The relevance of multiple sclerosis cortical lesions on cortical thinning and their clinical impact as assessed by 7.0-T MRI

Association of Levels of CSF Osteopontin With Cortical Atrophy and Disability in Early Multiple Sclerosis

BACKGROUND AND OBJECTIVES

To evaluate CSF inflammatory markers with accumulation of cortical damage as well as disease activity in patients with early relapsing-remitting MS (RRMS).

METHODS

CSF levels of osteopontin (OPN) and 66 inflammatory markers were assessed using an immune-assay multiplex technique in 107 patients with RRMS (82 F/25 M, mean age 35.7 ± 11.8 years). All patients underwent regular clinical assessment and yearly 3T MRI scans for 2 years while 39 patients had a 4-year follow-up. White matter lesion number and volume, cortical lesions (CLs) and volume, and global cortical thickness (CTh) were evaluated together with the 'no evidence of disease activity' (NEDA-3) status, defined by no relapses, no disability worsening, and no MRI activity, including CLs.

RESULTS

The random forest algorithm selected OPN, CXCL13, TWEAK, TNF, IL19, sCD30, sTNFR1, IL35, IL16, and sCD163 as significantly associated with changes in global CTh. OPN and CXCL13 were most related to accumulation of atrophy after 2 and 4 years. In a multivariate linear regression model on CSF markers, OPN (p < 0.001), CXCL13 (p = 0.001), and sTNFR1 (p = 0.024) were increased in those patients with accumulating atrophy (adjusted R-squared 0.615). The 10 markers were added in a model that included all clinical, demographic, and MRI variables: OPN (p = 0.002) and IL19 (p = 0.022) levels were confirmed to be significantly increased in patients developing more CTh change over the follow-up (adjusted R-squared 0.619). CXCL13 and OPN also revealed the best association with NEDA-3 after 2 years, with OPN significantly linked to disability accumulation (OR 2.468 [1.46-5.034], p = 0.004) at the multivariate logistic regression model.

DISCUSSION

These data confirm and expand our knowledge on the prognostic role of the CSF inflammatory profile in predicting changes in cortical pathology and disease activity in early MS. The data emphasize a crucial role of OPN.

Transcript Profiles of Microglia/Macrophage Cells at the Borders of Chronic Active and Subpial Gray Matter Lesions in Multiple Sclerosis

OBJECTIVE

Microglia/macrophages line the border of demyelinated lesions in both cerebral white matter and the cortex in the brains of multiple sclerosis patients. Microglia/macrophages associated with chronic white matter lesions are thought to be responsible for slow lesion expansion and disability progression in progressive multiple sclerosis, whereas those lining gray matter lesions are less studied. Profiling these microglia/macrophages could help to focus therapies on genes or pathways specific to lesion expansion and disease progression.

METHODS

We compared the morphology and transcript profiles of microglia/macrophages associated with borders of white matter (WM line) and subpial gray matter lesions (GM line) using laser capture microscopy. We performed RNA sequencing on isolated cells followed by immunocytochemistry to determine the distribution of translational products of transcripts increased in WM line microglia.

RESULTS

Cells in the WM line appear activated, with shorter processes and larger cell bodies, whereas those in the GM line appear more homeostatic, with smaller cell bodies and multiple thin processes. Transcript profiling revealed 176 genes in WM lines and 111 genes in GM lines as differentially expressed. Transcripts associated with immune activation and iron homeostasis were increased in WM line microglia, whereas genes belonging to the canonical Wnt signaling pathway were increased in GM line microglia.

INTERPRETATION

We propose that the mechanisms of demyelination and dynamics of lesion expansion are responsible for differential transcript expression in WM lines and GM lines, and posit that increased expression of the Fc epsilon receptor, spleen tyrosine kinase, and Bruton's tyrosine kinase, play a key role in regulating microglia/macrophage function at the border of chronic active white matter lesions. ANN NEUROL 2024;95:907-916.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.

Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent.

OBJECTIVE

We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure.

METHODS

MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis.

RESULTS

After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) =  - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology.

CONCLUSION

Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.

Cortical lesions uniquely predict motor disability accrual and form rarely in the absence of new white matter lesions in multiple sclerosis

Background and objectives

Cortical lesions (CL) are common in multiple sclerosis (MS) and associate with disability and progressive disease. We asked whether CL continue to form in people with stable white matter lesions (WML) and whether the association of CL with worsening disability relates to pre-existing or new CL.

