Thalamic Glutamate as a Marker of Global Brain Pathology -MS

Thalamic Glutamate as a Marker of Global fountainhead Pathology -MSAuthor contri butionsLP rule conceptualisation of the write up, analysis and interpretation of information, write the disseminated multiple sclerosis for mind content.JR design conceptualisation of the study, data collection, analysis and interpretation of data, drafting the manuscript for intellectual content.IRB analysis and interpretation of data, revising the manuscript for intellectual content.GS analysis and interpretation of dataKZ data collectionRN design conceptualisation of the study, analysis and interpretation of data, drafting the manuscript for intellectual content.LP1DisclosuresLP no disclosures.JR no disclosures.IRV no disclosures.GS no disclosures.KZ no disclosures.RN Bayer, Biogen, Genzyme, Merck Serono, Roche honorarium for speaking, in ar outrankory boards. Biogen, Genzyme, Novartis funds for organising education, staff. Biogen, Novartis Principal investigator.LP2LP3Multipl e sclerosisMultiple sclerosis (MS) is characterised by demyelination and variable degrees of axonal loss and gliosis. plurality with MS (pwMS) present with arresting disturbances, spasticity, fatigue, ataxia, pain and urinary dysfunction1. The most common form of MS is relapsing-remitting and 85% of pwMS initially present with it, with most counterbalancetually progress to a secondary, imperfect tense human body2. Without adequate handling, 25% of pwMS become wheelchair-bound3.Charcot was the first to describe the insurgent demyelinating boldness as a hallmark of MS in the late nineteenth century4. While sporting re knock over lesions (WML) contribute to disability5,6, they argon likely not its only drive. Recent evidence validates the concept that grey count lesions (GML) and shrivel are likely contributors to disability7,8. Furthermore, recent studies have looked at diffuse axonal loss and support the notion that this process drives long-term disability, due to a com bination of focal inflammation and cortical damage driven by meningeal inflammation9-13.Large clinical trials in MS infrequently agree the effect of therapies with head teacher lesion books and atrophy. This is due to the fact that as of today, no alter software exists which is able to consistently calculate WMLs14 and GMLs are grossly underestimated as they are not readily visible on magnetic resonance imaging15,16. Lastly, brain atrophy is hard to quantify, underside only be measured longitudinally and is bailiwick to non-tissue related (pseudo-atrophy) volume loss subsequent to disease modifying treatment17,18. There is an unmet accept for a simple biomarker that can act as a alternate for neural damage in MS for use in observational and interventional studies.NatalizumabNatalizumab (Tysabri) is a disease-modifying treatment abandoned intravenously as a periodic infusion19. In the UK it is licensed as a second-line treatment for severe, rapidly evolving, relapsing-rem itting MS. It is say against the 4 subunit of integrin on lymphocytes and acts as an immune-modulator by inhibiting their migration to the brain20,21. Compared to placebo, it has been shown to reduce revert rate by 68%. Furthermore, it reduced the risk of disability feeler by 42%, defined as a change in EDSS score sustained for 24 weeks21.charismatic resonance spectroscopyMagnetic resonance spectroscopy (MRS) is a non-invasive MRI sequence that allows identification and quantification of in vivo metabolites present in a small, preselected brain region. Proton nuclei (1H) are most usually employ in studies of the human brain due to their abundance and lofty sensitivity. MRS sequences distinguish in the midst of different metabolites by measuring the frequency at which 1H nuclei flip, which is in turn dependent on the molecular free radical carrying the foment content atom22. Measuring these metabolic changes allows researchers to gain an insight into changes at a cellular a nd molecular level in the brain, which cannot be acquired exploitation conventional MRI techniques23.The thalamus is a subcortical hub, with multiple reciprocal connections to both exsanguinous emergence tracts and cortical grey matter24. earlier studies evidenced the fact that it is sensitive to pathology occurring in opposite brain regions25. We speculated that by employ the thalamus as our region of fire (ROI), investigated metabolites would give a measure of global neuronal damage.AimsWe investigated thalamic MRS as a biomarker for global brain neuronal damage in MS by comparing service line metabolite submersions between pwMS and HCs. Metabolites that were found to be statistically probatively different between these two groups at baseline were investigated further. To additionally support utilise MRS imaging as a surrogate for global primordial nervous system pathology, we investigated the correlation between these metabolite concentrations in pwMS and enumerate lesion volume. In order to investigate whether thalamic MRS can be used to monitor treatment response, we measured changes in their concentration following treatment with the disease-modifying drug natalizumab. cosmosParticipants aged 21-65 underwent inclusion criteria screening. For the pwMS group, this included satisfying the McDonald criteria 2010, having super active