Cognitive phenotypes in multiple sclerosis

Mobile Health App (DIGICOG-MS) for Self-Assessment of Cognitive Impairment in People With Multiple Sclerosis: Instrument Validation and Usability Study

BACKGROUND

Mobile health (mHealth) apps have proven useful for people with multiple sclerosis (MS). Thus, easy-to-use digital solutions are now strongly required to assess and monitor cognitive impairment, one of the most disturbing symptoms in MS that is experienced by almost 43% to 70% of people with MS. Therefore, we developed DIGICOG-MS (Digital assessment of Cognitive Impairment in Multiple Sclerosis), a smartphone- and tablet-based mHealth app to self-assess cognitive impairment in MS.

OBJECTIVE

This study aimed to test the validity and usability of the novel mHealth app with a sample of people with MS.

METHODS

DIGICOG-MS includes 4 digital tests assumed to evaluate the most affected cognitive domains in MS (visuospatial memory [VSM], verbal memory [VM], semantic fluency [SF], and information processing speed [IPS]) and inspired by traditional paper-based tests that assess the same cognitive functions (10/36 Spatial Recall Test, Rey Auditory Verbal Learning Test, Word List Generation, Symbol Digit Modalities Test). Participants were asked to complete both digital and traditional assessments in 2 separate sessions. Convergent validity was analyzed using the Pearson correlation coefficient to determine the strength of the associations between digital and traditional tests. To test the app's reliability, the agreement between 2 repeated measurements was assessed using intraclass correlation coefficients (ICCs). Usability of DIGICOG-MS was evaluated using the System Usability Scale (SUS) and mHealth App Usability Questionnaire (MAUQ) administered at the conclusion of the digital session.

RESULTS

The final sample consisted of 92 people with MS (60 women) followed as outpatients at the Italian Multiple Sclerosis Society (AISM) Rehabilitation Service of Genoa (Italy). They had a mean age of 51.38 (SD 11.36) years, education duration of 13.07 (SD 2.74) years, disease duration of 12.91 (SD 9.51) years, and a disability level (Expanded Disability Status Scale) of 3.58 (SD 1.75). Relapsing-remitting MS was most common (68/92, 74%), followed by secondary progressive (15/92, 16%) and primary progressive (9/92, 10%) courses. Pearson correlation analyses indicated significantly strong correlations for VSM, VM, SF, and IPS (all P<.001), with r values ranging from 0.58 to 0.78 for all cognitive domains. Test-retest reliability of the mHealth app was excellent (ICCs>0.90) for VM and IPS and good for VSM and SF (ICCs>0.80). Moreover, the SUS score averaged 84.5 (SD 13.34), and the mean total MAUQ score was 104.02 (SD 17.69), suggesting that DIGICOG-MS was highly usable and well appreciated.

CONCLUSIONS

The DIGICOG-MS tests were strongly correlated with traditional paper-based evaluations. Furthermore, people with MS positively evaluated DIGICOG-MS, finding it highly usable. Since cognitive impairment poses major limitations for people with MS, these findings open new paths to deploy digital cognitive tests for MS and further support the use of a novel mHealth app for cognitive self-assessment by people with MS in clinical practice.

Correlation between cognitive changes and neuroradiological changes over time in multiple sclerosis: a systematic review and meta-analysis

BACKGROUND

While many studies have examined relationships of neuroimaging variables to cognitive measures in multiple sclerosis (MS), longitudinal studies are lacking. The relationship of cognitive changes to neuroradiological changes in MS is thus incompletely understood. The present study systematically reviews all studies reporting a relationship between MRI changes and cognitive changes after at least one year of follow-up.

METHOD

An extensive and methodical search of online databases was conducted to identify qualified studies until August 2023. Among various cognitive tests and magnetic resonance imaging (MRI) measures, Symbol Digit Modalities Test (SDMT), Paced Auditory Serial Addition Test (PASAT), verbal fluency, T2 lesion volume (T2LV), white matter lesion volume (WML), and grey matter volume (GMV) qualified for inclusion in a meta-analysis investigating the association of cognitive changes to neuroradiological changes.

RESULTS

We identified 35 studies that explored the link between MRI changes and changes in cognitive outcomes. Of these, twenty studies (57.14%) investigated the association between SDMT/PASAT and MRI metrics. Eleven studies (31.42%) focused on the relationship between MRI metrics and verbal learning and memory, while ten studies (28.57%) reported associations with visuospatial learning and memory. Furthermore, eight studies (22.85%) analyzed the correlation between verbal fluency and MRI measures. Only 5 were eligible for inclusion in the meta-analysis. The meta-analysis evaluated correlations between SDMT/PASAT and GMV (rs = 0.67, 95% CI 0.44-0.91), and verbal fluency and T2LV (rs = 0.35, 95% CI 0.09-0.60).

CONCLUSION

In this rigorously conducted systematic review, we found a significant association of cognitive changes, specifically SDMT/PASAT and verbal fluency, to changes in T2LV and atrophy in individuals with MS. Findings should be interpreted cautiously due to the limited amount of high-quality research, small sample sizes, and variability in study methodologies.

Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms

Multiple sclerosis (MS) is an autoimmune-mediated disease of the central nervous system characterized by inflammation, demyelination and chronic progressive neurodegeneration. Among its broad and unpredictable range of clinical symptoms, cognitive impairment (CI) is a common and disabling feature greatly affecting the patients' quality of life. Its prevalence is 20% up to 88% with a wide variety depending on the phenotype of MS, with highest frequency and severity in primary progressive MS. Involving different cognitive domains, CI is often associated with depression and other neuropsychiatric symptoms, but usually not correlated with motor and other deficits, suggesting different pathophysiological mechanisms. While no specific neuropathological data for CI in MS are available, modern research has provided evidence that it arises from the disease-specific brain alterations. Multimodal neuroimaging, besides structural changes of cortical and deep subcortical gray and white matter, exhibited dysfunction of fronto-parietal, thalamo-hippocampal, default mode and cognition-related networks, disruption of inter-network connections and involvement of the γ-aminobutyric acid (GABA) system. This provided a conceptual framework to explain how aberrant pathophysiological processes, including oxidative stress, mitochondrial dysfunction, autoimmune reactions and disruption of essential signaling pathways predict/cause specific disorders of cognition. CI in MS is related to multi-regional patterns of cerebral disturbances, although its complex pathogenic mechanisms await further elucidation. This article, based on systematic analysis of PubMed, Google Scholar and Cochrane Library, reviews current epidemiological, clinical, neuroimaging and pathogenetic evidence that could aid early identification of CI in MS and inform about new therapeutic targets and strategies.

Long-term characterization of cognitive phenotypes in children with seizures over 36 months

RATIONALE

Children with new-onset epilepsies often exhibit co-morbidities including cognitive dysfunction, which adversely affects academic performance. Application of unsupervised machine learning techniques has demonstrated the presence of discrete cognitive phenotypes at or near the time of diagnosis, but there is limited knowledge of their longitudinal trajectories. Here we investigate longitudinally the presence and progression of cognitive phenotypes and academic status in youth with new-onset seizures as sibling controls.

METHODS

282 subjects (6-16 years) were recruited within 6 weeks of their first recognized seizure along with 167 unaffected siblings. Each child underwent a comprehensive neuropsychological assessment at baseline, 18 and 36 months later. Factor analysis of the neuropsychological tests revealed four underlying domains - language, processing speed, executive function, and verbal memory. Latent trajectory analysis of the mean factor scores over 36 months identified clusters with prototypical cognitive trajectories.

RESULTS

Three unique phenotypic groups with distinct cognitive trajectories over the 36-month period were identified: Resilient, Average, and Impaired phenotypes. The Resilient phenotype exhibited the highest neuropsychological factor scores and academic performance that were all similar to controls; while the Impaired phenotype showed the polar opposite with the worst performances across all test metrics. These findings remained significant and stable over 36 months. Multivariate logistic regression indicated that age of onset, EEG, neurological examination, and sociodemographic disadvantage were associated with phenotype classification.

