operating pathways in converting and nonconverting CIS patients, which may partially explain the accumulation of neuroinflammation in converting patients. In summary, the variability of the apoptotic transcripts in the early MS patients with clinically silent disease reflects peripheral immune activation, which seems to play a role in MS. Because only a limited number of patients were included in this exploratory study, these observations need to be confirmed in larger number of patients with a longer follow-up period in order to find biomarkers for identifying patients who are at high risk for developing MS. Acknowledgements We would like to thank Raija Caliskan for the excellent technical assistance. This study was financially supported by the Competitive State Research Financing of the Expert Responsibility Area of Tampere University Hospital (9P010), Finnish Cultural Foundation, Pirkanmaa Regional Fund (50131294, 50141553), and Eemil Aaltonen Foundation. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jneuroim.2015.02.006. References Achiron, A., Feldman, A., Mandel, M., Gurevich, M., 2007. Impaired expression of peripheral blood apoptotic-related gene transcripts in acute multiple sclerosis relapse. Ann. N. Y. Acad. Sci. 1107, 155–167.
Bruck, W., Gold, R., Lund, B.T., Oreja-Guevara, C., Prat, A., Spencer, C.M., et al., 2013. Therapeutic decisions in multiple sclerosis: moving beyond efficacy. JAMA Neurol. 70 (10), 1315–1324. Chanvillard, C., Jacolik, R.F., Infante-Duarte, C., Nayak, R.C., 2013. The role of natural killer cells in multiple sclerosis and their therapeutic implications. Front. Immunol. 4, 63. Comabella, M., Khoury, S.J., 2012. Immunopathogenesis of multiple sclerosis. Clin. Immunol. 142 (1), 2–8. Comi, C., Fleetwood, T., Dianzani, U., 2012. The role of T cell apoptosis in nervous system autoimmunity. Autoimmun. Rev. 12 (2), 150–156. Ellwardt, E., Zipp, F., 2014. Molecular mechanisms linking neuroinflammation and neurodegeneration in MS. Exp. Neurol.; 262 Pt A: 8-17. Fox, E.J., Rhoades, R.W., 2012. New treatments and treatment goals for patients with relapsing–remitting multiple sclerosis. Curr. Opin. Neurol. (25 Suppl.), S11–S19. Freedman, M.S., 2013. Present and emerging therapies for multiple sclerosis. Continuum (Minneap Minn). Mult. Scler. 19 (4), 968–991. Gurevich, M., Achiron, A., 2012. The switch between relapse and remission in multiple sclerosis: continuous inflammatory response balanced by Th1 suppression and neurotrophic factors. J. Neuroimmunol. 252 (1–2), 83–88. Hagman, S., Raunio, M., Rossi, M., Dastidar, P., Elovaara, I., 2011. Disease-associated inflammatory biomarker profiles in blood in different subtypes of multiple sclerosis: prospective clinical and MRI follow-up study. J. Neuroimmunol. 234 (1–2), 141–147. Inoue, M., Shinohara, M.L., 2013. NLRP3 Inflammasome and MS/EAE. Autoimmune Dis. 2013, 859145. Kurtzke, J.F., 1983. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33 (11), 1444–1452. Lassmann, H., Bruck, W., Lucchinetti, C., 2001. Heterogeneity of multiple sclerosis pathogenesis: implications for diagnosis and therapy. Trends Mol. Med. 7 (3), 115–121. Mandel, I., Paperna, T., Miller, A., 2012. Aberrant expression of the apoptosis-related proteins BAK and MCL1 in T cells in multiple sclerosis. J. Neuroimmunol. 244 (1–2), 51–56. Mc Guire, C., Beyaert, R., van Loo, G., 2011. Death receptor signalling in central nervous system inflammation and demyelination. Trends Neurosci. 34 (12), 619–628. McDonald, W.I., Compston, A., Edan, G., Goodkin, D., Hartung, H.P., Lublin, F.D., et al., 2001. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International panel on the diagnosis of multiple sclerosis. Ann. Neurol. 50 (1), 121–127. Meylan, F., Richard, A.C., Siegel, R.M., 2011. TL1A and DR3, a TNF family ligand-receptor pair that promotes lymphocyte costimulation, mucosal hyperplasia, and autoimmune inflammation. Immunol. Rev. 244 (1), 188–196. Miller, D.H., Chard, D.T., Ciccarelli, O., 2012. Clinically isolated syndromes. Lancet Neurol. 11 (2), 157–169. Moreno, M., Negrotto, L., Río, J., Moubarak, R., Martín, I., Bustamante, M.F., et al., 2014. Activation-induced cell death in T lymphocytes from multiple sclerosis patients. J. Neuroimmunol. 272 (1–2), 51–55. Oh, H., Ghosh, S., 2013. NF-kappaB: roles and regulation in different CD4(+) T-cell subsets. Immunol. Rev. 252 (1), 41–51. Oh, S.A., Li, M.O., 2013. TGF-beta: guardian of T cell function. J. Immunol. 191 (8), 3973–3979. Polman, C.H., Reingold, S.C., Edan, G., Filippi, M., Hartung, H.P., Kappos, L., et al., 2005. Diagnostic criteria for multiple sclerosis: 2005 revisions to the “McDonald criteria”. Ann. Neurol. 58 (6), 840–846. Reichardt, H.M., Luhder, F., 2012. The ambivalent role of apoptosis in experimental autoimmune encephalomyelitis and multiple sclerosis. Curr. Pharm. Des. 18 (29), 4453–4464. Reuss, R., Mistarz, M., Mirau, A., Kraus, J., Bodeker, R.H., Oschmann, P., 2014. FADD is upregulated in relapsing remitting multiple sclerosis. Neuroimmunomodulation 21 (5), 221–225. Schuster, M., Annemann, M., Plaza-Sirvent, C., Schmitz, I., 2013. Atypical IkappaB proteins — nuclear modulators of NF-kappaB signaling. Cell Commun. Signal. 11 (1), 23 (–811X-11–23). Semra, Y.K., Seidi, O.A., Sharief, M.K., 2002a. Disease activity in multiple sclerosis correlates with T lymphocyte expression of the inhibitor of apoptosis proteins. J. Neuroimmunol. 122 (1–2), 159–166. Semra, Y.K., Seidi, O.A., Sharief, M.K., 2002b. Heightened intrathecal release of axonal cytoskeletal proteins in multiple sclerosis is associated with progressive disease and clinical disability. J. Neuroimmunol. 122 (1–2), 132–139. Sharief, M.K., Semra, Y.K., 2001. Heightened expression of survivin in activated T lymphocytes from patients with multiple sclerosis. J. Neuroimmunol. 119 (2), 358–364. Sharief, M.K., Douglas, M., Noori, M., Semra, Y.K., 2002. The expression of pro- and antiapoptosis Bcl-2 family proteins in lymphocytes from patients with multiple sclerosis. J. Neuroimmunol. 125 (1–2), 155–162. Sharief, M.K., Matthews, H., Noori, M.A., 2003. Expression ratios of the Bcl-2 family proteins and disease activity in multiple sclerosis. J. Neuroimmunol. 134 (1–2), 158–165.