Unraveling the substrates of cognitive impairment in multiple sclerosis: A multiparametric structural and functional magnetic resonance imaging study

Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms

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

The Prevalence of Cognitive Impairment in Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-analysis

It is increasingly recognized that cognitive symptoms are a common sequelae of relapsing-remitting multiple sclerosis and are associated with adverse functional consequences. However, estimates of cognitive impairment (CIm) prevalence vary widely. This study aimed to determine the pooled prevalence of CIm among adults with RRMS and investigate moderators of prevalence rates. Following prospective registration (PROSPERO; CRD42021281815), electronic databases (Embase, Scopus, Medline, and PsycINFO) were searched from inception until March 2023. Eligible studies reported the prevalence of CIm among adults with RRMS, as determined through standardized neuropsychological testing and defined as evidence of reduced performance across at least two cognitive domains (e.g., processing speed, attention) relative to normative samples, healthy controls, or premorbid estimates. The electronic database search yielded 8695 unique records, of which 50 met selection criteria. The pooled prevalence of cognitive impairment was 32.5% (95% confidence interval 29.3-36.0%) across 5859 participants. Mean disease duration and age were significant predictors of cognitive impairment prevalence, with samples with longer disease durations and older age reporting higher prevalence rates. Studies which administered more extensive test batteries also reported significantly higher cognitive impairment prevalence. Approximately one third of adults with RRMS experience clinical levels of CIm. This finding supports the use of routine cognitive testing to enable early detection of CIm, and to identify individuals who may benefit from additional cognitive and functional support during treatment planning.

Role of white matter in cognitive impairment among relapsing remitting multiple sclerosis patients

BACKGROUND

Multiple Sclerosis (MS) associated cognitive impairment is believed to be mostly connected with damage to gray matter. The contribution of white matter is still poorly understood. We aim to examine the relationship between cognition and white matter tracts among relapsing remitting MS (RRMS) patients.

METHODS

Thirty RRMS patients were selected undergo the (3-seconds-interstimulus-interval paced auditory serial addition test) PASAT-3, the (symbol digit modalities test (SDMT) and full-brain MRI scans on a SIEMENS 3 Tesla Verio scanner. Diffusion Tensor Imaging (DTI) parameters, such as fractional anisotropy (FA) and mean diffusivity (MD) were examined in 37 white matter (WM) tracts. WM tracts were selected from the association pathways, projection pathways, commissural pathways by applying Human Connectome project (HCP)842 tractography atlas after DTI data reconstruction and registration to HCP1065 diffusion template in DSI Studio (version March 2021) In SPSS v26, Spearman's rank correlation analysis was used to examine the connection between DTI WM tracts and cognitive scores. The power of the study was increased by using false discovery rate (FDR) software.

RESULTS

The mean scores on the PASAT-3 and SDMT were 31.5 ± 12.8 and 46.9 ± 16.7 respectively. Better cognitive performance was correlated to higher FA values, while lower cognitive function was correlated to higher MD values. There was a positive correlation between FA values in the right medial lemniscus and superior cerebellar peduncle and SDMT scores (p 0.05). Additionally, there was a trend for significance between the FA values in the left corticothalamic tract and SDMT scores. MD values in the superior cerebellar peduncle, left arcuate Fasciculus and left extreme capsule were negatively correlated with SDMT scores (p<0.05). PASAT-3 scores were negatively correlated with MD values in the right cerebellum, however, there was no significant correlation between PASAT-3 and FA values.

CONCLUSIONS

White matter tracts, particularly the superior cerebellar peduncle, contribute to the cognitive impairment in RRMS. Larger sample sizes for longitudinal research are necessary.

Cognitive function in primary and secondary progressive multiple sclerosis: A multiparametric magnetic resonance imaging study

BACKGROUND AND PURPOSE

The differences in cognitive function between primary progressive and secondary progressive multiple sclerosis (MS) remain unclear. We compared cognitive performance between primary progressive multiple sclerosis (PPMS) and secondary progressive multiple sclerosis (SPMS), and explored the structural and functional magnetic resonance imaging (MRI) correlates of their cognitive functions.

METHODS

Seventy-five healthy controls and 183 MS patients (60 PPMS and 123 SPMS) underwent 3.0-T MRI. MS patients were administered the Brief Repeatable Battery of Neuropsychological Tests; cognitive domain z-scores were calculated and then averaged to obtain a measure of global cognition. Using hierarchical linear regression analysis, the contribution of lesion volumes, normalized brain volumes, white matter (WM) fractional anisotropy (FA) and mean diffusivity abnormalities, and resting state (RS) functional connectivity (FC) alterations to global cognition in PPMS and SPMS was investigated.