MS and having been scheduled to initiate natalizumab treatment as part of routine NHS Case. side by side(p) ethics approval and written informed consent from participants, 17 pwMS and 12 HCs were recruited to the study.HCs underwent an MRI baseline scan while pwMS underwent a scan at baseline, and follow-up scans at 10 and 56 weeks after initiation of natalizumab treatment.acquirement of MRS dataAll experiments were carried out in the same Siemens 3T Magnetom Verio with a 32-channel receiver head coilLP4, used to acquire combined MRI and 1H-MRS scans. A magnetisation-prepared rapid gradient-echo sequence (MPRAGE ) was used to set about high-definition T1 weighted scans with the following parameters (repetition m (TR)= 2300secho time (TE)= 3ms everting time (TI)= 900 160 sagittal sections slice thickness 1.0mm in-plane resolution of 1x1mm2 . A hotshot voxel was placed over the leftover thalamus. In order to acquire the single-voxel scans, a Point-RESolved Spectroscopy sequence (PRESS) was used which had variable power and optimized relaxation delays (VAPOR) wet suppression (TR/TE, 2000/30ms) on a single 15-mm slab. This was reoriented to the T1 sequence sections ( portend 2). Four reference transients were used to align the data. The average of 96 transients was used for water suppressed spectra. The volume of evoke was 15x15x15mm, voxel size was 3.4mL. These parameters were in any case used to acquire reference MRS datasets without water suppression. This was through to obtain an internal water reference, which was used to scale metabolite signals. Double everting recovery pulse an d phase sensitive anastrophe recovery sequences were also acquired.Lesion volumesWhite and grey matter lesions were identified on 160-slice T1 scans with co-registered double inversion recovery sequences. Lesions were manually segmented in T1 space using the over-embellished College software ImSeg. The images obtained by this process LP5were used to derive proportions of grey matter, white matter and arrive lesion volumes. T1, double inversion recovery pulse and phase sensitive inversion recovery sequences were used to accord for presence of lesions in the thalamus.Data processingT1 and spectroscopy data were initially obtained from scans in dicom format (dcm). A modified MATLAB (v.2015b) script was used to convert the T1 scans into nifti format (nii), the single voxel spectroscopy scans into rda format (rda) and to generate cover files in rda format.LCModel (v.6.3-1K) was run by using a second modified MATLAB script, in order to obtain spectroscopy data from 0.2-4.0 ppm. The s oftware is a user-independent fitting routine that kit and caboodle by superimposing spectra obtained in vivo with high-resolution model spectra. It is an accurate and reliable system to quantify MRS data with short echo times (ET30ms)28,29.Partial volume subjects to explain different concentrations of water in the grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) were conducted by converting T1 sequences from dicom to nifti format, and segmenting the obtained images using MATLABs SPM8 toolbox. This allowed grading metabolite concentrations obtained from PRESS sequence with water-suppression, to the waters internal reference signal from the uninhibited water PRESS-sequence.The segmentation was used to calculate voxel proportions of GM, WM and CSF, which are in turn needed to obtain the water concentration (WCONC) value from the unsuppressed water reference signal used to estimate absolute concentrations of metabolites. Total WCONC value for each voxel were compu ted in accordance with Section 10.2.2.3 of the LCModel manual29.Eddy-current correction was performed by using LCModel. Relaxation effects were not corrected for, and therefore account metabolite concentrations go out differ from actual ones by an unknown factor. The latter is likely to be negligible, as all describe concentrations will deviate from actual concentrations by this same, unknown factor. As per LCModels manual, metabolite concentrations were multiplied by a factor of 1.04, which amounts to the proper(postnominal) gravity of brain tissue29, and were reported in mmol/L (mM).Data expulsionA heat map (Figure 4, right side) was created in order to check for voxel placement by using FSL view v.3.2.0. T1 sequences and mask files were reoriented to match the Montreal neurologic Institute standard template, followed by brain extraction from the surrounding tissue. T1 sequences and mask files were registered to standard space using the Montreal Neurological Institute templa te, which consists of 152 averaged brain T1 scans of 2mm resolution. The heat map is a depiction of each voxel mask overlaid onto the che2better template for T1 sequences taken from the mricron software.LP6 No MRS spectra were removed from the analysis owing to minimal inter-scan variability. Spectra generated by LCModel were checkered for overall data quality in accordance with the softwares instruction manual29. 