Thalamic atrophy in multiple sclerosis: A magnetic resonance imaging marker of neurodegeneration throughout disease

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

Association of volumetric MRI measures and disability in MS patients of the same age: Descriptions from a birth year cohort

BACKGROUND AND OBJECTIVES

Although MRI-based markers of neuroinflammation have proven crucial for the diagnosis of multiple sclerosis (MS), predicting clinical progression with inflammation remains difficult. Neurodegenerative markers such as brain volume loss show stronger clinical (predictive) correlations, but also harbor age-related variation that must be disentangled from disease duration. In this study we investigated how clinical disability is related to volumetric MRI measures in a cohort of MS patients and healthy controls (HC) of the same age: Project Y.

METHODS

This study included 234 MS patients born in 1966 and 112 HC born between 1965 and 1967 in the Netherlands. Disability was quantified using the expanded disability status scale (EDSS), nine hole peg test (9HPT), and timed 25 foot walking test (T25FWT). Volumes were quantified on 3T MRI as normalized whole brain (NBV) and regional gray matter (GM) volumes using the same scanner and MRI protocol: cortical (normalized cortical gray matter volume; NCGMV), deep (NDGMV), thalamic (NThalV), and cerebellar (NCbV) GM volumes. In addition, mean upper cervical cord area (MUCCA), white matter lesion volume (LV), and spinal cord lesions were assessed. These measures were compared between patients and HC, and related to disability measures using linear regression.

RESULTS

Mean age of people with MS (PwMS) was 52.8 years (SD 0.9) and median disease duration 15.8 years (IQR 8.7-24.8). All global and regional brain measures were lower in MS patients compared to HC. Univariate regression models showed that NDGMV (β = -0.20) and MUCCA (β = -0.38) were most strongly related to the EDSS in all PwMS. After subtype stratification, MUCCA was most strongly related to the EDSS (β = -0.60) and 9HPT (β = -0.55) in secondary progressive PwMS. Multivariate regression models demonstrated that in all PwMS, the EDSS was best explained by lower MUCCA, longer disease durations and a progressive disease course (adjusted-R (Sastre-Garriga et al., 2017) = 0.26, p < 0.001). MUCCA was a consistent correlate in separate models of the EDSS for all PwMS, relapsing and progressive onset PwMS. The 9HPT (adjusted-R (Sastre-Garriga et al., 2017) = 0.20, p < 0.001) was best explained by lower MUCCA, higher LV and pack years, while lower limb disability (adjusted-R (Sastre-Garriga et al., 2017) = 0.11, p < 0.001) was best explained by lower MUCCA, progressive onset MS and female sex.

DISCUSSION

Our results indicate that in a cohort unbiased by age differences, spinal cord and deep gray matter volumes best related to physical disability. Our results support the use of these measures in clinical practice and trials.

ALFF response interaction with learning during feedback in individuals with multiple sclerosis

Amplitude of low-frequency fluctuations (ALFF) is defined as changes of BOLD signal during resting state (RS) brain activity. Previous studies identified differences in RS activation between healthy and multiple sclerosis (MS) participants. However, no research has investigated the relationship between ALFF and learning in MS. We thus examine this here. Twenty-five MS and nineteen healthy participants performed a paired-associate word learning task where participants were presented with extrinsic or intrinsic performance feedback. Compared to healthy participants, MS participants showed higher local brain activation in the right thalamus. We also observed a positive correlation in the MS group between ALFF and extrinsic feedback within the left inferior frontal gyrus, and within the left superior temporal gyrus in association with intrinsic feedback. Healthy participants showed a positive correlation in the right fusiform gyrus between ALFF and extrinsic feedback. Findings suggest that while MS participants do not show a feedback learning impairment compared to the healthy participants, ALFF differences might suggest a general maladaptive pattern of task unrelated thalamic activation and adaptive activation in frontal and temporal regions. Results indicate that ALFF can be successfully used at capturing pathophysiological changes in local brain activation in MS in association with learning through feedback.

Mediterranean diet is linked to less objective disability in multiple sclerosis

BACKGROUND

The multiple sclerosis (MS) community is highly interested in diet as a potential protective factor against disability, but empirical evidence remains limited.

OBJECTIVE

Evaluate associations between patient-reported Mediterranean diet alignment and objective disability in a real-world MS cohort.

METHODS

Data were analyzed from persons with MS, aged 18-65, who completed the Mediterranean Diet Adherence Screener (MEDAS), MS Functional Composite (MSFC; primary disability metric), and patient-reported outcomes (PROs; disability, gait disturbance, fatigue, anxiety, and depression) as part of our Comprehensive Annual Assessment Program. Multiple regression predicted MSFC (and PROs) with MEDAS after adjusting for demographic (age, sex, race, ethnicity, and socioeconomic status) and health-related (body mass index (BMI), exercise, sleep disturbance, hypertension, diabetes, hyperlipidemia, and smoking) covariates.

RESULTS

Higher MEDAS independently predicted better outcomes across MSFC (z-score, B = 0.10 (95% confidence interval (CI): 0.06, 0.13), β = 0.18, p < 0.001), MSFC components, and PROs in 563 consecutive patients. Each MEDAS point was associated with 15.0% lower risk for MSFC impairment (⩽ 5th percentile on ⩾ 2 tasks; odds ratio (OR) = 0.850; 95% CI: 0.779, 0.928). Higher MEDAS attenuated effects of progressive disease and longer disease duration on disability.

CONCLUSION

With robust control for potential confounds, higher Mediterranean diet alignment predicted lower objective and patient-reported disability. Findings lay the necessary groundwork for longitudinal and interventional studies to guide clinical recommendations in MS.

Communicating the relevance of neurodegeneration and brain atrophy to multiple sclerosis patients: patient, provider and researcher perspectives

Central nervous system (CNS) atrophy provides valuable additional evidence of an ongoing neurodegeneration independent of lesion accrual in persons with multiple sclerosis (PwMS). However, there are limitations for interpretation of CNS volume changes at individual patient-level. Patients are receiving information on the topic of atrophy through various sources, including media, patient support groups and conferences, and discussions with their providers. Whether or not the topic of CNS atrophy should be proactively discussed with PwMS during office appointments is currently controversial. This commentary/perspective article represents perspectives of PwMS, providers and researchers with recommendations for minimizing confusion and anxiety, and facilitating proactive discussion about brain atrophy, as an upcoming routine measure in evaluating disease progression and treatment response monitoring. The following recommendations were created based on application of patient's and provider's surveys, and various workshops held over a period of 2 years: (1) PwMS should receive basic information on understanding of brain functional anatomy, and explanation of inflammation and neurodegeneration; (2) the expertise for atrophy measurements should be characterized as evolving; (3) quality patient education materials on these topics should be provided; (4) the need for standardization of MRI exams has to be explained and communicated; (5) providers should discuss background on volumetric changes, including references to normal aging; (6) the limitations of brain volume assessments at an individual-level should be explained; (7) the timing and language used to convey this information should be individualized based on the patient's background and disease status; (8) a discussion guide may be a very helpful resource for use by providers/staff to support these discussions; (9) understanding the role of brain atrophy and other MRI metrics may elicit greater patient satisfaction and acceptance of the value of therapies that have proven efficacy around these outcomes; (10) the areas that represent possibilities for positive self-management of MS symptoms that foster hope for improvement should be emphasized, and in particular regarding use of physical and mental exercise that build or maintain brain reserve through increased network efficiency, and (11) an additional time during clinical visits should be allotted to discuss these topics, including creation of specific educational programs.

Periventricular remyelination failure in multiple sclerosis: a substrate for neurodegeneration

In multiple sclerosis, spontaneous remyelination is generally incomplete and heterogeneous across patients. A high heterogeneity in remyelination may also exist across lesions within the same individual, suggesting the presence of local factors interfering with myelin regeneration. In this study we explored in vivo the regional distribution of myelin repair and investigated its relationship with neurodegeneration. We first took advantage of the myelin binding property of the amyloid radiotracer 11C-PiB to conduct a longitudinal 11C-PiB PET study in an original cohort of 19 participants with a relapsing-remitting form of multiple sclerosis, followed-up over a period of 1-4 months. We then replicated our results on an independent cohort of 40 people with multiple sclerosis followed-up over 1 year with magnetization transfer imaging, an MRI metrics sensitive to myelin content. For each imaging method, voxel-wise maps of myelin content changes were generated according to modality-specific thresholds. We demonstrated a selective failure of remyelination in periventricular white matter lesions of people with multiple sclerosis in both cohorts. In both the original and the replication cohort, we estimated that the probability of demyelinated voxels to remyelinate over the follow-up increased significantly as a function of the distance from ventricular CSF. Enlarged choroid plexus, a recently discovered biomarker linked to neuroinflammation, was found to be associated with the periventricular failure of remyelination in the two cohorts (r = -0.79, P = 0.0018; r = -0.40, P = 0.045, respectively), suggesting a role of the brain-CSF barrier in affecting myelin repair in surrounding tissues. In both cohorts, the failure of remyelination in periventricular white matter lesions was associated with lower thalamic volume (r = 0.86, P < 0.0001; r = 0.33; P = 0.069, respectively), an imaging marker of neurodegeneration. Interestingly, we also showed an association between the periventricular failure of remyelination and regional cortical atrophy that was mediated by the number of cortex-derived tracts passing through periventricular white matter lesions, especially in patients at the relapsing-remitting stage. Our findings demonstrate that lesion proximity to ventricles is associated with a failure of myelin repair and support the hypothesis that a selective periventricular remyelination failure in combination with the large number of tracts connecting periventricular lesions with cortical areas is a key mechanism contributing to cortical damage in multiple sclerosis.

