Social cognition in Multiple Sclerosis is associated to changes in brain connectivity: A resting-state fMRI study

The neural substrates of social cognition deficits in newly diagnosed multiple sclerosis patients

OBJECTIVE

Cognitive and affective symptoms in multiple sclerosis (MS) can be independently impaired and have different pathways of progression. Cognitive alterations have been described since the earliest MS stages; by contrast, the social cognition (SC) domain has never been investigated in the first year from MS diagnosis. We aimed to evaluate SC and unravel its neural bases in newly diagnosed MS patients.

METHODS

Seventy MS patients underwent at diagnosis a 3 T-MRI and a neuropsychological/SC assessment (median time between diagnosis and MRI/cognitive evaluation = 0 months). We tested two matched reference samples: 31 relapsing-remitting MS patients with longer course (mean ± SD disease duration = 7.0 ± 4.5 years) and 38 healthy controls (HCs). Cortical thicknesses (CTh) and volumes of brain regions were calculated.

RESULTS

Newly diagnosed MS patients performed significantly lower than HCs in facial emotion recognition (global: p < 0.001; happiness: p = 0.041, anger: p = 0.007; fear: p < 0.001; disgust: p = 0.004) and theory of mind (p = 0.005), while no difference was found between newly diagnosed and longer MS patients. Compared to lower performers, higher performers in facial emotion recognition showed greater volume of amygdala (p = 0.032) and caudate (p = 0.036); higher performers in theory of mind showed greater CTh in lingual gyrus (p = 0.006), cuneus (p = 0.024), isthmus cingulate (p = 0.038), greater volumes of putamen (p = 0.016), pallidum (p = 0.029), and amygdala (p = 0.032); patients with higher empathy showed lower cuneus CTh (p = 0.042) and putamen volume (p = 0.007).

INTERPRETATIONS

SC deficits are present in MS patients since the time of diagnosis and remain persistent along the disease course. Specific basal, limbic, and occipital areas play a significant role in the pathogenesis of these alterations.

A systematic review and meta-analysis of socio-cognitive impairments in multiple sclerose

Socio-cognitive impairment is frequent in multiple sclerosis (MS). However, little is known about the relationship between other potentially relevant clinical symptoms (i.e., cognition, depression, fatigue) and the degree of socio-cognitive impairment, and neural mechanisms underlying socio-cognitive deficits in MS. Therefore, we meta-analytically quantified socio-cognitive impairment in MS. A systematic literature search in MEDLINE Ovid, Web of Science Core Collection, CENTRAL, and PsycInfo was conducted until December 2022. Studies investigating affective or cognitive theory of mind (a/cToM), visual perspective taking (VPT) and social decision making (SDM) in MS patients relative to healthy controls were included. Risk-of-bias (RoB) was assessed using the CLARITY group "Tool for Assessing RoB in Cohort Studies". Mediation analysis investigated the contribution of clinical symptoms to socio-cognitive impairment. In total, n = 8534 studies were screened, 58 were included in the systematic review, 27 in the meta-analyses. Most studies were rated with a moderate RoB. Meta-analyses confirmed impairment of both aToM and cToM in MS patients, with larger effect sizes for aToM. Mediation analysis demonstrated that higher levels of fatigue selectively predicted the degree of cToM impairment. There was insufficient data available to quantify impairment in other socio-cognitive domains. Fourteen structural and functional imaging studies were identified and characterized by substantial heterogeneity. Summarized, this study confirmed substantial socio-cognitive impairment in MS and highlights the potential exacerbating role of comorbid clinical symptoms. We identify several evidence gaps that need to be addressed in future large-scale studies using comprehensive and coordinated assessments of socio-cognitive parameters, potential mediators, and neural correlates.Trial registration: The pre-registered review protocol can be assessed at www.crd.york.ac.uk/PROSPERO/ (ID: CRD42020206225).

Facial emotion impairment in multiple sclerosis is linked to modifying observation strategies of emotional faces

BACKGROUND

Facial emotion recognition (FER) may be impaired in patients with multiple sclerosis (MS). Nevertheless, the literature is heterogeneous, with studies not highlighting this kind of impairment. Moreover, most studies have not explored differences between MS spectrum disorders (radiologically isolated syndrome (RIS), clinically-isolated syndrome (CIS), relapsing-remitting (RRMS), and progressive (primary - (PPMS) and secondary - (SPMS)). One hypothesis would be that FER impairment results from an alteration of eye-gaze strategies while observing emotional faces. Consequently, a FER deficit would be found in MS patients for whom these observation strategies would be disturbed and more frequent in the progressive forms.

