Teriflunomide's Effect on Glia in Experimental Demyelinating...

来自 : 发布时间：2024-12-25

Journal of NeuroimagingVolume 29, Issue 1 p. 52-61 Experimental Laboratory Research Free Access Teriflunomide\'s Effect on Glia in Experimental Demyelinating Disease: A Neuroimaging and Histologic Study Suyog Pol, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMichele Sveinsson, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMichelle Sudyn, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorNatan Babek, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorDanielle Siebert, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorNicola Bertolino, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorClaire M. Modica, orcid.org/0000-0002-7033-7632 Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMarilena Preda, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorFerdinand Schweser, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorRobert Zivadinov, Corresponding Author rzivadinov@bnac.net orcid.org/0000-0002-7799-1485 Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYCorrespondence: Address correspondence to: Robert Zivadinov, MD, PhD, FAAN, FEAN, FANA, Buffalo Neuroimaging Analysis Center, Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, 100 High Street, Buffalo, NY 14203, USA. E-mail: rzivadinov@bnac.netSearch for more papers by this author Suyog Pol, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMichele Sveinsson, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMichelle Sudyn, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorNatan Babek, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorDanielle Siebert, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorNicola Bertolino, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorClaire M. Modica, orcid.org/0000-0002-7033-7632 Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorMarilena Preda, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorFerdinand Schweser, Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYSearch for more papers by this authorRobert Zivadinov, Corresponding Author rzivadinov@bnac.net orcid.org/0000-0002-7799-1485 Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NYCorrespondence: Address correspondence to: Robert Zivadinov, MD, PhD, FAAN, FEAN, FANA, Buffalo Neuroimaging Analysis Center, Center for Biomedical Imaging at the Clinical Translational Science Institute, University at Buffalo, State University of New York, 100 High Street, Buffalo, NY 14203, USA. E-mail: rzivadinov@bnac.netSearch for more papers by this author Acknowledgments and disclosures: : This study was supported by Sanofi-Genzyme (Cambridge, MA). Research reported in this publication was also supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award Number UL1TR001412. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Suyog Pol, Michele Sveinsson, Michelle Sudyn, Natan Babek, Danielle Siebert, Nicola Bertolino, Claire M. Modica, and Marilena Preda have nothing to disclose. Ferdinand Schweser received personal compensation from Toshiba Canada Medical Systems Limited and Goodwin Procter LLP for speaking and consultant fees. He received financial support for research activities from SynchroPET Inc. and travel sponsorship from GE Healthcare and SynchroPET Inc. Robert Zivadinov received personal compensation from EMD Serono, Celgene, Genzyme-Sanofi, and Novartis for speaking and consultant fees. He received financial support for research activities from Genzyme-Sanofi, Novartis, Claret Medical, Protembo, IMS Health, and Mapi Pharma. Dr. Zivadinov serves on editorial board of J Alzh Dis, BMC Med, BMC Neurol, Vein and Lymphatics, and Clinical CNS Drugs. We are grateful for the assistance of Jacqueline Krawiecki, Doug Weston, Trina Rudra, and John Barbieri in helping with this study. We also thank Dr. Irwin Gelman and Renae Holtz, who produced the TMEV virus at the Genomics/shRNA Shared Resource at Roswell Park Cancer Institute, which is funded by NCI P30CA16056 and RPCI Core Grant. Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URLShare a linkShare onEmailFacebookTwitterLinked InRedditWechat ABSTRACT BACKGROUND AND PURPOSE Teriflunomide reduces disability progression and brain atrophy in multiple sclerosis patients. The exact mechanism of action by which teriflunomide exerts these effects is currently unknown. We assessed the effect of teriflunomide on brain glial cells in the Theiler\'s murine encephalomyelitis virus (TMEV) by using a histological approach in combination with neuroimaging. METHODS Forty-eight SJL female mice received an intracerebral injection of TMEV at 6–8 weeks of age and were then treated with teriflunomide (n = 24) or placebo (n = 24) for 9 months. They were examined with MRI and behavioral testing at 2, 6, and 