2 baseline HC and 2 pwMS spectra were excluded from data analysis (Table 1).For a metabolite to be investigated, it had to be relevant to MS pathology as evidenced by previous studies, as well as to demonstrate sufficient data quality, measured by having Cramr -Rao get bounds ratio of 75% of soulfulness scans. Five metabolites were investigated choline-containing compounds (Cho), glutamate (Glu), myo-inositol (Ins), total creatine (tCr) and total n-acetylaspartate (tNAA) (Table 1). In a devoted subjects scan, metabolite concentrations with a Cramr-Rao lower bounds (CR LB) value of 15% were excluded from data analysis, as per LCModels manual of instructions. Concentrations exceeding 2 standard difference of opinions (2SD) out with the group mean were also excluded.QCa for entire spectraQC for individual metabolites Participant group in advance spectra QC(n) aft(prenominal) spectra QC(n)Metabolites (marker of)6 Participant groupBefore metabolite QC(n)After 1st QCf(n)After 2nd QCg(n)HCsb1210Cho1(membrane turnover)HCs1099pwMS BLc1715pwMS BL151212pwMS 10wd1616pwMS 10w161616pwMS 56we1616pwMS 56w161515Glu2(metabolism and neurotransmitter activity)HCs1066pwMS BL1598pwMS 10w161414pwMS 56w161514Ins3(glial marker)HCs1077pwMS BL151414pwMS 10w161514pwMS 56w161515tCr4(metabolic activity)HCs101010pwMS BL151514pwMS 10w161615pwMS 56w161616tNAA5(neuronal loss, mitochondrial activity)HCs10109pwMS BL151514pwMS 10w161616pwMS 56w161615statistical analysisPrism GraphPad (v.7) and IBM SPSS Statistics 24 software were used to conduct statistical analysis. Participant de mographics results are reported as mean and standard deviation (SD). Metabolite concentrations are reported as mean, standard error of measurement (SEM) and 95% confidence intervals. Parametric tests were used after testing for normal scattering of the data. Unpaired t-tests were used to liken metabolites between pwMS and HCs cross-sectionally. Pearsons coefficient was used to correlate between metabolite concentrations and bilateral lesion volumes. A linear mixed model was used to quantify longitudinal changes in metabolite concentrations in pwMS.MRS data were obtained from 17 pwMS (mean age (SD) was 41.6 (10.6), range 21-58 years) and 12 HCs (mean age (SD) was 41.9 (8.3), range 29-61 years). Mean time since diagnosis in years was 12.1 (10.6) and mean Expanded Disability Status Scale (EDSS) was 4.1 (1.1).People with MS, n17Age, mean (SD)41.6 (10.6)Sex, n (%)M6 (35)F11 (65)Years since diagnosis, mean (SD)12.1 (10.6)EDSS score, mean (SD)4.1 (1.1)Healthy checkers, n12Age, mean (SD) 41.9 (8.3)Sex, n (%)M9 (75)F3 (25) visit concentrations of glutamate are found at baseline in the thalami of people with highly active MSA statistically authoritative difference in the concentration of glutamate was found between the two groups (7.670.3456 in HCs and 6.550.232 in pwMS, p=0.016). No significant difference was found between the two groups using other metabolites.MetaboliteHealthy controls (n=10) People with MS (n=15) 95% CICho1. 690.0826,n=91.750.25, n=12-0.232 0.216Glu* 7.670.346, n=66.550.232, n=8*-2.00 0.253Ins3.980.250, n=74.450.281, n=14-0.452 1.380tCr340.134, n=105.420.150, n=14-0.350 0.510tNAA8.600.134, n=98.460.178, n=14-0.656 0.375 baseline thalamic glutamate concentrations in pwMS correlate negatively with total lesion volumesBaseline glutamate concentrations in pwMS negatively correlated with T1 scan total lesion volumes (n=8 r=-0.80, p=0.017 Figure 6). No other thalamic metabolite correlated with lesion volumes. Lesion volumes in HCs (n=6) were assum ed to be postal code and are depicted in Figure 6, but this parameter was excluded from statistical analyses. No lesions were found in the thalami of pwMS in this study.Glutamate concentration correlated even more strongly with left hemisphere lesion volumes (p=0.0091), an expected finding given that the left thalamus was used as the studys ROI. The correlation was least significant when using right hemisphere lesion volumes (p=0.030). These results are reported in Table 3.Sampled lesion load locationr, correlation coefficientp-value Left hemisphere-0.840.0091Right hemisphere-0.750.030 twain hemispheres/Total-0.800.016Thalamic glutamate concentrations increment following natalizumab treatmentGlutamate concentrations measured in the thalami of pwMS change magnitude significantly (p=LP7) between the 10 and 56 weeks (n=12 pairs of data-points) follow-up scans. At 56 weeks, no significant difference between the pwMS and HC groups was recorded, suggesting that glutamate levels had nor malisedLP8. No significant difference in glutamate concentration was recorded between baseline and 10 weeks follow-up scans (n=7 pairs of data-points) and between baseline and 56 weeks follow-up (n=7 pairs of data-points).LP9This observational study used proton magnetic resonance spectroscopy (1H-MRS) to compare metabolite concentrations in 17 pwMS and 12 HCs. Study findings indicate a lower baseline concentration of glutamate in the thalami of pwMS compared to HCs. In pwMS this correlated negatively with total baseline brain lesion volume, which supports our initial hypothesis that thalamic MRS specifically measuring glutamate can be used as a surrogate for global primaeval nervous system pathology. An increase in glutamate concentrations was recorded following natalizumab treatment between 10 and 56 weeks of follow-up. To our groups knowledge, this is the first 1H-MRS study to identify baseline cross-sectional differences in thalamic glutamate, correlate glutamate concentrations with total lesion volumes, and report longitudinal changes in thalamic glutamate following natalizumab treatment.Thalamic glutamate is a potency surrogate