Staging and stratifying cognitive dysfunction in multiple sclerosis

Advanced neuroimaging techniques to explore the effects of motor and cognitive rehabilitation in multiple sclerosis

INTRODUCTION

Progress in magnetic resonance imaging (MRI) technology and analyses is improving our comprehension of multiple sclerosis (MS) pathophysiology. These advancements, which enable the evaluation of atrophy, microstructural tissue abnormalities, and functional plasticity, are broadening our insights into the effectiveness and working mechanisms of motor and cognitive rehabilitative treatments.

AREAS COVERED

This narrative review with selected studies discusses findings derived from the application of advanced MRI techniques to evaluate structural and functional neuroplasticity modifications underlying the effects of motor and cognitive rehabilitative treatments in people with MS (PwMS). Current applications as outcome measure in longitudinal trials and observational studies, their interpretation and possible pitfalls and limitations in their use are covered. Finally, we examine how the use of these techniques could evolve in the future to improve monitoring of motor and cognitive rehabilitative treatments.

EXPERT COMMENTARY

Despite substantial variability in study design and participant characteristics in rehabilitative studies for PwMS, improvements in motor and cognitive functions accompanied by structural and functional brain modifications induced by rehabilitation can be observed. However, significant enhancements to refine rehabilitation strategies are needed. Future studies in this field should strive to implement standardized methodologies regarding MRI acquisition and processing, possibly integrating multimodal measures. This will help identifying relevant markers of treatment response in PwMS, thus improving the use of rehabilitative interventions at individual level. The combination of motor and cognitive strategies, longer periods of treatment, as well as adequate follow-up assessments will contribute to enhance the quality of evidence in support of their routine use.

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.

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.

Data-driven modelling of neurodegenerative disease progression: thinking outside the black box

Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.

Don't be late! Timely identification of cognitive impairment in people with multiple sclerosis: a study protocol

BACKGROUND

Cognitive impairment occurs in up to 65% of people with multiple sclerosis (PwMS), negatively affecting daily functioning and health-related quality of life. In general, neuropsychological testing is not part of standard MS-care due to insufficient time and trained personnel. Consequently, a baseline assessment of cognitive functioning is often lacking, hampering early identification of cognitive decline and change within a person over time. To assess cognitive functioning in PwMS in a time-efficient manner, a BICAMS-based self-explanatory digital screening tool called the Multiple Screener©, has recently been developed. The aim of the current study is to validate the Multiple Screener© in a representative sample of PwMS in the Netherlands. Additionally, we aim to investigate how cognitive functioning is related to psychological factors, and both work and societal participation.

METHODS

In this cross-sectional multicentre study, 750 PwMS (aged 18-67 years) are included. To obtain a representative sample, PwMS are recruited via 12 hospitals across the Netherlands. They undergo assessment with the Minimal Assessment of Cognitive Functioning in MS (MACFIMS; reference-standard) and the Multiple Screener©. Sensitivity, specificity, and predictive values for identifying (mild) cognitive impairment are determined in a subset of 300 participants. In a second step, the identified cut-off values are tested in an independent subset of at least 150 PwMS. Moreover, test-retest reliability for the Multiple Screener© is determined in 30 PwMS. Information on psychological and work-related factors is assessed with questionnaires.

DISCUSSION

Validating the Multiple Screener© in PwMS and investigating cognition and its determinants will further facilitate early identification and adequate monitoring of cognitive decline in PwMS.