9 months postinduction (mPI). Of those, 18 teriflunomide-treated and 17 controls mice were analyzed histologically at 9 mPI to sample from different brain regions for myelination status, microglial density, and oligodendroglial lineage. The histological and MRI outcomes were correlated.RESULTS Corpus callosum microglial density was numerically lower in the teriflunomide-treated mice compared to the control group (141.1 ± 21.7 SEM vs. 214.74 ± 34.79 SEM, Iba1+ cells/mm2, P = .087). Basal ganglia (BG) microglial density in the teriflunomide group exhibited a negative correlation with fractional anisotropy (P = .021) and a positive correlation with mean diffusivity (P = .034), indicating less inflammation and axonal damage. Oligodendroglial lineage cell and myelin density were not significantly different between treatment groups. However, a significant positive correlation between BG oligodendrocytes and BG volume (P = .027), and with N-acetyl aspartate concentration (P = .008), was found in the teriflunomide group, indicating less axonal loss.CONCLUSION Teriflunomide altered microglia density and oligodendrocytes differentiation, which was associated with less evident microstructural damage on MRI. Introduction Understanding of multiple sclerosis (MS) etiology has expanded greatly.1, 2 Current MS therapies focus on identification and control of the factors contributing to the inflammatory and neurodegenerative facets of the disease.3 Small molecules designed to target central nervous system (CNS) infiltratory inflammatory cells with higher metabolic rate aim to restrict such sporadic immune activity during MS relapses.3 Teriflunomide (Aubagio®, Sanofi-Genzyme) is one such Food and Drug Administration approved MS therapy.4-9 Teriflunomide targets T and B cells, and other metabolically active cells within the immune system.10 Teriflunomide is a noncompetitive reversible inhibitor of the mitochondrial enzyme dihydro-orotate dehydrogenase, suppressing de novo DNA synthesis of pyrimidine complexes in active cells.10 Preclinical studies have revealed teriflunomide\'s immunological effects. For example, in monophasic experimental autoimmune encephalomyelitis (EAE), teriflunomide was shown to significantly suppress disease progression even in uridine-supplemented animals.11 Parallel to its primary mode of action, teriflunomide has been proposed to participate in complementary mechanisms such as interfering with antigen presenting cell (APC)-T cell interactions, blocking TNFα-mediated NFκB activation, reducing endothelial cell adhesion molecule expression, inhibiting matrix metalloproteases, and cytokine secretion suppression.10, 12 Due to this proposed diversity of teriflunomide\'s activity, how this molecule generates positive outcomes in MS patients remains still unclear.13 In this study, we aimed to better characterize teriflunomide\'s effect on the glial cells within the brain. To this end, we utilized a demyelinating disease model in which direct immunization is not the primary driver. In contrast to EAE, Theiler\'s murine encephalomyelitis virus (TMEV) is an axonal viral infection-mediated demyelinating disease.14 In its biphasic disease course, the inability of TMEV-infected SJL mice to completely eliminate inflammation within the axons leads to an initial acute demyelination that is followed by prolonged inflammation of the axons resulting in progressively adverse demyelination and axonal loss.15 Teriflunomide treatment increased viral clearance and reduced serum TMEV antibody concentration in TMEV-infected mice.13 Furthermore, longitudinal MRI analysis of TMEV-infected mice suggested that teriflunomide suppressed cellular excitotoxicity in the thalamus (Th) and basal ganglia (BG).16 In this study, we aimed to understand how teriflunomide affects TMEV progression at two levels. First, we examined if teriflunomide was capable of modulating the density of microglial cells and myelin forming cells within white matter regions. Second, in conjunction with histological analysis at 9 months postinduction (mPI), we investigated the longitudinal associations16 of different MRI markers of neurodegeneration with histological observations. The study used 24 mice per treatment group. Because of death during MRI procedure or disease-related progression, 18 teriflunomide and 17 control-treated mice were preserved for tissue extraction at the final timepoint (9 mPI) and were assessed for myelin using solochrome staining. However, of these, five teriflunomide and five control mice brains were affected by prolonged storage, therefore the resulting sectioning and staining of these brains was suboptimal for accurate immunofluorescent staining-based histological assessment, and were therefore excluded. All procedures were carried out after approval