Trans-Synaptic Degeneration Following Acute Optic Neuritis in Multiple Sclerosis

OBJECTIVE

To explore longitudinal changes in brain volumetric measures and retinal layer thicknesses following acute optic neuritis (AON) in people with multiple sclerosis (PwMS), to investigate the process of trans-synaptic degeneration, and determine its clinical relevance.

METHODS

PwMS were recruited within 40 days of AON onset (n = 49), and underwent baseline retinal optical coherence tomography and brain magnetic resonance imaging followed by longitudinal tracking for up to 5 years. A comparator cohort of PwMS without a recent episode of AON were similarly tracked (n = 73). Mixed-effects linear regression models were used.

RESULTS

Accelerated atrophy of the occipital gray matter (GM), calcarine GM, and thalamus was seen in the AON cohort, as compared with the non-AON cohort (-0.76% vs -0.22% per year [p = 0.01] for occipital GM, -1.83% vs -0.32% per year [p = 0.008] for calcarine GM, -1.17% vs -0.67% per year [p = 0.02] for thalamus), whereas rates of whole-brain, cortical GM, non-occipital cortical GM atrophy, and T2 lesion accumulation did not differ significantly between the cohorts. In the AON cohort, greater AON-induced reduction in ganglion cell+inner plexiform layer thickness over the first year was associated with faster rates of whole-brain (r = 0.32, p = 0.04), white matter (r = 0.32, p = 0.04), and thalamic (r = 0.36, p = 0.02) atrophy over the study period. Significant relationships were identified between faster atrophy of the subcortical GM and thalamus, with worse visual function outcomes after AON.

INTERPRETATION

These results provide in-vivo evidence for anterograde trans-synaptic degeneration following AON in PwMS, and suggest that trans-synaptic degeneration may be related to clinically-relevant visual outcomes. ANN NEUROL 2023;93:76-87.

Neurodegeneration in multiple sclerosis

Axonal loss in multiple sclerosis (MS) is a key component of disease progression and permanent neurologic disability. MS is a heterogeneous demyelinating and neurodegenerative disease of the central nervous system (CNS) with varying presentation, disease courses, and prognosis. Immunomodulatory therapies reduce the frequency and severity of inflammatory demyelinating events that are a hallmark of MS, but there is minimal therapy to treat progressive disease and there is no cure. Data from patients with MS, post-mortem histological analysis, and animal models of demyelinating disease have elucidated patterns of MS pathogenesis and underlying mechanisms of neurodegeneration. MRI and molecular biomarkers have been proposed to identify predictors of neurodegeneration and risk factors for disease progression. Early signs of axonal dysfunction have come to light including impaired mitochondrial trafficking, structural axonal changes, and synaptic alterations. With sustained inflammation as well as impaired remyelination, axons succumb to degeneration contributing to CNS atrophy and worsening of disease. These studies highlight the role of chronic demyelination in the CNS in perpetuating axonal loss, and the difficulty in promoting remyelination and repair amidst persistent inflammatory insult. Regenerative and neuroprotective strategies are essential to overcome this barrier, with early intervention being critical to rescue axonal integrity and function. The clinical and basic research studies discussed in this review have set the stage for identifying key propagators of neurodegeneration in MS, leading the way for neuroprotective therapeutic development. This article is categorized under: Immune System Diseases > Molecular and Cellular Physiology Neurological Diseases > Molecular and Cellular Physiology.

Thalamic nuclei atrophy at high and heterogenous rates during cognitively unimpaired human aging

The thalamus is a central integration structure in the brain, receiving and distributing information among the cerebral cortex, subcortical structures, and the peripheral nervous system. Prior studies clearly show that the thalamus atrophies in cognitively unimpaired aging. However, the thalamus is comprised of multiple nuclei involved in a wide range of functions, and the age-related atrophy of individual thalamic nuclei remains unknown. Using a recently developed automated method of identifying thalamic nuclei (3T or 7T MRI with white-matter-nulled MPRAGE contrast and THOMAS segmentation) and a cross-sectional design, we evaluated the age-related atrophy rate for 10 thalamic nuclei (AV, CM, VA, VLA, VLP, VPL, pulvinar, LGN, MGN, MD) and an epithalamic nucleus (habenula). We also used T1-weighted images with the FreeSurfer SAMSEG segmentation method to identify and measure age-related atrophy for 11 extra-thalamic structures (cerebral cortex, cerebral white matter, cerebellar cortex, cerebellar white matter, amygdala, hippocampus, caudate, putamen, nucleus accumbens, pallidum, and lateral ventricle). In 198 cognitively unimpaired participants with ages spanning 20-88 years, we found that the whole thalamus atrophied at a rate of 0.45% per year, and that thalamic nuclei had widely varying age-related atrophy rates, ranging from 0.06% to 1.18% per year. A functional grouping analysis revealed that the thalamic nuclei involved in cognitive (AV, MD; 0.53% atrophy per year), visual (LGN, pulvinar; 0.62% atrophy per year), and auditory/vestibular (MGN; 0.64% atrophy per year) functions atrophied at significantly higher rates than those involved in motor (VA, VLA, VLP, and CM; 0.37% atrophy per year) and somatosensory (VPL; 0.32% atrophy per year) functions. A proximity-to-CSF analysis showed that the group of thalamic nuclei situated immediately adjacent to CSF atrophied at a significantly greater atrophy rate (0.59% atrophy per year) than that of the group of nuclei located farther from CSF (0.36% atrophy per year), supporting a growing hypothesis that CSF-mediated factors contribute to neurodegeneration. We did not find any significant hemispheric differences in these rates of change for thalamic nuclei. Only the CM thalamic nucleus showed a sex-specific difference in atrophy rates, atrophying at a greater rate in male versus female participants. Roughly half of the thalamic nuclei showed greater atrophy than all extra-thalamic structures examined (0% to 0.54% per year). These results show the value of white-matter-nulled MPRAGE imaging and THOMAS segmentation for measuring distinct thalamic nuclei and for characterizing the high and heterogeneous atrophy rates of the thalamus and its nuclei across the adult lifespan. Collectively, these methods and results advance our understanding of the role of thalamic substructures in neurocognitive and disease-related changes that occur with aging.

Alterations of Thalamic Nuclei Volumes and the Intrinsic Thalamic Structural Network in Patients with Multiple Sclerosis-Related Fatigue

Fatigue is a debilitating and prevalent symptom of multiple sclerosis (MS). The thalamus is atrophied at an earlier stage of MS and although the role of the thalamus in the pathophysiology of MS-related fatigue has been reported, there have been few studies on intra-thalamic changes. We investigated the alterations of thalamic nuclei volumes and the intrinsic thalamic network in people with MS presenting fatigue (F-MS). The network metrics comprised the clustering coefficient (Cp), characteristic path length (Lp), small-world index (σ), local efficiency (Eloc), global efficiency (Eglob), and nodal metrics. Volumetric analysis revealed that the right anteroventral, right central lateral, right lateral geniculate, right pulvinar anterior, left pulvinar medial, and left pulvinar inferior nuclei were atrophied only in the F-MS group. Furthermore, the F-MS group had significantly increased Lp compared to people with MS not presenting fatigue (NF-MS) (2.9674 vs. 2.4411, PAUC = 0.038). The F-MS group had significantly decreased nodal efficiency and betweenness centrality of the right mediodorsal medial magnocellular nucleus than the NF-MS group (false discovery rate corrected p < 0.05). The F-MS patients exhibited more atrophied thalamic nuclei, poorer network global functional integration, and disrupted right mediodorsal medial magnocellular nuclei interconnectivity with other nuclei. These findings might aid the elucidation of the underlying pathogenesis of MS-related fatigue.

