Predominant cognitive phenotypes in multiple sclerosis: Insights from patient-centered outcomes

Italian Version of the mHealth App Usability Questionnaire (Ita-MAUQ): Translation and Validation Study in People With Multiple Sclerosis

Background

Telemedicine and mobile health (mHealth) apps have emerged as powerful tools in health care, offering convenient access to services and empowering participants in managing their health. Among populations with chronic and progressive disease such as multiple sclerosis (MS), mHealth apps hold promise for enhancing self-management and care. To be used in clinical practice, the validity and usability of mHealth tools should be tested. The most commonly used method for assessing the usability of electronic technologies are questionnaires.

Objective

This study aimed to translate and validate the English version of the mHealth App Usability Questionnaire into Italian (ita-MAUQ) in a sample of people with MS.

Methods

The 18-item mHealth App Usability Questionnaire was forward- and back-translated from English into Italian by an expert panel, following scientific guidelines for translation and cross-cultural adaptation. The ita-MAUQ (patient version for stand-alone apps) comprises 3 subscales, which are ease of use, interface and satisfaction, and usefulness. After interacting with DIGICOG-MS (Digital Assessment of Cognitive Impairment in Multiple Sclerosis), a novel mHealth app for cognitive self-assessment in MS, people completed the ita-MAUQ and the System Usability Scale, included to test construct validity of the translated questionnaire. Confirmatory factor analysis, internal consistency, test-retest reliability, and construct validity were assessed. Known-groups validity was examined based on disability levels as indicated by the Expanded Disability Status Scale (EDSS) score and gender.

Results

In total, 116 people with MS (female n=74; mean age 47.2, SD 14 years; mean EDSS 3.32, SD 1.72) were enrolled. The ita-MAUQ demonstrated acceptable model fit, good internal consistency (Cronbach α=0.92), and moderate test-retest reliability (intraclass coefficient correlation 0.84). Spearman coefficients revealed significant correlations between the ita-MAUQ total score; the ease of use (5 items), interface and satisfaction (7 items), and usefulness subscales; and the System Usability Scale (all P values <.05). Known-group analysis found no difference between people with MS with mild and moderate EDSS (all P values >.05), suggesting that ambulation ability, mainly detected by the EDSS, did not affect the ita-MAUQ scores. Interestingly, a statistical difference between female and male participants concerning the ease of use ita-MAUQ subscale was found (P=.02).

Conclusions

The ita-MAUQ demonstrated high reliability and validity and it might be used to evaluate the usability, utility, and acceptability of mHealth apps in people with MS.

Sleep and cognitive outcomes in multiple sclerosis; a systematic review

BACKGROUND

Multiple sclerosis (MS) is a disabling disease of the central nervous system. People living with MS often have co-existing sleep disorders and cognitive dysfunction. The objective of this study was to scrutinize the relationship between cognitive outcomes and sleep conditions in MS.

METHODS

This study followed the Joanna Briggs Institute's (JBI) and PRISMA guidelines. PubMed, Scopus, Embase, and Web of Science databases were searched and original studies delineating the relationship between sleep status and cognitive findings in MS patients‌ were included. The risk of bias was assessed using the JBI critical appraisal tools.

RESULTS

In the final review, out of 1635 screened records, 35 studies with 5321 participants were included. Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and polysomnography were the most common assessment tools for evaluation of sleep condition, and cognitive evaluations were conducted using the tests including Paced Auditory Serial Addition Test (PASAT), California Verbal Learning Test (CVLT), Symbol Digit Modalities Test (SDMT) and Brief Visuospatial Memory Test (BVMT). Assessing the quality of studies showed no significant bias in most of the included articles. A link between sleep condition and cognitive abilities was suggested in the literature, especially with objective measurement of sleep condition; however, current evidence did not support a substantial association between self-reported sleep quality and processing speed and working memory in patients with MS.

DISCUSSION

Evidence proposes sleep is an independent factor associated with cognitive outcomes in MS. Given the limitations of the evidence such as the lack of well-designed prospective studies, these findings need to be interpreted with caution.

A taxonomy of cognitive phenotypes in Multiple Sclerosis: a 1-year longitudinal study

As meaningful measure of cognitive impairment (CI), cognitive phenotypes provide an avenue for symptom management and individualized rehabilitation. Since CI is highly variable in severity and progression, monitoring cognitive phenotypes over time may be useful to identify trajectory of cognitive decline in Multiple Sclerosis (MS). Based on cognitive and mood information from patient-reported outcomes (PROs) and clinician-assessed outcomes (CAOs), four cognitive subgroups of people with MS (PwMS) were identified: phenotype 1 (44.5%) showed a preserved cognitive profile; phenotype 2 (22.8%) had a mild-cognitive impairment profile with attention difficulties; phenotype 3 (24.3%) included people with marked difficulties in visuo-executive, attention, language, memory and information processing speed; lastly, phenotype 4 (8.4%) grouped individuals with a multi-domain impairment profile (visuo-executive, attention, language, memory, orientation, information processing speed and mood disorders). Although some fluctuations occurred considering the rate of impairment, cognitive phenotypes did not substantially vary at follow up in terms of type and number of impairments, suggesting that 1 year is a relatively brief temporal window to observe considerable changes. Our results corroborate that investigating cognitive phenotypes and their stability over time would provide valuable information regarding CI and, in addition, increase clinical importance of PROs and CAOs and their uptake in decision-making and individualized treatment planning for PwMS.