from the Institutional Board for Animal Care and Use (IACUC) committee at the University at Buffalo. Four to five-week old female (n = 48 total) SJL mice were used in this study (Envigo, Indianapolis, IN, USA). The cell line BHK-21 (gifted by Dr. Howard Lipton, University Illinois Chicago)17 generating TMEV BeAn 8386 viral strain (working stock 20A) was used to produce the virus (Genomics/shRNA Shared Resource at Roswell Park Cancer Institute).18 Mice were sedated with intraperitoneal (IP) injection of Ketamine (50-100 mg/kg) and Xylazine (2-5 mg/kg), followed by intracerebral injection of 30 μL TMEV virus at 3 × 106 PFU concentration. Anesthesia was counteracted with IP injection of 2.1 mg/kg Yohimbine. Mice were kept warm, supplemented with 1–3 mL of saline, and monitored over the following 3 days. Blood collected at 3 mPI was tested for the presence of TMEV antibodies using mouse TMEV ELISA Kit (XpressBio, Thurmont, MD, USA).19 The previously published Lipton scale was used for scoring clinical disability.20 Animals were MRI scanned in a 9.4T (Biospec 94/20 USR) small animal Bruker scanner (Bruker Biospin, Ettlingen, Germany). MRI scanner was operated with ParaVision (version 5.1; Bruker Biospin). The 440 mT/m and 3440 T/m/s imaging gradient system and a cryogenically cooled dual-element transceiver coil were employed for scanning as well (CryoProbe, Bruker Biospin). The coil was placed over the head of the mouse and animals were physically stabilized using custom-made head fixation cushions and bite bar. Induction and maintenance of anesthesia and animal care were conducted as previously described.16 The magnetic resonance spectroscopy (MRS) and volumetric data were acquired and analyzed, as previously reported.16 Briefly, spectroscopic data were acquired three times in different brain regions of the hemisphere contralateral to the injection site using a STEAM pulse sequence. The spectroscopic voxel was localized in the cortex (Cx), BG, and Th, respectively. All spectra were analyzed using LCModel,22 and gamma-aminobutyric acid (GABA), glutamate, glutamine, and N acetyl-aspartate (NAA) metabolites with a Cramér-Rao lower bound value below 20% were converted into concentration ratios relative to creatine, a common internal standard for MRS.23 For measuring volumes, brain images acquired using a multiecho gradient echo (MEGRE) sequence were segmented.16 This automated segmentation was done using a previously described multiatlas approach.16 To generate the atlases, regions of interest (ROI) were outlined manually using 3D Slicer (www.slicer.org) in 10 scans from three different representative animals,24 with the visual aid of Mouse BIRN Atlasing Toolkit-ready Labeled Atlas v0.6.2.25 ROIs included the Cx, BG, Th, and corpus callosum (CC). In addition to these MRI sequences, diffusion tensor imaging (DTI) was also acquired for generating fractional anisotropy (FA) and mean diffusivity (MD) in the Cx, BG, Th, and CC. DTI was acquired using an axial 2D segmented echo planar imaging spin echo sequence, 5 milliseconds diffusion gradient, 11 milliseconds diffusion separation, 30 directions, 5 b0 images, 1,000 s/mm2 b-value per direction, 1.5 × phase partial Fourier acceleration, 2 × parallel imaging under-sampling, 4 segments, 20 × 15 mm field of view, 250 μm slice thickness, 55 slices, 22.8 milliseconds echo time, 13,750 milliseconds repetition time, and 128 × 32 matrix, resulting in a total acquisition time of 32 minutes. We reconstructed DTI images on a 256 × 192 matrix, resulting in a nominal voxel size of 78 × 78 × 250 μm3. DTI scans were analyzed using FSL to produce voxel-wise values of FA and MD images. The resulting FA and MD images were coregistered to the MEGRE image space using modified ANTS tools. Brain segmentation maps calculated from the MEGRE images were used for calculation of brain region-wise mean value for FA and MD. Mice that survived up to the terminal time point (9 mPI) were intracardiacally perfused after a fatal dose of sodium pento-barbital. The perfusion was accomplished using saline followed by 4% paraformaldehyde solution. The brain tissue was extracted and placed in saline solution, 6% sucrose and 15% sucrose solutions sequentially each for 1 day, followed by flash freezing, unembedded in dimethylbutane using dry ice/ethanol. The frozen tissue was stored at –80°C.26 Coronal cryo-sections (16 μm thick) were collected from the rostral end where the CC first appears contiguous, and were used for assessing CC, Cx, and BG. Relatively, more caudal coronal sections where lateral ventricles were barely visible were used for sampling from the Th. From each of these two regions, two sections were analyzed (Fig 1). Figure 1Open in figure viewerPowerPoint Description of brain regions analyzed for histology. Sections