- Email: [email protected]
Cerebrospinal fluid concentration of Galectin-9 is increased in secondary progressive multiple sclerosis
Journal of Neuroimmunology 292 (2016) 40–44
Contents lists available at ScienceDirect
Journal of Neuroimmunology journal homepage: www.elsevier.com/locate/jneuroim
Cerebrospinal fluid concentration of Galectin-9 is increased in secondary progressive multiple sclerosis Joachim Burman a,b,⁎, Anders Svenningsson c,d a
Department of Neurosciences, Uppsala University, Uppsala, Sweden Department of Neurology, Uppsala University Hospital, Uppsala, Sweden Department of Pharmacology and Clinical Neuroscience, Umeå University and University Hospital of Northern Sweden, Umeå, Sweden d Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden b c
a r t i c l e
i n f o
Article history: Received 23 November 2015 Received in revised form 11 January 2016 Accepted 14 January 2016 Available online xxxx Keywords: Biomarker CSF Multiple sclerosis Galectin-9
a b s t r a c t Galectin-9 is produced by activated astrocytes, induces a pro-inflammatory response in microglia and may be important to the pathogenesis of secondary progressive MS. In this study, Galectin-9 concentrations in CSF samples from healthy controls and two independent patient cohorts of MS patients were determined by ELISA. Patients from one of the cohorts underwent MRI as well. Galectin-9 concentrations in CSF were higher in SPMS patients than healthy controls and RRMS patients in both cohorts. Galectin-9 concentrations correlated with the number of lesions on T1-weighted images, but not with gadolinium enhancing lesions, IgG index or CSF cell count. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Secondary progressive multiple sclerosis (SPMS) remains a challenge to clinicians and researches. In most cases, SPMS is diagnosed retrospectively by a history of gradual worsening after an initial relapsing–remitting disease course (RRMS). To date, there are no clear clinical, imaging, immunologic, or pathologic criteria to determine the transition point when RRMS converts to SPMS. Traditional measures of inflammation such as cerebrospinal fluid (CSF) pleocytosis, IgG-index and gadolinium enhancing lesions (Gd+) are generally lowgrade or absent. Nevertheless, neuropathological studies suggest that inflammation is present in all stages of MS and that it is intimately connected with neurodegeneration (Frischer et al., 2009). To account for these seemingly contradictory observations, it has been hypothesized that inflammation carries on in a compartmentalized form (Meinl et al., 2008), driven mainly by innate immune cells (Mayo et al., 2012), but so far no reliable method has been able to measure such inflammation in vivo. Galectin-9 is a member of the galectin family of carbohydratebinding proteins, which are characterized by the presence of conserved carbohydrate-recognition domains and share binding affinity for the basic carbohydrate unit galactose (Barondes et al., 1994; Wada and Kanwar, 1997). Interaction between the T-cell immunoglobulin mucin 3 (TIM-3) and Galectin-9 inhibits the differentiation of naïve T-cells ⁎ Corresponding author at: Uppsala University Hospital, SE-751 85 Uppsala, Sweden. E-mail address: [email protected] (J. Burman).
http://dx.doi.org/10.1016/j.jneuroim.2016.01.008 0165-5728/© 2016 Elsevier B.V. All rights reserved.
into T-helper 17 (Th17) cells (Seki et al., 2008), leads to apoptosis of mature differentiated T-helper 1 (Th1) and Th17 cells and promotes Foxp3+ regulatory T cells (Zhu et al., 2005; Oomizu et al., 2012). Galectin-9 is also a regulator of innate immunity, but in contrast to the inhibitory effects on adaptive immunity Galectin-9 induces a proinflammatory response in microglia, with increased production of TNF-α and IL-6 (Steelman and Li, 2014). Although Galectin-9 is undetectable on resting human astrocytes, it can be induced by pro-inflammatory cytokines, notably TNF-α (Steelman et al., 2013), and it has been demonstrated that Galectin-9 expression is elevated on astrocytes present in MS lesions (Anderson et al., 2007; Stancic et al., 2011). Further, astrocyte-derived galectin-9 promotes microglial TNF secretion (Steelman and Li, 2014), suggesting an important role for Galectin-9 in astrocyte–microglia interaction. Activated microglia have been implicated in the pathogenesis of SPMS and thus Galectin-9 could be a valuable biomarker for SPMS. The purpose of this exploratory study was to investigate Galectin-9 as a potential biomarker of SPMS.
2. Material and methods 2.1. Ethics statement The study was approved by the ethics committee of Uppsala University (DNr 2008/182) and Umeå University (DNr 08-157M). All subjects provided written informed consent.
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
2.2. Study outline
41
Table 2 Clinical data of controls and patients in cohort B.
The aim of this study was to determine if Galectin-9 concentrations in CSF were higher in patients with MS and more specifically SPMS. To this end, a two tiered approached was employed. First, Galectin-9 concentrations were determined in a well defined cohort of untreated and for the most part newly diagnosed RRMS patients in remission together with a group of SPMS patients with rapid progression. These results were then validated in a mixed cohort of patients, with the intention to determine whether the results could be replicated in a more real-life setting.
n Female/male Age, years (IQR) EDSS (IQR) Disease duration (IQR) Duration of progressive disease (IQR) On treatment Clinical relapse Gadolinium enhancing lesions IgG-index (IQR)
Controls
RRMS
SPMS
25 10/15 48 (41–52) n/a n/a n/a
31 18/7 39 (30–44) 2 (1.5–2.5) 6.75 (3.33–16.3) n/a
16 15/7 58.5 (53.8–66.8) 5.5 (3.63–6) 23.7 (18.1–29.6) 10.5 (8–15.5)
n/a n/a n/a n/a
13/31 8/31 18/31 1.0 (0.68–1.2)
2/16 0/16 5/16 0.79 (0.53–0.92)
2.3. Subjects Patients from both cohorts met the revised McDonald's criteria for MS diagnosis (Polman et al., 2011) and SPMS patients were clinically deteriorating in the absence of clinical relapses. 2.3.1. Controls The controls were healthy volunteers with no signs of neurological disease. Twenty-five controls (ten women and fifteen men) were recruited, their median age 48 years (IQR 41–52). 2.3.2. Cohort A Cohort A consisted of 25 RRMS patients and 22 SPMS patients recruited from the University Hospital of Northern Sweden. None of the RRMS patients had a clinical relapse within three months from the lumbar puncture and none of them was on treatment. Most patients were newly diagnosed with MS and donated CSF before starting treatment. Two of the SPMS patients were on interferon treatment. The characteristics of subjects in Cohort A are summarized in Table 1.