for total brain neuronal damage in highly active MSGlutamate, the chief telephone exchange nervous system excitatory neurotransmitter is mainly synthesized from glutamine31,32. In addition to its neurotransmitter role, glutamate concentration is closely linked to the Krebs cycle, which reflects the cells metabolic activity. Previous proton MRS studies in MS reported higher levels of glutamate in lesioned white matter of pwMS compared to HCs33,34. One of these studies also reported lower levels of glutamate in lesioned grey matter regions34. The limitation of using white or grey matter lesions as ROIs is the high heterogeneity of these brain regions. With regards to WMLs, their definition includes- among others- active, inactive and remyelinating lesions. As for grey matter, this can be bear upon by exposure to cytokines from me ningeal follicle-like structures or, similarly to WMLs, demyelination13,35,36. Current MRS imaging is unavailing to discriminate between these different pathologies. Therefore, metabolite concentrations obtained from these ROIs are likely to reflect the aforesaid(prenominal) local pathological changes, rather than global MS pathology. In contrast, the potential advantage of thalamic MRS is that the thalamus is rarely affected by local inflammation in MS37,38. Given that it is a subcortical hub highly connected with numerous other brain areas, this study hypothesised that the thalamus could be used as a biomarker of total brain neuronal damage in highly active MS. dickens results in our study support this hypothesis the decreased concentration of glutamate in pwMS and the negative correlation between glutamate and total brain lesion volume. Lesion volumes in MS have been found to correlate with axonal loss39 and disability40. Moreover, glutamate is mainly found in synaptic vesicles , therefore the decreased thalamic glutamate recorded in pwMS in this study could represent neuronal degeneration and synapse loss.Thalamic glutamate increases following natalizumab treatmentBetween 10 and 56 weeks of natalizumab treatment our group recorded a significant increase (p=,) in the concentration of thalamic glutamate in pwMS. At the end of the follow-up period, glutamate levels normalised, with no significant difference being recorded between pwMS and HC groups. No significant differences in glutamate concentration were found between baseline and 10 (n=x pairs?) and baseline and 56 weeks (n=x pairs?)LP10 follow-up scans. It can be hypothesised that the exceptional prove size of pairs of data-points between baseline and 56 weeks follow-up glutamate prevented us from recording an existing statistically significant difference. With regards to changes in glutamate between baseline and 10 weeks, there could be a significant change in glutamate concentration within this time frame, which was not picked up due to our limited sample size. It also cannot be excluded that thalamic MRS may take longer to respond to treatment.Previous published literature has shown lower glutamate concentrations in lesioned white matter of pwMS at baseline, which increased following treatment with natalizumab41. This effect can be attributed to the anti-inflammatory proprieties of natalizumab. By preventing production of nitrogen oxide and reactive oxygen species by macrophages, the drug could reduce axonal damage otherwise piddled by these compounds42,43.Study limitationsThe algorithmic program used my SPM8 is incapable of accurately differentiating between the brighter grey and surrounding white matter, as the image intensity level in the thalamus is very close to the intensity of white matter. Therefore the software records a higher white matter proportion in the thalamus than the true one. It should be however noted that this inaccuracy in measuring white/grey matter r atio should not cause any systematic error that would affect overall results.The studys HCs were adequately age-matched but poorly gender-matched to pwMS. Previous studies however reported no significant differences in any of the metabolite concentrations in the brain between different genders44. Therefore, no correction for a gender effect was made.The HC group only had a baseline scan, with no longitudinal data recorded. A useful longitudinal control group may be untreated pwMS. The absence of such a control group is currently however a common limitation, as people with highly active MS are nearly incessantly on treatment. Having no information on the natural history of thalamic MRS in pwMS, it is difficult to interpret the significance of longitudinal changes in glutamate seen in this study.Lastly, albeit the thalamus is rarely affected by inflammatory activity in pwMS, the presence of inflammatory lesions has been previously described45. Such lesions are a confounding factor a s they directly influence measured metabolite concentrations. However, based on T1, double inversion recovery pulse and phase sensitive inversion recovery sequences, no thalamic lesions were observed in our study.Future workStudies with larger sample sizes are needed to confirm our baseline findings, as well as to confidently interpret longitudinal changes in glutamate concentrations following natalizumab treatment. The presence of a pwMS untreated control group is not justifiable on ethical and healthy grounds, however fu