Automatic measure and normalization of spinal cord cross-sectional area using the pontomedullary junction

Spinal cord cross-sectional area (CSA) is a relevant biomarker to assess spinal cord atrophy in neurodegenerative diseases. However, the considerable inter-subject variability among healthy participants currently limits its usage. Previous studies explored factors contributing to the variability, yet the normalization models required manual intervention and used vertebral levels as a reference, which is an imprecise prediction of the spinal levels. In this study we implemented a method to measure CSA automatically from a spatial reference based on the central nervous system (the pontomedullary junction, PMJ), we investigated factors to explain variability, and developed normalization strategies on a large cohort (N = 804). Following automatic spinal cord segmentation, vertebral labeling and PMJ labeling, the spinal cord CSA was computed on T1w MRI scans from the UK Biobank database. The CSA was computed using two methods. For the first method, the CSA was computed at the level of the C2-C3 intervertebral disc. For the second method, the CSA was computed at 64 mm caudally from the PMJ, this distance corresponding to the average distance between the PMJ and the C2-C3 disc across all participants. The effect of various demographic and anatomical factors was explored, and a stepwise regression found significant predictors; the coefficients of the best fit model were used to normalize CSA. CSA measured at C2-C3 disc and using the PMJ differed significantly (paired t-test, p-value = 0.0002). The best normalization model included thalamus, brain volume, sex and the interaction between brain volume and sex. The coefficient of variation went down for PMJ CSA from 10.09 (without normalization) to 8.59%, a reduction of 14.85%. For CSA at C2-C3, it went down from 9.96 to 8.42%, a reduction of 15.13 %. This study introduces an end-to-end automatic pipeline to measure and normalize cord CSA from a neurological reference. This approach requires further validation to assess atrophy in longitudinal studies. The inter-subject variability of CSA can be partly accounted for by demographics and anatomical factors.

Differences in Age-related Retinal and Cortical Atrophy Rates in Multiple Sclerosis

BACKGROUND AND OBJECTIVES

The timing of neurodegeneration in multiple sclerosis (MS) remains unclear. It is critical to understand the dynamics of neuroaxonal loss if we hope to prevent or forestall permanent disability in MS. We therefore used a deeply phenotyped longitudinal cohort to assess and compare rates of neurodegeneration in retina and brain throughout the MS disease course.

METHODS

We analyzed 597 patients with MS who underwent longitudinal optical coherence tomography imaging annually for 4.5 ± 2.4 years and 432 patients who underwent longitudinal MRI scans for 10 ± 3.4 years, quantifying macular ganglion cell-inner plexiform layer (GCIPL) volume and cortical gray matter (CGM) volume. The association between the slope of decline in the anatomical structure and the age of entry in the cohort (categorized by the MRI cohort's age quartiles) was assessed by hierarchical linear models.

RESULTS

The rate of CGM volume loss declined with increasing age of study entry (1.3% per year atrophy for the age of entry in the cohort younger than 35 years; 1.1% for older than 35 years and younger than 41; 0.97% for older than 41 years and younger than 49; 0.9% for older than 49 years) while the rate of GCIPL thinning was highest in patients in the youngest quartile, fell by more than 50% in the following age quartile, and then stabilized (0.7% per year thinning for the age of entry in the cohort younger than 35 years; 0.29% for age older than 35 and younger than 41 years; 0.34% for older than 41 and younger than 49 years; 0.33% for age older than 49 years).

DISCUSSION

An age-dependent reduction in retinal and cortical volume loss rates during relapsing-remitting MS suggests deceleration in neurodegeneration in the earlier period of disease and further indicates that the period of greatest adaptive immune-mediated inflammatory activity is also the period with the greatest neuroaxonal loss.

Inhibitory synaptic loss drives network changes in multiple sclerosis: An ex vivo to in silico translational study

Background:

Synaptic and neuronal loss contribute to network dysfunction and disability in multiple sclerosis (MS). However, it is unknown whether excitatory or inhibitory synapses and neurons are more vulnerable and how their losses impact network functioning.

Objective:

To quantify excitatory and inhibitory synapses and neurons and to investigate how synaptic loss affects network functioning through computational modeling.

Methods:

Using immunofluorescent staining and confocal microscopy, densities of glutamatergic and GABAergic synapses and neurons were compared between post-mortem MS and non-neurological control cases. Then, a corticothalamic biophysical model was employed to study how MS-induced excitatory and inhibitory synaptic loss affect network functioning.

Results:

In layer VI of normal-appearing MS cortex, excitatory and inhibitory synaptic densities were significantly lower than controls (reductions up to 14.9%), but demyelinated cortex showed larger losses of inhibitory synapses (29%). In our computational model, reducing inhibitory synapses impacted the network most, leading to a disinhibitory increase in neuronal activity and connectivity.

Conclusion:

In MS, excitatory and inhibitory synaptic losses were observed, predominantly for inhibitory synapses in demyelinated cortex. Inhibitory synaptic loss affected network functioning most, leading to increased neuronal activity and connectivity. As network disinhibition relates to cognitive impairment, inhibitory synaptic loss seems particularly relevant in MS.

Thalamic atrophy moderates associations among aerobic fitness, cognitive processing speed, and walking endurance in persons with multiple sclerosis

BACKGROUND AND OBJECTIVES

Thalamic atrophy (TA) represents a biomarker of neurodegeneration and associated dysfunction/decline in physical and cognitive functioning among persons with multiple sclerosis (MS). Aerobic fitness, as an end point of exercise training, represents a promising target for restoring function in MS, but it is unknown if such effects differ by TA. This cross-sectional study examined whether aerobic fitness was differentially associated with cognitive processing speed and walking endurance in persons with MS who present with and without TA.

METHODS

44 fully ambulatory persons with MS completed a graded exercise test for measuring aerobic fitness (VO2peak) and underwent 3T MRI for measuring TA, the Symbol Digit Modalities Test (SDMT), and the 6-min walk (6MW). We performed Spearman correlations (rs) among VO2peak, SDMT, and 6MW scores overall, and in persons with and without TA. We applied Fisher's z-test for comparing correlations based on TA status.

RESULTS

When controlling for age, EDSS score, and global MRI measures of atrophy, VO2peak was strongly associated with SDMT scores (prs = 0.74, p < 0.01) and 6MW performance (prs = 0.77, p < 0.01) in persons with TA, whereas VO2peak was not associated with SDMT scores (prs =  - 0.01, p = 0.99) or 6MW performance (prs = 0.25, p = 0.38) in those without TA. The correlations between VO2peak and SDMT (z = 2.86, p < 0.01) and VO2peak and 6MW (z = 2.33, p = 0.02) were significantly stronger in the TA group.

DISCUSSION

This study provides initial evidence of strong, selective associations among aerobic fitness, cognitive processing speed, and walking endurance in persons with TA as a biomarker for MS-related neurodegeneration. Such data support TA as a moderator of the association among aerobic fitness, cognitive processing speed, and walking endurance in persons with MS. Future research should carefully consider the role of TA when designing trials of aerobic exercise, cognition, and mobility in MS.

Thalamic atrophy measured by artificial intelligence in a multicentre clinical routine real-word study is associated with disability progression

BACKGROUND

The thalamus is a key grey matter structure, and sensitive marker of neurodegeneration in multiple sclerosis (MS). Previous reports indicated that thalamic volumetry using artificial intelligence (AI) on clinical-quality T2-fluid-attenuated inversion recovery (FLAIR) images alone is fast and reliable.

OBJECTIVE

To investigate whether thalamic volume (TV) loss, measured longitudinally by AI, is associated with disability progression (DP) in patients with MS, participating in a large multicentre study.

METHODS

The DeepGRAI (Deep Grey Rating via Artificial Intelligence) Registry is a multicentre (30 USA sites), longitudinal, observational, retrospective, real-word study of relapsing-remitting (RR) MS patients. Each centre enrolled between 30 and 35 patients. Brain MRI exams acquired at baseline and follow-up on 1.5T or 3T scanners with no prior standardisation were collected. TV measurement was performed on T2-FLAIR using DeepGRAI, and on two dimensional (D)-weighted and 3D T1-weighted images (WI) by using FMRIB's Integrated Registration and Segmentation Tool software where possible.

RESULTS

1002 RRMS patients were followed for an average of 2.6 years. Longitudinal TV analysis was more readily available on T2-FLAIR (96.1%), compared with 2D-T1-WI (61.8%) or 3D-T1-WI (33.2%). Over the follow-up, DeepGRAI TV loss was significantly higher in patients with DP, compared with those with disability improvement (DI) or disease stability (-1.35% in DP, -0.87% in DI and -0.57% in Stable, p=0.045, Bonferroni-adjusted, age-adjusted and follow-up time-adjusted analysis of covariance). In a regression model including MRI scanner change, age, sex, disease duration and follow-up time, DP was associated with DeepGRAI TV loss (p=0.022).

CONCLUSIONS

Thalamic atrophy measured by AI in a multicentre clinical routine real-word setting is associated with DP over mid-term follow-up.