A future of AI-driven personalized care for people with multiple sclerosis

Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system resulting in progressive disability accumulation. As there is no cure available yet for MS, the primary therapeutic objective is to reduce relapses and to slow down disability progression as early as possible during the disease to maintain and/or improve health-related quality of life. However, optimizing treatment for people with MS (pwMS) is complex and challenging due to the many factors involved and in particular, the high degree of clinical and sub-clinical heterogeneity in disease progression among pwMS. In this paper, we discuss these many different challenges complicating treatment optimization for pwMS as well as how a shift towards a more pro-active, data-driven and personalized medicine approach could potentially improve patient outcomes for pwMS. We describe how the 'Clinical Impact through AI-assisted MS Care' (CLAIMS) project serves as a recent example of how to realize such a shift towards personalized treatment optimization for pwMS through the development of a platform that offers a holistic view of all relevant patient data and biomarkers, and then using this data to enable AI-supported prognostic modelling.

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.

Structural and functional imaging features of cognitive phenotypes in pediatric multiple sclerosis

OBJECTIVE

The present study aimed to identify the clinical and MRI features of the distinct cognitive phenotypes in pediatric multiple sclerosis (pedMS).

METHODS

PedMS patients (n = 73) and healthy controls (n = 30) underwent clinical examination and 3.0T MRI. All patients completed neuropsychological testing, and cognitive phenotypes were identified by performing K-means clustering on cognitive scores. MRI metrics included brain T2-hyperintese lesion volume and normalized brain volumes. Within seven cognitively relevant cortical networks, structural disconnectivity (i.e., the mean percentage of streamlines connecting each pair of cortical regions passing through a lesion) and resting-state (RS) functional connectivity (FC) were estimated.

RESULTS

Three cognitive phenotypes emerged: Preserved cognition (PC; n = 27, 37%), mild verbal learning and memory/semantic fluency involvement (MVS; n = 28, 38%), and multidomain involvement (MI; n = 18, 25%). Age, sex, and disease duration did not differ among groups. Compared with healthy subjects, PC patients had decreased RS FC within the default mode network (p = 0.045); MVS patients exhibited lower cortical volume and reduced RS FC within the frontoparietal network (all p = 0.045); and MI patients showed decreased volumes in all brain compartments except the hippocampus, and reduced RS FC within the frontoparietal network (all p ≤ 0.045). Compared to PC, MI patients had more severe disability and higher structural disconnectivity within four cortical networks (all p ≤ 0.045). Compared to PC and MVS, MI patients had lower intelligence quotient (all p ≤ 0.005).

INTERPRETATION

We identified three cognitive phenotypes in pedMS that demonstrate the existence of a spectrum of impairment. Such phenotypes showed distinct clinical and MRI characteristics that contributed to explain their cognitive profiles.

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.

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.

Isolated cognitive impairment in people with multiple sclerosis: frequency, MRI patterns and its development over time

OBJECTIVES

To study the frequency of isolated (i.e., single-domain) cognitive impairments, domain specific MRI correlates, and its longitudinal development in people with multiple sclerosis (PwMS).

METHODS

348 PwMS (mean age 48 ± 11 years, 67% female, 244RR/52SP/38PP) underwent neuropsychological testing (extended BRB-N) at baseline and at five-year follow-up. At baseline, structural MRI was acquired. Isolated cognitive impairment was defined as a Z-score of at least 1.5 SD below normative data in one domain only (processing speed, memory, executive functioning/working memory, and attention). Multi-domain cognitive impairment was defined as being affected in ≥ 2 domains, and cognitively preserved otherwise. For PwMS with isolated cognitive impairment, MRI correlates were explored using linear regression. Development of isolated cognitive impairment over time was evaluated based on reliable change index.

RESULTS

At baseline, 108 (31%) PwMS displayed isolated cognitive impairment, 148 (43%) PwMS displayed multi-domain cognitive impairment. Most PwMS with isolated cognitive impairment were impaired on executive functioning/working memory (EF/WM; N = 37), followed by processing speed (IPS; N = 25), memory (N = 23), and attention (N = 23). Isolated IPS impairment was explained by a model of cortical volume and fractional anisotropy (adj. R2 = 0.539, p < 0.001); memory by a model with cortical volume and hippocampal volume (adj. R2 = 0.493, p = 0.002); EF/WM and attention were not associated with any MRI measure. At follow-up, cognitive decline was present in 11/16 (69%) of PwMS with isolated IPS impairment at baseline. This percentage varied between 18 and 31% of PwMS with isolated cognitive impairment in domains other than IPS at baseline.