were collected from the two distinct regions as shown in panel A. The sagittal section diagram shown was downloaded from the Allen Brain Atlas. Two equivalent sections from each region were placed on the slide (total four sections per slide) as shown in B. C shows (red dotted box) positions of images from the cortex (CX), rostral lateral (RL) corpus callosum, rostral medial (RM) corpus callosum, and the basal ganglia (BG) in region I sections. Similarly, D shows the positions for caudal medial (CM), corpus callosum, and thalamus (TH) images in region II sections.The images were taken on both sides of the brain. Slides were allowed to warm up to room temperature and washed thrice with phosphate buffered saline solution (PBS). The slides were then placed in permeabilization solution (1% triton, 5% goat serum in PBS) solution for 15 minutes. The slides were then placed in blocking solution (.2% triton, 25% goat serum in PBS) for 1 hour at room temperature. The slides were incubated with primary antibodies overnight (1:400 dilution), except for CC1 staining (two nights, 1:50 dilution) at 4°C. The following day, the primary antibody-incubated slides were washed with PBS, slides were placed with blocking solution for 1 hour, and finally incubated with secondary antibodies for 2 hours. The cell nuclei were stained using DAPI (Sigma, St. Louis, MO, USA) for 5 minutes. The slides were then washed three times with PBS and a coverslip was mounted with Prolong Gold (Thermo-Fischer Scientific, Waltham, MA, USA) mounting media. The edges of the slides were sealed with nail enamel. We used rabbit anti Iba1 (Wako Chemicals, Japan), rabbit anti-olig2 (EMD Millipore, Burlington, MA, USA), and mouse anti-APC/CC1 (EMD Millipore) primary antibodies in this study. For fluorescence staining, we used goat anti-rabbit IgG Alexa-647, goat anti-rabbit IgG Alexa-594, and goat anti-mouse IgG Alexa-594 (Thermo-Fisher Scientific) secondary antibodies.26 The slides were allowed to reach room temperature, and washed thrice with PBS solution. The slides were placed in staining solution (.2% solochrome cyanine [Sigma], 5.6% K4Fe(CN)6-3H2O, 2.5% HCl in distilled water) for 20 minutes, followed by incubation in 5.6% K4Fe(CN)6-3H2O in distilled water for up to 5 minutes until the stain had generated visible contrast between the gray and white matter structures of the brain.27 The slides were then stained with DAPI solution for 10 minutes and washed thrice with PBS. Following this, the slides were dehydrated with sequential incubation in 75%, 95%, and 100% ethanol, followed by xylene. The cover slips were then mounted onto the slides using a xylene-based mounting medium (National Diagnostics, Atlanta, GA, USA ). Four images randomly positioned within the ROI within the brain sections were captured at 200 × magnification. The multichannel images were analyzed using automated Java scripts in-house generated for the open source software Fiji.28 Briefly, ROI was manually generated for each image to mark the anatomical boundaries and exclude damaged tissue regions, Automated quantification algorithms used these ROIs during image analysis. All the images were preprocessed using CLAHE plugin to enhance contrast between stained and unstained regions.29 Following this, to restrict the stain detection to cells present only in plane of the section, auto-thresholding plugin (set to Huang algorithm) in ImageJ was first applied to identify the borders for each of the nuclei stained with DAPI. Following this, dilate effect tool was used to generate an ROI around each in-plane cell. Finally, ITCN tool (Center for Bio-Image Informatics at University of California, USA) was used for counting the number of in-plane cells stained positively for markers Olig2, CC1, and Iba1. All the parameters were manually supervised to minimize the error rate. All the analyses were done using open source R-based statistics platform (version 3.3.4). For data extraction from the Fiji generated raw csv files, library \"reshape2” was used. Data summaries were generated using library \"dplyr.” For calculating Pearson correlations and the corresponding test P value, library \"psych” was used. For generation of graphs and tables, library \"ggplot2” was used. Between treatment arms, histological outcomes were compared using the chi-square test or the Student\'s t-test. Relationships between change in MRI and histological outcomes were analyzed using the Pearson correlation. The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant, and P .1 being considered a trend, using a two-tailed test. We determined the density of microglial Iba1-labeled cells within the MRI-assessed brain structures at 9 mPI. We detected a numerically lower microglial density in the CC in the teriflunomide versus the