Basal Ganglia Atrophy and Impaired Cognitive Processing Speed in Multiple Sclerosis

Impaired cognitive processing speed is among the important higher brain dysfunctions in multiple sclerosis (MS). However, the exact structural mechanisms of the dysfunction remain uncertain. This study aimed to identify the brain regions associated with the impaired cognitive processing speed in MS by comparing the cognitive processing speed, measured using the Cognitive Processing Speed Test (CogEval) z-score, and brain regional volumetric data. Altogether, 80 patients with MS (64 with relapsing-remitting MS [RRMS] and 16 with secondary progressive MS [SPMS]) were enrolled. Consequently, CogEval z-scores were worse in patients with SPMS than in those with RRMS (p=0.001). In the univariate correlation analyses, significant correlations with CogEval z-score were suggested in the MS lesion volume (p<0.001; Spearman's rank correlation test) and atrophies in the cerebral cortex (p=0.031), cerebral white matter (p=0.013), corpus callosum (p=0.001), thalamus (p=0.001), and putamen (p<0.001). Multiple linear regression analysis revealed that putamen atrophy was significantly associated with CogEval z-score (p=0.038) independent of volume in other brain regions, while thalamic atrophy was not (p=0.79). Univariate correlation analyses were further performed in each of RRMS and SPMS. None of the evaluated volumetric data indicated a significant correlation with the CogEval z-score in RRMS. Meanwhile, atrophies in the cerebral white matter (p=0.008), corpus callosum (p=0.002), putamen (p=0.011), and pallidum (p=0.017) demonstrated significant correlations with CogEval z-score in SPMS. In summary, the putamen could be an important region of atrophy contributing to the impaired cognitive speed in MS, especially in the later disease stages after a transition to SPMS.

Analysis of Pregnancy Outcomes Following Exposure to Intramuscular Interferon Beta-1a: The AVONEX® Pregnancy Exposure Registry

BACKGROUND AND OBJECTIVES

There is a lack of well-controlled US studies of intramuscular (IM) interferon beta (IFNβ)-1a use in pregnant women with multiple sclerosis; however, in the European Medicines Agency region, IFNβ formulations may be considered during pregnancy if clinically needed based on data from European Union cohort registries. The AVONEX Pregnancy Exposure Registry was established to prospectively study the effects of IM IFNβ-1a on the risk of birth defects and spontaneous pregnancy loss in a US population.

METHODS

Pregnant women with multiple sclerosis exposed to IM IFNβ-1a within ~ 1 week of conception or during the first trimester were included. Participants were followed until there was a pregnancy outcome, live-born infants were followed until age 8-12 weeks. Data were collected on IM IFNβ-1a exposure, demographics, patient characteristics, medical history, and pregnancy outcomes, including live births (with or without birth defect), spontaneous abortions/miscarriages and fetal death/stillbirth, elective abortions (with and without birth defect), and ectopic pregnancies. A population-based birth defect surveillance program, the Metropolitan Atlanta Congenital Defects Program (MACDP), served as the primary external control group for evaluating the risk of birth defects.

RESULTS

Three-hundred and two patients with a median (range) age of 31.0 (16-48) years and a median (range) gestational age at the time of enrollment of 10.1 (4-39) weeks were evaluable. Most patients (n = 278/302; 92%) reported IM IFNβ-1a exposure in the week before conception and most (n = 293/302; 97%) discontinued treatment before the end of the first trimester. Of 306 pregnancy outcomes, there were 272 live births, 28 spontaneous abortions of 266 pregnancies enrolled before 22 weeks' gestation (rate 10.5%; 95% confidence interval 7.2-15.0), five elective abortions, and one stillbirth. There were 17 adjudicator-confirmed major birth defects of 272 live births (rate 6.3%; 95% confidence interval 3.8-10.0); the pattern of birth defects observed was not suggestive of a relationship to prenatal IM IFNβ-1a exposure.

CONCLUSIONS

This large US registry study suggests IM IFNβ-1a exposure during early pregnancy was not clinically associated with adverse pregnancy outcomes in women with multiple sclerosis. These findings help inform clinicians and patients in weighing the risks and benefits of IM IFNβ-1a use during pregnancy.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: NCT00168714, 15 September, 2005.

