Multiscale networks in multiple sclerosis.

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Predictive value of retinal atrophy for cognitive decline across disease duration in multiple sclerosis.

BACKGROUND: We investigated the association between changes in retinal thickness and cognition in people with MS (PwMS), exploring the predictive value of optical coherence tomography (OCT) markers of neuroaxonal damage for global cognitive decline at different periods of disease. METHOD: We quantified the peripapillary retinal nerve fibre (pRFNL) and ganglion cell-inner plexiform (GCIPL) layers thicknesses of 207 PwMS and performed neuropsychological evaluations. The cohort was divided based on disease duration (≤5 years or >5 years). We studied associations between changes in OCT and cognition over time, and assessed the risk of cognitive decline of a pRFNL≤88 µm or GCIPL≤77 µm and its predictive value. RESULTS: Changes in pRFNL and GCIPL thickness over 3.2 years were associated with evolution of cognitive scores, in the entire cohort and in patients with more than 5 years of disease (p<0.01). Changes in cognition were related to less use of disease-modifying drugs, but not OCT metrics in PwMS within 5 years of onset. A pRFNL≤88 µm was associated with earlier cognitive disability (3.7 vs 9.9 years) and higher risk of cognitive deterioration (HR=1.64, p=0.022). A GCIPL≤77 µm was not associated with a higher risk of cognitive decline, but a trend was observed at ≤91.5 µm in PwMS with longer disease (HR=1.81, p=0.061). CONCLUSIONS: The progressive retinal thinning is related to cognitive decline, indicating that cognitive dysfunction is a late manifestation of accumulated neuroaxonal damage. Quantifying the pRFNL aids in identifying individuals at risk of cognitive dysfunction.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning.

BACKGROUND: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity. METHODS: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre. RESULTS: We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts. CONCLUSION: Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis.

BACKGROUND: Serum neurofilament light (sNfL) chain is a promising biomarker reflecting neuro-axonal injury in multiple sclerosis (MS). However, the ability of sNfL to predict outcomes in real-world MS cohorts requires further validation. OBJECTIVE: The aim of the study is to investigate the associations of sNfL concentration, magnetic resonance imaging (MRI) and retinal optical coherence tomography (OCT) markers with disease worsening in a longitudinal European multicentre MS cohort. METHODS: MS patients (n = 309) were prospectively enrolled at four centres and re-examined after 2 years (n = 226). NfL concentration was measured by single molecule array assay in serum. The patients' phenotypes were thoroughly characterized with clinical examination, retinal OCT and MRI brain scans. The primary outcome was disease worsening at median 2-year follow-up. RESULTS: Patients with high sNfL concentrations (⩾8 pg/mL) at baseline had increased risk of disease worsening at median 2-year follow-up (odds ratio (95% confidence interval) = 2.8 (1.5-5.3), p = 0.001). We found no significant associations of MRI or OCT measures at baseline with risk of disease worsening. CONCLUSION: Serum NfL concentration was the only factor associated with disease worsening, indicating that sNfL is a useful biomarker in MS that might be relevant in a clinical setting.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study.

BACKGROUND AND OBJECTIVES: Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker. METHODS: MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient's white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run. RESULTS: rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10-5), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80-0.83, p = 0.41-0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001). DISCUSSION: In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

Dynamics and Predictors of Cognitive Impairment along the Disease Course in Multiple Sclerosis.

(1) Background: The evolution and predictors of cognitive impairment (CI) in multiple sclerosis (MS) are poorly understood. We aimed to define the temporal dynamics of cognition throughout the disease course and identify clinical and neuroimaging measures that predict CI. (2) Methods: This paper features a longitudinal study with 212 patients who underwent several cognitive examinations at different time points. Dynamics of cognition were assessed using mixed-effects linear spline models. Machine learning techniques were used to identify which baseline demographic, clinical, and neuroimaging measures best predicted CI. (3) Results: In the first 5 years of MS, we detected an increase in the z-scores of global cognition, verbal memory, and information processing speed, which was followed by a decline in global cognition and memory (p < 0.05) between years 5 and 15. From 15 to 30 years of disease onset, cognitive decline continued, affecting global cognition and verbal memory. The baseline measures that best predicted CI were education, disease severity, lesion burden, and hippocampus and anterior cingulate cortex volume. (4) Conclusions: In MS, cognition deteriorates 5 years after disease onset, declining steadily over the next 25 years and more markedly affecting verbal memory. Education, disease severity, lesion burden, and volume of limbic structures predict future CI and may be helpful when identifying at-risk patients.