2.5. MRI examinations MRI was performed at 1.5 T using the same imager and imaging protocol in all examinations. Gadopentetate dimeglumine (Magnevist®, Bayer AG, Leverkusen, Germany; 0.4 ml/kg body weight, i.e. double dose) was used as a contrast agent. Lesions N3 mm in diameter were counted in fluid attenuated inversion recovery images (FLAIR) using T2-weighted (T2W) using proton density-weighted spin echo (SE) images as aid. Similarly, lesions N 3 mm in diameter were counted on T1weighted (T1W) images before and after administration of the contrast agent. 2.6. Statistical analysis
2.3.3. Cohort B Cohort B consisted of 31 RRMS patients and 16 SPMS patients recruited from Uppsala University Hospital. Thirteen RRMS patients were on disease modifying treatment (interferons, n = 4; glatiramer acetate, n = 3; natalizumab, n = 3; intravenous immunoglobulin, n = 2; mitoxantrone, n = 1). Two SPMS patients were on treatment (interferon, n = 1; natalizumab, n = 1). Eight RRMS patients had a recent relapse ≤ 1 month of CSF sampling. All patients underwent MRI of the brain in close proximity to the lumbar puncture. The characteristics of subjects in Cohort B are summarized in Table 2.
Statistical analyses were done with GraphPad Prism 6.0 (GraphPad Software, La Jolla, CA) and R version 3.1.0. Baseline characteristics were summarized by MS subtype using frequencies for categorical variables and medians with interquartile intervals for continuous variables. To determine statistically significant differences between two groups, the Mann–Whitney test was used; for statistical significance between three or more groups the Kruskal–Wallis test was used. Dunn's multiple comparison test was used for post hoc analysis. Correlations were described with Spearman's rank correlation coefficient and fit to regression line was described with the coefficient of determination (R2). An ANCOVA model with Galectin-9 as dependent variable and MS subtype, age and gender as independent variables was used. The model was used to perform pairwise comparisons between subtypes of MS. A two-tailed p value of b0.05 was considered significant. All described differences are statistically significant unless otherwise stated.
2.4. CSF collection and analysis
3. Results
CSF samples were collected and handled according to the 2009 consensus protocol on CSF biobanking (Teunissen et al., 2009). CSF concentrations of Galectin-9 were analyzed with a commercially available ELISA (R&D systems, Minneapolis, MN). Samples were run in duplicate by experienced laboratory personnel and the pooled CV of the analyses was 3.4%.
3.1. Cohort A
Table 1 Clinical data of controls and patients in cohort A.
n Female/male Age (IQR) EDSS (IQR) Disease duration (IQR) Duration of progressive disease (IQR) On treatment
SPMS patients displayed higher concentrations of Galectin-9 in CSF (mean 400 pg/mL ± 105) than RRMS patients (mean 306 pg/mL ± 96.6) and healthy controls (mean 257 pg/mL ± 56.6). No statistically significant difference was seen between RRMS patients and controls (Fig. 1A). 3.2. Cohort B
Controls
RRMS
SPMS
25 10/15 48 (41–52) n/a n/a n/a
25 18/7 36 (32–45.5) 2 (0–2.75) 0.67 (0.42–6.0) n/a
22 15/7 59 (53–64.5) 6 (5.25–6.5) 28 (13–29) 8 (4–13)
n/a
0/25
2/22
SPMS patients had higher concentrations of Galectin-9 in CSF (mean 399 pg/mL ± 78.0) than RRMS patients (mean 322 pg/mL ± 90.6) and healthy controls. In addition, RRMS patients had higher concentrations than controls (Fig. 1B). RRMS patients with a clinical relapse had similar concentrations of Galectin-9 as patients in remission. In order to assess how CSF concentrations of Galectin-9 could be influenced by passive transfer of Galectin-9 from serum to CSF over the blood-barrier, the correlation between Galectin-9 and albumin quotas
42
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
Fig. 1. Concentrations of Galectin-9 in two independent cohorts. (A) Levels of Galectin-9 in healthy controls and patients with different subtypes of MS from cohort A. (B) Levels of Galectin-9 in healthy controls and patients with different subtypes of MS from cohort B. (C) Levels of Galectin-9 in untreated vs treated RRMS patients from cohort B. (D) Galectin-9 concentrations from the combined cohorts (medians with interquartile range).
was determined. The albumin quotas correlated moderately with the levels of Galectin-9 (Spearman r = 0.35, p = 0.016). We therefore performed a linear regression analysis, which yielded a low and not statistically significant coefficient of determination (R2 = 0.079, p = NS). We also assessed how Galectin-9 correlated with traditional measures of inflammation, but found no correlation between Galectin-9 and the number of monocytes in the CSF or the IgG-index (data not shown). All patients with a clinical relapse had at least one Gd+ lesion. In addition to these, ten RRMS patients had at least one Gd + lesion. Five SPMS-patients had Gd+ lesions. The concentration of Galectin-9 was not different between patients with and without Gd + lesions in RRMS patients or SPMS patients, nor did the number of Gd + lesions correlate with the concentrations of Galectin-9. Treatment with disease modifying drugs did not seem to affect the concentration of Galectin-9 (Fig. 1C). Structural damage to the brain was assessed by estimation of the number of lesions on T1W and T2W images. The concentrations of Galectin-9 correlated moderately with the number of lesions on T1W images (Spearman r = 0.47, p = 0.0014) but not with the number of lesions on T2W images (Spearman r = 0.23, p = 0.15). 3.3. Combined cohorts When the two cohorts were combined, Galectin-9 concentrations in CSF were higher in SPMS patients (mean 400 pg/mL ± 93.0) than RRMS patients (mean 315 pg/mL ± 92.4) and healthy controls (mean 257 pg/mL ± 56.6). (Fig. 1D). The concentrations of Galectin-9 in MS patients correlated with disease duration (Spearman r = 0.34, p = 0.007) and EDSS (Spearman r = 0.36, p = 0.004).
The concentrations of Galectin-9 in healthy controls correlated with age (Spearman r = 0.42, p = 0.039). Furthermore, the gender composition of the control group was different from the patient cohorts. To account for these possible confounders an ANCOVA model was created, in which statistically significant differences between all groups were still present when age and gender were controlled for (Table 3). 4. Discussion In this study, we have demonstrated that the Galectin-9 concentration in CSF is increased in patients with SPMS. To the best of our knowledge, this is a novel finding that has not been reported before. In contrast to other candidate biomarkers of SPMS, such as YKL-40 (Malmestrom et al., 2014) and sCD28 (Komori et al., 2015), the concentrations of Galectin-9 did not correlate with traditional measures of inflammation. On the other hand, Galectin-9 correlated with the number of lesions on T1W images suggesting that at least part of the CSF Galectin-9 is produced within those lesions, supporting the notion of compartmentalized inflammation.