A French Version of a Voice Recognition Symbol Digit Modalities Test Analog

We previously showed that a fully automated voice recognition analog of the Symbol Digit Modalities Test (VR-SDMT) is sensitive in detecting processing speed deficits in people with multiple sclerosis (pwMS). We subsequently developed a French language version and administered it to 49 French-Canadian pwMS and 29 matched healthy control (HC) subjects. Significant correlations between the VR-SDMT and traditional oral SDMT were found in the MS (r = -0.716, p < 0.001) and HC (r = -0.623, p < 0.001) groups. These findings in French replicate our previous findings and confirm the utility of voice recognition software in assessing cognition in pwMS.

Profiling cognitive-motor interference in a large sample of persons with progressive multiple sclerosis and impaired processing speed: results from the CogEx study

BACKGROUND

Performing cognitive-motor dual tasks (DTs) may result in reduced walking speed and cognitive performance. The effect in persons with progressive multiple sclerosis (pwPMS) having cognitive dysfunction is unknown.

OBJECTIVE

To profile DT-performance during walking in cognitively impaired pwPMS and examine DT-performance by disability level.

METHODS

Secondary analyses were conducted on baseline data from the CogEx-study. Participants, enrolled with Symbol Digit Modalities Test 1.282 standard deviations below normative value, performed a cognitive single task ([ST], alternating alphabet), motor ST (walking) and DT (both). Outcomes were number of correct answers on the alternating alphabet task, walking speed, and DT-cost (DTC: decline in performance relative to the ST). Outcomes were compared between EDSS subgroups (≤ 4, 4.5-5.5, ≥ 6). Spearman correlations were conducted between the DTCmotor with clinical measures. Adjusted significance level was 0.01.

RESULTS

Overall, participants (n = 307) walked slower and had fewer correct answers on the DT versus ST (both p < 0.001), with a DTCmotor of 15.8% and DTCcognitive of 2.7%. All three subgroups walked slower during the DT versus ST, with DTCmotor different from zero (p's < 0.001). Only the EDSS ≥ 6 group had fewer correct answers on the DT versus ST (p < 0.001), but the DTCcognitive did not differ from zero for any of the groups (p ≥ 0.039).

CONCLUSION

Dual tasking substantially affects walking performance in cognitively impaired pwPMS, to a similar degree for EDSS subgroups.

Repeated forms, testing intervals, and SDMT performance in a large multiple sclerosis dataset

BACKGROUND

The Symbol Digit Modalities Test (SDMT), the most reliable and sensitive measure of cognition in people with multiple sclerosis (PwMS), is increasingly used in clinical trials and care.

OBJECTIVES

We aimed to establish how SDMT performance is influenced by repeating forms and frequency of use in PwMS.

METHODS

A retrospective analysis was completed on a large database of PwMS (n = 740) with multiple SDMT administrations. Change in SDMT performance was analyzed, accounting for frequency of tests and utilization of alternate- versus same-form conditions.

RESULTS

SDMT administrations ranged from 2 to 14 per subject over a mean (SD) of 5.9 (4.5) years. Accounting for demographics, the mixed effects model revealed a significant main effect of SDMT exposures (1.8 point improvement per repetition, p = 0.001) and an interaction between time since previous SDMT and whether the same test form was administered in the previous administration (estimate=-1.1, p = 0.037). As well, SDMT decline is observed when testing intervals exceed two years (F = 9.69, p<0.001).

CONCLUSION

Improvements in SDMT performance with repeated exposure, likely reflecting practice effects, were greatest when repeating the same SDMT form over briefer intervals. We recommend the use of alternate forms or analogous versions of timed symbol-digit coding particularly where samples are saturated with many administrations.

