Decline In Multiple Sclerosis Research Articles

Increased intraindividual variability (IIV) in reaction time is the earliest indicator of cognitive change in MS: A two-year observational study

BackgroundCognitive decline in multiple sclerosis (MS) is common, but unpredictable, and increases with disease duration. As such, early detection of cognitive decline may improve the effectiveness of interventions. To that end, the Symbol Digit Modalities Test (SDMT) is effective in detecting slow processing speed as it relates to cognitive impairment, and intraindividual variability (IIV) observed in trials assessing continuous reaction time (RT) may be a useful indicator of early cognitive changes. Here, we will assess cognitive IIV changes in adults with early MS. MethodsAdults with relapsing-remitting MS (RRMS), <11 years since diagnosis, were recruited nationally. Baseline and two-year follow-up assessments included Brief International Cognitive Assessment in MS (BICAMS) and Cogstate computerized tests. Intraindividual variability in RT was calculated from psychomotor tasks and data were age-normalized. ResultsA total of 44 of the 66 participants completed follow-up (mean age, 34.0 ± 5.5 years; 66 % female; mean disease duration, 4.1 ± 2.9 years; median Expanded Disability Status Scale (EDSS) score, 1.5 [0 to 6.0]). Participants were grouped by SDMT z-score median split. Groups did not differ in demographics or clinical features. The higher baseline SDMT group was faster (p = 0.05) in RT and less variable (lower IIV, p = 0.001). At the two-year follow-up, the higher SDMT group showed increased variability (p = 0.05) compared to the lower SDMT group, with no significant RT or BICAMS changes. ConclusionsIn early MS, higher SDMT performance at baseline is associated with less cognitive variability but may indicate susceptibility to increased variability over time, highlighting the importance of monitoring IIV for early cognitive changes.

Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study

BackgroundPrevious studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination. ObjectiveUsing 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS. MethodsHigh-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests. ResultsSmaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing. ConclusionUltrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.

Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis.

During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.

Multi-modal neuroimaging signatures predict cognitive decline in multiple sclerosis: A 5-year longitudinal study

BackgroundCognitive impairment is a hallmark of multiple sclerosis (MS) but is usually an under-recorded symptom of disease progression. Identifying the predictive signatures of cognitive decline in people with MS (pwMS) over time is important to ensure effective preventative treatment strategies. Structural and functional brain characteristics as measured by various magnetic resonance (MR) methods have been correlated with variation in cognitive function in MS, but typically these studies are limited to a single MR modality and/or are cross-sectional designs. Here we assess the predictive value of multiple different MR modalities in relation to cognitive decline in pwMS over 5 years. MethodsA cohort of 43 pwMS was assessed at baseline and 5 years follow-up. Baseline (input) data consisted of 70 multi-modal MRI measures for different brain regions including magnetic resonance spectroscopy (MRS), diffusion tensor imaging (DTI) and standard volumetrics. Age, sex, disease duration and treatment were included as clinical inputs. Cognitive function was assessed using the Audio Recorded Cognitive Screen (ARCS) and the Symbol Digit Modalities Test (SDMT). Prediction modelling was performed using the machine learning package - GLMnet, where a penalised regression was applied to identify multi-modal signatures with the most predictive value (and the least error) for each outcome. ResultsThe multi-modal approach to neuroimaging was able to accurately predict cognitive decline in pwMS. The best performing model for change in total ARCS (tARCS) included 16 features from across the various MR modalities and explained 54 % of the variation in change over time (R2=0.54, 95 % CI=0.48–0.51). The features included nine MRS, four volumetric and two DTI parameters. The model also selected disease duration, but not treatment, as a predictive feature. By comparison, the best model for SDMT included several of the same above features and explained 39 % of the change over time (R2=0.39, 95 % CI=0.48–0.51). Conventional volumetric measures were about half as good at predicting change in tARCS score compared to the best multi-modal model (R2=0.26 95 % CI:0.22–0.29). The clinical interpretation of the best predictive model for change in tARCS showed that cognitive decline could be predicted with >90 % accuracy in this cohort (AUC=0.92, SE=0.86 - 0.94). ConclusionMulti-modal MRI signatures can predict cognitive decline in a cohort of pwMS over 5 years with high accuracy. Future studies will benefit from the inclusion of even more MR modalities e.g., functional MRI, quantitative susceptibility mapping, magnetisation transfer imaging, as well as other potential predictors e.g., genetic and environmental factors. With further validation, this signature could be used in future trials with high-risk patients to personalise the management of cognitive decline in pwMS, even in the absence of relapses.