CONCLUSION

Isolated cognitive impairment is frequently present in PwMS and can serve as a proxy for further decline, particularly when it concerns processing speed. Cortical and deep grey matter atrophy seem to play a pivotal role in isolated cognitive impairment. Timely detection and patient-tailored intervention, predominantly for IPS, may help to postpone further cognitive decline.

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.

Evaluating Cognitive-Motor Interference in Multiple Sclerosis: A Technology-Based Approach

BACKGROUND

People with multiple sclerosis (PwMS) frequently present both cognitive and motor impairments, so it is reasonable to assume they may have difficulties in executing dual-tasks (DT). The aim of the present study is to identify novel technology-based parameters to assess cognitive-motor interference (CMI) in PwMS. In particular, we focused on the definition of dual-task cost (DTC) measures using wearable and portable tools such as insoles and mobile apps.

METHODS

All participants underwent a verbal fluency task (cognitive single-task, ST), a motor ST of walking, and a combination of these tasks (DT). Number of words uttered in the cognitive ST and steps recorded by insoles were used to calculate the motor and cognitive DTC.

RESULTS

The number of steps strongly correlated with the walked meters for both single- (r = 0.88, p < 0.05) and dual- (r = 0.91, p < 0.05) tasks. Motor but not cognitive performances significantly worsened during DT. Over the cognitive ST and DT, the number of pronounced words progressively decreased, probably due to the activation of different cognitive processes. Cognitive efforts could be the cause of cognitive task prioritization.

CONCLUSIONS

Our findings promote the use of low-cost devices to assess CMI easily in the clinical context and to detect ecologically valid DT impairments.

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.

Age and asymmetry of corticospinal excitability, but not cardiorespiratory fitness, predict cognitive impairments in multiple sclerosis

Background

Cognitive impairment is a disabling and underestimated consequence of multiple sclerosis (MS), with multiple determinants that are poorly understood.

Objectives

We explored predictors of MS-related processing speed impairment (PSI) and age-related mild cognitive impairment (MCI) and hypothesized that cardiorespiratory fitness and corticospinal excitability would predict these impairments.

Methods

We screened 73 adults with MS (53 females; median [range]: Age 48 [21-70] years, EDSS 2.0 [0.0-6.5]) for PSI and MCI using the Symbol Digit Modalities Test and Montréal Cognitive Assessment, respectively. We identified six persons with PSI (No PSI, n = 67) and 13 with MCI (No MCI, n = 60). We obtained clinical data from medical records and self-reports; used transcranial magnetic stimulation to test corticospinal excitability; and assessed cardiorespiratory fitness using a graded maximal exercise test. We used receiver operator characteristic (ROC) curves to discern predictors of PSI and MCI.

Results

Interhemispheric asymmetry of corticospinal excitability was specific for PSI, while age was both sensitive and specific for MCI. MS-related PSI was also associated with statin prescriptions, while age-related MCI was related to progressive MS and GABA agonist prescriptions. Cardiorespiratory fitness was associated with neither PSI nor MCI.

Discussion

Corticospinal excitability is a potential marker of neurodegeneration in MS-related PSI, independent of age-related effects on global cognitive function. Age is a key predictor of mild global cognitive impairment. Cardiorespiratory fitness did not predict cognitive impairments in this clinic-based sample of persons with MS.

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.

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.

Working memory dysfunction differs between secondary progressive and relapsing multiple sclerosis: Effects of clinical phenotype, age, disease duration, and disability

BACKGROUND

Cognitive dysfunction is relatively common in patients with multiple sclerosis (MS). Although it occurs in all stages and all phenotypes of MS, it is more prevalent in secondary progressive MS (SPMS) compared to relapsing MS (RMS). It is unclear whether the higher frequency of cognitive impairment in SPMS is linked to the progressive phenotype or other clinical factors. In this study, we compared working memory in patients with RMS, SPMS, and healthy subjects. We also investigated the effects of age, disease duration, and disability on working memory performance.

METHODS

This case-control study enrolled 134 MS patients, 69 patients were diagnosed with RMS and 65 patients with SPMS, and 77 healthy control subjects. We designed two working memory tasks with different sets of stimuli (face vs. checkerboard) and different instructions (same or different vs. which one is the same).

RESULTS

Accuracy was significantly more impaired in SPMS patients than in RMS patients and both groups were worse than healthy subjects. This finding was similar between both tasks. Age and overall cognitive functions (measured with MoCA) also affected accuracy, but disease duration and disability only affected accuracy in working memory task with checkerboard stimuli.