Table 3 Pairwise comparisons of patients from the combined cohort with correction for age and gender. Group 1
Group 2
Difference
CI
p-Value
Control Control RRMS
RRMS SPMS SPMS
69.8 126 56.5
(24.8–115) (77.9–175) (6.6–106)
0.003 b0.001 0.027
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
SPMS is characterized by fewer and milder relapses (Lublin and Reingold, 1996; Sospedra and Martin, 2005), less radiological activity (Filippi et al., 1997; Koziol et al., 1998), continuous deterioration of neurologic function(Confavreux et al., 2003) and by the development of chronically active white matter lesions. These lesions contain a demyelinated core with few T cells, which is surrounded by a rim of microglia nodules and activated astrocytes (Frischer et al., 2009; Prineas et al., 2001). Such slowly expanding lesions are believed to increase in size over time, contributing to demyelination, axonal damage and disability. It is well known that lesions on T1W images may evolve into black holes without showing evidence of contrast uptake, which probably is the MRI correlate of the chronically active lesion (Giannetti et al., 2014). While it is not possible to directly visualize microglia activation with MRI, two recent PET studies demonstrated increased binding of a marker for activated microglia (11C-PK11195) in 57–76% of lesions seen on T1W images (Giannetti et al., 2014; Rissanen et al., 2014). We saw a robust correlation between the concentrations of Galectin-9 and the number of lesions on T1W images and it seems likely that the source of CSF Galectin-9 is located within such lesions. On the other hand, concentrations of Galectin-9 did not correlate with measures of inflammation such as the number of Gd+ lesions, IgG index or CSF cell count nor were they higher in patients with clinical relapse or Gd + lesions. This suggests that Galectin-9 production in the CSF is essentially independent of adaptive immunity and we believe that Galectin-9 production is mainly driven by innate immunity intimately connected with progressive disease. Astrocyte and microglia interaction through Galectin-9 and TNF-α may play a crucial role to maintain the structure of the chronically active white matter lesion. It has previously been shown that Galectin-9 is produced within the CNS by activated astrocytes (Anderson et al., 2007; Stancic et al., 2011), which are abundant within the chronically active white matter lesions (Frischer et al., 2009). Galectin-9 production in astrocytes is primarily induced by TNF-α and to a lesser degree by other pro-inflammatory cytokines such as IL-1β and IFN-γ, whereas Galectin-9 production is not influenced by the anti-inflammatory cytokines IL-6, IL-10, and IL-13 (Steelman et al., 2013). Moreover, astrocyte-derived Galectin-9 in turn enhances microglial TNF production (Steelman and Li, 2014), creating favorable conditions for self-perpetuating inflammation beyond control of adaptive immunity. TNF-α has also been shown to be toxic to oligodendrocytes (Selmaj and Raine, 1988). Oligodendrocytes in close proximity to the rim of microglia nodules would be vulnerable to TNF-α mediated necroptosis further stimulating microglia, leading to a slowly expanding lesion. In theory, blockade of the astrocyte–microglia interaction by e.g. TNF inhibitors could be beneficial for treatment of SPMS, but this approach could also be dangerous since it is well established that Galectin-9 is a negative regulator of adaptive immunity (Zhu et al., 2011). Within the chronically active white matter lesion the high concentration of Galectin-9 creates a microenvironment which is very unfavorable to the survival of encephalitogenic T cells which are prone to Galectin-9 mediated apoptosis. It has been demonstrated that MBP-specific T cells from mice are prone to Galectin-9 mediated apoptosis when cocultured with TNF primed astrocytes (Steelman et al., 2013). Furthermore, the TNF-inhibitor lenercept has been tried for RRMS and was found to precipitate acute inflammatory lesions and exacerbations (1999). Treatment with other TNF-inhibitors probably also increases the risk of developing MS (Solomon et al., 2011). TNF deficient mice also develop severe neurological impairment with high mortality when experimental autoimmune encephalitis is induced (Liu et al., 1998). Although the mechanism behind the detrimental effect of TNF-inhibitors in MS is not known, it is possible that decreased CNS Galectin-9 production leading to increased survival of encephalitogenic T cells is a contributing factor. Thus a potentially beneficial effect of TNF-inhibitors in SPMS, might very well be overshadowed by increased severity of relapses.
43
We used two independent cohorts to study Galectin-9 in CSF with very similar results, suggesting that these results can be generalized to the wider MS population. Nevertheless some minor differences between the two cohorts were noted. RRMS patients from cohort B had on average somewhat higher Galectin-9 concentrations than patients from cohort A. Most of the RRMS patients in cohort A were sampled at or in close proximity to diagnosis, whereas patients from cohort B were a cross section of a typical outpatient clinic. Age and disease duration are risk factors for development of SPMS (Confavreux, 2006; Scalfari et al., 2014), which were higher in cohort B. Since Galectin-9 concentration may increase gradually in the transition from RRMS to SPMS it is not unlikely that some of the RRMS patients in cohort B were patients in transition to SPMS. Several questions still remain open. Whether high concentrations of Galectin-9 in RRMS patients predict conversion to clinically manifest SPMS needs to be addressed in a longitudinal cohort of RRMS patients followed for a long period of time. Moreover, Galectin-9 could serve as a biomarker for therapeutic effect of drugs targeting the astrocyte–microglia axis, such as minocycline, which could be explored in a clinical trial. Finally, the therapeutic potential in Galectin-9 inhibition should be considered. It was recently reported that Galectin-9 was able to promote TNF production in microglia independently of Tim-3 (Steelman and Li, 2014). If this molecular mechanism can be understood, it may provide a novel target for drugs to treat SPMS, which may be a safer alternative than e.g. TNF-inhibitors. 5. Conclusions Several lines of evidence point to the importance of astrocyte– microglia interaction in the pathogenesis of SPMS and Galectin-9 is a key molecule in astrocyte–microglia crosstalk. In the present study Galectin-9 concentrations were higher in CSF from SPMS patients. Furthermore, Galectin-9 levels were not influenced by traditional measures of inflammatory activity, suggesting that Galectin-9 reflects activity in the innate rather than the adaptive immune system. Thus, Galectin-9 may be a biomarker of the pathophysiological process that underlies SPMS that deserves to be explored further. Financial support This work was supported by a donation from Lars Tenerz; the Selander Foundation; Åke Löwnertz Foundation for Neurological Research; the MÅH Ländell Foundation; and Uppsala University Hospital. Conflicts of interest The authors report no conflict of interest. Author contributions JB designed the study. AS performed the lumbar punctures and collected clinical data from cohort A and JB did the same from cohort B. JB performed the CSF analyses and the analyses of MR images. JB wrote the draft and both authors provided creative input and approved of the final manuscript. References Anderson, A.C., Anderson, D.E., Bregoli, L., Hastings, W.D., Kassam, N., Lei, C., Chandwaskar, R., Karman, J., Su, E.W., Hirashima, M.,., Bruce, J.N.,., Kane, L.P., Kuchroo, V.K., Hafler, D.A., 2007. Promotion of tissue inflammation by the immune receptor Tim-3 expressed on innate immune cells. Science 318, 1141–1143. Barondes, S.H., Castronovo, V., Cooper, D.N., Cummings, R.D., Drickamer, K., Feizi, T., Gitt, M.A., Hirabayashi, J., Hughes, C., Kasai, K., et al., 1994. Galectins: a family of animal beta-galactoside-binding lectins. Cell 76, 597–598. Confavreux, C., 2006. Natural history of multiple sclerosis: a unifying concept. Brain 129, 606–616.