RESULTS

PPMS and SPMS had similar z-scores in all investigated cognitive domains. Poor global cognitive function was associated with decreased FA of the medial lemniscus (ΔR 2  = 0.11, p = 0.011) and lower normalized gray matter volume (ΔR 2  = 0.29, p < 0.001) in PPMS, and with decreased FA of the fornix (ΔR 2  = 0.35, p < 0.001) and lower normalized WM volume (ΔR 2  = 0.05; p = 0.034) in SPMS.

CONCLUSIONS

PPMS and SPMS had similar neuropsychological performance. Cognitive dysfunction in PPMS and SPMS was related to distinct patterns of structural MRI abnormalities and involvement of different WM tracts, whereas RS FC alterations did not contribute to explaining their global cognitive functioning.

Functional and structural brain MRI changes associated with cognitive worsening in multiple sclerosis: a 3-year longitudinal study

BACKGROUND

Heterogeneous processes may contribute to cognitive impairment in multiple sclerosis (MS).

OBJECTIVE

To apply a longitudinal multiparametric MRI approach to identify mechanisms associated with cognitive worsening in MS patients.

METHODS

3 T brain functional and structural MRI scans were acquired at baseline and after a median follow-up of 3.4 years in 35 MS patients and 22 healthy controls (HC). Associations between cognitive worsening (reliable change index score < - 1.25 at the Rao's battery) and longitudinal changes in regional T2-hyperintense white matter (WM) lesions, diffusion tensor microstructural WM damage, gray matter (GM) atrophy and resting state (RS) functional connectivity (FC) were explored.

RESULTS

At follow-up, HC showed no clusters of significant microstructural WM damage progression, GM atrophy or changes in RS FC. At follow-up, 10 MS patients (29%) showed cognitive worsening. Compared to cognitively stable, cognitively worsened MS patients showed more severe GM atrophy of the right anterior cingulate cortex and bilateral supplementary motor area (p < 0.001). Cognitively worsened vs cognitively stable MS patients showed also decreased RS FC in the right hippocampus of the right working memory network and in the right insula of the default mode network. Increased RS FC in the left insula of the executive control network was found in the opposite comparison (p < 0.001). No significant regional accumulation of focal WM lesions nor microstructural WM abnormalities occurred in both patients' groups.

CONCLUSIONS

GM atrophy progression in cognitively relevant brain regions combined with functional impoverishment in networks involved in cognitive functions may represent the substrates underlying cognitive worsening in MS.

Unraveling the link: exploring the causal relationship between diabetes, multiple sclerosis, migraine, and Alzheimer's disease through Mendelian randomization

Introduction

Observational studies suggested that diabetes mellitus [type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM)], multiple sclerosis (MS), and migraine are associated with Alzheimer's disease (AD). However, the causal link has not been fully elucidated. Thus, we aim to assess the causal link between T1DM, T2DM, MS, and migraine with the risk of AD using a two-sample Mendelian randomization (MR) study.

Methods

Genetic instruments were identified for AD, T1DM, T2DM, MS, and migraine respectively from genome-wide association study. MR analysis was conducted mainly using the inverse-variance weighted (IVW) method.

Results

The result of IVW method demonstrated that T2DM is causally associated with risk of AD (OR: 1.237, 95% CI: 1.099-1.391, P: 0.0003). According to the IVW method, there is no causal association between TIDM, MS, migraine, and the risk of AD (all p value > 0.05). Here we show, there is a causal link between T2DM and the risk of AD.

Conclusion

These findings highlight the significance of active monitoring and prevention of AD in T2DM patients. Further studies are required to actively search for the risk factors of T2DM combined with AD, explore the markers that can predict T2DM combined with AD, and intervene and treat early.

Diffusion tensor imaging metrics associated with future disability in multiple sclerosis

The relationship between brain diffusion microstructural changes and disability in multiple sclerosis (MS) remains poorly understood. We aimed to explore the predictive value of microstructural properties in white (WM) and grey matter (GM), and identify areas associated with mid-term disability in MS patients. We studied 185 patients (71% female; 86% RRMS) with the Expanded Disability Status Scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), and Symbol Digit Modalities Test (SDMT) at two time-points. We used Lasso regression to analyse the predictive value of baseline WM fractional anisotropy and GM mean diffusivity, and to identify areas related to each outcome at 4.1 years follow-up. Motor performance was associated with WM (T25FW: RMSE = 0.524, R² = 0.304; 9HPT dominant hand: RMSE = 0.662, R² = 0.062; 9HPT non-dominant hand: RMSE = 0.649, R² = 0.139), and SDMT with GM diffusion metrics (RMSE = 0.772, R² = 0.186). Cingulum, longitudinal fasciculus, optic radiation, forceps minor and frontal aslant were the WM tracts most closely linked to motor dysfunction, and temporal and frontal cortex were relevant for cognition. Regional specificity related to clinical outcomes provide valuable information that can be used to develop more accurate predictive models that could improve therapeutic strategies.