A - 58 Verbal Fluency Word Generation Slope among Older Adults with MS.

The decreasing rate of within-person word generation in verbal fluency (VF) tasks, here referred to as slope, is associated with mild cognitive impairment and with lower grey matter volume in select regions. While VF is sensitive to cognitive decline in Multiple Sclerosis (MS), VF slopes have yet to be assessed in older adults with MS. We, therefore, examined VF slopes in letter and category VF among dementia-free older adults with and without MS. 84 community-dwelling adults with MS (Mage = 64.7) and 86 without MS (Mage = 70.8) completed standard 60-sec letter (F, A, S) and category (fruits, vegetables, animals) VF tasks; responses were recorded in 20-sec intervals for each iteration of the task. Linear regressions showed that MS was associated with lower total word generation on category, but not letter, VF after accounting for age, sex, race, education, and health status (95% CI, [-2.27, -0.98], p < 0.001). Linear mixed effects models showed that word generation declined during the course of both tasks (all p's < 0.001) in both groups; MS status did not moderate category or letter VF slopes. Extant literature on total letter and category VF word generation in MS is mixed. The current study indicates that in community-dwelling older adults MS was associated with lower total word scores in category but not letter VF. Negative word generation slopes were documented in category and letter VF irrespective of group status. These results suggest that time effects on word generation in VF tasks were generalizable to normal aging and MS.

Lexical and syntactic deficits analyzed via automated natural language processing: the new monitoring tool in multiple sclerosis.

Impairment of higher language functions associated with natural spontaneous speech in multiple sclerosis (MS) remains underexplored. We presented a fully automated method for discriminating MS patients from healthy controls based on lexical and syntactic linguistic features. We enrolled 120 MS individuals with Expanded Disability Status Scale ranging from 1 to 6.5 and 120 age-, sex-, and education-matched healthy controls. Linguistic analysis was performed with fully automated methods based on automatic speech recognition and natural language processing techniques using eight lexical and syntactic features acquired from the spontaneous discourse. Fully automated annotations were compared with human annotations. Compared with healthy controls, lexical impairment in MS consisted of an increase in content words (p = 0.037), a decrease in function words (p = 0.007), and overuse of verbs at the expense of noun (p = 0.047), while syntactic impairment manifested as shorter utterance length (p = 0.002), and low number of coordinate clause (p < 0.001). A fully automated language analysis approach enabled discrimination between MS and controls with an area under the curve of 0.70. A significant relationship was detected between shorter utterance length and lower symbol digit modalities test score (r = 0.25, p = 0.008). Strong associations between a majority of automatically and manually computed features were observed (r > 0.88, p < 0.001). Automated discourse analysis has the potential to provide an easy-to-implement and low-cost language-based biomarker of cognitive decline in MS for future clinical trials.

Radial diffusivity reflects general decline rather than specific cognitive deterioration in multiple sclerosis

Advanced structural brain imaging techniques, such as diffusion tensor imaging (DTI), have been used to study the relationship between DTI-parameters and cognitive scores in multiple sclerosis (MS). In this study, we assessed cognitive function in 61 individuals with MS and a control group of 35 healthy individuals with the Symbol Digit Modalities Test, the California Verbal Learning Test-II, the Brief Visuospatial Memory Test-Revised, the Controlled Oral Word Association Test, and Stroop-test. We also acquired diffusion-weighted images (b = 1000; 32 directions), which were processed to obtain the following DTI scalars: fractional anisotropy, mean, axial, and radial diffusivity. The relation between DTI scalars and cognitive parameters was assessed through permutations. Although fractional anisotropy and axial diffusivity did not correlate with any of the cognitive tests, mean and radial diffusivity were negatively correlated with all of these tests. However, this effect was not specific to any specific white matter tract or cognitive test and demonstrated a general effect with only low to moderate individual voxel-based correlations of <0.6. Similarly, lesion and white matter volume show a general effect with medium to high voxel-based correlations of 0.5-0.8. In conclusion, radial diffusivity is strongly related to cognitive impairment in MS. However, the strong associations of radial diffusivity with both cognition and whole brain lesion volume suggest that it is a surrogate marker for general decline in MS, rather than a marker for specific cognitive functions.