44
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
Confavreux, C., Vukusic, S., Adeleine, P., 2003. Early clinical predictors and progression of irreversible disability in multiple sclerosis: an amnesic process. Brain 126, 770–782. Filippi, M., Rossi, P., Campi, A., Colombo, B., Pereira, C., Comi, G., 1997. Serial contrastenhanced MR in patients with multiple sclerosis and varying levels of disability. Am. J. Neuroradiol. 18, 1549–1556. Frischer, J.M., Bramow, S., Dal-Bianco, A., Lucchinetti, C.F., Rauschka, H., Schmidbauer, M., Laursen, H., Sorensen, P.S., Lassmann, H., 2009. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain 132, 1175–1189. Giannetti, P., Politis, M., Su, P., Turkheimer, F., Malik, O., Keihaninejad, S., Wu, K., Reynolds, R., Nicholas, R., Piccini, P., 2014. Microglia activation in multiple sclerosis black holes predicts outcome in progressive patients: an in vivo [11C](R)-PK11195-PET pilot study. Neurobiol. Dis. 65, 203–210. Komori, M., Blake, A., Greenwood, M., Lin, Y.C., Kosa, P., Ghazali, D., Winokur, P., Natrajan, M., Wuest, S.C., Romm, E., Panackal, A.A., Williamson, P.R., Wu, T., Bielekova, B., 2015. CSF markers reveal intrathecal inflammation in progressive multiple sclerosis. Ann. Neurol. Koziol, J., Wagner, S., Adams, H., 1998. Assessing information in T2-weighted MRI scans from secondary progressive MS patients. Neurology 51, 228–233. Liu, J., Marino, M.W., Wong, G., Grail, D., Dunn, A., Bettadapura, J., Slavin, A.J., Old, L., Bernard, C.C., 1998. TNF is a potent anti-inflammatory cytokine in autoimmunemediated demyelination. Nat. Med. 4, 78–83. Lublin, F., Reingold, S., 1996. Defining the clinical course of multiple sclerosis: results of an international survey. Neurology 46, 907–911. Malmestrom, C., Axelsson, M., Lycke, J., Zetterberg, H., Blennow, K., Olsson, B., 2014. CSF levels of YKL-40 are increased in MS and replaces with immunosuppressive treatment. J. Neuroimmunol. 269, 87–89. Mayo, L., Quintana, F.J., Weiner, H.L., 2012. The innate immune system in demyelinating disease. Immunol. Rev. 1, 170–187. Meinl, E., Krumbholz, M., Derfuss, T., Junker, A., Hohlfeld, R., 2008. Compartmentalization of inflammation in the CNS: a major mechanism driving progressive multiple sclerosis. J. Neurol. Sci. 274, 42–44. Oomizu, S., Arikawa, T., Niki, T., Kadowaki, T., Ueno, M., Nishi, N., Yamauchi, A., Hattori, T., Masaki, T., Hirashima, M., 2012. Cell surface galectin-9 expressing Th cells regulate Th17 and Foxp3+ Treg development by galectin-9 secretion. PLoS One 7, e48574. Polman, C.H., Reingold, S.C., Banwell, B., Clanet, M., Cohen, J.A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., Lublin, F.D., Montalban, X., O'connor, P., Sandberg-Wollheim, M., Thompson, A.J., Waubant, E., Weinshenker, B., Wolinsky, J.S., 2011. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302. Prineas, J.W., Kwon, E.E., Cho, E.S., Sharer, L.R., Barnett, M.H., Oleszak, E.L., Hoffman, B., Morgan, B.P., 2001. Immunopathology of secondary-progressive multiple sclerosis. Ann. Neurol. 50, 646–657.
Rissanen, E., Tuisku, J., Rokka, J., Paavilainen, T., Parkkola, R., Rinne, J.O., Airas, L., 2014. In vivo detection of diffuse inflammation in secondary progressive multiple sclerosis using PET imaging and the radioligand 11C-PK11195. J. Nucl. Med. Scalfari, A., Neuhaus, A., Daumer, M., Muraro, P.A., Ebers, G.C., 2014. Onset of secondary progressive phase and long-term evolution of multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 85, 67–75. Seki, M., Oomizu, S., Sakata, K.M., Sakata, A., Arikawa, T., Watanabe, K., Ito, K., Takeshita, K., Niki, T., Saita, N., Nishi, N., Yamauchi, A., Katoh, S., Matsukawa, A., Kuchroo, V., Hirashima, M., 2008. Galectin-9 suppresses the generation of Th17, promotes the induction of regulatory T cells, and regulates experimental autoimmune arthritis. Clin. Immunol. 127, 78–88. Selmaj, K.W., Raine, C.S., 1988. Tumor necrosis factor mediates myelin and oligodendrocyte damage in vitro. Ann. Neurol. 23, 339–346. Solomon, A.J., Spain, R.I., Kruer, M.C., Bourdette, D., 2011. Inflammatory neurological disease in patients treated with tumor necrosis factor alpha inhibitors. Mult. Scler. 17, 1472–1487. Sospedra, M., Martin, R., 2005. Immunology of multiple sclerosis. Annu. Rev. Immunol. 23, 683–747. Stancic, M., Van Horssen, J., Thijssen, V.L., Gabius, H.J., Van Der Valk, P., Hoekstra, D., Baron, W., 2011. Increased expression of distinct galectins in multiple sclerosis lesions. Neuropathol. Appl. Neurobiol. 37, 654–671. Steelman, A.J., Li, J., 2014. Astrocyte galectin-9 potentiates microglial TNF secretion. J. Neuroinflammation 11, 144. Steelman, A.J., Smith III, R., Welsh, C.J., Li, J., 2013. Galectin-9 protein is up-regulated in astrocytes by tumor necrosis factor and promotes encephalitogenic T-cell apoptosis. J. Biol. Chem. 288, 23776–23787. Teunissen, C.E., Petzold, A., Bennett, J.L., Berven, F.S., Brundin, L., Comabella, M., Franciotta, D., Frederiksen, J.L., Fleming, J.O., Furlan, R., Hintzen, R.Q., Hughes, S.G., Johnson, M.H., Krasulova, E., Kuhle, J., Magnone, M.C., Rajda, C., Rejdak, K., Schmidt, H.K., Van Pesch, V., Waubant, E., Wolf, C., Giovannoni, G., Hemmer, B., Tumani, H., Deisenhammer, F., 2009. A consensus protocol for the standardization of cerebrospinal fluid collection and biobanking. Neurology 73, 1914–1922. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/ MRI Analysis Group, 1999c. TNF neutralization in MS: results of a randomized, placebo-controlled multicenter study. Neurology 53, 457–465. Wada, J., Kanwar, Y.S., 1997. Identification and characterization of galectin-9, a novel beta-galactoside-binding mammalian lectin. J. Biol. Chem. 272, 6078–6086. Zhu, C., Anderson, A.C., Schubart, A., Xiong, H., Imitola, J., Khoury, S.J., Zheng, X.X., Strom, T.B., Kuchroo, V.K., 2005. The Tim-3 ligand galectin-9 negatively regulates T helper type 1 immunity. Nat. Immunol. 6, 1245–1252. Zhu, C., Anderson, A.C., Kuchroo, V.K., 2011. TIM-3 and its regulatory role in immune responses. Curr. Top. Microbiol. Immunol. 350, 1–15.