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a "network collapse". After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.

Grey matter atrophy in patients with benign multiple sclerosis

BACKGROUND

Brain atrophy appears during the progression of multiple sclerosis (MS) and is associated with the disability caused by the disease.

METHODS

We investigated global and regional grey matter (GM) and white matter (WM) volumes, WM lesion load, and corpus callosum index (CCI), in benign relapsing-remitting MS (BRRMS, n = 35) with and without any treatment and compared those to aggressive relapsing-remitting MS (ARRMS, n = 46). Structures were analyzed by using an automated MRI quantification tool (cNeuro®).

RESULTS

The total brain and cerebral WM volumes were larger in BRRMS than in ARRMS (p = .014, p = .017 respectively). In BRRMS, total brain volumes, regional GM volumes, and CCI were found similar whether or not disease-modifying treatment (DMT) was used. The total (p = .033), as well as subcortical (p = .046) and deep WM (p = .041) lesion load volumes were larger in BRRMS patients without DMT. Cortical GM volumes did not differ between BRRMS and ARRMS, but the volumes of total brain tissue (p = .014) and thalami (p = .003) were larger in patients with BRRMS compared to ARRMS. A positive correlation was found between CCI and whole-brain volume in both BRRMS (r = .73, p < .001) and ARRMS (r = .80, p < .01).

CONCLUSIONS

Thalamic volume is the most prominent measure to differentiate BRRMS and ARRMS. Validation of automated quantification of CCI provides an additional applicable MRI biomarker to detect brain atrophy in MS.

Innate Immune Cell–Related Pathology in the Thalamus Signals a Risk for Disability Progression in Multiple Sclerosis

Background and Objectives

Our aim was to investigate whether 18-kDa translocator protein (TSPO) radioligand binding in gray matter (GM) predicts later disability progression in multiple sclerosis (MS).

Methods

In this prospective imaging study, innate immune cells were investigated in the MS patient brain using PET imaging. The distribution volume ratio (DVR) of the TSPO-binding radioligand [¹¹C]PK11195 was determined in 5 GM regions: thalamus, caudate, putamen, pallidum, and cortical GM. Volumetric brain MRI parameters were obtained for comparison. The Expanded Disability Status Scale (EDSS) score was assessed at baseline and after follow-up of 3.0 ± 0.3 (mean ± SD) years. Disability progression was defined as an EDSS score increase of 1.0 point or 0.5 point if the baseline EDSS score was ≥6.0. A forward-type stepwise logistic regression model was constructed to compare multiple imaging and clinical variables in their ability to predict later disability progression.

Results

The cohort consisted of 66 patients with MS and 18 healthy controls. Patients with later disability progression (n = 17) had more advanced atrophy in the thalamus, caudate, and putamen at baseline compared with patients with no subsequent worsening. TSPO binding was significantly higher in the thalamus among the patients with later worsening. The thalamic DVR was the only measured imaging variable that remained a significant predictor of disability progression in the regression model. The final model predicted disability progression with 52.9% sensitivity and 93.9% specificity with an area under the curve value of 0.82 (receiver operating characteristic curve).

Discussion

Increased TSPO radioligand binding in the thalamus has potential in predicting short-term disability progression in MS and seems to be more sensitive for this than GM atrophy measures.

Does Ocrelizumab Limit Multiple Sclerosis Progression? Current Evidence from Clinical, MRI, and Fluid Biomarkers

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating, and neurodegenerative disease affecting the central nervous system, often characterized by the accumulation of irreversible clinical disability over time. In recent years, there has been a dramatic evolution in several key concepts of MS treatment. The demonstration of the effects of ocrelizumab, a selective monoclonal antibody against CD20+ B cells, has significantly modified our knowledge of the immune-pathophysiology of MS and has provided a new therapeutic target for relapsing and progressive MS patients. Emerging findings suggest that, besides its strong anti-inflammatory activity, ocrelizumab may limit disability progression and may exert beneficial effects on cognitive function, fatigue, and quality of life of MS patients. The significant reductions of the rate of global and regional brain atrophy and of serum neurofilament light chain levels, which were found to be partially independent of overt inflammatory activity, suggest that this treatment may also limit neuro-axonal damage. By discussing the most recent evidence regarding the effects of ocrelizumab on clinical measures as well as on magnetic resonance imaging and fluid biomarkers, this review summarizes current knowledge on the possible mechanisms underlying the effects of ocrelizumab in limiting MS progression and neurodegeneration.

Ocrelizumab reduces thalamic volume loss in patients with RMS and PPMS

Background:

In multiple sclerosis (MS), thalamic integrity is affected directly by demyelination and neuronal loss, and indirectly by gray/white matter lesions outside the thalamus, altering thalamic neuronal projections.

Objective:

To assess the efficacy of ocrelizumab compared with interferon beta-1a (IFNβ1a)/placebo on thalamic volume loss and the effect of switching to ocrelizumab on volume change in the Phase III trials in relapsing MS (RMS, OPERA I/II; NCT01247324/NCT01412333) and in primary progressive MS (PPMS, ORATORIO; NCT01194570).

Methods:

Thalamic volume change was computed using paired Jacobian integration and analyzed using an adjusted mixed-effects repeated measurement model.

Results:

Over the double-blind period, ocrelizumab treatment significantly reduced thalamic volume loss with the largest effect size (Cohen’s d: RMS: 0.561 at week 96; PPMS: 0.427 at week 120) compared with whole brain, cortical gray matter, and white matter volume loss. At the end of up to 7 years of follow-up, patients initially randomized to ocrelizumab still showed less thalamic volume loss than those switching from IFNβ1a ( p < 0.001) or placebo ( p < 0.001).

Conclusion:

Ocrelizumab effectively reduced thalamic volume loss compared with IFNβ1a/placebo. Early treatment effects on thalamic tissue preservation persisted over time. Thalamic volume loss could be a potential sensitive marker of persisting tissue damage.

Disease correlates of rim lesions on quantitative susceptibility mapping in multiple sclerosis

Quantitative susceptibility mapping (QSM), an imaging technique sensitive to brain iron, has been used to detect paramagnetic rims of iron-laden active microglia and macrophages in a subset of multiple sclerosis (MS) lesions, known as rim+ lesions, that are consistent with chronic active lesions. Because of the potential impact of rim+ lesions on disease progression and tissue damage, investigating their influence on disability and neurodegeneration is critical to establish the impact of these lesions on the disease course. This study aimed to explore the relationship between chronic active rim+ lesions, identified as having a hyperintense rim on QSM, and both clinical disability and imaging measures of neurodegeneration in patients with MS. The patient cohort was composed of 159 relapsing-remitting multiple sclerosis patients. The Expanded Disability Status Scale (EDSS) and Brief International Cognitive Assessment for Multiple Sclerosis, which includes both the Symbol Digit Modalities Test and California Verbal Learning Test-II, were used to assess clinical disability. Cortical thickness and thalamic volume were evaluated as imaging measures of neurodegeneration. A total of 4469 MS lesions were identified, of which 171 QSM rim+ (3.8%) lesions were identified among 57 patients (35.8%). In a multivariate regression model, as the overall total lesion burden increased, patients with at least one rim+ lesion on QSM performed worse on both physical disability and cognitive assessments, specifically the Symbol Digit Modalities Test (p = 0.010), California Verbal Learning Test-II (p = 0.030), and EDSS (p = 0.001). In a separate univariate regression model, controlling for age (p < 0.001) and having at least one rim+ lesion was related to more cortical thinning (p = 0.03) in younger patients (< 45 years). Lower thalamic volume was associated with older patients (p = 0.038) and larger total lesion burden (p < 0.001); however, the association did not remain significant with rim+ lesions (p = 0.10). Our findings demonstrate a novel observation that chronic active lesions, as identified on QSM, modify the impact of lesion burden on clinical disability in MS patients. These results support further exploration of rim+ lesions for therapeutic targeting in MS to reduce disability and subsequent neurodegeneration.

Deformation-based morphometry identifies deep brain structures protected by ocrelizumab

BACKGROUND

Despite advancements in treatments for multiple sclerosis, insidious disease progression remains an area of unmet medical need, for which atrophy-based biomarkers may help better characterize the progressive biology.

METHODS

We developed and applied a method of longitudinal deformation-based morphometry to provide voxel-level assessments of brain volume changes and identified brain regions that were significantly impacted by disease-modifying therapy.

RESULTS

Using brain MRI data from two identically designed pivotal trials of relapsing multiple sclerosis (total N = 1483), we identified multiple deep brain regions, including the thalamus and brainstem, where volume loss over time was reduced by ocrelizumab (p < 0.05), a humanized anti-CD20 + monoclonal antibody approved for the treatment of multiple sclerosis. Additionally, identified brainstem shrinkage, as well as brain ventricle expansion, was associated with a greater risk for confirmed disability progression (p < 0.05).