CONCLUSIONS

This study demonstrates the presence of diverse latent cognitive trajectory phenotypes over 36 months in youth with new-onset seizures that are associated with a stable neuropsychological and academic performance longitudinally.

Identifying and understanding cognitive profiles in multiple sclerosis: a role for visuospatial memory functioning

BACKGROUND

The heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired).

METHODS

We included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing-remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ - 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification.

RESULTS

Six profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997).

CONCLUSIONS

This study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.

Association Between Disease-Modifying Therapy and Information Processing Speed in Multiple Sclerosis

BACKGROUND

Cognitive impairment (CI) is common in multiple sclerosis (MS). Processing speed (PS) is often affected, making it an ideal target for monitoring CI. This study aims to evaluate the association between disease-modifying therapy (DMT) use and intensity and longitudinal changes in Processing Speed Test (PST) scores for individuals with MS.

METHODS

A retrospective analysis of individual PST scores at a single MS center was conducted. Individuals with 2 or more PST assessments were included. Scores on the PST were compared longitudinally between those who had been on a DMT for 2 or more years and those who had been off a DMT for 2 or more years and between those on high-efficacy DMTs and those on low-/moderate-efficacy DMTs. A linear regression model was approximated to evaluate the rate of cognitive change over time. A propensity score adjustment was conducted using a multivariable logistic regression.

RESULTS

The cohort was 642 individuals, 539 on DMT and 103 off DMT. Median age and disease duration was 49.7 (IQR 42.4-57.9) and 16.6 years (IQR 9.3-23.0) in the DMT group, and 58.9 (IQR 52.2-65.3) and 20.0 years (IQR 14.1-31.4) in the non-DMT group. Both cohorts were predominantly female (75% DMT, 79.6% non-DMT), with a mean of 4 assessments (IQR 3-5), and an average monitoring duration of 1.9 years (1.2-2.4) in the DMT group, and 1.8 years (1.4-2.4) in the non-DMT group. After adjusting for multiple factors, DMT status and intensity were not found to be significant predictors of longitudinal PST change.

CONCLUSIONS

Neither DMT status nor intensity was a significant predictor of cognitive processing speed over a period of approximately 2 years. Future prospective studies are needed to further support these findings.

Cognitive phenotypes in multiple sclerosis: mapping the spectrum of impairment

BACKGROUND

Available criteria for cognitive phenotypes in multiple sclerosis (MS) do not consider the severity of impairment.

OBJECTIVES

To identify cognitive phenotypes with varying degrees of impairment in MS patients and describe their demographic, clinical and MRI characteristics.

METHODS

Two hundred and forty-three MS patients and 158 healthy controls underwent neuropsychological tests to assess memory, attention, and executive function. For each domain, mild impairment was defined as performing 1.5 standard deviations below the normative mean on two tests, while the threshold for significant impairment was 2 standard deviations. Patients were classified into cognitive phenotypes based on severity of the impairment (mild/significant) and number of domains affected (one/more).

RESULTS

Five cognitive phenotypes emerged: Preserved cognition (PC; 56%), Mild Single-Domain Impairment (MSD; 15%), Mild Multi-Domain Impairment (MMD; 9%), Significant Single-Domain Impairment (SSD; 12%), Significant Multi-Domain Impairment (SMD; 8%). Compared with PC, MSD patients were older, had longer disease duration (DD) and higher T2-hyperintense lesion volume (LV; all p ≤ 0.02); MMD patients were older, had longer DD, higher disability, higher T2 LV and lower thalamic volume (all p ≤ 0.01); SSD patients had longer DD and lower gray matter cortical volume, thalamic, caudate, putamen and accumbens volumes (all p ≤ 0.04); and SMD patients were older, had longer DD, higher disability and more extensive structural damage in all brain regions explored (all p ≤ 0.03), except white matter and amygdala volumes.

CONCLUSIONS

We identified five cognitive phenotypes with graded levels of impairment. These phenotypes were characterized by distinct demographic, clinical and MRI features, indicating potential variations in the neural substrates of dysfunction throughout disease stages.

Utility of the Brief Assessment of Cognitive Health (BACH) computerized screening tool in identifying MS-related cognitive impairment

BACKGROUND

Current guidelines recommend that individuals with MS are screened annually for processing speed deficits, often using the Symbol Digit Modalities Test (SDMT). However, given the heterogeneity of cognitive deficits in individuals with MS, other screening measures that assess a range of cognitive domains are necessary. The current cross-sectional study aimed to examine the ability of the computerized, self-administered Brief Assessment of Cognitive Health (BACH) screening measure to detect the presence of cognitive impairment in adults with MS as determined by performance on a standard neuropsychological test battery.

METHODS

Seventy-two individuals with MS completed the BACH and a comprehensive neuropsychological test battery. Receiver operating characteristic (ROC) analyses were conducted to investigate the ability of the BACH to identify cognitively impaired and cognitively intact individuals. ROC analyses were also conducted to compare the ability of the SDMT to discriminate between cognitively intact and cognitively impaired groups as a comparison with the BACH.

RESULTS

Cognitive impairment was observed in 56 % of the sample. The BACH showed acceptable ability to discriminate between cognitively intact and cognitively impaired groups (AUC = 0.78). Additionally, the BACH was able to adequately predict cognitive impairment in domains other than processing speed (AUC = 0.71). The SDMT also demonstrated adequate utility in identifying individuals with cognitive impairment (AUC = 0.73); however, the SDMT was not able to adequately predict cognitive impairment in domains other than processing speed (AUC = 0.56).

CONCLUSION

The BACH showed adequate ability to detect cognitive impairment in individuals with MS. The BACH was able to identify impairments across various assessed cognitive domains, including individuals with and without processing speed deficits.

Visuo-Cognitive Phenotypes in Early Multiple Sclerosis: A Multisystem Model of Visual Processing

BACKGROUND

Cognitive impairment can emerge in the earliest stages of multiple sclerosis (MS), with heterogeneity in cognitive deficits often hindering symptom identification and management. Sensory-motor dysfunction, such as visual processing impairment, is also common in early disease and can impact neuropsychological task performance in MS. However, cognitive phenotype research in MS does not currently consider the relationship between early cognitive changes and visual processing impairment.

OBJECTIVES

This study explored the relationship between cognition and visual processing in early MS by adopting a three-system model of afferent sensory, central cognitive and efferent ocular motor visual processing to identify distinct visuo-cognitive phenotypes.

METHODS

Patients with clinically isolated syndrome and relapsing-remitting MS underwent neuro-ophthalmic, ocular motor and neuropsychological evaluation to assess each visual processing system. The factor structure of ocular motor variables was examined using exploratory factor analysis, and phenotypes were identified using latent profile analysis.

RESULTS

Analyses revealed three ocular-motor constructs (cognitive control, cognitive processing speed and basic visual processing) and four visuo-cognitive phenotypes (early visual changes, efferent-cognitive, cognitive control and afferent-processing speed). While the efferent-cognitive phenotype was present in significantly older patients than was the early visual changes phenotype, there were no other demographic differences between phenotypes. The efferent-cognitive and cognitive control phenotypes had poorer performance on the Symbol Digit Modalities Test compared to that of other phenotypes; however, no other differences in performance were detected.

CONCLUSION

Our findings suggest that distinct visual processing deficits in early MS may differentially impact cognition, which is not captured using standard neuropsychological evaluation. Further research may facilitate improved symptom identification and intervention in early disease.

Relationship between emotion recognition and cognition in multiple sclerosis: a meta-analysis protocol

Introduction

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease of the central nervous system characterised by a broad and unpredictable range of symptoms, including cognitive and socio-cognitive dysfunction. Alongside the well-known deficits in information processing speed (IPS), executive functioning and episodic memory, recent evidence also highlighted socio-cognitive impairments in MS, such as emotion-recognition deficits. Recently, several studies investigated the association between emotion-recognition and cognitive impairment to assess whether social cognition is parallel to (or even dependent on) general cognitive dysfunction. Yet, there have been inconsistent findings, raising the need for a meta-analysis of the literature.