Contents lists available at ScienceDirect
Journal of Neuroimmunology journal homepage: www.elsevier.com/locate/jneuroim
Cerebrospinal fluid concentration of Galectin-9 is increased in secondary progressive multiple sclerosis Joachim Burman a,b,⁎, Anders Svenningsson c,d a
Department of Neurosciences, Uppsala University, Uppsala, Sweden Department of Neurology, Uppsala University Hospital, Uppsala, Sweden Department of Pharmacology and Clinical Neuroscience, Umeå University and University Hospital of Northern Sweden, Umeå, Sweden d Department of Clinical Sciences, Karolinska Institutet Danderyd Hospital, Stockholm, Sweden b c
a r t i c l e
i n f o
Article history: Received 23 November 2015 Received in revised form 11 January 2016 Accepted 14 January 2016 Available online xxxx Keywords: Biomarker CSF Multiple sclerosis Galectin-9
a b s t r a c t Galectin-9 is produced by activated astrocytes, induces a pro-inflammatory response in microglia and may be important to the pathogenesis of secondary progressive MS. In this study, Galectin-9 concentrations in CSF samples from healthy controls and two independent patient cohorts of MS patients were determined by ELISA. Patients from one of the cohorts underwent MRI as well. Galectin-9 concentrations in CSF were higher in SPMS patients than healthy controls and RRMS patients in both cohorts. Galectin-9 concentrations correlated with the number of lesions on T1-weighted images, but not with gadolinium enhancing lesions, IgG index or CSF cell count. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Secondary progressive multiple sclerosis (SPMS) remains a challenge to clinicians and researches. In most cases, SPMS is diagnosed retrospectively by a history of gradual worsening after an initial relapsing–remitting disease course (RRMS). To date, there are no clear clinical, imaging, immunologic, or pathologic criteria to determine the transition point when RRMS converts to SPMS. Traditional measures of inflammation such as cerebrospinal fluid (CSF) pleocytosis, IgG-index and gadolinium enhancing lesions (Gd+) are generally lowgrade or absent. Nevertheless, neuropathological studies suggest that inflammation is present in all stages of MS and that it is intimately connected with neurodegeneration (Frischer et al., 2009). To account for these seemingly contradictory observations, it has been hypothesized that inflammation carries on in a compartmentalized form (Meinl et al., 2008), driven mainly by innate immune cells (Mayo et al., 2012), but so far no reliable method has been able to measure such inflammation in vivo. Galectin-9 is a member of the galectin family of carbohydratebinding proteins, which are characterized by the presence of conserved carbohydrate-recognition domains and share binding affinity for the basic carbohydrate unit galactose (Barondes et al., 1994; Wada and Kanwar, 1997). Interaction between the T-cell immunoglobulin mucin 3 (TIM-3) and Galectin-9 inhibits the differentiation of naïve T-cells ⁎ Corresponding author at: Uppsala University Hospital, SE-751 85 Uppsala, Sweden. E-mail address: [email protected] (J. Burman).
http://dx.doi.org/10.1016/j.jneuroim.2016.01.008 0165-5728/© 2016 Elsevier B.V. All rights reserved.
into T-helper 17 (Th17) cells (Seki et al., 2008), leads to apoptosis of mature differentiated T-helper 1 (Th1) and Th17 cells and promotes Foxp3+ regulatory T cells (Zhu et al., 2005; Oomizu et al., 2012). Galectin-9 is also a regulator of innate immunity, but in contrast to the inhibitory effects on adaptive immunity Galectin-9 induces a proinflammatory response in microglia, with increased production of TNF-α and IL-6 (Steelman and Li, 2014). Although Galectin-9 is undetectable on resting human astrocytes, it can be induced by pro-inflammatory cytokines, notably TNF-α (Steelman et al., 2013), and it has been demonstrated that Galectin-9 expression is elevated on astrocytes present in MS lesions (Anderson et al., 2007; Stancic et al., 2011). Further, astrocyte-derived galectin-9 promotes microglial TNF secretion (Steelman and Li, 2014), suggesting an important role for Galectin-9 in astrocyte–microglia interaction. Activated microglia have been implicated in the pathogenesis of SPMS and thus Galectin-9 could be a valuable biomarker for SPMS. The purpose of this exploratory study was to investigate Galectin-9 as a potential biomarker of SPMS.
2. Material and methods 2.1. Ethics statement The study was approved by the ethics committee of Uppsala University (DNr 2008/182) and Umeå University (DNr 08-157M). All subjects provided written informed consent.
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
2.2. Study outline
41
Table 2 Clinical data of controls and patients in cohort B.
The aim of this study was to determine if Galectin-9 concentrations in CSF were higher in patients with MS and more specifically SPMS. To this end, a two tiered approached was employed. First, Galectin-9 concentrations were determined in a well defined cohort of untreated and for the most part newly diagnosed RRMS patients in remission together with a group of SPMS patients with rapid progression. These results were then validated in a mixed cohort of patients, with the intention to determine whether the results could be replicated in a more real-life setting.
n Female/male Age, years (IQR) EDSS (IQR) Disease duration (IQR) Duration of progressive disease (IQR) On treatment Clinical relapse Gadolinium enhancing lesions IgG-index (IQR)
Controls
RRMS
SPMS
25 10/15 48 (41–52) n/a n/a n/a
31 18/7 39 (30–44) 2 (1.5–2.5) 6.75 (3.33–16.3) n/a
16 15/7 58.5 (53.8–66.8) 5.5 (3.63–6) 23.7 (18.1–29.6) 10.5 (8–15.5)
n/a n/a n/a n/a
13/31 8/31 18/31 1.0 (0.68–1.2)
2/16 0/16 5/16 0.79 (0.53–0.92)
2.3. Subjects Patients from both cohorts met the revised McDonald's criteria for MS diagnosis (Polman et al., 2011) and SPMS patients were clinically deteriorating in the absence of clinical relapses. 2.3.1. Controls The controls were healthy volunteers with no signs of neurological disease. Twenty-five controls (ten women and fifteen men) were recruited, their median age 48 years (IQR 41–52). 2.3.2. Cohort A Cohort A consisted of 25 RRMS patients and 22 SPMS patients recruited from the University Hospital of Northern Sweden. None of the RRMS patients had a clinical relapse within three months from the lumbar puncture and none of them was on treatment. Most patients were newly diagnosed with MS and donated CSF before starting treatment. Two of the SPMS patients were on interferon treatment. The characteristics of subjects in Cohort A are summarized in Table 1.
2.5. MRI examinations MRI was performed at 1.5 T using the same imager and imaging protocol in all examinations. Gadopentetate dimeglumine (Magnevist®, Bayer AG, Leverkusen, Germany; 0.4 ml/kg body weight, i.e. double dose) was used as a contrast agent. Lesions N3 mm in diameter were counted in fluid attenuated inversion recovery images (FLAIR) using T2-weighted (T2W) using proton density-weighted spin echo (SE) images as aid. Similarly, lesions N 3 mm in diameter were counted on T1weighted (T1W) images before and after administration of the contrast agent. 2.6. Statistical analysis
2.3.3. Cohort B Cohort B consisted of 31 RRMS patients and 16 SPMS patients recruited from Uppsala University Hospital. Thirteen RRMS patients were on disease modifying treatment (interferons, n = 4; glatiramer acetate, n = 3; natalizumab, n = 3; intravenous immunoglobulin, n = 2; mitoxantrone, n = 1). Two SPMS patients were on treatment (interferon, n = 1; natalizumab, n = 1). Eight RRMS patients had a recent relapse ≤ 1 month of CSF sampling. All patients underwent MRI of the brain in close proximity to the lumbar puncture. The characteristics of subjects in Cohort B are summarized in Table 2.