Methods

A cohort of adults with MS were evaluated annually with 7 tesla (T) brain magnetic resonance imaging (MRI) and 3T brain and spine MRI for 2 years, and clinical assessments for 3 years. CL were identified on 7T images at each timepoint. WML and brain tissue segmentation were performed using 3T images at baseline and year 2.

Results

59 adults with MS had ≥1 7T follow-up visit (mean follow-up time 2±0.5 years). 9 had "active" relapsing-remitting MS (RRMS), defined as new WML in the year prior to enrollment. Of the remaining 50, 33 had "stable" RRMS, 14 secondary progressive MS (SPMS), and 3 primary progressive MS. 16 total new CL formed in the active RRMS group (median 1, range 0-10), 7 in the stable RRMS group (median 0, range 0-5), and 4 in the progressive MS group (median 0, range 0-1) (p=0.006, stable RR vs PMS p=0.88). New CL were not associated with greater change in any individual disability measure or in a composite measure of disability worsening (worsening Expanded Disability Status Scale or 9-hole peg test or 25-foot timed walk). Baseline CL volume was higher in people with worsening disability (median 1010μl, range 13-9888 vs median 267μl, range 0-3539, p=0.001, adjusted for age and sex) and in individuals with RRMS who subsequently transitioned to SPMS (median 2183μl, range 270-9888 vs median 321μl, range 0-6392 in those who remained RRMS, p=0.01, adjusted for age and sex). Baseline WML volume was not associated with worsening disability or transition from RRMS to SPMS.

Discussion

CL formation is rare in people with stable WML, even in those with worsening disability. CL but not WML burden predicts future worsening of disability, suggesting that the relationship between CL and disability progression is related to long-term effects of lesions that form in the earlier stages of disease, rather than to ongoing lesion formation.

Imaging cortical lesions in multiple sclerosis

PURPOSE OF REVIEW

Cortical lesions are an established pathological feature of multiple sclerosis, develop from the earliest disease stages and contribute to disease progression. Here, we discuss current imaging approaches for detecting cortical lesions in vivo and their contribution for improving our understanding of cortical lesion pathogenesis as well as their clinical significance.

RECENT FINDINGS

Although a variable portion of cortical lesions goes undetected at clinical field strength and even at ultra-high field MRI, their evaluation is still clinically relevant. Cortical lesions are important for differential multiple sclerosis (MS) diagnosis, have relevant prognostic value and independently predict disease progression. Some studies also show that cortical lesion assessment could be used as a therapeutic outcome target in clinical trials. Advances in ultra-high field MRI not only allow increased cortical lesion detection in vivo but also the disclosing of some interesting features of cortical lesions related to their pattern of development and evolution as well to the nature of associated pathological changes, which might prove relevant for better understanding the pathogenesis of these lesions.

SUMMARY

Despite some limitations, imaging of cortical lesions is of paramount importance in MS for elucidating disease mechanisms as well as for improving patient management in clinic.

Recent Progress in the Identification of Early Transition Biomarkers from Relapsing-Remitting to Progressive Multiple Sclerosis

Despite extensive research into the pathophysiology of multiple sclerosis (MS) and recent developments in potent disease-modifying therapies (DMTs), two-thirds of relapsing-remitting MS patients transition to progressive MS (PMS). The main pathogenic mechanism in PMS is represented not by inflammation but by neurodegeneration, which leads to irreversible neurological disability. For this reason, this transition represents a critical factor for the long-term prognosis. Currently, the diagnosis of PMS can only be established retrospectively based on the progressive worsening of the disability over a period of at least 6 months. In some cases, the diagnosis of PMS is delayed for up to 3 years. With the approval of highly effective DMTs, some with proven effects on neurodegeneration, there is an urgent need for reliable biomarkers to identify this transition phase early and to select patients at a high risk of conversion to PMS. The purpose of this review is to discuss the progress made in the last decade in an attempt to find such a biomarker in the molecular field (serum and cerebrospinal fluid) between the magnetic resonance imaging parameters and optical coherence tomography measures.