Regional white matter and gray matter damage and cognitive performances in multiple sclerosis according to sex

In this study, we investigated whether regional distribution of white matter (WM) lesions, normal-appearing [NA] WM microstructural abnormalities and gray matter (GM) atrophy may differently contribute to cognitive performance in multiple sclerosis (MS) patients according to sex. Using the same scanner, brain 3.0T MRI was acquired for 287 MS patients (females = 173; mean age = 42.1 [standard deviation, SD = 12.7] years; relapsing-remitting = 196, progressive = 91; median Expanded Disability Status Scale = 2.5 [interquartile range, IQR = 1.5-5.0]; median disease duration = 12.1 [IQR = 6.3-19.0] years; treatment: none = 70, first-line = 130, second-line = 87) and 172 healthy controls (HC) (females = 92; mean age = 39.3 [SD = 14.8] years). MS patients underwent also Rao's neuropsychological battery. Using voxel-wise analyses, we investigated in patients sex-related differences in the association of cognitive performances with WM lesions, NAWM fractional anisotropy (FA) and GM volumes (p < 0.01, family-wise error [FWE]). Sixty-six female (38%) and 48 male (42%) MS patients were cognitively impaired, with no significant between-group difference (p = 0.704). However, verbal memory performance was worse in males (p = 0.001), whereas verbal fluency performance was worse in females (p = 0.004). In both sexes, a higher T2-hyperintense lesion prevalence in cognitively-relevant WM tracts was significantly associated with worse cognitive performance (p ≤ 0.006), with stronger associations in females than males in global cognition (p ≤ 0.004). Compared to sex-matched HC, male and female MS patients had widespread lower NAWM FA and GM volume (p < 0.01). In both sexes, worse cognitive performance was associated with widespread reduced NAWM FA (p < 0.01), with stronger associations in females than males in global cognition and verbal memory (p ≤ 0.009). Worse cognitive performance was significantly associated with clusters of cortical GM atrophy in males (p ≤ 0.007) and mainly with deep GM atrophy in females (p ≤ 0.006). In this study, only limited differences in cognitive performances were found between male and female MS patients. A disconnection syndrome due to focal WM lesions and diffuse NAWM microstructural abnormalities seems to be more relevant in female MS patients to explain cognitive impairment.

NODDI, diffusion tensor microstructural abnormalities and atrophy of brain white matter and gray matter contribute to cognitive impairment in multiple sclerosis

BACKGROUND

Pathologically specific MRI measures may elucidate in-vivo the heterogeneous processes contributing to cognitive impairment in multiple sclerosis (MS).

PURPOSE

Using diffusion tensor and neurite orientation dispersion and density imaging (NODDI), we explored the contribution of focal lesions and normal-appearing (NA) tissue microstructural abnormalities to cognitive impairment in MS.

METHODS

One hundred and fifty-two MS patients underwent 3 T brain MRI and a neuropsychological evaluation. Forty-eight healthy controls (HC) were also scanned. Fractional anisotropy (FA), mean diffusivity (MD), intracellular volume fraction (ICV_f) and orientation dispersion index (ODI) were assessed in cortical and white matter (WM) lesions, thalamus, NA cortex and NAWM. Predictors of cognitive impairment were identified using random forest.

RESULTS

Fifty-two MS patients were cognitively impaired. Compared to cognitively preserved, impaired MS patients had higher WM lesion volume (LV), lower normalized brain volume (NBV), cortical volume (NCV), thalamic volume (NTV), and WM volume (p ≤ 0.021). They also showed lower NAWM FA, higher NAWM, NA cortex and thalamic MD, lower NAWM ICV_f, lower WM lesion ODI, and higher NAWM ODI (false discovery rate-p ≤ 0.026). Cortical lesion number and microstructural abnormalities were not significantly different. The best MRI predictors of cognitive impairment (relative importance) (out-of-bag area under the curve = 0.727) were NAWM FA (100%), NTV (96.0%), NBV (84.7%), thalamic MD (43.4%), NCV (40.6%), NA cortex MD (26.0%), WM LV (23.2%) and WM lesion ODI (17.9%).

CONCLUSIONS

Our multiparametric MRI study including NODDI measures suggested that neuro-axonal damage and loss of microarchitecture integrity in focal WM lesions, NAWM, and GM contribute to cognitive impairment in MS.

