Background

Cognitive impairment (CI) is common in multiple sclerosis (MS), but due to a lack of longitudinal data it remains unclear which mechanisms relate to conversion to mild or even severe CI. Previous cross-sectional work has suggested the importance of cognition-related resting-state networks, such as the default-mode and attention networks.

Objectives

To characterize the functional network changes related to conversion to CI in a large sample of MS patients over a period of 5 years.

Methods

A total of 233 MS patients and 59 healthy controls (HC), all part of the Amsterdam MS cohort, underwent extensive neuropsychological testing and resting-state fMRI at baseline and follow-up (mean time-interval 4.9±0.9 years). At baseline, MS patients were categorized as being cognitively impaired (scoring ≤-2 SD on ≥2 domains, N=74), mildly impaired (MCI, being impaired on 1 domain or scoring between -1.5 and -2SD on ≥2 domains, N=33) or preserved (CP, not fulfilling the CI or MCI criteria, N=126). In addition, these groups were categorized according to the group to which they converted at follow-up (e.g. CP to CI). Network function was quantified using eigenvector centrality, a measure of network importance, which was averaged over established resting-state networks at both time-points. Correlations with brain volumes were calculated.

Results

Over time, 26.2% of CP patients deteriorated and developed MCI (66.7%) or CI (33.3%) and 73.8% remained CP. 23.5% of MCI patients, progressed to CI. Centrality analysis showed that patients who were CI at baseline demonstrated a higher cross-sectional DMN centrality compared to controls (P=.05). Longitudinally, patients who remained CP and CP-to-MCI converters showed increasing ventral attention network (VAN) centrality over time time (P=.017 and .008, respectively), , whereas in the MCI and CI converter groups this increase was absent. Patients with less severe deep gray matter atrophy at baseline showed stronger increases in VAN centrality over time.

Conclusions

We showed that conversion from intact cognition to impairment in MS is related to an increase in centrality of the VAN, which is absent when overt impairment has manifested, then shifting towards DMN dysfunction. As the ventral attention network is known to normally relay information to the DMN, our results suggest that developing cognitive impairment is related to a progressive loss of control over the DMN by means of VAN dysfunction.

Background

Typing behavior on a smartphone may be used as a biomarker in patients with multiple sclerosis (MS) by analyzing their keystroke dynamics (KD). The continuous acquisition of high sample rate data may provide unprecedented insights in short-term changes in important health outcomes in MS.

Objectives

To investigate the sensitivity of KD to clinically relevant change (i.e. responsiveness) in disease activity, fatigue, and clinical disability outcomes in patients with MS.

Methods

Patients with MS were recruited in this cohort study. Clinical outcomes were assessed at baseline and 3 months follow-up, including: MRI gadolinium-enhancing lesions (Gd-EL), patient-perceived fatigue, and clinical disability measures (Expanded Disability Status Scale, EDSS; Timed 25-foot Walk Test, TWT; Nine-Hole Peg Test, NHPT; Arm function in MS Questionnaire, AMSQ). Throughout the study, patients used the Neurokeys App which replaces the native keyboard with a smart-keyboard and unobtrusively collects time-stamped key press and release events in the real-world setting. Keystroke data of 14 days surrounding the clinical visits were aggregated for the analyses. The area under the receiver operating characteristics curve (AUROC) was calculated to assess responsiveness of KD in classifying anchor-based change within clinical outcomes. The minimally important change (MIC) was calculated as the mean change in KD in the lower +2 SD portion (to approximate minimal change) of patients with clinically relevant change for each clinical outcome. The MIC was compared to the smallest detectable change (SDC) to assess the capability of KD to distinguish important change from measurement error.

Results

102 patients with MS were included, of whom 94 completed follow-up. Responsiveness of KD were acceptable for change in number of MRI Gd-EL (highest AUROC = 0.73) and arm function based on the AMSQ score (highest AUROCs = 0.75). KD had excellent responsiveness to change in ambulatory function measured with TWT (highest AUROC = 0.84). EDSS and NHPT had lower AUC values than KD in classifying change in Gd-EL and AMSQ, respectively. For all keystroke features the MIC exceeded the SDC with differences ranging from 3.6 to 92.4%.

Conclusions

KD collected in patients with MS using the Neurokeys App demonstrated responsiveness to clinically relevant changes in gadolinium-enhancing lesions on MRI and clinical disability measures for arm and ambulatory function. Responsiveness of KD was higher than commonly used clinical measures in MS and sensitive enough to discriminate important change from measurement error.

