Background

Background: An improved understanding of the impact of demyelination on multiple sclerosis (MS) related cognitive impairment is crucial for targeting and testing therapies with the potential to slow cognitive decline. Demyelination can be assessed using myelin water imaging, a quantitative magnetic resonance imaging (MRI) technique that measures signal from water in the myelin bilayers, providing a specific measure of myelin (myelin water fraction, MWF).

Objectives

Objective: To determine if there is an anatomical-functional relationship between myelin content and location with cognitive performance.

Methods

Methods: 76 MS participants (mean (SD) age:50.4y(10.6y), 51F) underwent T2 relaxation imaging to calculate MWF maps and cognitive testing (Symbol Digit Modalities Test (SDMT); Selective Reminding Test (SRT); Controlled Oral Word Association Test (COWAT); Brief Visuospatial Memory Test-Revised (BVMT-R)). Nonparametric permutation testing with FSL Randomise was used to determine which white matter (WM) MWF voxels were associated with cognitive test performance for each test (p<0.01, after multiple comparisons correction), creating test-specific maps of associated WM areas. Pearson ́s correlations assessed relationships between mean MWF in the cognitive test-specific WM areas and respective test scores. MS patients were categorized into cognitively impaired, mildly impaired and cognitively preserved groups based on published norms. Kruskal Wallis ANOVA with post hoc pairwise comparisons investigated mean MWF differences between cognitive groups.

Results

Results: MWF in several WM areas was significantly associated with SDMT, SRT and BVMT-R scores but not the COWAT. All tests found voxels within the corona radiata, posterior thalamic radiation and parts of the corpus callosum significant. Unique WM areas were the inferior longitudinal fasciculus and anterior cingulum for SDMT and the retrolenticular part of the internal capsule for the BVMT-R. Mean MWF in the test-specific WM areas correlated significantly with performance on the SDMT (r=0.58, p= 4.11 x 10^-8), SRT (r=0.56, p= 4.14 x 10^-7) and BVMT-R (r=0.56, p= 1.0 x 10^-6). Mean MWF in the test-specific WM areas was significantly lower in the cognitively impaired group relative to the cognitively preserved group (p<0.01).

Conclusions

Conclusions: There is an anatomical-functional relationship between myelin damage and cognitive performance in MS with unique WM patterns for different cognitive domains.

Background

Limiting MS progression requires characterization of the pathological processes that distinguish disease subtypes that progress from those that do not. CD5 antigen-like (CD5L) protein is predominantly macrophage-secreted with roles in modulating inflammation, lipid metabolism, and inhibiting cell apoptosis. Previous studies have found serum CD5L levels tend to decrease with age in healthy individuals yet are elevated in inflammatory conditions including chronic infections, psoriatic arthritis, and systemic lupus erythematosus.

Objectives

To compare serum CD5L levels in healthy controls (HC) to individuals with relapsing remitting MS (RRMS), secondary progressive MS (SPMS), primary progressive MS (PPMS), and clinically isolated syndrome (CIS).

Methods

The study cohort included 35 HC, 20 CIS, and 83 clinically definite MS (CDMS: 33 RRMS, 30 SPMS, 20 PPMS) participants recruited at the University of British Columbia MS clinic. Serum CD5L levels were assessed with a commercial enzyme-linked immunosorbent assay. Correlation, univariate and multivariate linear regression analyses were used to determine the relationship between CD5L levels and age, sex, disease duration (DD), and expanded disability status scale (EDSS).

Results

Compared to HC (median [IQR], 4.2 [2.8-6.3] μg/ml), SPMS had elevated serum CD5L (7.0 [4.6-8.5] μg/ml, p=0.0006). There were no differences between HC and RRMS (4.8 [3.5-5.8] μg/ml) or PPMS (4.3 [3.3-5.8] μg/ml), and CIS tended to have higher CD5L (5.1 [4.0-7.5] μg/ml, p=0.45). PPMS CD5L levels were low compared to SPMS (p=0.02), but this was not due to differences in age between subtypes. CD5L levels tended to correlate negatively with age in HC (p=0.06), but not in RRMS, SPMS, and PPMS. In contrast, CD5L levels correlated positively with age in the CIS group (p=0.03). Multivariate (p=0.009) and univariate (p=0.002) analyses showed increased CD5L in CDMS was associated with longer DD rather than differences in age, sex, or EDSS. Univariate analysis showed the pattern of increased CD5L in CDMS with longer DD seems to be driven mostly by SPMS (p=0.16).