Regional grey matter microstructural changes and volume loss according to disease duration in multiple sclerosis patients.

The spatio-temporal characteristics of grey matter (GM) impairment in multiple sclerosis (MS) are poorly understood. We used a new surface-based diffusion MRI processing tool to investigate regional modifications of microstructure, and we quantified volume loss in GM in a cohort of patients with MS classified into three groups according to disease duration. Additionally, we investigated the relationship between GM changes with disease severity. We studied 54 healthy controls and 247 MS patients classified regarding disease duration: MS1 (less than 5 years, n = 67); MS2 (5-15 years, n = 107); and MS3 (more than15 years, n = 73). We compared GM mean diffusivity (MD), fractional anisotropy (FA) and volume between groups, and estimated their clinical associations. Regional modifications in diffusion measures (MD and FA) and volume did not overlap early in the disease, and became widespread in later phases. We found higher MD in MS1 group, mainly in the temporal cortex, and volume reduction in deep GM and left precuneus. Additional MD changes were evident in cingulate and occipital cortices in the MS2 group, coupled to volume reductions in deep GM and parietal and frontal poles. Changes in MD and volume extended to more than 80% of regions in MS3 group. Conversely, increments in FA, with very low effect size, were observed in the parietal cortex and thalamus in MS1 and MS2 groups, and extended to the frontal lobe in the later group. MD and GM changes were associated with white matter lesion load and with physical and cognitive disability. Microstructural integrity loss and atrophy present differential spatial predominance early in MS and accrual over time, probably due to distinct pathogenic mechanisms that underlie tissue damage.

In Vivo Molecular Changes in the Retina of Patients With Multiple Sclerosis.

Purpose: Raman spectroscopy allows molecular changes to be quantified in vivo from the tissues like the retina. Here we aimed to assess the metabolic changes in the retina of patients with multiple sclerosis (MS). Methods: We built a Raman spectroscopy prototype by connecting a scanning laser ophthalmoscope to a spectrophotometer. We defined the spectra of 10 molecules participating on energy supply, axon biology, or synaptic damage, which have been shown to be altered in the brain of patients with MS: cytochrome C, flavin adenine dinucleotide (FAD), nicotinamide adenine dinucleotide (NADH), N-acetyl-aspartate (NAA), excitotoxicity, glutamate, amyloid ß (Aß), τ and α-synuclein (SNCA), phosphatidyl-ethanolamine, and phosphatidyl-choline. We studied these molecules in a prospective cohort of patients with MS, either in the chronic phase or during relapses of acute optic neuritis (AON). Results: Significant changes to all these molecules were associated with age in healthy individuals. There was a significant decrease in NADH and a trend toward a decrease in NAA in patients with MS, as well as an increase in Aß compared with healthy controls. Moreover, NADH and FAD increased over time in a longitudinal analysis of patients with MS, whereas Aß diminished. In patients with acute retinal inflammation due to AON, there was a significant increase in FAD and a decrease in SNCA in the affected retina. Moreover, glutamate levels increased in the affected eyes after a 6-month follow-up. Conclusions: Alterations of molecules related to axonal degeneration are observed during neuroinflammation and show dynamic changes over time, suggesting progressive neurodegeneration.

Cortical fractal dimension predicts disability worsening in Multiple Sclerosis patients.

BACKGROUND: Fractal geometry measures the morphology of the brain and detects CNS damage. We aimed to assess the longitudinal changes on brain's fractal geometry and its predictive value for disease worsening in patients with Multiple Sclerosis (MS). METHODS: We prospectively analyzed 146 consecutive patients with relapsing-remitting MS with up to 5 years of clinical and brain MRI (3 T) assessments. The fractal dimension and lacunarity were calculated for brain regions using box-counting methods. Longitudinal changes were analyzed in mixed-effect models and the risk of disability accumulation were assessed using Cox Proportional Hazard regression analysis. RESULTS: There was a significant decrease in the fractal dimension and increases of lacunarity in different brain regions over the 5-year follow-up. Lower cortical fractal dimension increased the risk of disability accumulation for the Expanded Disability Status Scale [HR 0.9734, CI 0.8420-0.9125; Harrell C 0.59; Wald p 0.038], 9-hole peg test [HR 0.9734, CI 0.8420-0.9125; Harrell C 0.59; Wald p 0.0083], 2.5% low contrast vision [HR 0.4311, CI 0.2035-0.9133; Harrell C 0.58; Wald p 0.0403], symbol digit modality test [HR 2.215, CI 1.043-4.705; Harrell C 0.65; Wald p 0.0384] and MS Functional Composite-4 [HR 0.55, CI 0.317-0.955; Harrell C 0.59; Wald p 0.0029]. CONCLUSIONS: Fractal geometry analysis of brain MRI identified patients at risk of increasing their disability in the next five years.