Background

Wearable technology refers to any sensor worn on the person, which as a result makes continuous and remote monitoring available to many people with chronic diseases, including multiple sclerosis (MS). Daily monitoring seems an ideal solution either as an outcome measure or as an adjunct to support rater-based monitoring in both clinical and research settings. There has been an increase in solutions that are available and we look to identify next generation wearables.

Objectives

To identify all validated wearable solutions for PwMS and identify areas of focus for wearable solutions in multiple sclerosis.

Methods

We completed a scoping review (using the PRISMA-ScR guidelines) to summarise the wearable solutions currently available in MS.

Our search strategy utilized subject heading searches: ‘Multiple Sclerosis’ and ‘wearable electronic devices’, as well as keywords ‘wearable technology’, and ‘electronic devices’. The literature search was conducted using MEDLINE (via PubMed) and Embase (via OVID) databases. This search included articles published from database inception to 30 May 2019. Additional searches looked at frequently published authors with different devices, as well as forward and backward citation tracking of included papers.

Results

We identified 35 validated unique solutions that measure gait, cognition, upper limb function, activity, mood and fatigue with most of these solutions being phone applications. Of these, 51% looked at lower limb function with activity levels being looked at by 37% of the total solutions. There was least focus on visual, and mood solutions at 3%, closely followed by quality of life and balance at 5%. Cognition and fatigue accounted for 14% of the total.

Conclusions

Looking forward, there is a change occurring from single measure solutions to multi-measure and multi-sensor solutions, such as the Floodlight Open app, which utilises multiple sensors within a smart-phone to remotely measure gait, cognition and upper limb function. Future research should consider costs and include implementation science as part of their research and design to ensure cost of delivery strategy is also accounted for.

As development in wearable technology in MS is still on-going, we can expect to see newer wearables focusing on other areas with technology advancements that allow for more upper body and cognitive measures. There is a dearth of validated solutions available for fatigue, mood, and pain.

Background

The MAGNIFY-MS study (NCT03364036) aims to determine the onset of action of cladribine tablets 3.5 mg/kg over 2 years (CT3.5) in patients with relapsing multiple sclerosis (RMS). Efficacy data from the pivotal trial CLARITY showed that outcomes in CT3.5-treated patients were superior to placebo with regard to number and relative reduction of standardized combined unique active (CUA) lesions over the 96-week trial. Carrying out early and frequent magnetic resonance imaging (MRI) will provide valuable insights into the onset of action of CT3.5.

Objectives

To report on the onset of action of CT3.5 by observing changes in counts of CUA MRI lesions during the first 6 months of the MAGNIFY-MS study.

Methods

MRI scans were performed at screening, baseline, and at months 1, 2, 3 and 6 following CT3.5 treatment on patients with highly active RMS. Differences in CUA lesions between post-baseline periods (period 1, months 1–6, period 2, months 2–6, and period 3, months 3–6) were compared to the baseline period. CUA lesion count was standardized to period length and number of MRIs in a period. A mixed effects linear model was used to account for within pooled centre correlation and adjusted for CUA lesion count during the baseline period, age, and baseline expanded disability status scale (EDSS; >3, ≤3). Type-I-error inflation due to multiple testing was controlled by a gatekeeping procedure.

Results

The full analysis set considered for primary analysis included 270 patients. Reductions in mean CUA count were observed from month 1 onwards compared to baseline; by -1.193 in period 1, -1.500 in period 2 and -1.692 in period 3 (all p<0.0001). In particular, the mean T1 Gd+ lesion counts were decreased from month 2 onwards compared to baseline; by -0.857 at month 2, -1.355 at month 3 and -1.449 at month 6 (all p<0.0001). Sensitivity analysis using negative binomial distribution showed that the treatment effect increased with time measured as lack of CUA in subsequent periods; by 61% in period 1, 77% in period 2, and 87% in period 3 (all p<0.0001). The proportion of patients without any CUA lesions increased in the first 6 months; by 52% in period 1 (p=0.0241), 66% in period 2 (p<0.001), and 81% in period 3 (p<0.001).

Conclusions

MRI was used to assess disease activity in a group of highly active RMS on CT3.5 treatment from one month onwards. Data show an early onset of action on CUA lesions that was significant from month 1 versus baseline, with a treatment effect that increased over the first 6 months.