Conclusions

Our studies suggest that CD5L titers could reflect differences underlying neurological mechanisms in PPMS and SPMS. The positive relationship between CD5L and DD in SPMS points to a distinct and chronic peripheral inflammatory profile compared to other subtypes. Further studies are needed to characterize the processes driving CD5L expression in MS and its potential utility as a biomarker of MS progression.

Background

Susac’s Syndrome (SuS) is a rare autoimmune endotheliopathy of the brain, retina and cochlea that mimics multiple sclerosis (MS). Lesions presumed to be microinfarcts classically involve the corpus callosum (CC). While one brain biopsy reported demyelination, and MRI studies have shown reduced fractional anisotropy in the CC, the specific processes underlying SuS pathology are not yet clear. Myelin water imaging (MWI) and diffusion basis spectrum imaging (DBSI) can provide information about microstructural changes occurring in SuS. MWI provides a quantitative measurement of myelin, termed the myelin water fraction (MWF). DBSI yields various physiologically relevant metrics characterized by water diffusion: the apparent diffusion coefficient (ADC) which relates to overall tissue damage; fractional anisotropy (FA), which decreases with white matter (WM) damage; and radial diffusivity (RD) which increases with myelin loss.

Objectives

Determine in vivo WM microstructural changes in Susac Syndrome compared to MS and healthy controls (HC) using MWI and DBSI.

Methods

Participants included 7 SuS patients following the proposed European Susac Consortium diagnostic criteria (mean age 43.3y (30-78y), 6F), 10 MS patients (mean age 43.2y (26-70y), 9F) and 10 HC (MWI: 44y (27-64y), 9F, DBSI: 35.9y (22-47y), 5F). 3T MRI included MWI (48-echo 3D GRASE sequence), DBSI (9 b-values, 0-1500 s/mm², 99 directions) and a 3DT1 for anatomical reference. The CC and global WM (non-lesional tissue) were segmented and registered using FSL and the JHU atlas. One-way ANOVA with Tukey correction compared CC and global WM between groups.

Results

CC: SuS MWF (0.09±0.01) was lower than MS (0.11±0.02, p=0.03) and trending lower than HC (0.11±0.02, p=0.07). SuS ADC (0.84 ± 0.08 x 10^-3μm²/ms) was higher than MS (0.73±0.04 x 10^-3μm²/ms, p<0.001) and controls (0.71±0.04 x 10^-3μm²/ms, p<0.001). SuS FA (0.82±0.02) was lower than HC (0.86±0.02, p= 0.02). SuS RD was higher (0.27±0.03 x 10^-3μm²/ms) than HC (0.21±0.01 x 10^-3μm²/ms, p=0.004) and trending higher than MS (0.23±0.05 x 10^-3μm²/ms, p=0.05).

Global WM: ADC and RD findings in the Global WM were similar to CC, i.e. ADC and RD were significantly higher in SuS compared to MS and HC (all p<=0.03). However, MWF and FA was insignificantly different between the groups.

Conclusions

We report the first use of MWI in SuS. Both CC and the global WM showed non-lesional myelin damage, which was more severe than MS.

Background

Deep grey matter (DGM) atrophy is a feature in all multiple sclerosis (MS) phenotypes. Studies have shown a strong relationship between DGM atrophy and clinical worsening but the utility of DGM volumes for predicting disease activity is largely unexplored, especially in early disease. Machine learning (ML) is a computational approach that can identify patterns that predict disease outcomes. In ML, the study dataset is divided into training and test subsets. The training set contains known outcomes, which the ML algorithm uses to form a prediction model, which is then evaluated on the test set.

Objectives

To develop an ML model for predicting new disease activity (clinical or MRI) within 2 years of a first clinical demyelinating event, using baseline DGM volumes. The motivation is to identify individuals at higher risk of new disease activity.