CONCLUSION

MS patients are impaired in keeping the information in the visual working memory for a few seconds. Progressive phenotype significantly affected working memory accuracy, and this effect did not explain out with other demographic or clinical factors. Future studies are needed to reveal underlying mechanisms of working memory dysfunction in SPMS and working memory dysfunction as a biomarker of disease progression.

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.

Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes

Introduction

Fatigue, cognitive impairment, depression, and pain are highly prevalent symptoms in multiple sclerosis (MS). These often co-occur and may be explained by a common etiology. By reviewing existing literature, we aimed to identify potential underlying biological processes implicated in the interconnectivity between these symptoms.

Methods

A literature search was conducted to identify articles reporting research into the biological mechanisms responsible for the manifestation of fatigue, cognitive impairment, depression, and pain in MS. PubMed was used to search for articles published from July 2011 to July 2021. We reviewed and assessed findings from the literature to identify biological processes common to the symptoms of interest.

Results

Of 693 articles identified from the search, 252 were selected following screening of titles and abstracts and assessing reference lists of review articles. Four biological processes linked with two or more of the symptoms of interest were frequently identified from the literature: (1) direct neuroanatomical changes to brain regions linked with symptoms of interest (e.g., thalamic injury associated with cognitive impairment, fatigue, and depression), (2) pro-inflammatory cytokines associated with so-called ‘sickness behavior,’ including manifestation of fatigue, transient cognitive impairment, depression, and pain, (3) dysregulation of monoaminergic pathways leading to depressive symptoms and fatigue, and (4) hyperactivity of the hypothalamic–pituitary-adrenal (HPA) axis as a result of pro-inflammatory cytokines promoting the release of brain noradrenaline, serotonin, and tryptophan, which is associated with symptoms of depression and cognitive impairment.

Conclusion

The co-occurrence of fatigue, cognitive impairment, depression, and pain in MS appears to be associated with a common set of etiological factors, namely neuroanatomical changes, pro-inflammatory cytokines, dysregulation of monoaminergic pathways, and a hyperactive HPA axis. This association of symptoms and biological processes has important implications for disease management strategies and, eventually, could help find a common therapeutic pathway that will impact both inflammation and neuroprotection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00368-2.

Disentangling self-reported fatigue, depression, and cognitive impairment in people with multiple sclerosis

BACKGROUND

Fatigue is a common problem among people with multiple sclerosis (MS) and can have a negative effect on mental, physical, and social function. Self-reported measures of MS fatigue are often operationalized as a multi-dimensional symptom. However, questions remain about how best to account for the multi-dimensional aspects of self-reported fatigue and whether these aspects are distinct entities. Thus, the purpose of this study was to explore the overlap and distinctions between self-reported measures of the severity and impact of fatigue, between mental and physical fatigue, and between mental fatigue, depressive symptoms, and cognitive impairment.

METHODS

An observational study was conducted with 289 participants with MS . The questionnaires were the Unidimensional Fatigue Impact Scale (UFIS), the Chalder Fatigue Scale (CFS), the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNSQ), and the Quality of Life in Neurological Disorders short form for depression (Neuro-QoL). Spearman's correlation coefficient was used to examine the bivariate correlations between composite and subscale scores. Exploratory structural equation modeling (ESEM) was used to determine the factor structure under a pre-specified number of factors to retain in the modeling of multiple items across questionnaires and examine model fit. Subsequently for poor fitting models in an iterative procedure to determine a better fitting multidimensional model, we posited a bifactor confirmatory factor analysis model.

RESULTS

The bivariate correlation analysis revealed that subscales from the same questionnaire measuring different aspects of fatigue had the highest correlations (r = 0.61-0.68), subscales from different questionnaires measuring the same aspect of fatigue had the next highest correlations (r = 0.43-0.60), and subscales from different questionnaires measuring different aspects of fatigue had the lowest correlations (r = 0.34-0.40). Bifactor models with a general fatigue factor and subdomains pertaining to impact, severity, and mental and physical fatigue had relatively good model fits compared to models omitting the subdomains. However, an ESEM model using subscales from the CFS and FSMC fit poorly and did not adequately identify separate factors for mental and physical fatigue. An ESEM model with separate factors for self-reported mental fatigue, depressive symptoms, and cognitive impairment was a good fit.

CONCLUSIONS

The working study hypothesis that fatigue constructs would be moderately correlated yet distinct entities was generally supported by the results of the study. However, we found that our hypothesized separation into a latent dimension existed only when the items or subscales came from the same questionnaire, in which case their level of specificity in terms of target, action, context, and time elements for measuring fatigue were consistent. The implications for the principle of compatibility in measuring self-reported MS fatigue are discussed.

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.