Objectives

The aim of the present paper is to outline the protocol for an upcoming meta-analysis we designed to clarify these conclusions.

Methods and analysis

We plan to estimate combined effect sizes for the association between emotion-recognition and cognitive impairment in MS across three cognitive domains (IPS, executive functions and episodic memory) and 7 emotion scores of interests (total and by 6-basic emotions subscores). Further, we plan to investigate whether identified variables are the cause for heterogeneity in any combined association. To that end, we will conduct additional meta-regression analyses to explore whether overall correlations differ according to clinical characteristics of MS patients (ie, disease duration, MS-phenotype, severity of depression and disability). Ultimately, this study will provide support either for an association of these disorders (in which emotion-recognition deficits might result from more fundamental cognitive dysfunction), or for two distinct sets of symptoms which may occur independently, for targeted patient profiles.

Don't plan, just do it: Cognitive and sensorimotor contributions to manual dexterity

Manual dexterity is referred to as the skill to perform fine motor movements and it has been assumed to be associated to the cognitive domain, as well as the sensorimotor one. In this work, we investigated with functional near-infrared spectroscopy the cortical activations elicited by the execution of the 9-HPT, i.e., a standard test evaluating manual dexterity in which nine pegs were taken, placed into and then removed from nine holes on a board as quickly as possible. For comparison, we proposed a new active control task mainly involving the sensorimotor domain, in which the pegs must be placed and removed using the same single hole (1-HPT). Behaviorally, we found two distinct groups based on the difference between the execution time of the 9-HPT and the 1-HPT (ΔHPT). Cortical areas belonging to the network controlling reaching and grasping movements were active in both groups; however, participants showing a large ΔHPT presented significantly higher activation in prefrontal cortical areas (right BA10 and BA11) during 9-HPT and 1-HPT performance with respect to the participants with a small ΔHPT, who showed a deactivation in BA10. Unexpectedly, we observed a significant linear relationship between ΔHPT and right BA10 activity. This suggested that participants performing the 9-HPT more slowly than the 1-HPT recruited prefrontal areas implicitly exploiting the cognitive skills of planning, perhaps in search of a motor strategy to solve the test activating attentional and cognitive control processes, but this resulted not efficient and instead increased the time to accomplish a manual dexterity task.

Cognitive enrichment and education quality moderate cognitive dysfunction in black and white adults with multiple sclerosis

OBJECTIVE

To examine the extent to which three sociobehavioral proxies of cognitive reserve-years of education, education quality, and cognitive enrichment-differ in their prediction of cognitive performance among Black and White people with MS (PwMS).

METHODS

82 PwMS (Black n = 41, White n = 41) underwent a neurological examination and a neuropsychological evaluation that included tests of word recognition (Wechsler Test of Adult Reading) as well as measures of verbal memory, visuospatial memory, and processing speed (the Brief International Cognitive Assessment for MS; BICAMS). Participants rated their lifetime engagement in various cognitively-enriching activities (Cognitive Reserve Scale).

RESULTS

For the full sample, education quality and cognitive enrichment were more strongly associated with cognitive performance than were years of education. Cognitive enrichment was not associated with cognitive performance among participants with high education quality. In contrast, among participants with low education quality, cognitive enrichment was strongly associated with cognitive performance, suggesting that high engagement in cognitively-enriching activities provided similar protection to high education quality. Furthermore, among Black participants, cognitive enrichment and educational quality moderated the relationship between disability level and cognitive performance. In contrast, among White participants, cognitive enrichment did not provide additional protection beyond the buffering effect of education quality.

CONCLUSIONS

PwMS can successfully build reserve through multiple routes, including formal education or informal cognitive enrichment. Treatment for MS should incorporate cognitively-enriching activities to build resilience against cognitive decline, particularly for members of marginalized racial/ethnic groups, who are at greatest risk for poor health outcomes, and for whom years of education may not best reflect education quality.

Differences in metacognition between multiple sclerosis phenotypes: cognitive impairment and fatigue are key factors

Background

Cognitive impairment is present in 40-65% of patients with multiple sclerosis (pwMS). Objectively measured cognitive performance often does not match patients' subjective perception of their own performance.

Objective

We aimed to compare cognitive performance and subjective perception of cognitive deficits between pwMS and healthy controls (HCs), as well as the accuracy of subjective perception.

Methods

In total, 54 HC and 112 pwMS (relapsing-remitting, RRMS, and progressive PMS) underwent neuropsychological evaluation and completed perceived deficit, fatigue, and anxiety-depression scales. Participants were classified according to their consistency between subjective self-evaluation of cognitive abilities and objective cognitive performance to assess accuracy. Regression models were used to compare cognitive performance between groups and explore factors explaining inaccuracy in the estimation of cognitive performance.

Results

PMS showed greater and more widespread cognitive differences with HC than RRMS. No differences were found between pwMS and HC in the perception of deficit. PMS had higher ratios of overestimators. In explaining inaccuracy, fatigue and cognitive preservation were found to be risk factors for underestimation, whereas physical disability and cognitive impairment were risk factors for overestimation.

Conclusion

PwMS have metacognitive knowledge impairments. This study provides new information about metacognition, data on the prevalence of impairments over a relatively large sample of PwMS, and new insights into factors explaining it. Anosognosia, related to cognitive impairment, may be present in pwMS. Fatigue is a key factor in underestimating cognition.

Depressive symptoms, anxiety and cognitive impairment: emerging evidence in multiple sclerosis

Neuropsychiatric abnormalities may be broadly divided in two categories: disorders of mood, affect, and behavior and abnormalities affecting cognition. Among these conditions, clinical depression, anxiety and neurocognitive disorders are the most common in multiple sclerosis (MS), with a substantial impact on patients' quality of life and adherence to treatments. Such manifestations may occur from the earliest phases of the disease but become more frequent in MS patients with a progressive disease course and more severe clinical disability. Although the pathogenesis of these neuropsychiatric manifestations has not been fully defined yet, brain structural and functional abnormalities, consistently observed with magnetic resonance imaging (MRI), together with genetic and immunologic factors, have been suggested to be key players. Even though the detrimental clinical impact of such manifestations in MS patients is a matter of crucial importance, at present, they are often overlooked in the clinical setting. Moreover, the efficacy of pharmacologic and non-pharmacologic approaches for their amelioration has been poorly investigated, with the majority of studies showing marginal or no beneficial effect of different therapeutic approaches, possibly due to the presence of multiple and heterogeneous underlying pathological mechanisms and intrinsic methodological limitations. A better evaluation of these manifestations in the clinical setting and improvements in the understanding of their pathophysiology may offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. This review provides an updated overview regarding the pathophysiology of the most common neuropsychiatric symptoms in MS, the clinical and MRI characteristics that have been associated with mood disorders (i.e., depression and anxiety) and cognitive impairment, and the treatment approaches currently available or under investigation.

Impact of depression on the perception of fatigue and information processing speed in a cohort of multiple sclerosis patients

BACKGROUND

Information processing speed is commonly impaired in people with multiple sclerosis (PwMS). However, depression and fatigue can affect the cognitive profile of patients: fatigue has a negative impact from the disease's earliest stage and a reduced information processing speed is often associated with higher levels of depression. Therefore, the aim of this study was to investigate the correlations between information processing speed and physical fatigue in a cohort of Italian PwMS from a single center, considering the effect of depression.

METHODS

Two hundred (W = 128; mean age = 39.83 years; SD = 11.86) PwMS, from the Bari University Hospital, underwent testing for processing speed (Symbol Digit Modalities Test [SDMT]), fatigue level (Fatigue Severity Scale [FSS]), and depression (Beck's Depression Inventory [BDI]).

RESULTS

Statistically significant correlations emerged between SDMT and FSS, SDMT and BDI, FSS and BDI. Mediation analyses revealed that while physical fatigue had no significant direct negative effect on information processing speed (z=-0.891; p > 0.05), depression predicted the relationship between fatigue and information processing speed (z=-2.181; p < 0.05).