Statistical analyses were done with GraphPad Prism 6.0 (GraphPad Software, La Jolla, CA) and R version 3.1.0. Baseline characteristics were summarized by MS subtype using frequencies for categorical variables and medians with interquartile intervals for continuous variables. To determine statistically significant differences between two groups, the Mann–Whitney test was used; for statistical significance between three or more groups the Kruskal–Wallis test was used. Dunn's multiple comparison test was used for post hoc analysis. Correlations were described with Spearman's rank correlation coefficient and fit to regression line was described with the coefficient of determination (R2). An ANCOVA model with Galectin-9 as dependent variable and MS subtype, age and gender as independent variables was used. The model was used to perform pairwise comparisons between subtypes of MS. A two-tailed p value of b0.05 was considered significant. All described differences are statistically significant unless otherwise stated.
2.4. CSF collection and analysis
3. Results
CSF samples were collected and handled according to the 2009 consensus protocol on CSF biobanking (Teunissen et al., 2009). CSF concentrations of Galectin-9 were analyzed with a commercially available ELISA (R&D systems, Minneapolis, MN). Samples were run in duplicate by experienced laboratory personnel and the pooled CV of the analyses was 3.4%.
3.1. Cohort A
Table 1 Clinical data of controls and patients in cohort A.
n Female/male Age (IQR) EDSS (IQR) Disease duration (IQR) Duration of progressive disease (IQR) On treatment
SPMS patients displayed higher concentrations of Galectin-9 in CSF (mean 400 pg/mL ± 105) than RRMS patients (mean 306 pg/mL ± 96.6) and healthy controls (mean 257 pg/mL ± 56.6). No statistically significant difference was seen between RRMS patients and controls (Fig. 1A). 3.2. Cohort B
Controls
RRMS
SPMS
25 10/15 48 (41–52) n/a n/a n/a
25 18/7 36 (32–45.5) 2 (0–2.75) 0.67 (0.42–6.0) n/a
22 15/7 59 (53–64.5) 6 (5.25–6.5) 28 (13–29) 8 (4–13)
n/a
0/25
2/22
SPMS patients had higher concentrations of Galectin-9 in CSF (mean 399 pg/mL ± 78.0) than RRMS patients (mean 322 pg/mL ± 90.6) and healthy controls. In addition, RRMS patients had higher concentrations than controls (Fig. 1B). RRMS patients with a clinical relapse had similar concentrations of Galectin-9 as patients in remission. In order to assess how CSF concentrations of Galectin-9 could be influenced by passive transfer of Galectin-9 from serum to CSF over the blood-barrier, the correlation between Galectin-9 and albumin quotas
42
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
Fig. 1. Concentrations of Galectin-9 in two independent cohorts. (A) Levels of Galectin-9 in healthy controls and patients with different subtypes of MS from cohort A. (B) Levels of Galectin-9 in healthy controls and patients with different subtypes of MS from cohort B. (C) Levels of Galectin-9 in untreated vs treated RRMS patients from cohort B. (D) Galectin-9 concentrations from the combined cohorts (medians with interquartile range).
was determined. The albumin quotas correlated moderately with the levels of Galectin-9 (Spearman r = 0.35, p = 0.016). We therefore performed a linear regression analysis, which yielded a low and not statistically significant coefficient of determination (R2 = 0.079, p = NS). We also assessed how Galectin-9 correlated with traditional measures of inflammation, but found no correlation between Galectin-9 and the number of monocytes in the CSF or the IgG-index (data not shown). All patients with a clinical relapse had at least one Gd+ lesion. In addition to these, ten RRMS patients had at least one Gd + lesion. Five SPMS-patients had Gd+ lesions. The concentration of Galectin-9 was not different between patients with and without Gd + lesions in RRMS patients or SPMS patients, nor did the number of Gd + lesions correlate with the concentrations of Galectin-9. Treatment with disease modifying drugs did not seem to affect the concentration of Galectin-9 (Fig. 1C). Structural damage to the brain was assessed by estimation of the number of lesions on T1W and T2W images. The concentrations of Galectin-9 correlated moderately with the number of lesions on T1W images (Spearman r = 0.47, p = 0.0014) but not with the number of lesions on T2W images (Spearman r = 0.23, p = 0.15). 3.3. Combined cohorts When the two cohorts were combined, Galectin-9 concentrations in CSF were higher in SPMS patients (mean 400 pg/mL ± 93.0) than RRMS patients (mean 315 pg/mL ± 92.4) and healthy controls (mean 257 pg/mL ± 56.6). (Fig. 1D). The concentrations of Galectin-9 in MS patients correlated with disease duration (Spearman r = 0.34, p = 0.007) and EDSS (Spearman r = 0.36, p = 0.004).
The concentrations of Galectin-9 in healthy controls correlated with age (Spearman r = 0.42, p = 0.039). Furthermore, the gender composition of the control group was different from the patient cohorts. To account for these possible confounders an ANCOVA model was created, in which statistically significant differences between all groups were still present when age and gender were controlled for (Table 3). 4. Discussion In this study, we have demonstrated that the Galectin-9 concentration in CSF is increased in patients with SPMS. To the best of our knowledge, this is a novel finding that has not been reported before. In contrast to other candidate biomarkers of SPMS, such as YKL-40 (Malmestrom et al., 2014) and sCD28 (Komori et al., 2015), the concentrations of Galectin-9 did not correlate with traditional measures of inflammation. On the other hand, Galectin-9 correlated with the number of lesions on T1W images suggesting that at least part of the CSF Galectin-9 is produced within those lesions, supporting the notion of compartmentalized inflammation.