control-treated group (141.1 ± 21.7 SEM vs. 214.74 ± 34.79 SEM, Iba1+ cells/mm2, P = .087, Fig 2B, E, and F), possibly indicating lower inflammation, but we did not observe any numerical or statistical significant difference in the density of microglial cells measured in the BG, Cx, and Th (Fig 2A, C-E, and F). Figure 2Open in figure viewerPowerPoint Region-wise microglial density quantification in different brain regions. Up to four images were taken from each region of interest to assess the density of microglial cells. Each panel shows one representative image from teriflunomide- and control-treated mice. A shows representative images from the basal ganglia region, B shows cells from the corpus callosum, C shows cortex, and D shows cells from the thalamus. E shows a bar graph of the measured density of the Iba1+. Red bars refer to the teriflunomide-treated group and blue bars refer to control-treated group. The error bars represent the standard error of the mean. Panel F shows a table summarizing statistics for the measured parameters. CX = cortex; CC = corpus callosum; BG = basal ganglia; TH = thalamus. Scale bar: 25 μm. We also compared the 9 mPI MRI-determined measures with the region specific microglial densities (Table 1). Higher microglial density in the control group was associated with a higher BG volume (r=.76, P=.024). Similarly, there was a positive correlation between higher microglial density and higher Cx volume (r=.64, P=.077) in the control group, although it was not statistically significant. These correlations were not significant for the teriflunomide group. By contrast, decreased microglial density was related to increased FA in the BG region (r=−.74, P=.021) and decreased MD (r=.69, P=.034), indicating less inflammation and axonal damage. Table 1. Pearson Correlation between Microglial Density and MRI Measures in the Specific Regions in Teriflunomide- and Control-Treated Groups .024*The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. .036 .936 .021*The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. .034*The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. FA = fractional anisotropy; MD = mean diffusivity; QSM = quantitative susceptibility mapping; GABA = gamma-aminobutyric acid; GLN = glutamine; GLU = glutamate; NAA = N acetyl-aspartate; n = number. The Pearson correlation coefficient was used to explore association between microglial density and MRI markers in specific brain regions. The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. Teriflunomide\'s Effect on Oligodendroglial Density and Differentiation in Specific Brain Regions We quantified the density of Olig2-labeled oligodendrocyte lineage cells in different structures of the brain (Fig 3). As expected, the density of oligodendroglial cells was high in the CC for both the teriflunomide- and control-treated groups. However, we did not find any numerical or statistically significant differences between the two treatment groups for different brain regions. Similarly, there was a higher density of CC1-labeled mature oligodendroglial cells within the CC when compared to other brain regions in both treatment groups. However, we found a numerically higher density of CC1-labeled cells within the BG for the teriflunomide versus the control-treated group (530 ± 122 SEM in teriflunomide vs. 438 ± 84 SEM in the control-treated group). Finally, we did not observe any significant differences between teriflunomide and control-treated groups for percentage of mature olig2 cells (CC1+/Olig2+). Figure 3Open in figure viewerPowerPoint Quantification of oligodendroglial density and differentiation in different brain regions. To quantify the status of the oligodendroglial cells in the brain, we stained the sections for the oligodendrocyte lineage marker Olig2 and the mature oligodendrocyte marker CC1. Panels A-D show representative images from the teriflunomide- and control-treated groups each for basal ganglia, corpus callosum, cortex, and thalamus, respectively. In panel A, sample Olig2+/CC1+ (mature) cells are marked by arrows and * indicates Olig2+/CC1− (immature) cells. E-G show bar plots and summary statistics tables for Olig2 positive cell density (mm2), density of CC1-positive cells (mm2), and percentage mature oligodendrocytes (Olig2+/CC1+), respectively. Red bars refer to the teriflunomide-treated group and blue bars refer to the control-treated group. Error bars refer to the standard error of the mean. CX = cortex; CC = corpus callosum; BG = basal ganglia; TH = thalamus. Scale bar: 25 μm. We also compared the 9 mPI MRI-determined measures with the region specific oligodendrocyte lineage cells (Table 2). We did not find any significant correlations in the control group, but there was a trend for a correlation between a higher percentage