Stages of brain volume loss and performance in the Brief International Cognitive Assessment for Multiple Sclerosis

BACKGROUND

Cognitive dysfunction occurs in a substantial proportion of patients with multiple sclerosis (MS), negatively affects their daily activities, and is associated with poor prognosis. Cognitive dysfunction in MS can extend across multiple cognitive domains, depending on the patterns and extent of the brain regions affected. Therefore, a combination of tests, including the Brief International Cognitive Assessment for MS (BICAMS), that assess different aspects of cognition is recommended to capture the full picture of cognitive impairment in each patient. However, the temporal relationships between the progression of the MS brain pathology and the performances in different cognitive tests remain unclear.

METHODS

Global and regional brain volume data were obtained based on T1-weighted magnetic resonance imaging from 61 patients with MS, and hierarchical cluster analysis was performed using these brain volume data. Cognitive function was assessed using the three subcomponents of the BICAMS: the Symbol Digit Modalities Test (SDMT), California Verbal Learning Test Second Edition (CVLT2), and Brief Visuospatial Memory Test-Revised (BVMTR). Clinical characteristics, patterns of regional brain volume loss, and cognitive test scores were compared among clusters.

RESULTS

Cluster analysis of the global and regional brain volume data classified patients into three clusters (Clusters 1, 2, and 3) in order of decreasing global brain volume. A comparison of the clinical profiles of the patients suggested that those in Clusters 1, 2, and 3 are in the early, intermediate, and advanced stages of MS, respectively. Pair-wise analysis of regional brain volume among the three clusters suggested brain regions where volume loss starts early and continues throughout the disease course, occurs preferentially at the early phase, or evolves relatively slowly. SDMT scores differed significantly among the three clusters, with a decrease from Clusters 1 to 3. BVMTR scores also declined in this order, whereas the CVLT2 was significantly impaired only in Cluster 3.

CONCLUSION

Our results suggest that SDMT performance declines in conjunction with brain volume loss throughout the disease course of MS. Performance in the BVMTR also declines in line with the brain volume loss, but impairment in the CVLT2 becomes particularly apparent at the late phase of MS.

Cognitive dysfunction and mortality in multiple sclerosis: Long-term retrospective review

BACKGROUND

Cognitive dysfunction as a predictor of clinical progression and mortality in multiple sclerosis (MS) is still a matter of debate.

OBJECTIVE

The aim of this study was to explore the long-term outcome associated with neuropsychological performance in a cohort of patients with MS.

METHODS

A series of 408 MS patients had previously undergone a comprehensive neuropsychological assessment and a contemporaneous neurological evaluation (T1). A retrospective review of the clinical records was conducted 102-192 months after T1. Demographic and clinical data regarding the last clinical appointment with EDSS measurement (T2) were collected and the date of the last clinical contact or death (TS) was recorded.

RESULTS

This review revealed that cognitive dysfunction (T1) was associated with higher odds of transitioning from relapsing-remitting course to a progressive disease course (adjusted odds ratio (OR) = 2.29, p = 0.043) and higher hazard of death in the total sample (adjusted hazard ratio (HR) = 3.07, p = 0.006) and the progressive disease course subgroup (adjusted HR = 3.68, p = 0.007), even when adjusting for other covariates.

DISCUSSION

The study results demonstrate that cognitive dysfunction in MS is predictive of poorer prognosis and mortality.

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

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

Benchmarks of meaningful improvement on neurocognitive tests in multiple sclerosis

BACKGROUND

Previous studies have established benchmarks of clinically meaningful decline on neuropsychological tests. However, little is known about meaningful testing benchmarks based on gains in function.

OBJECTIVE

Investigate neuropsychological changes in multiple sclerosis (MS) patients with work gains and calculate benchmarks of meaningful improvement on neuropsychological tests.

METHODS

A total of 323 people with MS were monitored longitudinally with neuropsychological testing and the Buffalo Vocational Monitoring Survey.

RESULTS/CONCLUSIONS

Those with work gains showed significant improvement (~3 points) on the Symbol Digit Modalities Test (SDMT) over time, p = 0.01. Benchmarks for clinically meaningful improvement on the SDMT are similar to those previously established for clinically meaningful decline.