Impact of Cognitive Reserve and Structural Connectivity on Cognitive Performance in Multiple Sclerosis

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.

Predictive value of retinal atrophy for cognitive decline across disease duration in multiple sclerosis

BACKGROUND

We investigated the association between changes in retinal thickness and cognition in people with MS (PwMS), exploring the predictive value of optical coherence tomography (OCT) markers of neuroaxonal damage for global cognitive decline at different periods of disease.

METHOD

We quantified the peripapillary retinal nerve fibre (pRFNL) and ganglion cell-inner plexiform (GCIPL) layers thicknesses of 207 PwMS and performed neuropsychological evaluations. The cohort was divided based on disease duration (≤5 years or >5 years). We studied associations between changes in OCT and cognition over time, and assessed the risk of cognitive decline of a pRFNL≤88 µm or GCIPL≤77 µm and its predictive value.

RESULTS

Changes in pRFNL and GCIPL thickness over 3.2 years were associated with evolution of cognitive scores, in the entire cohort and in patients with more than 5 years of disease (p<0.01). Changes in cognition were related to less use of disease-modifying drugs, but not OCT metrics in PwMS within 5 years of onset. A pRFNL≤88 µm was associated with earlier cognitive disability (3.7 vs 9.9 years) and higher risk of cognitive deterioration (HR=1.64, p=0.022). A GCIPL≤77 µm was not associated with a higher risk of cognitive decline, but a trend was observed at ≤91.5 µm in PwMS with longer disease (HR=1.81, p=0.061).

CONCLUSIONS

The progressive retinal thinning is related to cognitive decline, indicating that cognitive dysfunction is a late manifestation of accumulated neuroaxonal damage. Quantifying the pRFNL aids in identifying individuals at risk of cognitive dysfunction.

Systematic review of cognitive reserve in multiple sclerosis: Accounting for physical disability, fatigue, depression, and anxiety

BACKGROUND

Cognitive reserve (CR) describes an individual's ability to adapt cognitive processes in response to brain atrophy, and has been reported to explain some of the discrepancy between brain atrophy and cognitive functioning outcomes in multiple sclerosis (MS). CR in MS is typically investigated by assessing an individual's pre- and/or post-diagnosis enrichment, which includes premorbid intellectual abilities, educational level, occupational attainment, and engagement in cognitively enriching leisure activities. Common MS symptoms (e.g., physical disability, fatigue, depression, anxiety) may impact an individual's ability to engage in various CR-enhancing activities post-diagnosis. It is unknown to what extent these MS symptoms have been taken into account in MS research on CR. As such, we identified whether studies assessed CR using measures of premorbid or continuous (including post-diagnosis) enrichment. For studies investigating continuous enrichment, we identified whether studies accounted for MS-impact, which MS symptoms were accounted for, and how, and whether studies acknowledged MS symptoms as potential CR-confounds.

METHODS

Three electronic databases (PsycINFO, PubMed, Scopus) were searched. Eligible studies investigated CR proxies (e.g., estimated premorbid intellectual abilities, vocabulary knowledge, educational level, occupational attainment, cognitively enriching leisure activities, or a combination thereof) in relation to cognitive, brain atrophy or connectivity, or daily functioning outcomes in adult participants with MS. We extracted data on methods and measures used, including any MS symptoms taken into account. Objectives were addressed using frequency analyses and narrative synthesis.

RESULTS

115 studies were included in this review. 47.8% of all studies investigated continuous enrichment. Approximately half of the studies investigating continuous enrichment accounted for potential MS-impact in their analyses, with only 31.0% clearly identifying that they treated MS symptoms as potential confounds for CR-enhancement. A narrative synthesis of studies which investigated CR with and without controlling statistically for MS-impact indicated that accounting for MS symptoms may impact findings concerning the protective nature of CR.

CONCLUSION

Fewer than half of the studies investigating CR proxies in MS involved continuous enrichment. Just over half of these studies accounted for potential MS-impact in their analyses. To achieve a more complete and accurate understanding of CR in MS, future research should investigate both pre-MS and continuous enrichment. In doing so, MS symptoms and their potential impact should be considered. Establishing greater consistency and rigour across CR research in MS will be crucial to produce an evidence base for the development of interventions aimed at improving quality of care and life for pwMS.

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

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Multiple sclerosis (MS) can be considered as a network disorder.

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This review discusses network concepts in order to understand progression in MS.

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Damage is hypothesized to lead to a “network collapse” and clinical progression.

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New concepts are discussed that will likely influence the field in the near future.

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These include brain wiring, how regions communicate and robustness to damage.

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.

Cognitive resilience depends on white matter connectivity: The Maastricht Study

INTRODUCTION

Differences in brain network connectivity may reflect the capability of the neurological substrate to compensate for brain damage and preserve cognitive function (cognitive reserve). We examined the associations between white matter connectivity, brain damage markers, and cognition in a population sample of middle-aged individuals.

METHODS

A total of 4759 participants from The Maastricht Study (mean age = 59.2, SD = 8.7, 50.2% male) underwent cognitive testing and diffusion magnetic resonance imaging (dMRI), from which brain volume, structural connectivity, and vascular damage were quantified. Multivariable linear regression was used to investigate whether connectivity modified the association between brain damage and cognition, adjusted for demographic and cardiometabolic risk factors.

RESULTS

More atrophic and vascular brain damage was associated with worse cognition scores. Increasing connectivity moderated the negative association between damage and cognition (χ² = 8.64, df = 3, p ≤ 0.001); individuals with high damage but strong connectivity showed normal cognition.

DISCUSSION

Findings support the reserve hypothesis by showing that brain connectivity is associated with cognitive resilience.

The Chinese Translation Study of the Cognitive Reserve Index Questionnaire

Purpose

The purpose of this study was to perform the translation and adaption of the Cognitive Reserve Index questionnaire into Chinese and assess the reliability of the Chinese version.

Materials and Methods

The Chinese version of the Cognitive Reserve Index questionnaire was created from a standard forward-backward translation. A total of 371 volunteers, aged between 20 and 89 years, participated in this survey. Participants were divided into three age-groups (Young, Middle-aged, and Elderly), and subgroup differences were examined by independent samples t-tests, ANOVA analysis as well as post-hoc analysis. Pearson correlation analysis was applied to test the association between the total scores and each subscore (CRI-Education, CRI-WorkingActivity, and CRI-LeisureTime). The internal consistency and test-retest reliability of the Cognitive Reserve Index questionnaire were assessed. The test-retest reliability was measured among 40 participants with a 2-week interval using intraclass correlation coefficient.

Results

Strong correlations were observed between the total scores and each subscore (CRI-Education, CRI-WorkingActivity, and CRI-LeisureTime: r = 0.65, 0.79, and 0.70, respectively). In contrast, it was found low to moderate correlations among three subscores. The internal consistency was acceptable (Cronbach's alpha coefficient = 0.68). The intraclass correlation coefficient for total scores of the Chinese version of the Cognitive Reserve Index questionnaire was 0.87 (95% CI 0.74–0.93).

Conclusion

The Chinese version of the Cognitive Reserve Index questionnaire was a potentially reliable and practical tool for evaluating cognitive reserve accumulated through a person's life span.

Structure-function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis

Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear.

This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1 and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. ROC analyses were performed on coupling values to identify biomarker potential.

Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = −0.26, p = 0.023, only in MS). Long-range structure-function coupling was higher in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range AUC = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095).

Long-range structure-function coupling was higher in CI-MS compared to HC, but more research is needed to further explore this measure as biomarkers in MS.

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

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

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.