CONCLUSION

Our findings showed that cognitive performance at SDMT was not affected by patients' perceived level of physical fatigue, but by depression. The presence of a high BDI score mediates the physical fatigue on cognitive performance impact.

Incremental validity of brief and abbreviated neuropsychological tests toward predicting functional outcomes in multiple sclerosis

OBJECTIVE

This study examined the relationships among functional outcomes and performance on standard-length and abbreviated cognitive screening measures for multiple sclerosis (MS).

METHOD

72 adults with MS underwent neurological examination and cognitive screening. They completed standard-length and abbreviated versions of tests from the Minimal Assessment of Cognitive Function in MS (MACFIMS), the abbreviated aMACFIMS, and the Brief International Cognitive Assessment for MS (BICAMS). Functional outcomes included neurological disability, physical and psychological dysfunction, and employment status.

RESULTS

Concordance of impairment classifications was examined between standard-length and abbreviated tests using logistic regression and ROC curve analyses. Overall, the abbreviated test versions showed a broad range of concordance with impairment classifications made using the full-length tests. Processing speed was the strongest correlate of neurological disability and employment status; immediate recall was the strongest predictor of subjective physical dysfunction. Test performance provided unique value toward predicting neurological disability and employment status, but not physical and psychological dysfunction.

CONCLUSIONS

The findings replicate some support for abbreviated tests in MS assessment, although caveats regarding loss of validity associated with abbreviation remain. The findings extend prior research showing that abbreviated tests of processing speed and immediate recall can provide unique predictive information regarding objective functional outcomes.

Subtypes of relapsing-remitting multiple sclerosis identified by network analysis

We used network analysis to identify subtypes of relapsing-remitting multiple sclerosis subjects based on their cumulative signs and symptoms. The electronic medical records of 113 subjects with relapsing-remitting multiple sclerosis were reviewed, signs and symptoms were mapped to classes in a neuro-ontology, and classes were collapsed into sixteen superclasses by subsumption. After normalization and vectorization of the data, bipartite (subject-feature) and unipartite (subject-subject) network graphs were created using NetworkX and visualized in Gephi. Degree and weighted degree were calculated for each node. Graphs were partitioned into communities using the modularity score. Feature maps visualized differences in features by community. Network analysis of the unipartite graph yielded a higher modularity score (0.49) than the bipartite graph (0.25). The bipartite network was partitioned into five communities which were named fatigue, behavioral, hypertonia/weakness, abnormal gait/sphincter, and sensory, based on feature characteristics. The unipartite network was partitioned into five communities which were named fatigue, pain, cognitive, sensory, and gait/weakness/hypertonia based on features. Although we did not identify pure subtypes (e.g., pure motor, pure sensory, etc.) in this cohort of multiple sclerosis subjects, we demonstrated that network analysis could partition these subjects into different subtype communities. Larger datasets and additional partitioning algorithms are needed to confirm these findings and elucidate their significance. This study contributes to the literature investigating subtypes of multiple sclerosis by combining feature reduction by subsumption with network analysis.

Characterizing fatigue phenotypes with other symptoms and clinically relevant outcomes among people with multiple sclerosis

PURPOSE

Fatigue is a common symptom of multiple sclerosis (MS) and can adversely affect all aspect of quality of life. The etiology of fatigue remains unclear, and its treatments are suboptimal. Characterizing the phenotypes of fatigued persons with MS may help advance research on fatigue's etiology and identify ways to personalize fatigue interventions to improve quality of life. The purpose of this study was to identify fatigue phenotypes; examine phenotype stability overtime; and characterize phenotypes by health and function, social and environmental determinants, psychosocial factors, and engagement in healthy behaviors.

METHODS

We conducted a longitudinal study over a 3-month period with 289 fatigued participants with MS. To identify fatigue phenotypes and determine transition probabilities, we used latent profile and transition analyses with valid self-report measures of mental and physical fatigue severity, the mental and physical impact of fatigue, depression, anxiety, and sleep quality. We used ANOVAs and effect sizes to characterize differences among phenotypes.

RESULTS

The best fitting model included six subgroups of participants: Mild Phenotype, Mild-to-Moderate Phenotype, Moderate-to-Severe Phenotype, Severe Phenotype, Fatigue-dominant Phenotype, and Mental Health-dominant Phenotype. The transition analysis indicated that phenotypic membership was highly stable. Variables with a large eta squared effect size included environmental barriers, self-efficacy, and fatigue catastrophizing.

CONCLUSION

These results indicate that the magnitude of fatigue experienced may be more important to consider than the type of fatigue when characterizing fatigue phenotypes. Future research should explore whether tailoring interventions to environmental barriers, self-efficacy, and fatigue catastrophizing reduce the likelihood of transitioning to a more severe phenotype.

Cognitive rehabilitation in multiple sclerosis: Three digital ingredients to address current and future priorities

Multiple sclerosis (MS) is a neurological chronic disease with autoimmune demyelinating lesions and one of the most common disability causes in young adults. People with MS (PwMS) experience cognitive impairments (CIs) and clinical evidence shows their presence during all MS stages even in the absence of other symptoms. Cognitive rehabilitation (CR) aims at reducing CI and improving PwMS' awareness of cognitive difficulties faced in their daily living. More defined cognitive profiles, easier treatment access and the need to transfer intervention effects into everyday life activities are aims of utmost relevance for CR in MS. Currently, advanced technologies may pave the way to rethink CR in MS to address the priority of more personalized and effective, accessible and ecological interventions. For this purpose, digital twins, tele-cognitive-rehabilitation and metaverse are the main candidate digital ingredients. Based on scientific evidences, we propose digital twin technology to enhance MS cognitive phenotyping; tele-cognitive-rehabilitation to make feasible the cognitive intervention access to a larger number of PwMS; and metaverse to represent the best choice to train real-world dual- and multi-tasking deficits in virtual daily life environments. Moreover, multi-domain high-frequency big-data collected through tele-cognitive-assessment, tele-cognitive-rehabilitation, and metaverse may be merged to refine artificial intelligence algorithms and obtain increasingly detailed patient's cognitive profile in order to enhance intervention personalization. Here, we present how these digital ingredients and their integration could be crucial to address the current and future needs of CR facilitating the early detection of subtle CI and the delivery of increasingly effective treatments.

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.

Moving towards a taxonomy of cognitive impairments in epilepsy: application of latent profile analysis to 1178 patients with temporal lobe epilepsy

In efforts to understand the cognitive heterogeneity within and across epilepsy syndromes, cognitive phenotyping has been proposed as a new taxonomy aimed at developing a harmonized approach to cognitive classification in epilepsy. Data- and clinically driven approaches have been previously used with variability in the phenotypes derived across studies. In our study, we utilize latent profile analysis to test several models of phenotypes in a large multicentre sample of patients with temporal lobe epilepsy and evaluate their demographic and clinical profiles. For the first time, we examine the added value of replacing missing data and examine factors that may be contributing to missingness. A sample of 1178 participants met the inclusion criteria for the study, which included a diagnosis of temporal lobe epilepsy and the availability of comprehensive neuropsychological data. Models with two to five classes were examined using latent profile analysis and the optimal model was selected based on fit indices, posterior probabilities and proportion of sample sizes. The models were also examined with imputed data to investigate the impact of missing data on model selection. Based on the fit indices, posterior probability and distinctiveness of the latent classes, a three-class solution was the optimal solution. This three-class solution comprised a group of patients with multidomain impairments, a group with impairments predominantly in language and a group with no impairments. Overall, the multidomain group demonstrated a worse clinical profile and comprised a greater proportion of patients with mesial temporal sclerosis, a longer disease duration and a higher number of anti-seizure medications. The four-class and five-class solutions demonstrated the lowest probabilities of a group membership. Analyses with imputed data demonstrated that the four-class solution was the optimal solution; however, there was a weak agreement between the missing and imputed data sets for the four-Class solutions (κ = 0.288, P < 0.001). This study represents the first to use latent profile analysis to test and compare multiple models of cognitive phenotypes in temporal lobe epilepsy and to determine the impact of missing data on model fit. We found that the three-phenotype model was the most meaningful based on several fit indices and produced phenotypes with unique demographic and clinical profiles. Our findings demonstrate that latent profile analysis is a rigorous method to identify phenotypes in large, heterogeneous epilepsy samples. Furthermore, this study highlights the importance of examining the impact of missing data in phenotyping methods. Our latent profile analysis-derived phenotypes can inform future studies aimed at identifying cognitive phenotypes in other neurological disorders.