Oligoclonal IgM bands in the cerebrospinal fluid of patients with relapsing MS to inform long-term MS disability.

BACKGROUND: Prognostic markers are needed to guide multiple sclerosis (MS) management in the context of large availability of disease-modifying drugs (DMDs). OBJECTIVE: To investigate the role of cerebrospinal fluid (CSF) markers to inform long-term MS outcomes. METHODS: Demographic features, IgM index, oligoclonal IgM bands (OCMB), lipid-specific OCMB, CSF neurofilament light chain protein levels, expanded disability status scale (EDSS), relapses and DMD use over the study period and peripapillary retinal nerve fiber layer (pRNFL) and ganglion cell plus inner plexiform layer (GCIPL) thicknesses in non-optic neuritis eyes (end of follow-up) were collected from relapsing MS (RMS) patients with CSF obtained ⩽2 years after MS onset prospectively followed at the Hospital Clinic of Barcelona. We assessed associations between CSF markers and MS outcomes using multivariable models. RESULTS: A total of 89 patients (71 females; median 32.9 years of age) followed over a median of 9.6 years were included. OCMB were associated with a 33% increase in the annualized relapse rate (ARR; p = 0.06), higher odds for high-efficacy DMDs use (OR = 4.8; 95% CI = (1.5, 16.1)), thinner pRNFL (ß = -4.4; 95% CI = (-8.6, -0.2)) and GCIPL (ß = -2.9; 95% CI = (-5.9, +0.05)), and higher rates to EDSS ⩾ 3.0 (HR = 4.4; 95% CI = (1.6, 11.8)) and EDSS ⩾ 4.0 (HR = 5.4; 95% CI = (1.1, 27.1)). No overall associations were found for other CSF markers. CONCLUSION: The presence of OCMB was associated with unfavorable long-term outcomes. OCMB should be determined in RMS to inform long-term prognosis.

Impact of Cognitive Reserve and Structural Connectivity on Cognitive Performance in Multiple Sclerosis.

Background: Cognitive reserve (CR) could attenuate the impact of the brain burden on the cognition in people with multiple sclerosis (PwMS). Objective: To explore the relationship between CR and structural brain connectivity and investigate their role on cognition in PwMS cognitively impaired (PwMS-CI) and cognitively preserved (PwMS-CP). Methods: In this study, 181 PwMS (71% female; 42.9 ± 10.0 years) were evaluated using the Cognitive Reserve Questionnaire (CRQ), Brief Repeatable Battery of Neuropsychological tests, and MRI. Brain lesion and gray matter volumes were quantified, as was the structural network connectivity. Patients were classified as PwMS-CI (z scores = -1.5 SD in at least two tests) or PwMS-CP. Linear and multiple regression analyses were run to evaluate the association of CRQ and structural connectivity with cognition in each group. Hedges's effect size was used to compute the strength of associations. Results: We found a very low association between CRQ scores and connectivity metrics in PwMS-CP, while in PwMS-CI, this relation was low to moderate. The multiple regression model, adjusted for age, gender, mood, lesion volume, and graph metrics (local and global efficiency, and transitivity), indicated that the CRQ (ß = 0.26, 95% CI: 0.17-0.35) was associated with cognition (adj R 2 = 0.34) in PwMS-CP (55%). In PwMS-CI, CRQ (ß = 0.18, 95% CI: 0.07-0.29), age, and network global efficiency were independently associated with cognition (adj R 2 = 0.55). The age- and gender-adjusted association between CRQ score and global efficiency on having an impaired cognitive status was -0.338 (OR: 0.71, p = 0.036) and -0.531 (OR: 0.59, p = 0.002), respectively. Conclusions: CR seems to have a marginally significant effect on brain structural connectivity, observed in patients with more severe clinical impairment. It protects PwMS from cognitive decline regardless of their cognitive status, yet once cognitive impairment has set in, brain damage and aging are also influencing cognitive performance.

Characterization of multiple sclerosis lesions with distinct clinical correlates through quantitative diffusion MRI.

Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis. Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions "in vivo" and correlate these to an individual's clinical profile. We evaluated this in a cohort of 59 multiple sclerosis patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. The magnetic resonance imaging protocol included conventional sequences to define focal lesions, and multi-shell diffusion imaging was used with b-values of 1000, 2000 and 3000 s/mm2 in 180 encoding directions. Quantitative diffusion properties on a macro- and micro-scale were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesion types were correlated with parameters of the disease. The combination of diffusion tensor imaging metrics (fractional anisotropy and radial diffusivity) and multi-compartment spherical mean technique values (microscopic fractional anisotropy and intra-neurite volume fraction) differentiated two type of lesions, with a prediction strength of 0.931. The B-type lesions had larger diffusion changes compared to the A-type lesions, irrespective of their location (P < 0.001). The number of A and B type lesions was similar, although in juxtacortical areas B-type lesions predominated (60%, P < 0.001). Also, the percentage of B-type lesion volume was higher (64%, P < 0.001), indicating that these lesions were larger. The number and volume of B-type lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P = 0.004, Bonferroni correction). Specifically, more and larger B-type lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance. Thus, by combining several microscopic and macroscopic diffusion properties, the severity of damage within focal lesions can be characterized, further contributing to our understanding of the mechanisms that drive disease evolution. Accordingly, the classification of lesion types has the potential to permit more specific and better-targeted treatment of patients with multiple sclerosis.

Retinal and brain damage during multiple sclerosis course: inflammatory activity is a key factor in the first 5 years.

Understanding of the role of focal inflammation, a treatable feature, on neuro-axonal injury, is paramount to optimize neuroprotective strategy in MS. To quantify the impact of focal inflammatory activity on the rate of neuro-axonal injury over the MS course. We quantified the annualized rates of change in peripapillary retinal nerve fiber layer, ganglion cell plus inner plexiform layer (GCIPL), whole-brain, gray matter and thalamic volumes in patients with and without focal inflammatory activity in 161 patients followed over 5 years. We used mixed models including focal inflammatory activity (the presence of at least one relapse or a new/enlarging T2-FLAIR or gadolinium- enhancing lesion), and its interaction with time adjusted by age, sex, use of disease-modifying therapies and steroids, and prior optic neuritis. The increased rate of neuro-axonal injury during the first five years after onset was more prominent among active patients, as reflected by the changes in GCIPL thickness (p = 0.02), whole brain (p = 0.002) and thalamic volumes (p < 0.001). Thereafter, rates of retinal and brain changes stabilized and were similar in active and stable patients. Focal inflammatory activity is associated with neurodegeneration early in MS which reinforces the use of an early intensive anti-inflammatory therapy to prevent neurodegeneration in MS.

Distance disintegration delineates the brain connectivity failure of Alzheimer's disease.

Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.

Using Acute Optic Neuritis Trials to Assess Neuroprotective and Remyelinating Therapies in Multiple Sclerosis.

Importance: Neuroprotective and remyelinating therapies are required for multiple sclerosis (MS), and acute optic neuritis (AON) is a potential condition to evaluate such treatments. Objective: To comprehensively assess key biological and methodological aspects of AON trials for testing neuroprotection and remyelination in MS. Design, Setting, and Participants: The AON-VisualPath prospective cohort study was conducted from February 2011 to November 2018 at the Hospital Clinic of University of Barcelona, Barcelona, Spain. Consecutive patients with AON were prospectively enrolled in the cohort and followed up for 18 months. Data analyses occurred from November 2018 to February 2019. Exposures: Participants were followed up for 18 months using optical coherence tomography, visual acuity tests, and in a subset of 25 participants, multifocal visual evoked potentials. Main Outcomes and Measures: Dynamic models of retinal changes and nerve conduction and their associations with visual end points; and eligibility criteria, stratification, and sample-size estimation for future trials. Results: A total of 60 patients (50 women [83%]; median age, 34 years) with AON were included. The patients studied displayed early and intense inner retinal thinning, with a thinning rate of approximately 2.38 µm per week in the ganglion cell plus inner plexiform layer (GCIPL) during the first 4 weeks. Eyes with AON displayed a 6-month change in latency of about 20 milliseconds, while the expected change in the eyes of healthy participants by random variability was 0.13 (95% CI, -0.80 to 1.06) milliseconds. The strongest associations with visual end points were for the 6-month intereye difference in 2.5% low-contrast letter acuity, which was correlated with the peripapillary retinal nerve fiber layer thinning (adjusted R2, 0.57), GCIPL thinning (adjusted R2, 0.50), and changes in mfVEP latency (adjusted R2, 0.26). A 5-letter increment in high-contrast visual acuity at presentation (but not sex or age) was associated with 6-month retinal thinning (1.41 [95% CI, 0.60-2.23] µm less peripapillary retinal nerve fiber layer thinning thinning; P = .001; adjusted R2, 0.20; 0.86 [95% CI, 0.35-1.37] µm less GCIPL thinning; P = .001; adjusted R2, 0.19) but not any change in multifocal visual evoked potential latency. To demonstrate 50% efficacy in GCIPL thinning or change in multifocal visual evoked potential latency, a 6-month, 2-arm, parallel-group trial would need 37 or 50 participants per group to test a neuroprotective or remyelinating drug, respectively (power, 80%; α, .05). Conclusions and Relevance: Acute optic neuritis is a suitable condition to test neuroprotective and remyelinating therapies after acute inflammation, providing sensitive markers to assess the effects on both processes and prospective visual recovery within a manageable timeframe and with a relatively small sample size.