of Olig2 cells positive for CC1 and higher GABA within the Cx (r = .71, P = .081). By contrast, in the teriflunomide-treated group, the higher percentage of Olig2 cells positive for CC1 was significantly correlated with the higher volume of the BG (r = .75, P = .027) and higher NAA concentration in the BG (r = .79, P = .008), suggesting less axonal loss. Table 2. Pearson Correlation Test Results between Oligodendrocyte Lineage Staining and MRI Measures in the Specific Regions in Teriflunomide- and Control-Treated Groups .027*The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. .008*The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. FA = fractional anisotropy; MD = mean diffusivity; QSM = quantitative susceptibility mapping; GABA = gamma-aminobutyric acid; GLN = glutamine; GLU = glutamate; NAA = N acetyl-aspartate; n = number. The Pearson correlation coefficient was used to explore association between oligodendroglial density, oligodendroglial differentiation, and MRI markers in specific brain regions. The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant (*), using a two-tailed test. We stained the brain sections with solochrome cyanine to determine if teriflunomide affected demyelinated lesions in the TMEV-infected brain. We assessed three separate areas, including caudal-medial, rostral-lateral, and rostral medial within the CC (Fig 1). We did not observe any significant difference in the percentage demyelinated area, demyelinated area mean intensity, or mean staining intensity in the lesion areas of the brain regions between the two treatment groups (Fig 4). Figure 4Open in figure viewerPowerPoint Assessment of solochrome-based myelin staining in different brain regions. To determine the extent of demyelination, brain sections were stained for myelin using solochrome cyanine staining. Panels A and B show representative images of the rostral corpus callosum collected from teriflunomide- and control-treated mice. The yellow borders represent the demyelinated regions within the CC detected using an automated algorithm. C-E show bar graphs and corresponding summary statistic tables showing percentage demyelination, mean stain intensity in myelinated regions, and mean stain intensity at lesion sites in different parts of the corpus callosum. Red bars refer to the teriflunomide-treated group and blue bars refer to the control-treated group. Error bars refer to the standard error of the mean. Scale bar: 50 μm. We also compared the 9 mPI MRI-determined measures with the region-specific solochrome cyanine stain (Table 3). There were no significant correlations between solochrome cyanine stain and MRI measures between the teriflunomide or control-treated groups. Table 3. Pearson Correlation Test Results between Myelin Measures and MRI Measures in the Specific Regions in Teriflunomide- and Control-Treated Groups FA = fractional anisotropy; MD = mean diffusivity; QSM = quantitative susceptibility mapping. The Pearson correlation coefficient was used to explore association between myelin stain intensity, stained area, nonstained, and MRI markers in specific brain regions. The P values were corrected for multiple testing using the Benjamini-Hochberg correction with P values .05 being considered significant, using a two-tailed test. Teriflunomide\'s role in decreasing MS inflammation and neurodegenration is under intensive investigation.4-10, 12 The present study examined the effects of teriflunomide on TMEV infection-mediated demyelinating disease course. With this disease model, we have shown previously that Cx-BG-Th connectivity may play a role in relaying the neurodegeneration between these regions, thus amplifying the disease\'s deleterious effects.16 As a continuation of these initial MRI-related findings, we conducted a histological analysis of brain glial population in the Cx, BG, Th, and CC. In TMEV-infected mice, the inflammation of the axons within the brain tissue mobilizes the macrophages to infiltrate across the blood-brain barrier.30, 31 Additionally, endogenous microglia are activated by day 40 PI in the TMEV model of chronic progressive disease.32, 33 It has been shown that teriflunomide attenuates the response of activated macrophages and microglia in the EAE Myelin oligodendrocyte glycoprotein (MOG) disease model.21, 34 In line with these findings, we found a numerically lower level of microglial activation within the CC in the teriflunomide-treated group. Regulation of microglial activation aides myelin maintenance as well. Microglia secreted factors target oligodendrocyte progenitors, promote proliferation, and eventual differentiation resulting in remyelination.35 Teriflunomide has been shown to promote oligodendrocyte differentiation and myelin formation in vitro.36 Therefore, in this study, along