A proposed new taxonomy of cognitive phenotypes in multiple sclerosis: The International Classification of Cognitive Disorders in MS (IC-CoDiMS)

BACKGROUND

Characterization of cognitive impairment (CI) in multiple sclerosis into distinct phenotypes holds promise for individualized treatments and biomarker exploration.

OBJECTIVE

Apply a previously validated, neuropsychologically driven diagnostic algorithm to identify a taxonomy of the type of cognitive phenotypes in multiple sclerosis.

METHODS

An algorithm developed and validated in other neurological diseases was applied to a cohort of 1281 people with multiple sclerosis who underwent clinical neuropsychological evaluation across three multiple sclerosis centers. A domain was marked impaired if scores on two tests within the domain fell below one of the two thresholds of interest (compared to controls; -1.0 SD and -1.5 SD below the mean). Results were then tabulated for each participant to determine the type of impairments across the sample.

RESULTS

At -1 SD threshold, 48.7% were intact, 21.6% had single-domain, 14.3% bi-domain, and 15.4% multi-domain impairment. At -1.5 SD threshold, 72.9% were intact, 14.0% had single-domain, 8.2% bi-domain, and 5.0% multi-domain impairment. Processing speed was the most frequent single-domain impairment, followed by executive function and memory.

CONCLUSIONS

These findings advance the taxonomy of cognitive phenotypes in multiple sclerosis and clarify the type and distribution of possible cognitive diagnoses, pave the way for further investigation of associated biomarkers, and provide clinically meaningful information to guide individualized treatment and rehabilitation.

Identifying different cognitive phenotypes and their relationship with disability in neuromyelitis optica spectrum disorder

Background

The existence, frequency, and features of cognitive impairment (CI) in patients with neuromyelitis optica spectrum disorder (NMOSD) are still debated. A precise classification and characterization of cognitive phenotypes in patients with NMOSD are lacking.

Methods

A total of 66 patients with NMOSD and 22 healthy controls (HCs) underwent a neuropsychological assessment. Latent profile analysis (LPA) on cognitive test z scores was used to identify cognitive phenotypes, and ANOVA was used to define the clinical features of each phenotype. Univariate and multivariate analyses were used to explore the predictors of severe CI, and a corresponding nomogram was created to visualize the predictive model.

Results

LPA results suggested four distinct meaningful cognitive phenotypes in NMOSD: preserved cognition (n = 20, 30.3%), mild-attention (n = 21, 31.8%), mild-multidomain (n = 18, 27.3%), and severe-multidomain (n = 7, 10.6%). Patients with the last three phenotypes were perceived to have CI, which accounts for 67.6% of patients with NMOSD. Patients with NMOSD and worse cognitive function were older (p < 0.001) and had lower educational levels (p < 0.001), later clinical onset (p = 0.01), worse Expanded Disability Status Scale scores (p = 0.001), and poorer lower-limb motor function (Timed 25-Foot Walk, p = 0.029; 12-item Multiple Sclerosis Walking Scale [MSWS-12], p < 0.001). Deterioration of Nine-Hole Peg Test (odds ratio, OR: 1.115 [1, 1.243], p = 0.05) and MSWS-12 (OR: 1.069 [1.003, 1.139], p = 0.04) were the independent risk factors for severe cognitive dysfunction. Finally, a nomogram was built based on the entire cohort and the above factors to serve as a useful tool for clinicians to evaluate the risk of severe cognitive dysfunction.

Conclusions

We introduced a classification scheme for CI and highlighted that the deterioration of upper- and lower-limb motor disability potentially predicts cognitive phenotypes in NMOSD.

Role of artificial intelligence in MS clinical practice

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For medical applications, machine learning (including deep learning) are the most commonly used artificial intelligence (AI) approaches.

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It can improve multiple sclerosis (MS) diagnosis, prognostication and treatment monitoring.

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Thanks to AI, MRI and cognitive phenotypes of MS patients were identified.

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AI can shorten MRI protocols for MS, allowing the application of advanced techniques.

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It can reduce the human effort for MRI analysis, especially for lesion segmentation.

Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and management of patients with multiple sclerosis (MS), this disease is an ideal candidate for the application of AI techniques. In this narrative review, we are going to discuss the potential applications of AI for MS clinical practice, together with their limitations. Among their several advantages, ML algorithms are able to automate repetitive tasks, to analyze more data in less time and to achieve higher accuracy and reproducibility than the human counterpart. To date, these algorithms have been applied to MS diagnosis, prognosis, disease and treatment monitoring. Other fields of application have been improvement of MRI protocols as well as automated lesion and tissue segmentation. However, several challenges remain, including a better understanding of the information selected by AI algorithms, appropriate multicenter and longitudinal validations of results and practical aspects regarding hardware and software integration. Finally, one cannot overemphasize the paramount importance of human supervision, in order to optimize the use and take full advantage of the potential of AI approaches.

Comparing diagnostic criteria for the diagnosis of neurocognitive disorders in multiple sclerosis

BACKGROUND

People with multiple sclerosis (MS) commonly experience cognitive impairment associated with the disease, but there is currently no agreed-upon operational definition for identifying the presence of that impairment, in either research or clinic contexts. The International MS Cognition Society (IMSCOGS) established a task force to begin to examine this issue and this paper represents the results of an initial pilot investigation. The aim of this paper was to compare two criterion sets to determine how to identify cognitive impairment among people with MS: the general Diagnostic and Statistical Manual (DSM-5) Criteria for neurocognitive disorders and criteria derived from existing MS research (scores in two domains fall 1.5 standard deviations below normative controls).

METHODS

Two hundred and ten people with MS presented for a brief cognitive evaluation in an MS Multidisciplinary Clinic at a midwestern academic medical center in the United States. Participants were generally middle aged (average 51.5 years), female (73.8%), and white (93.3%). McNemar's test was computed to compare the number of individuals whose cognitive test score performance was deemed cognitively normal, mildly impaired, or more significantly impaired.

RESULTS

DSM-5 criteria classified 87.2% of the sample as cognitively impaired, where 66.7% were more mildly impaired and 20.5% more significantly impaired. By contrast, research-based criteria classified 63.3% of the sample as cognitively impaired, with 49.5% as mildly impaired and 13.8% as more significantly impaired.

CONCLUSIONS

These findings indicate that compared to research criteria, the DSM-5 criteria classified far more people with MS as having cognitive impairment secondary to the disease. The paper discusses the potential benefits and drawbacks of the two diagnostic methods, highlighting that more work will be needed in order to establish a standardized and validated method for characterizing these impairments.

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.

Is computerized screening for processing speed impairment sufficient for identifying MS-related cognitive impairment in a clinical setting?

BACKGROUND

Annual screening for processing speed impairment (PSI) is recommended for patients with multiple sclerosis (pwMS). However, cognitive deficits in pwMS are heterogeneous, and whether PSI screening identifies patients with impairment in other cognitive domains is unclear. The objective of this study was to examine sensitivity and specificity of the self-administered, computerized Processing Speed Test (PST) in identifying cognitive impairment defined by a comprehensive neuropsychological battery (NPT).

METHODS

Ninety-one pwMS completed PST and NPT, with raw scores demographically adjusted. Cognitive impairment on NPT was defined as performance <5^th percentile in at least one domain. Receiver operating characteristic (ROC) analyses were performed to determine the ability of the PST to discriminate between cognitively normal (CN) and cognitively impaired with PSI (CI-PSI) and cognitively impaired with normal processing speed (CI-PSN) groups.