Methods

3D T1-weighted MRIs acquired within 90 days of a first clinical event in 140 subjects from a completed placebo-controlled trial of minocycline were used. Eighty subjects had new disease activity within 2 years, 28 were stable, and 32 withdrew early (unknown outcome). The stable and unknown groups were combined into 1 for ML training. Advanced Normalization Tools and FMRIB Software Library were used to segment the thalami, putamina, globi pallidi, and caudate nuclei. A random forest ML model was trained to predict new disease activity with feature vectors composed of individual DGM nuclei volumes and several other variables (e.g., minocycline vs. placebo, mono-focal vs. multi-focal CIS, normalized brain volume, and sex). Model performance was evaluated using 3-fold cross-validation, with 80% of the data used for training, and the rest for testing.

Results

Sequential elimination of variables ranked the least important by the trained model resulted in improved classification accuracy. Therefore, the less predictive variables were pruned from the feature vector. The best model used DGM volumes alone and achieved 82.1% accuracy, 87% precision, 81% recall and F1-score of 0.84 with area under the curve (AUC) of 0.76.

Conclusions

ML can learn patterns predictive of new disease activity within 2 years after a first clinical demyelinating event from baseline DGM volumes. This approach can potentially augment the many other clinical and demographic variables used in a typical MS clinical work up. Further investigation with larger data sets is warranted to determine generalizability of the approach.

Background

Intrathecal production of immunoglobulin (Ig) and the presence of cerebrospinal fluid (CSF)–specific oligoclonal bands (OCBs) are hallmarks of multiple sclerosis (MS) that persist throughout the disease course and treatment.

Objectives

To describe baseline (BL) correlations of CSF IgM and IgG production with CSF biomarkers and to assess the pharmacodynamic effects of ocrelizumab (OCR) treatment on these parameters in patients with relapsing MS (RMS) from the Ocrelizumab Biomarker Outcome Evaluation (OBOE) study (NCT02688985).

Methods

Seventy-nine of 100 total patients with RMS had available BL CSF samples for assessment of IgG OCBs, IgG and IgM (measured at University Medical Center Göttingen), with demographic, MRI and clinical parameters representative of the total RMS population. CSF samples at either 12 (n=22), 24 (n=24) or 52 (n=17) weeks postdose and from a 12-week reference arm (no OCR; n=16) were assessed for longitudinal changes.

Results

Median (interquartile range [IQR]) CSF levels at BL were as follows: IgG index, 0.79 (0.63–1.28); IgM index, 0.19 (0.11–0.33); CD3⁺ T cell number, 2.52 (0.80–5.61) cells/µL; CXCL13, 9.89 (3.91–31.50) pg/mL; CCL19, 47.95 (31.09–70.86) pg/mL; neurofilament light chain (NfL) 1280.0 (828.1–2968.9) pg/mL. At BL, IgG index and IgM index correlated moderately with levels of B cells (r=0.65, r=0.4 respectively), T cells (r=0.54, r=0.3 respectively) and CXCL13 (r=0.58, r=0.43 respectively), but not CCL19 or NfL. IgG index tended to decrease with OCR treatment and was significantly reduced by 52 weeks (n=17/79; median [IQR] change from BL −9.5% [−20.4% to −0.1%]; p<0.02) compared with stable levels in the reference arm. While IgG OCBs were detected at BL in all patients, IgG OCBs tended to decrease with OCR treatment, with three of 17 patients having no detectable IgG OCBs at 52 weeks. Reductions in IgM index were not observed with OCR treatment.

Conclusions

Baseline CSF levels of B cells, T cells and CXCL13 correlated with IgG index and to a lesser degree IgM index in patients with RMS from the OBOE study. Significant reductions were observed in IgG index with OCR treatment, along with a trend toward reduced OCBs, with three patients showing no detectable OCBs. These data suggest that OCR impacts CSF Ig production, a hallmark of MS not previously thought to be affected by B-cell depletion therapy. These 1-year observations need to be confirmed with longer-term data and correlated with clinical response.

Background

Myelin water imaging can isolate the magnetic resonance imaging (MRI) signal from myelin water, providing a quantitative measure associated with myelin, termed the myelin water fraction (MWF), which has been validated in histopathologic studies. The amyloid tracer ¹¹C Pittsburg compound B (PiB) also has an affinity for myelin and its binding can be reduced in MS lesions compared to normal-appearing white matter (NAWM). We sought to determine whether these myelin-sensitive techniques provide overlapping or complementary information in MS.