METHODS

We prospectively enroled 52 patients (10 RIS, 10 CIS, 12RRMS, 10 SPMS, 10 PPMS) and 23 healthy controls (HC) to assess FER using Ekman Faces Test. Eye movements (number and duration of fixations) were recorded with an eye-tracking device.

RESULTS

21% of the MS participants had significant FER impairment. This impairment was observed in all phenotypes. In progressive forms, FER impairment was more frequent, more severe, and associated with modified emotional face observation strategies. MS participants with significant FER impairment had significantly more modification of eye-gaze strategies during observation of expressive faces than MS participants without FER impairment.

CONCLUSION

FER impairment seems to be linked to a deficit of attention orientation in MS. Remediation of eye-gaze strategies during observation of emotional faces could be beneficial, as observed in other neurological diseases.

Executive Dysfunction, Social Cognition Impairment, and Gray Matter Pathology in Myotonic Dystrophy Type 2: A Pilot Study

BACKGROUND

In contrast to myotonic dystrophy type 1, the cognitive and radiologic profile of myotonic dystrophy type 2 (DM2) is relatively poorly characterized.

OBJECTIVE

To conduct a pilot study to systematically evaluate cognitive and radiologic features in a cohort of Greek individuals with DM2.

METHOD

Eleven genetically confirmed individuals with DM2 and 26 age- and education-matched healthy controls were administered the Edinburgh Cognitive and Behavioural Amyotrophic Lateral Sclerosis Screen (ECAS) to screen for impairment in multiple cognitive domains. MRI data were evaluated by morphometric analyses to identify disease-specific gray and white matter alterations. The following statistical thresholds were used for cognitive comparisons: PFDR < 0.05 and Bayes factor (BF 10 ) >10.

RESULTS

The DM2 group exhibited cognitive impairment (ECAS Total score; PFDR = 0.001; BF 10 = 108.887), which was dominated by executive impairment ( PFDR = 0.003; BF 10 = 25.330). A trend toward verbal fluency impairment was also identified. No significant impairments in memory, language, or visuospatial function were captured. The analysis of subscores revealed severe impairments in social cognition and alternation. Voxel-based morphometry identified widespread frontal, occipital, and subcortical gray matter atrophy, including the left superior medial frontal gyrus, right medial orbitofrontal gyrus, right operculum, right precuneus, bilateral fusiform gyri, and bilateral thalami.

CONCLUSION

DM2 may be associated with multifocal cortical and thalamic atrophy, which is likely to underpin the range of cognitive manifestations mostly characterized by executive impairment and specifically by impaired social cognition.

Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration

The proposal to use brain connectivity as a biomarker for dementia phenotyping can be potentiated by conducting large-scale multicentric studies using high-density electroencephalography (hd- EEG). Nevertheless, several barriers preclude the development of a systematic "ConnEEGtome" in dementia research. Here we review critical sources of variability in EEG connectivity studies, and provide general guidelines for multicentric protocol harmonization. We describe how results can be impacted by the choice for data acquisition, and signal processing workflows. The implementation of a particular processing pipeline is conditional upon assumptions made by researchers about the nature of EEG. Due to these assumptions, EEG connectivity metrics are typically applicable to restricted scenarios, e.g., to a particular neurocognitive disorder. "Ground truths" for the choice of processing workflow and connectivity analysis are impractical. Consequently, efforts should be directed to harmonizing experimental procedures, data acquisition, and the first steps of the preprocessing pipeline. Conducting multiple analyses of the same data and a proper integration of the results need to be considered in additional processing steps. Furthermore, instead of using a single connectivity measure, using a composite metric combining different connectivity measures brings a powerful strategy to scale up the replicability of multicentric EEG connectivity studies. These composite metrics can boost the predictive strength of diagnostic tools for dementia. Moreover, the implementation of multi-feature machine learning classification systems that include EEG-based connectivity analyses may help to exploit the potential of multicentric studies combining clinical-cognitive, molecular, genetics, and neuroimaging data towards a multi-dimensional characterization of the dementia.

Multimodal emotion perception in young and elderly patients with multiple sclerosis

BACKGROUND

Studies suggest that emotion recognition and empathy are impaired in patients with MS (pwMS). Nonetheless, most studies are restricted to young samples, to facial emotion recognition and to self-report assessments of empathy. The aims of this study are to determine the impact of MS and age on multimodal emotion recognition (facial emotions and vocal emotional bursts) and on socioemotional sensitivity (as reported by the participants and their informants). We also aim to investigate the associations between emotion recognition, socioemotional sensitivity, and cognitive measures.