RESULTS

Cognitive impairment was observed in 23.1% of pwMS on PST and in 42.9% on NPT. PST demonstrated excellent ability to discriminate between CN (57.1%) and CI-PSI (20.9%) groups (Area Under the Curve [AUC] = 0.86, p < 0.001). In contrast, PST was unable to discriminate CN and CI-PSN (22.0%) groups (AUC = 0.42, p = 0.32).

CONCLUSION

The PST demonstrates excellent ability to detect PSI in pwMS but is unable to identify cognitively impaired pwMS without PSI, highlighting the importance of developing additional screening measures.

Identifying the Distinct Cognitive Phenotypes in Multiple Sclerosis

Importance

Cognitive impairment is a common and disabling feature of multiple sclerosis (MS), but a precise characterization of cognitive phenotypes in patients with MS is lacking.

Objectives

To identify cognitive phenotypes in a clinical cohort of patients with MS and to characterize their clinical and magnetic resonance imaging (MRI) features.

Design, Setting, and Participants

This multicenter cross-sectional study consecutively screened clinically stable patients with MS and healthy control individuals at 8 MS centers in Italy from January 1, 2010, to October 31, 2019. Patients with MS and healthy control individuals who were not using psychoactive drugs and had no history of other neurological or medical disorders, learning disability, severe head trauma, and alcohol or drug abuse were enrolled.

Main Outcomes and Measures

Participants underwent a neurological examination and a cognitive evaluation with the Rao Brief Repeatable Battery and Stroop Color and Word Test. A subgroup of participants also underwent a brain MRI examination. Latent profile analysis was used on cognitive test z scores to identify cognitive phenotypes. Linear regression and mixed-effects models were used to define clinical and MRI features of each phenotype.

Results

A total of 1212 patients with MS (mean [SD] age, 41.1 [11.1] years; 784 women [64.7%]) and 196 healthy control individuals (mean [SD] age, 40.4 [8.6] years; 130 women [66.3%]) were analyzed in this study. Five cognitive phenotypes were identified: preserved cognition (n = 235 patients [19.4%]), mild-verbal memory/semantic fluency (n = 362 patients [29.9%]), mild-multidomain (n = 236 patients [19.5%]), severe-executive/attention (n = 167 patients [13.8%]), and severe-multidomain (n = 212 patients [17.5%]) involvement. Patients with preserved cognition and mild-verbal memory/semantic fluency were younger (mean [SD] age, 36.5 [9.8] years and 38.2 [11.1] years) and had shorter disease duration (mean [SD] 8.0 [7.3] years and 8.3 [7.6] years) compared with patients with mild-multidomain (mean [SD] age, 42.6 [11.2] years; mean [SD] disease duration, 12.8 [9.6] years; P < .001), severe-executive/attention (mean [SD] age, 42.9 [11.7] years; mean [SD] disease duration, 12.2 [9.5] years; P < .001), and severe-multidomain (mean [SD] age, 44.0 [11.0] years; mean [SD] disease duration, 13.3 [10.2] years; P < .001) phenotypes. Severe cognitive phenotypes prevailed in patients with progressive MS. At MRI evaluation, compared with those with preserved cognition, patients with mild-verbal memory/semantic fluency exhibited decreased mean (SE) hippocampal volume (5.42 [0.68] mL vs 5.13 [0.68] mL; P = .04), patients with the mild-multidomain phenotype had decreased mean (SE) cortical gray matter volume (687.69 [35.40] mL vs 662.59 [35.48] mL; P = .02), patients with severe-executive/attention had higher mean (SE) T2-hyperintense lesion volume (51.33 [31.15] mL vs 99.69 [34.07] mL; P = .04), and patients with the severe-multidomain phenotype had extensive brain damage, with decreased volume in all the brain structures explored, except for nucleus pallidus, amygdala and caudate nucleus.

Conclusions and Relevance

This study found that by defining homogeneous and clinically meaningful phenotypes, the limitations of the traditional dichotomous classification in MS can be overcome. These phenotypes can represent a more meaningful measure of the cognitive status of patients with MS and can help define clinical disability, support clinicians in treatment choices, and tailor cognitive rehabilitation strategies.

RISCOP-Cognitive profile in a Portuguese cohort of radiological isolated syndrome patients: A case-control study

INTRODUCTION

Radiologically isolated syndrome (RIS) refers to the incidental discovery of white matter lesions suggestive of MS, on brain MRI, in asymptomatic patients. Recent studies suggest similar features of cognitive impairment between RIS and MS patients. Also, lower levels of health-related quality of life (QOL) and fatigue are reported in such patients.

AIMS

characterize and compare the cognitive profile of a multicentric Portuguese cohort of RIS patients with a control group.

METHODS

multicentric comparative study of a cohort of adult patients with RIS, and age and gender-matched controls followed in the headache outpatient clinic with prior MRI not fulfilling criteria for RIS diagnosis. We conducted interviews with participants, collected clinical data and applied the BICAMS battery and self-reported questionnaires (HADS, MFIS, MSQOL-54).

RESULTS

we evaluated 31 patients with RIS (median age 46 years, IQR [(Dusankova et al., 2012-52], 72% women) and 19 control individuals (median age 32 years, IQR [(O'Jile et al., 2005-48], 71% women). Prevalence of cognitive impairment did not differ between groups (16% of the RIS and 10% of the controls, p=0.579). We found no differences between groups on the BICAMS tests, although the results of the California Verbal Learning Test (CVLT-II) score presented a trend to significance, with a lower value on the RIS group (53.9 vs. 59.3, p=0.066). There were no significant differences regarding fatigue, QOL, anxiety/depression scores.

CONCLUSION

this is the first study on a Portuguese cohort of RIS patients assessing cognitive profile with BICAMS. A non-neglectable part of our cohort presented cognitive impairment. Our findings add to previous studies in suggesting that a more pronounced impairment of verbal memory and learning, evaluated by CVLT-II, may be present in RIS patients compared to controls. BICAMS should be assessed on future studies with larger cohorts.

Associations between cognitive and clinical disability across MS subtypes: The role of the underlying brain damage

BACKGROUND

Cognitive impairment (CI) is present in all stages and subtypes of multiple sclerosis (MS). However, the majority of studies examined relapsing-remitting (RRMS) patients, and did not address cognitive phenotyping. Is still not clear whether patients with progressive MS (PMS) have a distinct pattern of CI compared to RRMS. In addition, there is conflicting data regarding the correlation between clinical and cognitive disability.

OBJECTIVE

To investigate the differences of CI between PMS and RRMS patients, evaluating cognitive phenotypes. We also aimed to analyze the association between physical and cognitive disability with MRI measures of grey-matter atrophy and lesion burden.

METHODS

Thirty patients with PMS and twenty-four with RRMS underwent neurological, neuropsychological (BRB-N, Boston Naming, and Tower of London), and MRI assessments (3T). Brain volume evaluations were performed using FreeSurfer. Principal Components Analysis on neuropsychological yielded six principal cognitive domains. Cognitive deficits were classified according to three categories: no CI, impairment in isolated cognitive domain, or impairment in combined domains.

RESULTS

In the overall sample, the most frequently impaired cognitive domains were information processing speed (IPS) and visual memory. PMS patients had a higher prevalence of verbal memory and verbal fluency deficits, and more frequent impairment in combined cognitive domains compared to RRMS individuals. After multivariable regression analysis with clinical variables, EDSS was associated with most cognitive domains. Nevertheless, after including T1-lesion volume in the model, it was the most consistent predictor of cognitive performance. To further analyze the interaction between EDSS and T1-lesions, we performed GLM analysis with EDSS and T1-hypointense lesion volume as covariates, and T1-lesion volume adjusted better the model for verbal memory (p = 0.013), IPS (p = 0.021) and total number of impaired cognitive domains (p = 0.021).