Table 3 Pairwise comparisons of patients from the combined cohort with correction for age and gender. Group 1
Group 2
Difference
CI
p-Value
Control Control RRMS
RRMS SPMS SPMS
69.8 126 56.5
(24.8–115) (77.9–175) (6.6–106)
0.003 b0.001 0.027
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
SPMS is characterized by fewer and milder relapses (Lublin and Reingold, 1996; Sospedra and Martin, 2005), less radiological activity (Filippi et al., 1997; Koziol et al., 1998), continuous deterioration of neurologic function(Confavreux et al., 2003) and by the development of chronically active white matter lesions. These lesions contain a demyelinated core with few T cells, which is surrounded by a rim of microglia nodules and activated astrocytes (Frischer et al., 2009; Prineas et al., 2001). Such slowly expanding lesions are believed to increase in size over time, contributing to demyelination, axonal damage and disability. It is well known that lesions on T1W images may evolve into black holes without showing evidence of contrast uptake, which probably is the MRI correlate of the chronically active lesion (Giannetti et al., 2014). While it is not possible to directly visualize microglia activation with MRI, two recent PET studies demonstrated increased binding of a marker for activated microglia (11C-PK11195) in 57–76% of lesions seen on T1W images (Giannetti et al., 2014; Rissanen et al., 2014). We saw a robust correlation between the concentrations of Galectin-9 and the number of lesions on T1W images and it seems likely that the source of CSF Galectin-9 is located within such lesions. On the other hand, concentrations of Galectin-9 did not correlate with measures of inflammation such as the number of Gd+ lesions, IgG index or CSF cell count nor were they higher in patients with clinical relapse or Gd + lesions. This suggests that Galectin-9 production in the CSF is essentially independent of adaptive immunity and we believe that Galectin-9 production is mainly driven by innate immunity intimately connected with progressive disease. Astrocyte and microglia interaction through Galectin-9 and TNF-α may play a crucial role to maintain the structure of the chronically active white matter lesion. It has previously been shown that Galectin-9 is produced within the CNS by activated astrocytes (Anderson et al., 2007; Stancic et al., 2011), which are abundant within the chronically active white matter lesions (Frischer et al., 2009). Galectin-9 production in astrocytes is primarily induced by TNF-α and to a lesser degree by other pro-inflammatory cytokines such as IL-1β and IFN-γ, whereas Galectin-9 production is not influenced by the anti-inflammatory cytokines IL-6, IL-10, and IL-13 (Steelman et al., 2013). Moreover, astrocyte-derived Galectin-9 in turn enhances microglial TNF production (Steelman and Li, 2014), creating favorable conditions for self-perpetuating inflammation beyond control of adaptive immunity. TNF-α has also been shown to be toxic to oligodendrocytes (Selmaj and Raine, 1988). Oligodendrocytes in close proximity to the rim of microglia nodules would be vulnerable to TNF-α mediated necroptosis further stimulating microglia, leading to a slowly expanding lesion. In theory, blockade of the astrocyte–microglia interaction by e.g. TNF inhibitors could be beneficial for treatment of SPMS, but this approach could also be dangerous since it is well established that Galectin-9 is a negative regulator of adaptive immunity (Zhu et al., 2011). Within the chronically active white matter lesion the high concentration of Galectin-9 creates a microenvironment which is very unfavorable to the survival of encephalitogenic T cells which are prone to Galectin-9 mediated apoptosis. It has been demonstrated that MBP-specific T cells from mice are prone to Galectin-9 mediated apoptosis when cocultured with TNF primed astrocytes (Steelman et al., 2013). Furthermore, the TNF-inhibitor lenercept has been tried for RRMS and was found to precipitate acute inflammatory lesions and exacerbations (1999). Treatment with other TNF-inhibitors probably also increases the risk of developing MS (Solomon et al., 2011). TNF deficient mice also develop severe neurological impairment with high mortality when experimental autoimmune encephalitis is induced (Liu et al., 1998). Although the mechanism behind the detrimental effect of TNF-inhibitors in MS is not known, it is possible that decreased CNS Galectin-9 production leading to increased survival of encephalitogenic T cells is a contributing factor. Thus a potentially beneficial effect of TNF-inhibitors in SPMS, might very well be overshadowed by increased severity of relapses.
43
We used two independent cohorts to study Galectin-9 in CSF with very similar results, suggesting that these results can be generalized to the wider MS population. Nevertheless some minor differences between the two cohorts were noted. RRMS patients from cohort B had on average somewhat higher Galectin-9 concentrations than patients from cohort A. Most of the RRMS patients in cohort A were sampled at or in close proximity to diagnosis, whereas patients from cohort B were a cross section of a typical outpatient clinic. Age and disease duration are risk factors for development of SPMS (Confavreux, 2006; Scalfari et al., 2014), which were higher in cohort B. Since Galectin-9 concentration may increase gradually in the transition from RRMS to SPMS it is not unlikely that some of the RRMS patients in cohort B were patients in transition to SPMS. Several questions still remain open. Whether high concentrations of Galectin-9 in RRMS patients predict conversion to clinically manifest SPMS needs to be addressed in a longitudinal cohort of RRMS patients followed for a long period of time. Moreover, Galectin-9 could serve as a biomarker for therapeutic effect of drugs targeting the astrocyte–microglia axis, such as minocycline, which could be explored in a clinical trial. Finally, the therapeutic potential in Galectin-9 inhibition should be considered. It was recently reported that Galectin-9 was able to promote TNF production in microglia independently of Tim-3 (Steelman and Li, 2014). If this molecular mechanism can be understood, it may provide a novel target for drugs to treat SPMS, which may be a safer alternative than e.g. TNF-inhibitors. 5. Conclusions Several lines of evidence point to the importance of astrocyte– microglia interaction in the pathogenesis of SPMS and Galectin-9 is a key molecule in astrocyte–microglia crosstalk. In the present study Galectin-9 concentrations were higher in CSF from SPMS patients. Furthermore, Galectin-9 levels were not influenced by traditional measures of inflammatory activity, suggesting that Galectin-9 reflects activity in the innate rather than the adaptive immune system. Thus, Galectin-9 may be a biomarker of the pathophysiological process that underlies SPMS that deserves to be explored further. Financial support This work was supported by a donation from Lars Tenerz; the Selander Foundation; Åke Löwnertz Foundation for Neurological Research; the MÅH Ländell Foundation; and Uppsala University Hospital. Conflicts of interest The authors report no conflict of interest. Author contributions JB designed the study. AS performed the lumbar punctures and collected clinical data from cohort A and JB did the same from cohort B. JB performed the CSF analyses and the analyses of MR images. JB wrote the draft and both authors provided creative input and approved of the final manuscript. References Anderson, A.C., Anderson, D.E., Bregoli, L., Hastings, W.D., Kassam, N., Lei, C., Chandwaskar, R., Karman, J., Su, E.W., Hirashima, M.,., Bruce, J.N.,., Kane, L.P., Kuchroo, V.K., Hafler, D.A., 2007. Promotion of tissue inflammation by the immune receptor Tim-3 expressed on innate immune cells. Science 318, 1141–1143. Barondes, S.H., Castronovo, V., Cooper, D.N., Cummings, R.D., Drickamer, K., Feizi, T., Gitt, M.A., Hirabayashi, J., Hughes, C., Kasai, K., et al., 1994. Galectins: a family of animal beta-galactoside-binding lectins. Cell 76, 597–598. Confavreux, C., 2006. Natural history of multiple sclerosis: a unifying concept. Brain 129, 606–616.