A more unstable resting-state functional network in cognitively declining multiple sclerosis.

Cognitive impairment is common in people with multiple sclerosis and strongly affects their daily functioning. Reports have linked disturbed cognitive functioning in multiple sclerosis to changes in the organization of the functional network. In a healthy brain, communication between brain regions and which network a region belongs to is continuously and dynamically adapted to enable adequate cognitive function. However, this dynamic network adaptation has not been investigated in multiple sclerosis, and longitudinal network data remain particularly rare. Therefore, the aim of this study was to longitudinally identify patterns of dynamic network reconfigurations that are related to the worsening of cognitive decline in multiple sclerosis. Resting-state functional MRI and cognitive scores (expanded Brief Repeatable Battery of Neuropsychological tests) were acquired in 230 patients with multiple sclerosis and 59 matched healthy controls, at baseline (mean disease duration: 15 years) and at 5-year follow-up. A sliding-window approach was used for functional MRI analyses, where brain regions were dynamically assigned to one of seven literature-based subnetworks. Dynamic reconfigurations of subnetworks were characterized using measures of promiscuity (number of subnetworks switched to), flexibility (number of switches), cohesion (mutual switches) and disjointedness (independent switches). Cross-sectional differences between cognitive groups and longitudinal changes were assessed, as well as relations with structural damage and performance on specific cognitive domains. At baseline, 23% of patients were cognitively impaired (≥2/7 domains Z < −2) and 18% were mildly impaired (≥2/7 domains Z < −1.5). Longitudinally, 28% of patients declined over time (0.25 yearly change on ≥2/7 domains based on reliable change index). Cognitively impaired patients displayed more dynamic network reconfigurations across the whole brain compared with cognitively preserved patients and controls, i.e. showing higher promiscuity (P = 0.047), flexibility (P = 0.008) and cohesion (P = 0.008). Over time, cognitively declining patients showed a further increase in cohesion (P = 0.004), which was not seen in stable patients (P = 0.544). More cohesion was related to more severe structural damage (average r = 0.166, P = 0.015) and worse verbal memory (r = −0.156, P = 0.022), information processing speed (r = −0.202, P = 0.003) and working memory (r = −0.163, P = 0.017). Cognitively impaired multiple sclerosis patients exhibited a more unstable network reconfiguration compared to preserved patients, i.e. brain regions switched between subnetworks more often, which was related to structural damage. This shift to more unstable network reconfigurations was also demonstrated longitudinally in patients that showed cognitive decline only. These results indicate the potential relevance of a progressive destabilization of network topology for understanding cognitive decline in multiple sclerosis.

Targeted cognitive game training enhances cognitive performance in multiple sclerosis patients treated with interferon beta 1-a

BackgroundPrevention of cognitive decline in Multiple Sclerosis (MS) is of major importance. We explored the effect of a 6 months computerized game training program on cognitive performance in MS patients with mild cognitive impairment.MethodsThis was a single-center, randomized prospective study. We enrolled in this study 100 eligible MS patients treated with Interferon-beta-1a (Rebif). All had mild cognitive impairment in either executive function or information processing speed. Patients were randomized 1:1 to either use the cognitive games platform by HappyNeuron (HN) or receive no intervention. Executive function and information processing speed scores were measured at 3 and 6 months from baseline to evaluate the effect of game training on cognitive scores.ResultsIn both executive function and information processing speed, the game Training group showed significant improvement after 3 and 6 months. The Non-Training group showed mild deterioration in both domains at 3 months, and further deterioration that became significant at 6 months in executive function. Furthermore, at 6 months, the percent of patients in the Training group that improved or remained stable in both cognitive domains was significantly higher compared to the Non-Training group.ConclusionsOur findings suggest that cognitive game training has a beneficial effect on cognitive performance in MS patients suffering from mild cognitive impairment. While further evaluation is required to assess the longevity of that effect, we nonetheless recommend to MS patients to be engaged in cognitive gaming practice as part of a holistic approach to treating their condition.