CONCLUSIONS

RRMS and PMS patients tend to have a similar neuropsychological profile in general, but the extent of CI was greater in PMS patients. Worse cognitive performance was associated with increased physical disability, but this correlation was no longer significant after controlling for T1-lesion volume, suggesting that the underlying MS pathology might be involved in this relationship. Thalamic and T1-lesion volumes were the most consistent MRI predictors associated with cognitive disability.

Course of neuropsychological impairment during natalizumab-associated progressive multifocal leukoencephalopathy

BACKGROUND AND PURPOSE

Progressive multifocal leukoencephalopathy (PML), an opportunistic infection of the central nervous system from the John Cunningham virus (JCV), is a side effect of natalizumab (NTZ) treatment for relapsing-remitting multiple sclerosis (RRMS), potentially leading to a substantial increase of physical and mental disability. Nevertheless, data of neuropsychological impairment during the NTZ-PML disease course are missing. Our objective was to evaluate the neuropsychological disease course of NTZ-PML patients and to compare neuropsychological deficits of NTZ-PML patients with two different non-PML multiple sclerosis (MS) cohorts.

METHODS

Neuropsychological examinations of 28 NTZ-PML patients performed during different phases of the disease ([i] at PML diagnosis, [ii] during immune reconstitution inflammatory syndrome [IRIS], and [iii] post-IRIS/PML) were retrospectively analyzed and compared to those of NTZ-treated RRMS or secondary progressive MS patients with and without immunotherapy.

RESULTS

Compared to controls, NTZ-PML patients performed worse in neuropsychological examinations during all stages of disease, mainly affecting visuospatial ability and working memory. Furthermore, failure to eliminate the JCV from the central nervous system was associated with a progredient decline of cognition, especially working memory.

CONCLUSIONS

Working memory and visuospatial abilities are the core neuropsychological deficits of NTZ-PML patients in long-term follow-up. Our findings should be implemented in neurorehabilitation strategies.

Classifying multiple sclerosis patients on the basis of SDMT performance using machine learning

Objective:

To build a model to predict cognitive status reflecting structural, functional, and white matter integrity changes in early multiple sclerosis (MS).

Methods:

Based on Symbol Digit Modalities Test (SDMT) performance, 183 early MS patients were assigned “lower” or “higher” performance groups. Three-dimensional (3D)-T2, T1, diffusion weighted, and resting-state magnetic resonance imaging (MRI) data were acquired in 3T. Using Random Forest, five models were trained to classify patients into two groups based on 1—demographic/clinical, 2—lesion volume/location, 3—local/global tissue volume, 4—local/global diffusion tensor imaging, and 5—whole-brain resting-state-functional-connectivity measures. In a final model, all important features from previous models were concatenated. Area under the receiver operating characteristic curve (AUC) values were calculated to evaluate classifier performance.

Results:

The highest AUC value (0.90) was achieved by concatenating all important features from neuroimaging models. The top 10 contributing variables included volumes of bilateral nucleus accumbens and right thalamus, mean diffusivity of left cingulum-angular bundle, and functional connectivity among hubs of seven large-scale networks.

Conclusion:

These results provide an indication of a non-random brain pattern mostly compromising areas involved in attentional processes specific to patients who perform worse in SDMT. High accuracy of the final model supports this pattern as a potential neuroimaging biomarker of subtle cognitive changes in early MS.

Dissociable cognitive patterns related to depression and anxiety in multiple sclerosis

BACKGROUND

Individuals with multiple sclerosis (MS) frequently present with depression and anxiety, as well as cognitive impairment, challenging clinicians to disentangle interrelationships among these symptoms.

OBJECTIVE

To identify cognitive functions associated with anxiety and depression in MS.

METHODS

Mood and cognition were measured in 185 recently diagnosed patients (Reserve Against Disability in Early Multiple Sclerosis (RADIEMS) cohort), and an independent validation sample (MEM CONNECT cohort, n = 70). Partial correlations evaluated relationships of cognition to anxiety and depression controlling for age, sex, education, and premorbid verbal intelligence.

RESULTS

In RADIEMS cohort, lower anxiety was associated with better nonverbal memory (rp = -0.220, p = 0.003) and lower depression to better attention/processing speed (rp = -0.241, p = 0.001). Consistently, in MEM CONNECT cohort, lower anxiety was associated with better nonverbal memory (rp = -0.271, p = 0.028) and lower depression to better attention/processing speed (rp = -0.367, p = 0.002). Relationships were unchanged after controlling for T2 lesion volume and fatigue.

CONCLUSION

Consistent mood-cognition relationships were identified in two independent cohorts of MS patients, suggesting that cognitive correlates of anxiety and depression are separable. This dissociation may support more precise models to inform treatment development. Treatment of mood symptoms may mitigate effects on cognition and/or treatment of cognition may mitigate effects on mood.

A global view of comorbidity in multiple sclerosis: a systematic review with a focus on regional differences, methodology, and clinical implications

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system which is associated with numerous comorbidities. These include cardiovascular disease, psychiatric and neurologic disturbances, restless leg syndrome, migraine, cancer, autoimmune diseases, and metabolic disorders. Comorbid disease is an important consideration for clinicians treating patients with MS; early presentation of comorbidities can obscure or delay MS diagnosis, as well as significantly impacting the disease course. Improved understanding of comorbidities and their emergence in MS populations is important for improving the quality of life and optimizing treatment for patients. Therefore, we evaluated published studies reporting epidemiologic data on comorbidities and their associated impact on disease progression in patients with MS (PwMS). The prevalence of neurologic, cardiovascular, metabolic, and autoimmune comorbidities was elevated in PwMS in general, and furthermore, this adversely affected a broad range of outcomes. Compared with PwMS, cancer rates in people without MS or the general population were lower, which should prompt further studies into the mechanisms of both diseases. Studies were under-represented in many regions owing to the latitudinal gradient of MS and possible underfunding of studies.

Corpus callosum index correlates with brain volumetry and disability in multiple sclerosis patients

OBJECTIVE

To analyze the correlation between corpus callosum index (CCI), brain volumetry, and disability in multiple sclerosis (MS) patients. The brain volumetry consists of the corpus callosum, cortical gray matter, subcortical gray matter, and white matter volumes.

METHODS

This was a retrospective cross-sectional study from October 2018 to February 2019 of 30 patients with MS aged 20 to 61 years old. Brain volumetry was performed using FreeSurfer software. The CCI were measured manually using conventional best mid-sagittal T1W brain MRI. The anterior, posterior, and medium segments were measured and divided to its greatest anteroposterior diameter. Higher CCI values indicated greater corpus callosum volumes. Clinical evaluation was comprised of MS subtype, age of onset, relapse frequency and Expanded Disability Status Scale (EDSS).

RESULTS

Thirty MS patients with median of age 22 years were included. Relapsing-remitting (RRMS) subtype were 73.3%. Very significant correlations were shown between the CCI and corpus callosum volume (CCV) (r=0.79; p<0.0001) and cerebral white matter volume (r=0.81; p<0.0001). Significant correlations were shown between the CCI and cortical gray matter volume (r=0.64; p<0.0001) and subcortical gray matter volume (r=0.69; p<0.0001). The CCI was positively correlated with age of onset and inversely with EDSS. The CCV and CCI were smaller in secondary progressive MS (SPMS).

CONCLUSION

The CCI is easy and fast to obtain in conventional MRI and significantly correlated with brain volumetry, age of onset and disability in MS patients.

Frontoparietal connectivity correlates with working memory performance in multiple sclerosis

Working Memory (WM) impairment is the most common cognitive deficit of patients with Multiple Sclerosis (MS). However, evidence of its neurobiological mechanisms is scarce. Here we recorded electroencephalographic activity of twenty patients with relapsing-remitting MS and minimal cognitive deficit, and 20 healthy control (HC) subjects while they solved a WM task. In spite of similar performance, the HC group demonstrated both a correlation between temporoparietal theta activity and memory load, and a correlation between medial frontal theta activity and successful memory performances. MS patients did not show theses correlations leading significant differences between groups. Moreover, cortical connectivity analyses using granger causality and phase-amplitude coupling between theta and gamma revealed that HC group, but not MS group, presented a load-modulated progression of the frontal-to-parietal connectivity. This connectivity correlated with working memory capacity in MS groups. This early alterations in the oscillatory dynamics underlaying working memory could be useful for plan therapeutic interventions.