Background

Cognitive impairment in multiple sclerosis (MS) is strongly related to functional network dysfunction. In the absence of MS, optimal cognitive functioning of an individual is ensured by dynamically adapting the configuration of the functional network as needed. How these dynamic patterns are altered in MS remains unclear.

Objectives

Our aim was to investigate the dynamic reconfiguration of cognitively relevant brain networks in MS, to identify specific brain network patterns related to progression of cognitive impairment.

Methods

Resting-state functional MRI (rs-fMRI) and cognitive scores were acquired from 230 patients with MS and 59 matched healthy controls, at baseline and at 5 year follow-up. Seven cognitive domains were examined with the expanded Brief Repeatable Battery of Neuropsychological tests. A sliding-window approach was used on the rs-fMRI data, for which brain regions were assigned to one of seven classic literature-based resting-state networks based on connectivity patterns at that point in time. How regions switched between networks was described using measures of promiscuity (number of networks switched to), flexibility (number of switches), cohesion (switches with another region), and disjointedness (independent switches). Linear mixed models were used for baseline and longitudinal analyses, controlling for age, sex, and education.

Results

At baseline, 42% of patients showed cognitive impairment (CI) (18% Mild CI, ≥2 tests Z<-1.5; 23% severe CI, ≥2 tests Z<-2) and 28% of patients declined over time (≥2 tests yearly reliable decline>0.25). At baseline, CI patients showed increased promiscuity, flexibility and cohesion (i.e. more switching between networks) compared to preserved patients. Patients displaying cognitive deterioration showed increases in cohesion over time. Higher baseline cohesion was related to less gray matter volume, and more white matter integrity loss and lesion volume. Within cognitive domains, cohesion was inversely related to verbal memory, information processing speed, and working memory.

Conclusions

In patients with MS, increased switching between brain networks was related to cognitive impairment and structural damage. Cohesion particularly increased over time in patients showing cognitive decline, indicating that switching together with other regions might be particularly more common. These results provide support for the hypothesis of a progressive destabilization of the functional brain network in MS.

Background

Natalizumab is an effective disease modifying therapy (DMT) for relapsing remitting multiple sclerosis (RRMS). However, it is associated with an increased risk of progressive multifocal leukoencephalopathy (PML). Nine confirmed cases of PML have been reported in patients using ocrelizumab, another effective DMT for MS. In 8 cases, patients previously used natalizumab or fingolimod, likely causing PML. This phenomenon has been described as carry-over PML.

Objectives

To describe the disease course of carry-over PML after switching from natalizumab to ocrelizumab in two patients with RRMS.

Methods

Two case reports with 1 year of follow-up and retrospective longitudinal measurements of serum neurofilament light (sNfL) levels and B-cell count. Both patients provided informed consent.

Results

Regular follow-up showed no disease activity under natalizumab treatment and both patients switched to ocrelizumab following a stringent safety protocol including two additional MRI brain scans and cerebrospinal fluid (CSF) analysis. Both patients received a single infusion of 300 mg ocrelizumab before PML diagnosis. PML was diagnosed ±11 weeks (case 1) and ±13 weeks (case 2) after the last natalizumab infusion. At that time, both patients were asymptomatic. In retrospect, subtle signs suggestive of PML were already present on MRI under natalizumab treatment. One patient developed PML despite extended interval dosing of natalizumab. Both patients developed mild immune reconstitution inflammatory syndrome (IRIS) despite complete B-cell depletion. SNfL levels were 9.9 pg/ml (reference range 1-15 pg/ml) for case 1 and 16.7 pg/ml (reference range 2-18 pg/ml) for case 2 at the time of PML diagnosis and increased to 15.0 pg/ml and 36.5 pg/mL during PML-IRIS. SNfL was not elevated before radiological diagnosis of PML. PML-IRIS lesions stabilized after treatment with mefloquine and mirtazapine followed by methylprednisolone with sNfL levels of 9.0 pg/mL and 12.3 pg/mL, respectively. One patient reported no clinical symptoms and one patient only mild clinical symptoms with full recovery during the disease course of PML-IRIS. Both patients continued with ocrelizumab when B-cells started to repopulate ±10 months after the first ocrelizumab infusion.

Conclusions

The clinical course of carry-over PML was mild in both patients, suggesting that B-cell depletion did not aggravate PML-IRIS in these two patients.