Modified connectivity of vulnerable brain nodes in multiple sclerosis, their impact on cognition and their discriminative value.

Brain structural network modifications in multiple sclerosis (MS) seem to be clinically relevant. The discriminative ability of those changes to identify MS patients or their cognitive status remains unknown. Therefore, this study aimed to investigate connectivity changes in MS patients related to their cognitive status, and to define an automatic classification method to classify subjects as patients and healthy volunteers (HV) or as cognitively preserved (CP) and impaired (CI) patients. We analysed structural brain connectivity in 45 HV and 188 MS patients (104 CP and 84 CI). A support vector machine with k-fold cross-validation was built using the graph metrics features that best differentiate the groups (p < 0.05). Local efficiency (LE) and node strength (NS) network properties showed the largest differences: 100% and 69.7% of nodes had reduced LE and NS in CP patients compared to HV. Moreover, 55.3% and 57.9% of nodes had decreased LE and NS in CI compared to CP patients, in associative multimodal areas. The classification method achieved an accuracy of 74.8-77.2% to differentiate patients from HV, and 59.9-60.8% to discriminate CI from CP patients. Structural network integrity is widely reduced and worsens as cognitive function declines. Central network properties of vulnerable nodes can be useful to classify MS patients.

Immune tolerance in multiple sclerosis and neuromyelitis optica with peptide-loaded tolerogenic dendritic cells in a phase 1b trial.

There are adaptive T-cell and antibody autoimmune responses to myelin-derived peptides in multiple sclerosis (MS) and to aquaporin-4 (AQP4) in neuromyelitis optica spectrum disorders (NMOSDs). Strategies aimed at antigen-specific tolerance to these autoantigens are thus indicated for these diseases. One approach involves induction of tolerance with engineered dendritic cells (tolDCs) loaded with specific antigens. We conducted an in-human phase 1b clinical trial testing increasing concentrations of autologous tolDCs loaded with peptides from various myelin proteins and from AQP4. We tested this approach in 12 patients, 8 with MS and 4 with NMOSD. The primary end point was the safety and tolerability, while secondary end points were clinical outcomes (relapses and disability), imaging (MRI and optical coherence tomography), and immunological responses. Therapy with tolDCs was well tolerated, without serious adverse events and with no therapy-related reactions. Patients remained stable clinically in terms of relapse, disability, and in various measurements using imaging. We observed a significant increase in the production of IL-10 levels in PBMCs stimulated with the peptides as well as an increase in the frequency of a regulatory T cell, known as Tr1, by week 12 of follow-up. In this phase 1b trial, we concluded that the i.v. administration of peptide-loaded dendritic cells is safe and feasible. Elicitation of specific IL-10 production by peptide-specific T cells in MS and NMOSD patients indicates that a key element in antigen specific tolerance is activated with this approach. The results warrant further clinical testing in larger trials.

Magnetic resonance markers of tissue damage related to connectivity disruption in multiple sclerosis.