Cognitive Decline in Multiple Sclerosis Is Related to the Progression of Retinal Atrophy and Presence of Oligoclonal Bands: A 5-Year Follow-Up Study.

Background: Brain atrophy, which is associated with cognitive impairment and retinal nerve fiber layer (RNFL) atrophy, is the main biomarker of neurodegeneration in multiple sclerosis (MS). However, data on the relationship between inflammatory markers, such as oligoclonal bands (OCBs) in the cerebrospinal fluid (CSF), and cognition, RNFL atrophy, and brain atrophy are scarce. The aim of this study was to assess the influence of RNFL thickness, brain atrophy markers, intrathecal OCBs, and the immunoglobulin G (IgG) index on cognitive decline over a 5-year period in patients with MS.Methods: This prospective, single-center, observational cohort study included 49 patients with relapsing MS followed up over 5 years. At baseline, the patients underwent brain magnetic resonance imaging (MRI). Cognitive evaluation was performed using the Brief International Cognitive Assessment for MS (BICAMS), and RNFL thickness was assessed using optical coherence tomography (OCT). OCBs and IgG levels in the CSF were evaluated at baseline. The BICAMS, OCT, and MRI findings were re-evaluated after 5 years.Results: A significant reduction in information processing speed, visual learning, temporal RNFL thickness, the Huckman index, and third ventricle mean diameter was found in all 49 patients with relapsing MS over the observation period (p < 0.05). Of the patients, 63.3% had positive OCBs and 59.2% had elevated IgG indices. The atrophy of the temporal segment and papillomacular bundle and the presence of OCBs were significantly related to a decline in information processing speed in these patients (p < 0.05). However, brain atrophy markers were not found to be significant on the general linear models.Conclusions: RNFL atrophy and the presence of OCBs were related to cognitive decline in patients with MS over a 5-year follow-up period, thereby suggesting their utility as potential biomarkers of cognitive decline in MS.

Evaluation of a connectivity-based imaging metric that reflects functional decline in Multiple Sclerosis.

Cognitive impairment is a common symptom in individuals with Multiple Sclerosis (MS), but meaningful, reliable biomarkers relating to cognitive decline have been elusive, making evaluation of the impact of therapeutics on cognitive function difficult. Here, we combine pathway-based MRI measures of structural and functional connectivity to construct a metric of functional decline in MS. The Structural and Functional Connectivity Index (SFCI) is proposed as a simple, z-scored metric of structural and functional connectivity, where changes in the metric have a simple statistical interpretation and may be suitable for use in clinical trials. Using data collected at six time points from a 2-year longitudinal study of 20 participants with MS and 9 age- and sex-matched healthy controls, we probe two common symptomatic domains, motor and cognitive function, by measuring structural and functional connectivity in the transcallosal motor pathway and posterior cingulum bundle. The SFCI is significantly lower in participants with MS compared to controls (p = 0.009) and shows a significant decrease over time in MS (p = 0.012). The change in SFCI over two years performed favorably compared to measures of brain parenchymal fraction and lesion volume, relating to follow-up measures of processing speed (r = 0.60, p = 0.005), verbal fluency (r = 0.57, p = 0.009), and score on the Multiple Sclerosis Functional Composite (r = 0.67, p = 0.003). These initial results show that the SFCI is a suitable metric for longitudinal evaluation of functional decline in MS.

Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Background and rationaleThalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. MethodsStandardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. ResultsIn smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. ConclusionAutomated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings.

Functional brain network organization measured with magnetoencephalography predicts cognitive decline in multiple sclerosis

Background: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients. Objective: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology. Methods: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage. Results: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years (), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band. Conclusions: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.