CONCLUSIONS

The identification of deep brain structures has a strong implication for developing new biomarkers of brain atrophy reduction to advance drug development for multiple sclerosis, which has an increasing focus on targeting the progressive biology.

The association between neurodegeneration and local complement activation in the thalamus to progressive multiple sclerosis outcome

The extent of grey matter demyelination and neurodegeneration in the progressive multiple sclerosis (PMS) brains at post‐mortem associates with more severe disease. Regional tissue atrophy, especially affecting the cortical and deep grey matter, including the thalamus, is prognostic for poor outcomes. Microglial and complement activation are important in the pathogenesis and contribute to damaging processes that underlie tissue atrophy in PMS. We investigated the extent of pathology and innate immune activation in the thalamus in comparison to cortical grey and white matter in blocks from 21 cases of PMS and 10 matched controls. Using a digital pathology workflow, we show that the thalamus is invariably affected by demyelination and had a far higher proportion of active inflammatory lesions than forebrain cortical tissue blocks from the same cases. Lesions were larger and more frequent in the medial nuclei near the ventricular margin, whilst neuronal loss was greatest in the lateral thalamic nuclei. The extent of thalamic neuron loss was not associated with thalamic demyelination but correlated with the burden of white matter pathology in other forebrain areas (Spearman r = 0.79, p < 0.0001). Only thalamic neuronal loss, and not that seen in other forebrain cortical areas, correlated with disease duration (Spearman r = −0.58, p = 0.009) and age of death (Spearman r = −0.47, p = 0.045). Immunoreactivity for the complement pattern recognition molecule C1q, and products of complement activation (C4d, Bb and C3b) were elevated in thalamic lesions with an active inflammatory pathology. Complement regulatory protein, C1 inhibitor, was unchanged in expression. We conclude that active inflammatory demyelination, neuronal loss and local complement synthesis and activation in the thalamus, are important to the pathological and clinical disease outcomes of PMS.

Quantitative brain MRI morphology in severe and attenuated forms of mucopolysaccharidosis type I

OBJECTIVE

To assess our hypothesis that brain macrostructure is different in individuals with mucopolysaccharidosis type I (MPS I) and healthy controls (HC), we conducted a comprehensive multicenter study using a uniform quantitative magnetic resonance imaging (qMRI) protocol, with analyses that account for the effects of disease phenotype, age, and cognition.

METHODS

Brain MRIs in 23 individuals with attenuated (MPS IA) and 38 with severe MPS I (MPS IH), aged 4-25 years, enrolled under the study protocol NCT01870375, were compared to 98 healthy controls.

RESULTS

Cortical and subcortical gray matter, white matter, corpus callosum, ventricular and choroid plexus volumes in MPS I significantly differed from HC. Thicker cortex, lower white matter and corpus callosum volumes were already present at the youngest MPS I participants aged 4-5 years. Age-related differences were observed in both MPS I groups, but most markedly in MPS IH, particularly in cortical gray matter metrics. IQ scores were inversely associated with ventricular volume in both MPS I groups and were positively associated with cortical thickness only in MPS IA.

CONCLUSIONS

Quantitatively-derived MRI measures distinguished MPS I participants from HC as well as severe from attenuated forms. Age-related neurodevelopmental trajectories in both MPS I forms differed from HC. The extent to which brain structure is altered by disease, potentially spared by treatment, and how it relates to neurocognitive dysfunction needs further exploration.

Longitudinal changes of deep gray matter shape in multiple sclerosis

•

Specific shape changes over time occur at the bilateral ventrolateral pallidal and the left posterolateral striatal surface in relapse-onset multiple sclerosis.

•

These shape changes over time were not associated with disease progression.

•

The average shape of deep gray matter structures was associated with the patients’ average disease severity as well as white matter lesion-load.

Objective

This study aimed to investigate longitudinal deep gray matter (DGM) shape changes and their relationship with measures of clinical disability and white matter lesion-load in a large multiple sclerosis (MS) cohort.

Materials and Methods

A total of 230 MS patients (179 relapsing-remitting, 51 secondary progressive; baseline age 44.5 ± 11.3 years; baseline disease duration 12.99 ± 9.18) underwent annual clinical and MRI examinations over a maximum of 6 years (mean 4.32 ± 2.07 years). The DGM structures were segmented on the T1-weighted images using the “Multiple Automatically Generated Templates” brain algorithm. White matter lesion-load was measured on T2-weighted MRI. Clinical examination included the expanded disability status scale, 9-hole peg test, timed 25-foot walk test, symbol digit modalities test and paced auditory serial addition test. Vertex‐wise longitudinal analysis of DGM shapes was performed using linear mixed effect models and evaluated the association between average/temporal changes of DGM shapes with average/temporal changes of clinical measurements, respectively.

Results

A significant shrinkage over time of the bilateral ventrolateral pallidal and the left posterolateral striatal surface was observed, whereas no significant shape changes over time were observed at the bilateral thalamic and right striatal surfaces. Higher average lesion-load was associated with an average inwards displacement of the global thalamic surface with relative sparing on the posterior side (slight left-side predominance), the antero-dorso-lateral striatal surfaces bilaterally (symmetric on both sides) and the antero-lateral pallidal surface (left-side predominance). There was also an association between shrinkage of large lateral DGM surfaces with higher clinical motor and cognitive disease severity. However, there was no correlation between any DGM shape changes over time and measurements of clinical progression or lesion-load changes over time.

Conclusions

This study showed specific shape change of DGM structures occurring over time in relapse-onset MS. Although these shape changes over time were not associated with disease progression, we demonstrated a link between DGM shape and the patients’ average disease severity as well as white matter lesion-load.

BTK inhibition limits B-cell-T-cell interaction through modulation of B-cell metabolism: implications for multiple sclerosis therapy

Inhibition of Bruton's Tyrosine Kinase (BTKi) is now viewed as a promising next-generation B-cell-targeting therapy for autoimmune diseases including multiple sclerosis (MS). Surprisingly little is known; however, about how BTKi influences MS disease-implicated functions of B cells. Here, we demonstrate that in addition to its expected impact on B-cell activation, BTKi attenuates B-cell:T-cell interactions via a novel mechanism involving modulation of B-cell metabolic pathways which, in turn, mediates an anti-inflammatory modulation of the B cells. In vitro, BTKi, as well as direct inhibition of B-cell mitochondrial respiration (but not glycolysis), limit the B-cell capacity to serve as APC to T cells. The role of metabolism in the regulation of human B-cell responses is confirmed when examining B cells of rare patients with mitochondrial respiratory chain mutations. We further demonstrate that both BTKi and metabolic modulation ex vivo can abrogate the aberrant activation and costimulatory molecule expression of B cells of untreated MS patients. Finally, as proof-of-principle in a Phase 1 study of healthy volunteers, we confirm that in vivo BTKi treatment reduces circulating B-cell mitochondrial respiration, diminishes their activation-induced expression of costimulatory molecules, and mediates an anti-inflammatory shift in the B-cell responses which is associated with an attenuation of T-cell pro-inflammatory responses. These data collectively elucidate a novel non-depleting mechanism by which BTKi mediates its effects on disease-implicated B-cell responses and reveals that modulating B-cell metabolism may be a viable therapeutic approach to target pro-inflammatory B cells.

White matter tracts that overlap with the thalamus and the putamen are protected against multiple sclerosis pathology

BACKGROUND

The thalamus and the putamen are highly connected hubs implicated in multiple sclerosis (MS) pathology. It remains unclear if white matter (WM) tracts, which pass through them, have a different susceptibility to MS pathology, and if so, if their impact on disability predominates over that exerted by disease in other WM tracts. We hypothesized that WM tracts connected to and passing through these hubs (subsequently termed hub+ tracts) would be more susceptible to MS-related pathology than tracts that do not pass through them (hub- tracts) due to retrograde and anterograde distant degeneration. Thus, we compared the lesion load and neurite orientation dispersion and density imaging (NODDI) derived metrics between hub+ and hub- tracts and assessed the relationship between these MRI metrics and those of physical impairment.

METHODS

Eighteen patients (mean age of 45.5 years, 12 females) had 3 Tesla MRI consisting of T1-weighted and T2-weighted Fluid Attenuated Inversion Recovery (FLAIR), and NODDI from which the orientation dispersion index (ODI), neurite density index (NDI), and isotropic volume fraction (IVF) were derived. Forty-nine WM tracts, i.e., 12 hub+ and 37 hub- tracts, were segmented out. Exploratory analyses of the differences in lesion burden, whole tract and normal appearing WM (NAWM) NODDI metrics were carried out between the two types of tracts using a Mann-Whitney U test. Correlations with physical impairment, quantified using the expanded disability status scale (EDSS) and timed 25-foot walk (T25FW) test were assessed using Spearman correlation analyses.