44
J. Burman, A. Svenningsson / Journal of Neuroimmunology 292 (2016) 40–44
Confavreux, C., Vukusic, S., Adeleine, P., 2003. Early clinical predictors and progression of irreversible disability in multiple sclerosis: an amnesic process. Brain 126, 770–782. Filippi, M., Rossi, P., Campi, A., Colombo, B., Pereira, C., Comi, G., 1997. Serial contrastenhanced MR in patients with multiple sclerosis and varying levels of disability. Am. J. Neuroradiol. 18, 1549–1556. Frischer, J.M., Bramow, S., Dal-Bianco, A., Lucchinetti, C.F., Rauschka, H., Schmidbauer, M., Laursen, H., Sorensen, P.S., Lassmann, H., 2009. The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain 132, 1175–1189. Giannetti, P., Politis, M., Su, P., Turkheimer, F., Malik, O., Keihaninejad, S., Wu, K., Reynolds, R., Nicholas, R., Piccini, P., 2014. Microglia activation in multiple sclerosis black holes predicts outcome in progressive patients: an in vivo [11C](R)-PK11195-PET pilot study. Neurobiol. Dis. 65, 203–210. Komori, M., Blake, A., Greenwood, M., Lin, Y.C., Kosa, P., Ghazali, D., Winokur, P., Natrajan, M., Wuest, S.C., Romm, E., Panackal, A.A., Williamson, P.R., Wu, T., Bielekova, B., 2015. CSF markers reveal intrathecal inflammation in progressive multiple sclerosis. Ann. Neurol. Koziol, J., Wagner, S., Adams, H., 1998. Assessing information in T2-weighted MRI scans from secondary progressive MS patients. Neurology 51, 228–233. Liu, J., Marino, M.W., Wong, G., Grail, D., Dunn, A., Bettadapura, J., Slavin, A.J., Old, L., Bernard, C.C., 1998. TNF is a potent anti-inflammatory cytokine in autoimmunemediated demyelination. Nat. Med. 4, 78–83. Lublin, F., Reingold, S., 1996. Defining the clinical course of multiple sclerosis: results of an international survey. Neurology 46, 907–911. Malmestrom, C., Axelsson, M., Lycke, J., Zetterberg, H., Blennow, K., Olsson, B., 2014. CSF levels of YKL-40 are increased in MS and replaces with immunosuppressive treatment. J. Neuroimmunol. 269, 87–89. Mayo, L., Quintana, F.J., Weiner, H.L., 2012. The innate immune system in demyelinating disease. Immunol. Rev. 1, 170–187. Meinl, E., Krumbholz, M., Derfuss, T., Junker, A., Hohlfeld, R., 2008. Compartmentalization of inflammation in the CNS: a major mechanism driving progressive multiple sclerosis. J. Neurol. Sci. 274, 42–44. Oomizu, S., Arikawa, T., Niki, T., Kadowaki, T., Ueno, M., Nishi, N., Yamauchi, A., Hattori, T., Masaki, T., Hirashima, M., 2012. Cell surface galectin-9 expressing Th cells regulate Th17 and Foxp3+ Treg development by galectin-9 secretion. PLoS One 7, e48574. Polman, C.H., Reingold, S.C., Banwell, B., Clanet, M., Cohen, J.A., Filippi, M., Fujihara, K., Havrdova, E., Hutchinson, M., Kappos, L., Lublin, F.D., Montalban, X., O'connor, P., Sandberg-Wollheim, M., Thompson, A.J., Waubant, E., Weinshenker, B., Wolinsky, J.S., 2011. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 69, 292–302. Prineas, J.W., Kwon, E.E., Cho, E.S., Sharer, L.R., Barnett, M.H., Oleszak, E.L., Hoffman, B., Morgan, B.P., 2001. Immunopathology of secondary-progressive multiple sclerosis. Ann. Neurol. 50, 646–657.
Rissanen, E., Tuisku, J., Rokka, J., Paavilainen, T., Parkkola, R., Rinne, J.O., Airas, L., 2014. In vivo detection of diffuse inflammation in secondary progressive multiple sclerosis using PET imaging and the radioligand 11C-PK11195. J. Nucl. Med. Scalfari, A., Neuhaus, A., Daumer, M., Muraro, P.A., Ebers, G.C., 2014. Onset of secondary progressive phase and long-term evolution of multiple sclerosis. J. Neurol. Neurosurg. Psychiatry 85, 67–75. Seki, M., Oomizu, S., Sakata, K.M., Sakata, A., Arikawa, T., Watanabe, K., Ito, K., Takeshita, K., Niki, T., Saita, N., Nishi, N., Yamauchi, A., Katoh, S., Matsukawa, A., Kuchroo, V., Hirashima, M., 2008. Galectin-9 suppresses the generation of Th17, promotes the induction of regulatory T cells, and regulates experimental autoimmune arthritis. Clin. Immunol. 127, 78–88. Selmaj, K.W., Raine, C.S., 1988. Tumor necrosis factor mediates myelin and oligodendrocyte damage in vitro. Ann. Neurol. 23, 339–346. Solomon, A.J., Spain, R.I., Kruer, M.C., Bourdette, D., 2011. Inflammatory neurological disease in patients treated with tumor necrosis factor alpha inhibitors. Mult. Scler. 17, 1472–1487. Sospedra, M., Martin, R., 2005. Immunology of multiple sclerosis. Annu. Rev. Immunol. 23, 683–747. Stancic, M., Van Horssen, J., Thijssen, V.L., Gabius, H.J., Van Der Valk, P., Hoekstra, D., Baron, W., 2011. Increased expression of distinct galectins in multiple sclerosis lesions. Neuropathol. Appl. Neurobiol. 37, 654–671. Steelman, A.J., Li, J., 2014. Astrocyte galectin-9 potentiates microglial TNF secretion. J. Neuroinflammation 11, 144. Steelman, A.J., Smith III, R., Welsh, C.J., Li, J., 2013. Galectin-9 protein is up-regulated in astrocytes by tumor necrosis factor and promotes encephalitogenic T-cell apoptosis. J. Biol. Chem. 288, 23776–23787. Teunissen, C.E., Petzold, A., Bennett, J.L., Berven, F.S., Brundin, L., Comabella, M., Franciotta, D., Frederiksen, J.L., Fleming, J.O., Furlan, R., Hintzen, R.Q., Hughes, S.G., Johnson, M.H., Krasulova, E., Kuhle, J., Magnone, M.C., Rajda, C., Rejdak, K., Schmidt, H.K., Van Pesch, V., Waubant, E., Wolf, C., Giovannoni, G., Hemmer, B., Tumani, H., Deisenhammer, F., 2009. A consensus protocol for the standardization of cerebrospinal fluid collection and biobanking. Neurology 73, 1914–1922. The Lenercept Multiple Sclerosis Study Group and The University of British Columbia MS/ MRI Analysis Group, 1999c. TNF neutralization in MS: results of a randomized, placebo-controlled multicenter study. Neurology 53, 457–465. Wada, J., Kanwar, Y.S., 1997. Identification and characterization of galectin-9, a novel beta-galactoside-binding mammalian lectin. J. Biol. Chem. 272, 6078–6086. Zhu, C., Anderson, A.C., Schubart, A., Xiong, H., Imitola, J., Khoury, S.J., Zheng, X.X., Strom, T.B., Kuchroo, V.K., 2005. The Tim-3 ligand galectin-9 negatively regulates T helper type 1 immunity. Nat. Immunol. 6, 1245–1252. Zhu, C., Anderson, A.C., Kuchroo, V.K., 2011. TIM-3 and its regulatory role in immune responses. Curr. Top. Microbiol. Immunol. 350, 1–15.