Cognitive Decline and Treatment Strategies in Multiple Sclerosis Patients

Multiple Sclerosis (MS) is an autoimmune disease of the Central Nervous System (CNS), mainly appeared in young adults, characterized by neuroinflammation, demyelination, neurodegeneration and remyelination and with a variety of CNS-related symptoms. The prevalence of cognitive decline in MS patients has been reported to range widely, from 13% to 72%, occurring in all stages of the disease, and can lead to mental disability, social impairment, and an impoverished quality of life. The pathogenetic mechanism of the cognitive decline in MS has yet to be revealed, and, thus, we are still unable to predict which patients are more likely to manifest such a decline and at what stage of the disease. Clinical factors, including the type and the course of the disease, but also fatigue and emotional disturbances, can impact the degree of MSrelated cognitive impairment. It has been reported that almost 40% of the MS patients demonstrate a significant deficit in recognizing and recalling verbal and visual memories, either at the onset of the disease or at its later stages, whereas short-term memory remains almost intact. Many patients also demonstrate deficits in complex attention, a slower efficiency in information processing, a declined ability of problemsolving, planning, and prioritization tasks or even visual agnosia and aphasia. Most of the MS-specific disease-modifying treatments seem to reduce the rate of MS attacks and slower the progression; however, their impact on cognitive impairment remains unclear. We propose that cognitive function evaluations should be incorporated in the regular assessment and monitoring of MS patients since they seem to be well correlated with the progression of the disease. Even if the effect of the neuropsychological batteries used for diagnostic and therapeutic purposes still remains very much limited, especially due to the validation and standardization issues, specific cognitive functions treatment strategies should be implemented in the therapeutic scheme of MS patients.

Macular Carotenoids, Retinal Morphometry, and Cognitive Function in Multiple Sclerosis (OR05-07-19)

ObjectivesIndividuals with multiple sclerosis (MS) often suffer a progressive loss in visual and cognitive function. While the exact reason for the cognitive decline in MS is unknown, generalized neurodegeneration of the central nervous system has been associated with lower carotenoid levels. Carotenoids have antioxidant effects that could support nerve health and be protective against cognitive decline. Carotenoids are also found in high concentration within the center of the retina, or macula. Their role in the brain may be related to their role in the eye and vision health. We investigated the correlation among macular carotenoids, retinal and nerve fiber layer thickness, and cognitive function in patients with MS. MethodsSubjects included persons diagnosed with MS between 45–64 years (N = 29) living in Illinois. Carotenoid accumulation, defined as macular pigment optical density (MPOD), was measured using heterochromatic flicker photometry. Optical coherence tomography (Heidelberg Engineering, Germany) was used to assess total macular volume (TMV), central foveal (CF), and retinal nerve fiber layer thickness (RNFL). Cognitive function was assessed using an Eriksen flanker task for attentional control with event-related brain potentials. ResultsWhile MPOD was not correlated with TMV (Rho = 0.23, P = 0.14), CF (Rho < –0.01, P = 0.50), or RNFL (Rho = 0.19, P = 0.19), MPOD was correlated with faster congruent (Rho = –0.34, P = 0.04) and incongruent reaction time (Rho = –0.33, P = 0.04) and faster congruent (Rho = –0.52, P < 0.01) and incongruent (Rho = –0.37, P = 0.04) P2 latency. RNFL was positively correlated with incongruent accuracy (Rho = 0.41, P = 0.02) and inversely related to incongruent P2 latency (Rho = –0.41, P = 0.05), N2 congruent (Rho = –0.46, P = 0.03), and incongruent (Rho = –0.47, P = 0.03) amplitude. Additionally, RNFL was inversely related to congruent (Rho = –0.51, P = 0.02) and incongruent (Rho = –0.54, P = 0.01) P3 amplitude. Larger TMV was related to faster congruent (Rho = –0.43, P = 0.04) and incongruent P2 latency (Rho = –0.48, P = 0.02). CF was not correlated with any of the cognitive task outcomes. ConclusionsMacular pigmentation and markers of retinal and optic nerve health may positively influence cognitive function in MS. However, MPOD and OCT measures were not correlated, suggesting that macular carotenoids, and retinal and optic nerve thickness may exert independent benefits for cognitive function. Funding SourcesThis work was funded by Pilot Research Grant from the National Multiple Sclerosis Society.