Cortical lesions at diagnosis predict long-term cognitive impairment in multiple sclerosis: A 20-year study

BACKGROUND AND PURPOSE

Although cognitive impairment (CI) is frequent in multiple sclerosis (MS) patients, few studies (and with conflicting results) have evaluated early predictors of CI in the long term. We aimed at determining associations between early clinical/neuroradiological variables with reference to CI after 20 years of MS.

METHODS

We investigated in 170 MS patients the relationship between clinical/magnetic resonance imaging (MRI) data at diagnosis and cognitive status almost 20 years after MS onset. Among others, number and volume of both white matter lesions (WMLs) and cortical lesions (CLs) were evaluated at diagnosis and after 2 years. All MS patients were followed over time and underwent a comprehensive neuropsychological assessment at the end of study. Advanced statistical methods (unsupervised cluster analysis and random forest model) were conducted.

RESULTS

CI patients showed higher focal cortical pathology at diagnosis compared to cognitively normal subjects (p < 0.001). Volumes of both WMLs and CLs emerged as the MRI metrics most associated with long-term CI. Moreover, number of CLs (especially ≥3) was also strongly associated with long-term CI (≥3 CLs: odds ratio [OR] = 3.7, 95% confidence interval = 1.8-7.5, p < 0.001), more than number of WMLs; the optimal cutoff of three CLs (area under the curve = 0.67, specificity = 75%, sensitivity = 55%) was estimated according to the risk of developing CI.

CONCLUSIONS

These results highlight the impact of considering both white and gray matter focal damage from early MS stages. Given the low predictive value of WML number and the poor clinical applicability of lesion volume estimation in the daily clinical context, the evaluation of number of CLs could represent a reliable prognostic marker of CI.

An Interpretable Machine Learning Model to Predict Cortical Atrophy in Multiple Sclerosis

To date, the relationship between central hallmarks of multiple sclerosis (MS), such as white matter (WM)/cortical demyelinated lesions and cortical gray matter atrophy, remains unclear. We investigated the interplay between cortical atrophy and individual lesion-type patterns that have recently emerged as new radiological markers of MS disease progression. We employed a machine learning model to predict mean cortical thinning in whole-brain and single hemispheres in 150 cortical regions using demographic and lesion-related characteristics, evaluated via an ultrahigh field (7 Tesla) MRI. We found that (i) volume and rimless (i.e., without a "rim" of iron-laden immune cells) WM lesions, patient age, and volume of intracortical lesions have the most predictive power; (ii) WM lesions are more important for prediction when their load is small, while cortical lesion load becomes more important as it increases; (iii) WM lesions play a greater role in the progression of atrophy during the latest stages of the disease. Our results highlight the intricacy of MS pathology across the whole brain. In turn, this calls for multivariate statistical analyses and mechanistic modeling techniques to understand the etiopathogenesis of lesions.

Cortical lesion hotspots and association of subpial lesions with disability in multiple sclerosis

BACKGROUND

Dramatic improvements in visualization of cortical (especially subpial) multiple sclerosis (MS) lesions allow assessment of impact on clinical course.

OBJECTIVE

Characterize cortical lesions by 7 tesla (T) T₂^*-/T₁-weighted magnetic resonance imaging (MRI); determine relationship with other MS pathology and contribution to disability.

METHODS

Sixty-four adults with MS (45 relapsing-remitting/19 progressive) underwent 3 T brain/spine MRI, 7 T brain MRI, and clinical testing.

RESULTS

Cortical lesions were found in 94% (progressive: median 56/range 2-203; relapsing-remitting: 15/0-168; p = 0.004). Lesion distribution across 50 cortical regions was nonuniform (p = 0.006), with highest lesion burden in supplementary motor cortex and highest prevalence in superior frontal gyrus. Leukocortical and white matter lesion volumes were strongly correlated (r = 0.58, p < 0.0001), while subpial and white matter lesion volumes were moderately correlated (r = 0.30, p = 0.002). Leukocortical (p = 0.02) but not subpial lesions (p = 0.40) were correlated with paramagnetic rim lesions; both were correlated with spinal cord lesions (p = 0.01). Cortical lesion volumes (total and subtypes) were correlated with expanded disability status scale, 25-foot timed walk, nine-hole peg test, and symbol digit modality test scores.

CONCLUSION

Cortical lesions are highly prevalent and are associated with disability and progressive disease. Subpial lesion burden is not strongly correlated with white matter lesions, suggesting differences in inflammation and repair mechanisms.