Correlations of health status indicators with perceived neuropsychological impairment and cognitive processing speed in multiple sclerosis

BACKGROUND

Comorbidity and health behaviours may explain heterogeneity regarding cognitive performance in multiple sclerosis. Patient-reported cognitive difficulties have impact but do not consistently correlate with objective cognitive performance. Our study aims to investigate whether health status indicators including comorbidities, body mass index, physical activity, smoking, sleeping behaviour and consumption patterns for fish, alcohol and caffeinated drinks are associated with measures of subjective and objective cognitive performance.

METHODS

Survey data on self-reported cognitive performance, assessed with the MS Neuropsychological Screening Questionnaire (MSNQ), were related to the presence of arterial hypertension, diabetes mellitus, cardiovascular and chronic renal diseases, hypercholesterolemia, depression based on 2-question screening tool, health and consumption behaviors. We included the Symbol Digit Modalities Test when available within 6 months as an objective, performance-based metric of cognitive processing speed. We investigated the interrelation between all variables with a Spearman correlation matrix and corrected for multiple testing. Regression models were built and controlled for age, sex and phenotype.

RESULTS

We used available data from 751 patients with definite MS, including 290 SDMT scores within a time window of 6 months, to study relations between variables. MSNQ and SDMT scores were not significantly correlated. Correlation patterns for subjective and objective performance differed. Age, disease duration and physical disability correlated with SDMT scores only. Regression analyses could be performed for MSNQ scores in 595/751 (79.2%) and for SDMT scores in 234/751 (31.2%) participants. After restricting variables to avoid collinearity and adjusting for the number of variables, regression models explained 15% of the variance for subjective and 14% of the variance for objective cognitive performance. A higher number of physical comorbidities, reporting depressive symptoms, sleeping 9 h or more and daily use of sleeping medication were associated with lower subjective cognitive performance, whereas increasing age was associated with reduced processing speed. These associations persisted after correction for multiple testing.

CONCLUSION

Increasing age is associated with reduced cognitive processing speed whereas comorbidities and sleep behaviors contribute to subjective cognitive performance.

Mobile Brain/Body Imaging of cognitive-motor impairment in multiple sclerosis: Deriving EEG-based neuro-markers during a dual-task walking study

OBJECTIVE

Individuals with a diagnosis of multiple sclerosis (MS) often present with cognitive and motor deficits, and thus the ability to perform tasks that rely on both domains may be particularly impaired. Yet, dual-task walking studies yield mixed results. Individual variance in the ability to cope with brain insult and mobilize additional brain resources may contribute to mixed findings.

METHODS

To test this hypothesis, we acquired event-related potentials (ERP) in individuals with MS and healthy controls (HCs) performing a Go/NoGo task while sitting (i.e., single task) or walking (i.e., dual-task) and looked at the relationship between task related modulation of the brain response and performance.

RESULTS

On the Go/NoGo task the MS group showed dual-task costs when walking, whereas HCs showed a dual-task benefit. Further, whereas the HC group showed modulation of the brain response as a function of task load, this was not the case in the MS group. Analysis for the pooled sample revealed a positive correlation between load-related ERP effects and dual-task performance.

CONCLUSIONS

These data suggest a neurophysiological marker of cognitive-motor dysfunction in MS.

SIGNIFICANCE

Understanding neural processes underlying dual-task walking will help identify objective brain measurements of real-world issues and may improve assessment of MS.

Multiple brain networks support processing speed abilities of patients with multiple sclerosis

Objectives: Many people affected by multiple sclerosis (MS) experience cognitive impairment, especially decreases in information processing speed (PS). Neural disconnection is thought to represent the neural marker of this symptom, although the role played by alterations of specific functional brain networks still remains unclear. The aim is to investigate and compare patterns of association between PS-demanding cognitive performance and functional connectivity across two MS phenotypes. Methods: Forty patients with relapsing-remitting MS (RRMS) and 25 with secondary progressive MS (SPMS) had neuropsychological and MRI assessments. Multiple regression models were used to investigate the relationship between performance on tests of visuomotor and verbal PS, and on the verbal fluency tests, and functional connectivity of four cognitive networks, i.e. left and right frontoparietal, salience and default-mode, and two control networks, i.e. visual and sensorimotor. Results: Patients with SPMS were older and had longer disease history than patients with RRMS and presented with worse overall clinical conditions: higher disease severity, total lesion volume, and cognitive impairment rates. However, in both patient samples, cognitive performance across tests was negatively correlated with functional connectivity of the salience and default-mode networks, and positively with connectivity of the left frontoparietal network. Only the visuomotor PS scores of the RRMS group were also associated with connectivity of the sensorimotor network. Conclusions: PS-demanding cognitive performance in patients with MS appears mainly associated with strength of functional connectivity of frontal networks involved in the evaluation and manipulation of information, as well as the default mode network. These results are in line with the hypothesis that multiple neural networks are needed to support normal cognitive performance across MS phenotypes. However, different PS measures showed partially different patterns of association with functional connectivity. Therefore, further investigations are needed to clarify the contribution of inter-network communication to specific cognitive deficits due to MS.

Effect of dalfampridine on information processing speed impairment in multiple sclerosis

Objective

To test a possible benefit of dalfampridine on information processing speed (IPS), a key function for cognitive impairment (CogIm) in multiple sclerosis (MS).

Methods

In this randomized, double-blind, placebo-controlled trial, we included patients with a score on the Symbol Digit Modalities Test (SDMT) under the 10th percentile of the reference value. Patients were randomized in a 2:1 ratio to receive dalfampridine 10 mg or placebo twice daily for 12 weeks. They underwent a comprehensive neuropsychological evaluation at screening (T0), at the end of treatment (T1), and after a 4-week follow-up (T2). The primary endpoint was improvement in SDMT.

Results

Out of 208 patients screened, 120 were randomized to receive either dalfampridine (n = 80) or placebo (n = 40). At T1, the dalfampridine group presented an increase of SDMT scores vs placebo group (mean change 9.9 [95% confidence interval (CI) 8.5–11.4] vs 5.2 [95% CI 2.8–7.6], p = 0.0018; d = 0.60 for raw score; and 0.8 [95% CI 0.6–1] vs 0.3 [95% CI 0.0–0.5], p = 0.0013; d = 0.61 for z scores; by linear mixed model with robust standard error). The improvement was not sustained at T2. A beneficial effect of dalfampridine was observed in the Paced Auditory Serial Addition Test and in cognitive fatigue.

Conclusion

Dalfampridine could be considered as an effective treatment option for IPS impairment in MS.

Trial registration

2013-002558-64 EU Clinical Trials Register.

Classification of evidence

This study provides Class I evidence that for patients with MS with low scores on the SDMT, dalfampridine improves IPS.

Identifying risk factors for cognitive issues in multiple sclerosis

INTRODUCTION

Cognitive impairment (CI) in Multiple Sclerosis (MS) has progressively regained clinical and research interest and is currently recognized as a debilitating and burdensome problem for these patients. Studying risk and protecting factors that may influence the development and course of CI is currently an area of increasing interest, due to the potential for preventive strategies. Areas covered: In this narrative review the authors briefly addressed the physiopathologic basis, assessment and management of CI in MS and then focused on identifying modifiable and not modifiable risk factors for CI in MS, providing an overview of the current knowledge in the field and indicating avenues for future research. Expert opinion: Improving our understanding of potentially modifiable environmental and lifestyle risk factors or protective factors for CI is important in order to prompt preventive strategies and orient patient counselling and clinical management. To this aim, we need to enhance the current level of evidence linking lifestyle factors to cognition and evaluate some factors that were only preliminary addressed in research. Moreover, we need to explore the role of each factor into the subject cognitive outcome, next to the possible interactions between different environmental factors as well as between environmental and genetic factors.