Slowed articulation rate is associated with information processing speed decline in multiple sclerosis: A pilot study

BackgroundImpairment of cognition and speech are common in multiple sclerosis (MS) patients, but their relationship is not well understood. ObjectiveTo describe the relationship between articulation rate characteristics and processing speed and to investigate the potential role of objective speech analysis for the detection of cognitive decline in MS. MethodsA total of 122 patients with clinically definite MS were included in this cross-sectional pilot study. Patients underwent three speaking tasks (oral diadochokinesis, reading text and monologue) and assessment of processing speed (Symbol Digit Modalities Test [SDMT], Paced Auditory Serial Addition Test-3 s [PASAT-3]). Association between articulation rate and cognition was analyzed using linear regression analysis. We estimated the area under the receiver operating characteristics curves (AUC) to evaluate the predictive accuracy of articulation rate measures for the detection of abnormal processing speed. ResultsWe observed an association between articulation rate and cognitive measures (rho = 0.45–0.58; p < 0.001). Faster reading speed by one word per second was associated with an 18.7 point (95% confidence interval [CI] 14.9–22.5) increase of the SDMT score and 14.7 (95% CI 8.9–20.4) point increase of PASAT-3 score (both p < 0.001). AUC values of articulation rate characteristics for the identification of processing speed impairment ranged between 0.67 and 0.79. Using a cutoff of 3.10 in reading speed, we were able to identify impairment in both the SDMT and PASAT-3 with 91% sensitivity and 54% specificity. ConclusionSlowed articulation rate is strongly associated with processing speed decline. Objective quantitative speech analysis identified patients with abnormal cognitive performance.

A Controlled Clinical Trial on the Effects of Exercise on Cognition and Mobility in Adults With Multiple Sclerosis.

The aim of the study was to investigate the effects of a 6-mo exercise program on cognition and mobility in participants with multiple sclerosis. This is a prospective, single-blind, controlled clinical trial. A community rehabilitation program within a large metropolitan health service. Twenty-eight patients with multiple sclerosis were referred for outpatient rehabilitation. Participants were allocated to one of two groups and undertook a cognitive-motor exercise program or monitoring (control group). Cognition and mobility were the main outcome measures. Cognition was evaluated using the Mini-Mental State Examination and the Frontal Assessment Battery. Mobility was assessed with the Timed Get Up and Go test, applied with and without dual task distractors. The findings showed benefits provided by exercise on cognition and mobility. Differently, participants of the control group did not have significant changes in cognition scores after 6 mos of follow-up and had a worse performance in mobility tests. Six months of exercise provided benefits to cognition and mobility in adults with multiple sclerosis. This trial was registered prospectively with the Brazilian Clinical Trials Register, ID: RBR-9gh4km (http://www.ensaiosclinicos.gov.br/rg/?q=RBR-9gh4km). Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME CME OBJECTIVES: Upon completion of this article, the reader should be able to: (1) Recognize the physical and cognitive decline in multiple sclerosis; (2) Identify the importance of exercise on cognition and mobility in patients with multiple sclerosis; and (3) Appreciate the potential benefit of dual tasking in the rehabilitation of individuals with multiple sclerosis.Level: Advanced ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.