METHODS

We recruited 13 young healthy controls (HC), 14 young pwMS, 14 elderly HC and 15 elderly pwMS. They underwent a short neuropsychological battery, an experimental emotion recognition task including facial emotions and vocal emotional bursts. Both participants and their study informants completed the Revised-Self Monitoring Scale (RSMS) to assess the participant's socioemotional sensitivity.

RESULTS

There was a significant effect of age and group on recognition of both facial emotions and emotional vocal bursts, HC performing significantly better than pwMS, and young participants performing better than elderly participants (no interaction effect). The same effects were observed on self-reported socioemotional sensitivity. However, lower socioemotional sensitivity in pwMS was not reported by the informants. Finally, multimodal emotion recognition did not correlate with socioemotional sensitivity, but it correlated with global cognitive severity.

CONCLUSION

PwMS present with multimodal emotion perception deficits. Our results extend previous findings of decreased emotion perception and empathy to a group of elderly pwMS, in which advancing age does not accentuate these deficits. However, the decreased socioemotional sensitivity reported by pwMS does not appear to be observed by their relatives, nor to correlate with their emotion perception impairments. Future studies should investigate the real-life impacts of emotion perception deficits in pwMS.

Amygdala network reorganization mediates the theory of mind performances in multiple sclerosis

Theory of mind (ToM) seems to be affected in multiple sclerosis (MS). MRI studies suggested a role of the amygdala in social cognitive performances. Therefore, we explored the role of the amygdala network in ToM using a multimodal MRI approach. In MS, patients with impaired ToM showed contradictory dysexecutive neuropsychological profile. Therefore, we compared neural networks involved in ToM and executive functions (EFs). Twenty patients with relapsing-remitting MS and 15 matched healthy controls were selected. ToM (Faux Pas test and mind stories) and EFs were assessed within and outside the scanner. All subjects underwent a battery of neuropsychological tests. Multimodal MRI with structural (diffusion imaging) and functional (resting-state and task-based) sequences was used to analyze the role and connections of the amygdala in ToM functioning. Cognitive and ToM performances were similar between patients and controls. Resting-state data revealed decreased connectivity of the left amygdala with frontal areas in patients compared to controls (p < 0.0001). During the task-based functional MRI, patients demonstrated increased connectivity between the amygdala and several cerebellar and left temporal regions (all p < 0.05). The microstructural alterations between the left amygdala and left temporal regions were associated with increased functional connectivity within the same pathway (r = 0.74; p < 0.01). No overlap was observed between functional networks involved in ToM and EFs. Our study demonstrates more connectivity recruitment between the amygdala and cerebellar and temporal regions in MS patients to reach preserved ToM performance. Microstructural abnormalities have been related to this compensatory network. Finally, different networks were involved in EFs and ToM.

Resting-State Functional Brain Connectivity for Human Mentalizing: Biobehavioral Mechanisms of Theory of Mind in Multiple Sclerosis

Although neural hubs of mentalizing are acknowledged, the brain mechanisms underlying mentalizing deficit, characterizing different neurological conditions, are still a matter of debate. To investigate the neural underpinning of Theory of Mind (ToM) deficit in Multiple Sclerosis (MS), a region of interest (ROI)-based resting-state fMRI study was proposed. 37 MS patients (23 females, mean age=54.08±11.37 years, median Expanded Disability Status Scale=6.00) underwent an MRI and a neuro-psychosocial examination, and were compared with 20 sex-age-education matched healthy subjects. A neuroanatomical ToM model was constructed deriving 11 bilateral ROI, then between and within-functional connectivity (FC) were assessed to test for group differences. Correlation with psychosocial scores was also investigated. Lower ToM performance was registered for MS both in cognitive and affective ToM, significantly associated with processing speed. A disconnection between limbic-paralimbic network and prefrontal execution loops was observed. A trend of aberrant intrinsic connectivity in MS within the anterior cingulate cortex (ACC) was also reported. Finally, a correlation between cognitive ToM and intrinsic FC was detected in ACC and dorsal striatum, belonging to the limbic-paralimbic network, likely explaining the behavioral deficit in MS. The results suggest that aberrant intrinsic and extrinsic connectivity constitutes a crucial neural mechanism underlying ToM deficit in MS.

Prediction of unenhanced lesion evolution in multiple sclerosis using radiomics-based models: a machine learning approach

BACKGROUND

The volume change of multiple sclerosis (MS) lesion is related to its activity and can be used to assess disease progression. Therefore, the purpose of this study was to develop radiomics models for predicting the evolution of unenhanced MS lesions by using different kinds of machine learning algorithms and explore the optimal model.