RESULTS

Hub- tracts had larger T1- (p<0.001) and T2-lesion (p<0.001) volumes; lower ODI (p<0.001), NDI (p<0.001) and higher IVF (p = 0.020) in comparison to hub+ tracts. Measures of tissue injury in hub+ tracts correlated with those of clinical disability, though less strongly than in hub- tracts.

CONCLUSIONS

Contrary to our hypothesis, our exploratory pilot study results suggest that WM tracts that overlap with the thalamus and the putamen have a lower degree of lesional and non-lesional tissue injury, suggesting a protective role of the hubs against MS pathology or a higher degree of vulnerability of those not passing through hub stations. We also show a weaker association between disability impairment and hub+ pathology, compared to that in hub- tracts. Our findings point to a potential role of disease location in relation to hubs as guidance for treatment personalization in MS.

Subcortical volumes as early predictors of fatigue in multiple sclerosis

OBJECTIVE

Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after four years by applying structural equation modeling (SEM).

METHODS

This multi-center cohort study included 601 treatment-naive MS patients after the first demyelinating event. All patients underwent a standardized 3T MRI protocol. A subgroup of 230 patients with available clinical follow-up data after four years was also analyzed. Associations of subcortical volumes (included into SEM) with MS-related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis.

RESULTS

Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient]=0.763, p=0.003 [left]; s=0.755, p=0.006 [right]), putamen (s=0.614, p=0.002 [left]; s=0.606, p=0.003 [right]) and pallidum (s=0.606, p=0.012 [left]; s=0.606, p=0.012 [right]) as prognostic factors for fatigue severity in the cross-sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s=0.605, p=0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p=0.008 [left]; p=0.007 [right]) and pons (p=0.0001).

INTERPRETATION

We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. This article is protected by copyright. All rights reserved.

Spinal cord atrophy predicts progressive disease in relapsing multiple sclerosis

Objective

A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS).

Methods

From a single‐center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12‐year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion.

Results

Patients who developed SPMS showed faster cord atrophy rates (−2.19%/yr) at least 4 years before conversion compared to their RRMS matches (−0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (−1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (−1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively.

Interpretation

Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268–281

Automated quantification of deep grey matter structures and white matter lesions using magnetic resonance imaging in relapsing remission multiple sclerosis

Background

Brain volume loss (BVL) is widespread in MS and occurs throughout the disease course at a rate considerably greater than in the general population. In MS, brain volume correlates with and predicts future disability, making BVL a relevant measure of diffuse CNS damage leading to clinical disease progression, as well as serving as a useful outcome in evaluating MS therapies. The aim of our study was to evaluate the role of automated segmentation and quantification of deep grey matter structures and white matter lesions in Relapsing Remitting Multiple Sclerosis patients using MR images and to correlate the volumetric results with different degrees of disability based on expanded disability status scale (EDSS) scores.

Results

All the patients in our study showed relative atrophy of the thalamus and the putamen bilaterally when compared with the normal control group. Statistical analysis was significant for the thalamus and the putamen atrophy (P value < 0.05). On the other hand, statistical analysis was not significant for the caudate and the hippocampus (P value > 0.05); there was a significant positive correlation between the white matter lesions volume and EDSS scores (correlation coefficient of 0.7505). On the other hand, there was a significant negative correlation between the thalamus and putamen volumes, and EDSS scores (correlation coefficients < − 0.9), while the volumes of the caudate and the hippocampus had a very weak and non-significant correlation with the EDSS scores (correlation coefficients > − 0.35).

Conclusions

The automated segmentation and quantification tools have a great role in the assessment of brain structural changes in RRMS patients, and that it became essential to integrate these tools in the daily medical practice for the great value they add to the current evaluation measures.

MRI-based thalamic volumetry in multiple sclerosis using FSL-FIRST: Systematic assessment of common error modes

BACKGROUND AND PURPOSE

FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL-FIRST) is a widely used and well-validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL-FIRST's algorithm is based on shape models derived from non-MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL-FIRST on MRIs from people with multiple sclerosis (PwMS).

METHODS

FSL-FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated.

RESULTS

In the entire quantitative volumetric group, the mean volumetric error of FSL-FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ²  = 18.14, p < .01 and χ²  = 64.89, p < .001, respectively). Finally, thalamus volume error was negatively associated with degree of atrophy, such that smaller thalami were systematically overestimated (r = -.28, p < .001).

CONCLUSIONS

In PwMS, FSL-FIRST thalamic segmentation miscalculates thalamic volumetry in a predictable fashion, and may be biased to overestimate highly atrophic thalami. As such, it is recommended that segmentations be reviewed and corrected manually when appropriate for specific studies.

Prediction in treatment outcomes in multiple sclerosis: challenges and recent advances

INTRODUCTION

Multiple Sclerosis (MS) is a chronic autoimmune and neurodegenerative disease of the central nervous system with a course dependent on early treatment response. Increasing evidence also suggests that despite eliminating disease activity (relapses and lesions), many patients continue to accrue disability, highlighting the need for a more comprehensive definition of treatment success. Optimizing disability outcome measures, as well as continuously improving our understanding of neuroinflammatory and neurodegenerative biomarkers is required.

AREAS COVERED

This review describes the challenges inherent in classifying and monitoring disease phenotype in MS. The review also provides an assessment of clinical, radiological, and blood biomarker tools for current and future practice.

EXPERT OPINION

Emerging MRI techniques and standardized patient outcome assessments will increase the accuracy of initial diagnosis and understanding of disease progression.

Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model in restoring the image quality of accelerated routine clinical brain MR scans for PwMS. Methods: We acquired fast 3D T1w BRAVO and fast 3D T2w FLAIR MRI sequences (half the phase encodes and half the number of slices) in parallel to conventional parameters. Using a subset of the scans, we trained a DL model to generate images from fast scans with quality similar to the conventional scans and then applied the model to the remaining scans. We calculated clinically relevant T1w volumetrics (normalized whole brain, thalamic, gray matter, and white matter volume) for all scans and T2 lesion volume in a sub-analysis. We performed paired t-tests comparing conventional, fast, and fast with DL for these volumetrics, and fit repeated measures mixed-effects models to test for differences in correlations between volumetrics and clinically relevant patient-reported outcomes (PRO). Results: We found statistically significant but small differences between conventional and fast scans with DL for all T1w volumetrics. There was no difference in the extent to which the key T1w volumetrics correlated with clinically relevant PROs of MS symptom burden and neurological disability. Conclusion: A deep learning model that improves the image quality of the accelerated routine clinical brain MR scans has the potential to inform clinically relevant outcomes in MS.

Thalamus Atrophy in the Peri-Pregnancy Period in Clinically Stable Multiple Sclerosis Patients: Preliminary Results

Radiological activity in the post-partum period in MS patients is a well-known phenomenon, but there is no data concerning the influence of pregnancy on regional brain atrophy. The aim of this article was to investigate local brain atrophy in the peri-pregnancy period (PPP) in patients with MS. Thalamic volume (TV); corpus callosum volume (CCV) and classical MRI activity (new gadolinium enhancing lesions (Gd+), new T2 lesions, T1 lesions volume (T1LV) and T2 lesions volume (T2LV)) were analyzed in 12 clinically stable women with relapsing–remitting MS and with MRI performed in the PPP. We showed that there was a significant decrease in TV (p = 0.021) in the PPP. We also observed a significant increase in the T1 lesion volume (p = 0.028), new gadolinium-enhanced and new T2 lesions (in 46% and 77% of the scans, respectively) in the post-partum period. Our results suggest that the PPP in MS may be associated not only with classical MRI activity but, also, with regional brain atrophy.

A Combined Radiomics and Machine Learning Approach to Overcome the Clinicoradiologic Paradox in Multiple Sclerosis

BACKGROUND AND PURPOSE

Conventional MR imaging explains only a fraction of the clinical outcome variance in multiple sclerosis. We aimed to evaluate machine learning models for disability prediction on the basis of radiomic, volumetric, and connectivity features derived from routine brain MR images.

MATERIALS AND METHODS

In this retrospective cross-sectional study, 3T brain MR imaging studies of patients with multiple sclerosis, including 3D T1-weighted and T2-weighted FLAIR sequences, were selected from 2 institutions. T1-weighted images were processed to obtain volume, connectivity score (inferred from the T2 lesion location), and texture features for an atlas-based set of GM regions. The site 1 cohort was randomly split into training (n = 400) and test (n = 100) sets, while the site 2 cohort (n = 104) constituted the external test set. After feature selection of clinicodemographic and MR imaging-derived variables, different machine learning algorithms predicting disability as measured with the Expanded Disability Status Scale were trained and cross-validated on the training cohort and evaluated on the test sets. The effect of different algorithms on model performance was tested using the 1-way repeated-measures ANOVA.