Somatosensory evoked potentials and their relation to microstructural damage in patients with multiple sclerosis—A whole brain DTI study

Introduction

Somatosensory evoked potentials (SSEP) play a pivotal role in the diagnosis and disease monitoring of multiple sclerosis (MS). Delayed latencies are a surrogate for demyelination along the sensory afference. This study aimed to evaluate if SSEP latencies are representative of demyelination of the brain overall, by correlating with cerebral microstructural integrity as measured by Magnetic resonance (MR) diffusion tensor imaging (DTI). Analysis was performed in a hypothesis-free whole brain approach using tract-based spatial statistics (TBSS).

Material and methods

A total of 46 patients with MS or clinically isolated syndrome were included in the study. Bilateral SSEPs of the median nerve measuring mean N20 latencies (mN20) and Central Conduction Time (CCT), were acquired. MRI scans were performed at 3T. DTI acquisition was done with a single-shot echoplanar imaging technique with 80 diffusion directions. The FSL software package was used to process the DTI datasets and to calculate maps of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD). These maps were then further analyzed using the TBSS module. The mean N20 and CCT and the right- and left-sided N20 and CCT were separately correlated to FA, AD, and RD, controlled for age, gender, and EDSS as variables of non-interest.

Results

Widespread negative correlations of SSEP latencies with FA (p = 0.0005) and positive correlations with RD (p = 0.0003) were measured in distinct white matter tracts, especially the optic tracts, corpus callosum, and posterior corona radiata. No correlation with AD was found in any white matter tract.

Conclusion

Highly significant correlations of FA and RD to SSEPs suggest that their latency is representative of widespread microstructural change, and especially demyelination in patients suffering from MS, reaching beyond the classic somatosensory regions. This points to the usefulness of SSEPs as a non-invasive tool in the evaluation of microstructural damage to the brain.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Spatial patterns of brain lesions assessed through covariance estimations of lesional voxels in multiple Sclerosis: The SPACE-MS technique

Predicting disability in progressive multiple sclerosis (MS) is extremely challenging. Although there is some evidence that the spatial distribution of white matter (WM) lesions may play a role in disability accumulation, the lack of well-established quantitative metrics that characterise these aspects of MS pathology makes it difficult to assess their relevance for clinical progression. This study introduces a novel approach, called SPACE-MS, to quantitatively characterise spatial distributional features of brain MS lesions, so that these can be assessed as predictors of disability accumulation. In SPACE-MS, the covariance matrix of the spatial positions of each patient's lesional voxels is computed and its eigenvalues extracted. These are combined to derive rotationally-invariant metrics known to be common and robust descriptors of ellipsoid shape such as anisotropy, planarity and sphericity. Additionally, SPACE-MS metrics include a neuraxis caudality index, which we defined for the whole-brain lesion mask as well as for the most caudal brain lesion. These indicate how distant from the supplementary motor cortex (along the neuraxis) the whole-brain mask or the most caudal brain lesions are. We applied SPACE-MS to data from 515 patients involved in three studies: the MS-SMART (NCT01910259) and MS-STAT1 (NCT00647348) secondary progressive MS trials, and an observational study of primary and secondary progressive MS. Patients were assessed on motor and cognitive disability scales and underwent structural brain MRI (1.5/3.0 T), at baseline and after 2 years. The MRI protocol included 3DT1-weighted (1x1x1mm3) and 2DT2-weighted (1x1x3mm3) anatomical imaging. WM lesions were semiautomatically segmented on the T2-weighted scans, deriving whole-brain lesion masks. After co-registering the masks to the T1 images, SPACE-MS metrics were calculated and analysed through a series of multiple linear regression models, which were built to assess the ability of spatial distributional metrics to explain concurrent and future disability after adjusting for confounders. Patients whose WM lesions laid more caudally along the neuraxis or were more isotropically distributed in the brain (i.e. with whole-brain lesion masks displaying a high sphericity index) at baseline had greater motor and/or cognitive disability at baseline and over time, independently of brain lesion load and atrophy measures. In conclusion, here we introduced the SPACE-MS approach, which we showed is able to capture clinically relevant spatial distributional features of MS lesions independently of the sheer amount of lesions and brain tissue loss. Location of lesions in lower parts of the brain, where neurite density is particularly high, such as in the cerebellum and brainstem, and greater spatial spreading of lesions (i.e. more isotropic whole-brain lesion masks), possibly reflecting a higher number of WM tracts involved, are associated with clinical deterioration in progressive MS. The usefulness of the SPACE-MS approach, here demonstrated in MS, may be explored in other conditions also characterised by the presence of brain WM lesions.