with cellular inflammatory response, we determined the density of oligodendroglial cells and their differentiation in the brains of TMEV-infected mice treated with teriflunomide or control. We did not find significant differences between the two groups with respect to quantitative assessment of the oligodendroglial lineage cells or in myelin staining. We also conducted solochrome staining for myelin assessment within the CC. We noted that solochrome staining was greatly reduced in all the TMEV-infected mice, implying loss of myelin within these brain regions.37 However, we did not observe any significant difference between the two treatment groups. MRI imaging-based assessment of the TMEV-infected mice allows for longitudinal tracking of structurally specific changes within the brain. Previously, we have reported MRI-measured decreased glutamate concentration in the BG region of teriflunomide-treated mice during early disease stages.16 Glutamate is a maker for excitotoxicity which can be induced by prolonged inflammation of the TMEV-infected brain.38, 39 We noted that decreased microglial density in the BG in the teriflunomide group was associated with increased FA and decreased MD. High FA is associated with higher connectivity between axonal bundles present in the structure of interest.40 Prolonged inflammation leading to a loss of tissue integrity results in a higher MD in specific brain regions.41 Thus, decreased microglial density in the teriflunomide-treated group was associated with less microstructural damage, as measured by DTI indices. In agreement with this, and only in the teriflunomide-treated group, were higher NAA concentrations and BG volumes associated with increased oligodendrocyte maturation. NAA concentration has been associated with increased oligodendroglial development42 and preserved neuronal integrity.43, 44 Furthermore, association of BG volume increase with oligodendroglial differentiation would suggest less volume loss in that structure. Together, our findings suggest that teriflunomide potentially suppresses TMEV-induced excitotoxicity in the BG, stimulated oligodendrocyte differentiation, and suppressed microglial density. Additionally, the teriflunomide-treated group showed a numerically lower microglial density within the CC, putatively indicating that teriflunomide suppressed white matter inflammation. However, we did not observe any MRI measures associated with this observation, perhaps due to the relatively smaller volume of this structure, and less pronounced effect size making the differences technically challenging to measure. Overall, teriflunomide\'s effects in the current study were limited to specific brain regions. Future studies should administer the drug IP to improve its efficacy, and dose ranging to confirm that the observed changes are mediated via the biological effects of the drug.13, 45 This could enable better characterization on teriflunomide\'s effect on the early stages of microglial cell proliferation and activation. Additionally, since the primary driver of hind limb paralysis in TMEV disease course is due to demyelinating lesions in the spinal cord white and gray matter damage, the effect of teriflunomide should be studied in that CNS compartment. In conclusion, we have shown altered associations between histological measures and MRI measures in the brain of TMEV-infected and teriflunomide-treated mice. Our findings suggest that teriflunomide altered the course of the TMEV disease. However, the effect of the teriflunomide on TMEV was limited to specific structures, ie, the BG and CC. In a clinical setting, association of pathology with MRI findings is difficult, and this study provides an important step in addressing this limitation. 1Dietz KC, Polanco JJ, Pol SU, etal. Targeting human oligodendrocyte progenitors for myelin repair. Exp Neurol 2016; 283: 489- 500. 2Lassmann H, van Horssen J, Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. 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Wiley Online Library 44Cifelli A, Arridge M, Jezzard P, etal. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002; 52: 650- 3. Wiley Online Library 45Pachner A, Libin L. Teriflunomide ameliorates disability progression in the Theiler\'s virus-induced demyelinating disease model of MS (abstract). Neurology 2013; 80(Suppl 7): P05.196. The full text of this article hosted at iucr.org is unavailable due to technical difficulties. Please check your email for instructions on resetting your password. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account. Can\'t sign in? Forgot your username? Enter your email address below and we will send you your username If the address matches an existing account you will receive an email with instructions to retrieve your username