RESULTS

The selection procedure identified the 9 most informative variables, including age and secondary-progressive course and a subset of radiomic features extracted from the prefrontal cortex, subcortical GM, and cerebellum. The machine learning models predicted disability with high accuracy (r approaching 0.80) and excellent intra- and intersite generalizability (r ≥ 0.73). The machine learning algorithm had no relevant effect on the performance.

CONCLUSIONS

The multidimensional analysis of brain MR images, including radiomic features and clinicodemographic data, is highly informative of the clinical status of patients with multiple sclerosis, representing a promising approach to bridge the gap between conventional imaging and disability.

Clinical and Paraclinical Biomarkers and the Hitches to Assess Conversion to Secondary Progressive Multiple Sclerosis: A Systematic Review

Conversion to secondary progressive (SP) course is the decisive factor for long-term prognosis in relapsing multiple sclerosis (MS), generally considered the clinical equivalent of progressive MS-associated neuroaxonal degeneration. Evidence is accumulating that both inflammation and neurodegeneration are present along a continuum of pathologic processes in all phases of MS. While inflammation is the prominent feature in early stages, its quality changes and relative importance to disease course decreases while neurodegenerative processes prevail with ongoing disease. Consequently, anti-inflammatory disease-modifying therapies successfully used in relapsing MS are ineffective in SPMS, whereas specific treatment for the latter is increasingly a focus of MS research. Therefore, the prevention, but also the (anticipatory) diagnosis of SPMS, is of crucial importance. The problem is that currently SPMS diagnosis is exclusively based on retrospectively assessing the increase of overt physical disability usually over the past 6–12 months. This inevitably results in a delay of diagnosis of up to 3 years resulting in periods of uncertainty and, thus, making early therapy adaptation to prevent SPMS conversion impossible. Hence, there is an urgent need for reliable and objective biomarkers to prospectively predict and define SPMS conversion. Here, we review current evidence on clinical parameters, magnetic resonance imaging and optical coherence tomography measures, and serum and cerebrospinal fluid biomarkers in the context of MS-associated neurodegeneration and SPMS conversion. Ultimately, we discuss the necessity of multimodal approaches in order to approach objective definition and prediction of conversion to SPMS.

Cortical Thickness and Serum NfL Explain Cognitive Dysfunction in Newly Diagnosed Patients With Multiple Sclerosis

Background and Objectives

To determine the relative importance of global or regional MRI and blood markers of neurodegeneration and neuroaxonal injury in predicting cognitive performance for recently diagnosed patients with multiple sclerosis (MS).

Methods

Thirty-five newly diagnosed patients with relapsing-remitting MS (RRMS) and 23 healthy controls (HCs) simultaneously completed a full clinical and neuropsychological assessment, structural brain MRI, and serum neurofilament light chain (sNfL) level test. Linear regression analyses were performed to determine which global or regional measures of gray matter (GM) atrophy and cortical thickness (CT), in combination with sNfL levels and clinical scores, are most strongly related to neuropsychological impairment.

Results

Compared with HCs, patients with MS showed bilateral thalamic GM atrophy (left, p = 0.033; right, p = 0.047) and diminished CT, particularly in the right superior and transverse temporal gyri (p = 0.045; p = 0.037). Regional atrophy failed to add predictive variance, whereas anxiety symptoms, sNfL, and global CT were the best predictors (R² = 0.404; p < 0.001) of cognitive outcomes, with temporal thickness accounting for greater variance in cognitive deficits than global CT.

Discussion

Thalamic GM atrophy and thinning in temporal regions represent a distinctive MRI trait in the early stages of MS. Although sNfL levels alone do not clearly differentiate HCs and patients with RRMS, in combination with global and regional CT, sNfL levels can better explain the presence of underlying cognitive deficits. Hence, cortical thinning and sNfL increases can be considered 2 parallel neurodegenerative markers in the pathogenesis of progression in newly diagnosed patients with MS.

Predicting disability progression and cognitive worsening in multiple sclerosis using patterns of grey matter volumes

OBJECTIVE

In multiple sclerosis (MS), MRI measures at the whole brain or regional level are only modestly associated with disability, while network-based measures are emerging as promising prognostic markers. We sought to demonstrate whether data-driven patterns of covarying regional grey matter (GM) volumes predict future disability in secondary progressive MS (SPMS).

METHODS

We used cross-sectional structural MRI, and baseline and longitudinal data of Expanded Disability Status Scale, Nine-Hole Peg Test (9HPT) and Symbol Digit Modalities Test (SDMT), from a clinical trial in 988 people with SPMS. We processed T1-weighted scans to obtain GM probability maps and applied spatial independent component analysis (ICA). We repeated ICA on 400 healthy controls. We used survival models to determine whether baseline patterns of covarying GM volume measures predict cognitive and motor worsening.

RESULTS

We identified 15 patterns of regionally covarying GM features. Compared with whole brain GM, deep GM and lesion volumes, some ICA components correlated more closely with clinical outcomes. A mainly basal ganglia component had the highest correlations at baseline with the SDMT and was associated with cognitive worsening (HR=1.29, 95% CI 1.09 to 1.52, p<0.005). Two ICA components were associated with 9HPT worsening (HR=1.30, 95% CI 1.06 to 1.60, p<0.01 and HR=1.21, 95% CI 1.01 to 1.45, p<0.05). ICA measures could better predict SDMT and 9HPT worsening (C-index=0.69-0.71) compared with models including only whole and regional MRI measures (C-index=0.65-0.69, p value for all comparison <0.05).

CONCLUSIONS

The disability progression was better predicted by some of the covarying GM regions patterns, than by single regional or whole-brain measures. ICA, which may represent structural brain networks, can be applied to clinical trials and may play a role in stratifying participants who have the most potential to show a treatment effect.

Lesion features on magnetic resonance imaging discriminate multiple sclerosis patients

BACKGROUND

Magnetic resonance imaging (MRI) provides insight into various pathological processes in multiple sclerosis (MS) and may provide insight into patterns of damage among patients.

OBJECTIVE

We sought to determine if MRI features have clinical discriminative power among a cohort of MS patients.

METHODS

Ninety-six relapsing remitting and seven progressive MS patients underwent myelin water fraction (MWF) imaging and conventional MRI for cortical thickness and thalamic volume. Patients were clustered based on lesion level MRI features using an agglomerative hierarchical clustering algorithm based on principal component analysis (PCA).

RESULTS

One hundred and three patients with 1689 MS lesions were analyzed. PCA on MRI features demonstrated that lesion MWF and volume distributions (characterized by 25th, 50th, and 75th percentiles) accounted for 87% of the total variability based on four principal components. The best hierarchical cluster confirmed two distinct patient clusters. The clustering features in order of importance were lesion median MWF, MWF 25th, MWF 75th, volume 75th percentiles, median individual lesion volume, total lesion volume, cortical thickness, and thalamic volume (all p values <0.01368). The clusters were associated with patient Expanded Disability Status Scale (EDSS) (n = 103, p = 0.0338) at baseline and at 5 years (n = 72, p = 0.0337).

CONCLUSIONS

These results demonstrate that individual MRI features can identify two patient clusters driven by lesion-based values, and our unique approach is an analysis blinded to clinical variables. The two distinct clusters exhibit MWF differences, most likely representing individual remyelination capabilities among different patient groups. These findings support the concept of patient-specific pathophysiological processes and may guide future therapeutic approaches.

Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement

Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.

Neurocognitive performance in relapsing-remitting multiple sclerosis patients is associated with metabolic abnormalities of the thalamus but not the hippocampus- GABA-edited 1H MRS study

OBJECTIVES

Multiple sclerosis (MS) is an inflammatory demyelinating disease that may cause physical disabling as well as cognitive dysfunction. The presented study investigated how the neuropsychological status depends on the thalamus and hippocampus's metabolic processes, using γ-aminobutyric acid-edited magnetic resonance spectroscopy (GABA-edited ¹H MRS) in patients with early MS, and how the results differ from healthy volunteers.

METHODS

We recruited 36 relapsing-remitting (RRMS) MS patients and 22 controls (CON). In addition to common ¹H MRS metabolites, such as N-acetyl-aspartate (tNAA), myoinositol (mIns), total choline and creatine (tCr, tCho), we also evaluated GABA and glutamate/glutamine (Glx). Metabolite ratios were correlated with the results of Single-Digit Modality Test (SDMT) and Expanded Disability Status Score (EDSS).

RESULTS

In the thalamus, GABA ratios (GABA/tCr, GABA/tNAA) were significantly lower in RRMS patients than in CON. Both tCho- and mIns-ratios correlated with lower scores of SDMT but not with EDSS. Metabolic ratios in the hippocampus did not differ between RRMS and CON and did not correlate with any of performed tests.