Resting-state MEG measurement of functional activation as a biomarker for cognitive decline in MS

Background: Neurophysiological measures of brain function, such as magnetoencephalography (MEG), are widely used in clinical neurology and have strong relations with cognitive impairment and dementia but are still underdeveloped in multiple sclerosis (MS). Objectives: To demonstrate the value of clinically applicable MEG-measures in evaluating cognitive impairment in MS. Methods: In eyes-closed resting-state, MEG data of 83 MS patients and 34 healthy controls (HCs) peak frequencies and relative power of six canonical frequency bands for 78 cortical and 10 deep gray matter (DGM) areas were calculated. Linear regression models, correcting for age, gender, and education, assessed the relation between cognitive performance and MEG biomarkers. Results: Increased alpha1 and theta power was strongly associated with impaired cognition in patients, which differed between cognitively impaired (CI) patients and HCs in bilateral parietotemporal cortices. CI patients had a lower peak frequency than HCs. Oscillatory slowing was also widespread in the DGM, most pronounced in the thalamus. Conclusion: There is a clinically relevant slowing of neuronal activity in MS patients in parietotemporal cortical areas and the thalamus, strongly related to cognitive impairment. These measures hold promise for the application of resting-state MEG as a biomarker for cognitive disturbances in MS in a clinical setting.

The subtleties of cognitive decline in multiple sclerosis: an exploratory study using hierarchichal cluster analysis of CANTAB results

BackgroundIt is essential to investigate cognitive deficits in multiple sclerosis (MS) to develop evidence-based cognitive rehabilitation strategies. Here we refined cognitive decline assessment using the automated tests of the Cambridge Neuropsychological Test Automated Battery (CANTAB) and hierarchical cluster analysis.MethodsWe searched for groups of distinct cognitive profiles in 35 relapsing-remitting MS outpatients and 32 healthy controls. All individuals participated in an automated assessment (CANTAB) and in a pencil and paper general neuropsychological evaluation.ResultsHierarchical cluster analysis of the CANTAB results revealed two distinct groups of patients based mainly on the Simple Reaction Time (RTI) and on the Mean Latency of Rapid Visual Processing (RVP). The general neuropsychological assessment did not show any statistically significant differences between the cluster groups. Compared to the healthy control group, all MS outpatients had lower scores for RTI, RVP, paired associate learning, and delayed matching to sample. We also analyzed the associations between CANTAB results and age, education, sex, pharmacological treatment, physical activity, employment status, and the Expanded Disability Status Scale (EDSS). Although limited by the small number of observations, our findings suggest a weak correlation between performance on the CANTAB and age, education, and EDSS scores.ConclusionsWe suggest that the use of selected large-scale automated visuospatial tests from the CANTAB in combination with multivariate statistical analyses may reveal subtle and earlier changes in information processing speed and cognition. This may expand our ability to define the limits between normal and impaired cognition in patients with Multiple Sclerosis.

Interplay Between Age and Neuroinflammation in Multiple Sclerosis: Effects on Motor and Cognitive Functions.

Aging is one of the main risk factors for the development of many neurodegenerative diseases. Emerging evidence has acknowledged neuroinflammation as potential trigger of the functional changes occurring during normal and pathological aging. Two main determinants have been recognized to cogently contribute to neuroinflammation in the aging brain, i.e., the systemic chronic low-grade inflammation and the decline in the regulation of adaptive and innate immune systems (immunosenescence, ISC). The persistence of the inflammatory status in the brain in turn may cause synaptopathy and synaptic plasticity impairments that underlie both motor and cognitive dysfunctions. Interestingly, such inflammation-dependent synaptic dysfunctions have been recently involved in the pathophysiology of multiple sclerosis (MS). MS is an autoimmune neurodegenerative disease, typically affecting young adults that cause an early and progressive deterioration of both cognitive and motor functions. Of note, recent controlled studies have clearly shown that age at onset modifies prognosis and exerts a significant effect on presenting phenotype, suggesting that aging is a significant factor associated to the clinical course of MS. Moreover, some lines of evidence point to the different impact of age on motor disability and cognitive deficits, being the former most affected than the latter. The precise contribution of aging-related factors to MS neurological disability and the underlying molecular and cellular mechanisms are still unclear. In the present review article, we first emphasize the importance of the neuroinflammatory dependent mechanisms, such as synaptopathy and synaptic plasticity impairments, suggesting their potential exacerbation or acceleration with advancing age in the MS disease. Lastly, we provide an overview of clinical and experimental studies highlighting the different impact of age on motor disability and cognitive decline in MS, raising challenging questions on the putative age-related mechanisms involved.