Objectives

To determine (1) whether MWF and PiB binding are decreased in lesions compared to NAWM and (2) if there is a correlation between MWF andPiB binding.

Methods

Eleven participants (5 relapsing-remitting MS, 3 secondary progressive MS, 3 primary progressive MS) were scanned on a 3T Philips MRI scanner, and on a Siemens HRRT PET scanner with an injection of 18 mCi ¹¹C PiB. Two RRMS participants were treated with glatiramer acetate 40 mg subcutaneously three times per week. MRI scans included structural scans for tissue segmentation and a myelin water sequence for MWF calculation. PIB binding was quantified with the Logan method-derived non-displaceable binding potential (BP_ND) using healthy grey matter from cerebellum as reference region. Lesion masks included all lesions within the imaging volume. Regional mean values of MWF and BP_ND were determined for NAWM and lesions.

Results

Lesions showed a 38% decreased MWF and a 23% decreased BP_ND compared to NAWM (MWF: lesions=0.08±0.01 vs NAWM=0.13±0.02, p<0.0001; BP_ND: lesions=0.91±0.08 vs NAWM=1.18±0.07, p<0.0001). A correlation was found between MWF and BP_ND when including both NAWM and lesions (r=0.73, p=0.0001). However, there was no correlation when fitting for NAWM or lesions alone (NAWM: r=-0.51, p=0.06; lesions: r=0.39, p=0.23).

Conclusions

In this pilot study, lesions showed a decrease in both myelin water and PiB binding as expected in demyelinated tissue. The partial correlation between MWF and PIB BP_ND suggests that each technique might have different sensitivity for detecting the severity of demyelination in heterogeneously affected tissue. PIB BP_ND values in NAWM were relatively homogenous. PIB BP_ND was good at discriminating between NAWM and lesions. MWF showed more subtle differences in myelination in NAWM and lesions. PET-PiB imaging and MWF appear to provide reliable measures of myelin abnormality in MS lesions. MWF may be able to provide additional information on the heterogeneity of demyelination in lesions and NAWM.

Background

People with antibodies to myelin oligodendrocyte glycoprotein (MOG) using reliable cell-based assays have heterogeneous course. Best management practices and outcome predictors are still uncertain.

Objectives

This study aimed to assess the treatment experience in a relapsing MOG positive cohort and the impact on disability accrual.

Methods

Retrospective chart review of (aquaporin4 negative) MOG antibody positive patients at University of British Columbia Multiple Sclerosis Clinic with relapsing disease, and minimum 1year follow-up.

Results

Of 49 MOG positive patients, 37(64.8% female) met inclusion criteria. Median age was 26 years (range 3-62; 10 pediatric cases) with median follow-up of 6years(range 1-36). Median time to second disease episode from first was 12 months (range 1-228); and to third (n=27) was 25 months (range 3-312). Median number total disease episodes was 3 (range 2-10).

For some, management decisions were initiated prior to MOG diagnosis. At first disease presentation 35/37 patients received acute therapy but only 1 started chronic therapy. First-line chronic therapies were later started in another 30 patients; in 35%(13/37) after second disease episode, and at the third in 27%(10/37). Most common were azathioprine(61%) and rituximab(19%). Sixteen patients(52%) required second line therapy, mostly due to adverse effects(62.5%) or disease activity(31%). Most common second line therapies were mycophenolate mofetil (MMF) or rituximab. Three patients required third line therapy.

17/37 patients had good outcome (EDSS<2) at last follow-up despite relapsing course, whilst 20(54%) had residual disability. Onset clinical phenotype distribution was similar between these two outcomes. 5% had persistent disability from disease onset, but mostly this developed from the second(19%) or third(16%) episode. 4/6 untreated patients had good outcome. Only 30% of the pediatric cohort vs 63% of the adult cohort had EDSS ≥2.0.

Conclusions

Chronic therapy was not typically started at disease onset, mostly due to initial absence of diagnosis. Azathioprine, MMF and rituximab were all effective therapies. Azathioprine was associated with high proportion of intolerance. Approximately half of patients recovered well from the initial episode; the rest accrued disability, typically from second or third disease episode, independent of clinical phenotype at onset. Further studies are required to identify factors influencing disability accrual, to enable earlier effective treatment in those at highest risk.