DISCUSSION

This study is the first to provide GABA-edited ¹H MRS evidence for MS-related metabolic changes of the thalamus and hippocampus. The findings underline the importance of evaluating subcortical grey matter in MS patients to improve understanding of the clinical manifestations of MS and as a potential future target for treatment.

MRI brain volume loss, lesion burden, and clinical outcome in secondary progressive multiple sclerosis

BACKGROUND

Magnetic resonance imaging (MRI) of brain volume measures are widely used outcomes in secondary progressive multiple sclerosis (SPMS), but it is unclear whether they are associated with physical and cognitive disability.

OBJECTIVE

To investigate the association between MRI outcomes and physical and cognitive disability worsening in people with SPMS.

METHODS

We used data from ASCEND, a large randomized controlled trial (n = 889). We investigated the association of change in whole brain and gray matter volume, contrast enhancing lesions, and T2 lesions with significant worsening on the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk (T25FW), Nine-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT) with logistic regression models.

RESULTS

We found no association between MRI measures and EDSS or SDMT worsening. T25FW worsening at 48 and 96 weeks, and NHPT worsening at 96 weeks were associated with cumulative new or newly enlarging T2 lesions at 96 weeks. NHPT worsening at 48 and 96 weeks was associated with normalized brain volume loss at 48 weeks, but not with other MRI outcomes.

CONCLUSION

The association of standard MRI outcomes and disability was noticeably weak and inconsistent over 2 years of follow-up. These MRI outcomes may not be useful surrogates of disability measures in SPMS.

Feasibility of accelerated 3D T1-weighted MRI using compressed sensing: application to quantitative volume measurements of human brain structures

OBJECTIVE

Scan time reduction is necessary for volumetric acquisitions to improve workflow productivity and to reduce motion artifacts during MRI procedures. We explored the possibility that Compressed Sensing-4 (CS-4) can be employed with 3D-turbo-field-echo T1-weighted (3D-TFE-T1W) sequence without compromising subcortical measurements on clinical 1.5 T MRI.

MATERIALS AND METHODS

Thirty-three healthy volunteers (24 females, 9 males) underwent imaging scans on a 1.5 T MRI equipped with a 12-channel head coil. 3D-TFE-T1W for whole-brain coverage was performed with different acceleration factors, including SENSE-2, SENSE-4, CS-4. Freesurfer, FSL's FIRST, and volBrain packages were utilized for subcortical segmentation. All processed data were assessed using the Wilcoxon signed-rank test.

RESULTS

The results obtained from SENSE-2 were considered as references. For SENSE-4, the maximum signal-to-noise ratio (SNR) drop was detected in the Accumbens (51.96%). For CS-4, the maximum SNR drop was detected in the Amygdala (10.55%). Since the SNR drop in CS-4 is relatively small, the SNR in all of the subcortical volumes obtained from SENSE-2 and CS-4 are not statistically different (P > 0.05), and their Pearson's correlation coefficients are larger than 0.90. The maximum biases of SENSE-4 and CS-4 were found in the Thalamus with the mean of differences of 1.60 ml and 0.18 ml, respectively.

CONCLUSION

CS-4 provided sufficient quality of 3D-TFE-T1W images for 1.5 T MRI equipped with a 12-channel receiver coil. Subcortical volumes obtained from the CS-4 images are consistent among different post-processing packages.

Neurodegeneration in Multiple Sclerosis: Symptoms of Silent Progression, Biomarkers and Neuroprotective Therapy-Kynurenines Are Important Players

Neurodegeneration is one of the driving forces behind the pathogenesis of multiple sclerosis (MS). Progression without activity, pathopsychological disturbances (cognitive impairment, depression, fatigue) and even optic neuropathy seems to be mainly routed in this mechanism. In this article, we aim to give a comprehensive review of the clinical aspects and symptomology, radiological and molecular markers and potential therapeutic targets of neurodegeneration in connection with MS. As the kynurenine pathway (KP) was evidenced to play an important role in the pathogenesis of other neurodegenerative conditions (even implied to have a causative role in some of these diseases) and more and more recent evidence suggest the same central role in the neurodegenerative processes of MS as well, we pay special attention to the KP. Metabolites of the pathway are researched as biomarkers of the disease and new, promising data arising from clinical evaluations show the possible therapeutic capability of KP metabolites as neuroprotective drugs in MS. Our conclusion is that the kynurenine pathway is a highly important route of research both for diagnostic and for therapeutic values and is expected to yield concrete results for everyday medicine in the future.

Secondary Progressive Multiple Sclerosis: New Insights

In most cases, multiple sclerosis (MS) begins with a relapsing-remitting course followed by insidious disability worsening that is independent from clinically apparent relapses and is termed secondary progressive MS (SMPS). Major differences exist between relapsing-remitting MS (RRMS) and SPMS, especially regarding therapeutic response to treatment. This review provides an overview of the pathology, differentiation, and challenges in the diagnosis and treatment of SPMS. We emphasize the criticality of conversion from a relapsing-remitting to a secondary progressive disease course not only because such conversion is evidence of disability progression, but also because, until recently, treatments that effectively reduced disability progression in relapsing MS were not proven to be effective in SPMS. Clear clinical, imaging, immunologic, or pathologic criteria marking the transition from RRMS to SPMS have not yet been established. Early identification of SPMS will require tools that, together with the use of appropriate treatments, may result in better long-term outcomes for the population of patients with SPMS.

Clinical predictivity of thalamic sub-regional connectivity in clinically isolated syndrome: a 7-year study

Here, we explored trajectories of sub-regional thalamic resting state (RS) functional connectivity (FC) modifications occurring in clinically isolated syndrome (CIS) patients early after their first clinical episode, and assessed their relationship with disability over 7 years. RS fMRI and clinical data were prospectively acquired from 59 CIS patients and 13 healthy controls (HC) over 2 years. A clinical re-assessment was performed in 53 (89%) patients after 7 years. Using a structural connectivity-based atlas, five thalamic sub-regions (frontal, motor, postcentral, occipital, and temporal) were used for seed-based RS FC. Thalamic RS FC abnormalities and their longitudinal changes were correlated with disability. Thirty-nine (66.1%) patients suffered a second clinical relapse, but the median EDSS remained stable over time. At baseline, CIS patients vs HC showed reduced RS FC (p < 0.001, uncorrected) with: (1) frontal cortices, for the whole thalamus, occipital, postcentral, and temporal thalamic sub-regions, (2) occipital cortices, for the occipital thalamic sub-region. In CIS, the longitudinal analysis revealed at year 2 vs baseline: (1) no significant whole-thalamic RS FC changes; (2) reduction of motor, postcentral, and temporal sub-regional RS FC with occipital cortices (p < 0.05, corrected); (3) an increase (p < 0.001, uncorrected) of postcentral and occipital sub-regional thalamic RS FC with frontal cortices, left putamen, and ipsi- and contralateral thalamus, this latter correlating with less severe clinical disability at year 7. Thalamo-cortical disconnections were present in CIS mainly in thalamic sub-regions closer to the third ventricle early after the demyelinating event, evolved in the subsequent 2 years, and were associated with long-term clinical disability.

Sleep disturbance and memory dysfunction in early multiple sclerosis

OBJECTIVE

Sleep-dependent memory processing occurs in animals including humans, and disturbed sleep negatively affects memory. Sleep disturbance and memory dysfunction are common in multiple sclerosis (MS), but little is known about the contributions of sleep disturbance to memory in MS. We investigated whether subjective sleep disturbance is linked to worse memory in early MS independently of potential confounders.

METHODS

Persons with early MS (n = 185; ≤5.0 years diagnosed) and demographically matched healthy controls (n = 50) completed four memory tests to derive a memory composite, and four speeded tests to derive a cognitive efficiency composite. Z-scores were calculated relative to healthy controls. Sleep disturbance was defined by the Insomnia Severity Index score ≥ 10. ANCOVAs examined differences in memory and cognitive efficiency between patients with and without sleep disturbance controlling for potential confounds (e.g., mood, fatigue, disability, T2 lesion volume, gray matter volume). Comparisons were made to healthy controls.

RESULTS

Seventy-four (40%) patients reported sleep disturbance. Controlling for all covariates, patients with sleep disturbance had worse memory (z = -0.617; 95% CI: -0.886, -0.348) than patients without disturbance (z = -0.171, -0.425, 0.082, P = .003). Cognitive efficiency did not differ between groups. Relative to healthy controls, memory was worse among patients with sleep disturbance, but not among patients without sleep disturbance.

INTERPRETATION

Sleep disturbance contributes to MS memory dysfunction, which may help explain differential risk for memory dysfunction in persons with MS, especially since sleep disturbance is common in MS. Potential mechanisms linking sleep disturbance and memory are discussed, as well as recommendations for further mechanistic and interventional research.