METHODS

In this prospective observation, 45 follow-up MR images obtained in 36 patients with MS (mean age 32.53±10.91; 23 women, 13 men) were evaluated. The lesions will be defined as interval activity and interval inactivity, respectively, based on the percentage of enlargement or reduction of the lesion >20% in the follow-up MR images. We extracted radiomic features of lesions on FLAIR images, and used recursive feature elimination (RFE), ReliefF algorithm and least absolute shrinkage and selection operator (LASSO) for feature selection, then three classification models including logistic regression, random forest and support vector machine (SVM) were used to build predictive models. The performance of the models were evaluated based on the sensitivity, specificity, precision, negative predictive value (NPV) and receiver operating characteristic curve (ROC) curves analyses.

RESULTS

135 interval inactivity lesions and 110 interval activity lesions were registered in our study. A total of 972 radiomics features were extracted, of which 265 were robust. The consistency and effectiveness of model performance were compared and verified by different combinations of feature selection and machine learning methods in different K-fold cross-validation strategies where K ranges from 5 to 10, thus demonstrating the stability and robustness. SVM classifier with ReliefF algorithm had the best prediction performance with an average accuracy of 0.827, sensitivity of 0.809, specificity of 0.841, precision of 0.921, NPV of 0.948 and the areas under the ROC curves (AUC) of 0.857 (95% CI: 0.812-0.902) in the cohorts.

CONCLUSION

The results demonstrated that the radiomics-based machine learning model has potential in predicting the evolution of MS lesions.

Social Cognition in Multiple Sclerosis: A 3-Year Follow-Up MRI and Behavioral Study

Social cognition (SC) has become a topic of widespread interest in the last decade. SC deficits were described in multiple sclerosis (MS) patients, in association with amygdala lesions, even in those without formal cognitive impairment. In this 3-year follow-up study, we aimed at longitudinally investigating the evolution of SC deficits and amygdala damage in a group of cognitive-normal MS patients, and the association between SC and psychological well-being. After 3 years (T3) from the baseline examination (T0), 26 relapsing-remitting MS patients (RRMS) were retested with a neuropsychological battery and SC tasks (theory of mind, facial emotion recognition, empathy). A SC composite score (SCcomp) was calculated for each patient. Emotional state, fatigue, and quality of life (QoL) were also evaluated. RRMS patients at T3 underwent a 3T-MRI as performed at T0, from which were calculated both volume and cortical lesion volume (CLV) of the amygdalae. Compared to T0, at T3 all RRMS patients were still cognitive-normal and remained stable in their global SC impaired performance. At T0, SCcomp correlated with amygdala CLV (p = 0.002) while, at T3, was more associated with amygdala volume (p = 0.035) rather than amygdala CLV (p = 0.043). SCcomp change T3-T0 correlated with global emotional state (p = 0.043), depression (p = 0.046), anxiety (p = 0.034), fatigue (p = 0.025), and QoL-social functioning (p = 0.033). We showed the longitudinal stability of SC deficits in cognitive-normal RRMS patients, mirroring the amygdala structural damage and the psychological well-being. These results highlight that SC exerts a key role in MS.

Empathy and Theory of Mind in Multiple Sclerosis: A Meta-Analysis

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system. Studies have shown that MS disrupts several social cognitive abilities [including empathy and theory of mind (ToM)]. Overall ToM deficits in MS are well documented, but how the specific ToM subcomponents and empathic capacity are affected remains unclear. For this meta-analysis, we searched PubMed, Web of Science, and Embase from inception to July 2020. Effect sizes were calculated using Hedges g with a random-effects model. Thirty-three studies were included. Relative to healthy controls (HCs), patients with MS were moderately impaired in overall empathy (g = -0.67), overall ToM (g = -74), cognitive ToM (g = -0.72), and the overlapping domains of cognitive empathy/affective ToM (g = -0.79); no group differences were identified for affective empathy (g = -0.19). Compared with HCs, patients with relapsing-remitting MS (RRMS) and progressive MS were impaired in overall empathy, overall ToM, cognitive ToM, and cognitive empathy/affective ToM, without significant RRMS-progressive MS differences in impairment degree. We conducted the first meta-analytic review investigating the empathy and ToM functioning patterns in patients with MS and examined the overlapping and distinct subcomponents of these constructs. The findings suggest differential impairment of the core aspects of social cognitive processing in patients with MS, which may importantly inform the development of structured social cognitive MS interventions.