Patients with multiple sclerosis (MS) display reduced structural connectivity among brain regions, but the pathogenic mechanisms underlying network disruption are still unknown. We aimed to investigate the association between the loss of diffusion-based structural connectivity, measured with graph theory metrics, and magnetic resonance (MR) markers of microstructural damage. Moreover, we evaluated the cognitive consequences of connectivity changes. We analysed the frontoparietal network in 102 MS participants and 25 healthy volunteers (HV). MR measures included radial diffusivity (RD), as marker of demyelination, and ratios of myo-inositol, N-acetylaspartate and glutamate+glutamine with creatine in white (WM) and grey matter as markers of astrogliosis, neuroaxonal integrity and glutamatergic neurotoxicity. Patients showed decreased global and local efficiency, and increased assortativity (p < 0.01) of the network, as well as increased RD and myo-inositol, and decreased N-acetylaspartate in WM compared with HV (p < 0.05). In patients, the age-adjusted OR of presenting abnormal global and local efficiency was increased for each increment of 0.01 points in RD and myo-inositol, while it was decreased for each increment of 0.01 points in N-acetylaspartate (the increase of N-acetylaspartate reduced the risk of having abnormal connectivity), all in WM. In a multiple logistic regression analysis, the OR of presenting abnormal global efficiency was 0.95 (95% confidence interval, CI: 0.91-0.99, p = 0.011) for each 0.01 increase in N-acetylaspartate, and the OR of presenting abnormal local efficiency was 1.39 (95% CI: 1.14-1.71, p = 0.001) for each 0.01 increase in RD. Patients with abnormal efficiency had worse performance in attention, working memory and processing speed (p < 0.05). In conclusion, patients with MS exhibit decreased structural network efficiency driven by diffuse microstructural impairment of the WM, probably related to demyelination, astroglial and neuroaxonal damage. The accumulation of neuroaxonal pathological burden seems to magnify the risk of global network collapse, while demyelination may contribute to the regional disorganization. These network modifications have negative consequences on cognition.

Assessing Biological and Methodological Aspects of Brain Volume Loss in Multiple Sclerosis.

Importance: Before using brain volume loss (BVL) as a marker of therapeutic response in multiple sclerosis (MS), certain biological and methodological issues must be clarified. Objectives: To assess the dynamics of BVL as MS progresses and to evaluate the repeatability and exchangeability of BVL estimates with Jacobian Integration (JI) and Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) (specifically, the Structural Image Evaluation, Using Normalisation, of Atrophy-Cross-Sectional [SIENA-X] tool or FMRIB's Integrated Registration and Segmentation Tool [FIRST]). Design, Setting, and Participants: A cohort of patients who had either clinically isolated syndrome or MS was enrolled from February 2011 through October 2015. All underwent a series of annual magnetic resonance imaging (MRI) scans. Images from 2 cohorts of healthy volunteers were used to evaluate short-term repeatability of the MRI measurements (n = 34) and annual BVL (n = 20). Data analysis occurred from January to May 2017. Main Outcomes and Measures: The goodness of fit of different models to the dynamics of BVL throughout the MS disease course was assessed. The short-term test-retest error was used as a measure of JI and FSL repeatability. The correlations (R2) of the changes quantified in the brain using JI and FSL, together with the accuracy of the annual BVL cutoffs to discriminate patients with MS from healthy volunteers, were used to measure compatibility of imaging methods. Results: A total of 140 patients with clinically isolated syndrome or MS were enrolled, including 95 women (67.9%); the group had a median (interquartile range) age of 40.7 (33.6-48.1) years. Patients underwent 4 MRI scans with a median (interquartile range) interscan period of 364 (351-379) days. The 34 healthy volunteers (of whom 18 [53%] were women; median [IQR] age, 33.5 [26.2-42.5] years) and 20 healthy volunteers (of whom 10 [50%] were women; median [IQR] age, 33.0 [28.7-39.2] years) underwent 2 MRI scans within a median (IQR) of 24.5 (0.0-74.5) days and 384.5 (366.3-407.8) days for the short-term and long-term MRI follow-up, respectively. The BVL rates were higher in the first 5 years after MS onset (R2 = 0.65 for whole-brain volume change and R2 = 0.52 for gray matter volume change) with a direct association with steroids (ß = 0.280; P = .02) and an inverse association with age at MS onset, particularly in the first 5 years (ß = 0.015; P = .047). The reproducibility of FSL (SIENA) and JI was similar for whole-brain volume loss, while JI gave more precise, less biased estimates for specific brain regions than FSL (SIENA-X and FIRST). The correlation between whole-brain volume loss using JI and FSL was high (R2 = 0.92), but the same correlations were poor for specific brain regions. The area under curve of the whole-brain volume change to discriminate between patients with MS and healthy volunteers was similar, although the thresholds and accuracy index were distinct for JI and FSL. Conclusions and Relevance: The proposed BVL threshold of less than 0.4% per year as a marker of therapeutic efficiency should be reconsidered because of the different dynamics of BVL as MS progresses and because of the limited reproducibility and variability of estimates using different imaging methods.