Increased brain atrophy and lesion load is associated with stronger lower alpha MEG power in multiple sclerosis patients.
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ABSTRACT:
SUBMITTER: Van Schependom J
PROVIDER: S-EPMC8022249 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCigarette smoking has been linked to higher susceptibility and increased risk of progressive multiple sclerosis (MS). The effects of smoking on MRI characteristics of patients with MS have not been evaluated.ObjectivesTo compare the MRI characteristics in cigarette smoker and nonsmoker patients with MS.MethodsWe studied 368 consecutive patients with MS (age 44.0 +/-SD 10.2 years, disease duration 12.1 +/- 9.1 years) comprising 240 never-smokers and 128 (34.8%) ever-smokers (currently active and former smokers). The average number of packs per day smoked (+/-SD) was 0.95 +/- 0.65, and the mean duration of smoking was 18.0 +/- 9.5 years. All patients obtained full clinical and quantitative MRI evaluation. MRI measures included T1, T2, and gadolinium contrast-enhancing (CE) lesion volumes (LVs) and measures of central, global, and tissue-specific brain atrophy. The associations between smoking status and MRI measurements were assessed in regression analysis.ResultsSmoking was associated with increased Expanded Disability Status Scale (EDSS) scores (p = 0.004). The median EDSS scores (interquartile range) in the ever-smoker group and the active-smoker group were both 3.0 (2.0), compared with 2.5 (2.5) in never-smokers. There were adverse associations between smoking and the lesion measures including increased number of CE lesions (p < 0.001), T2 LV (p = 0.009), and T1 LV (p = 0.003). Smoking was associated with decreased brain parenchymal fraction (p = 0.047) and with increases in the lateral ventricle volume (p = 0.001) and third ventricle width (p = 0.023).ConclusionsSmoking is associated with increased blood-brain barrier disruption, higher lesion volumes, and greater atrophy in multiple sclerosis.
| S-EPMC2833095 | biostudies-literature
Project description:The relation between pathological findings and clinical and cognitive decline in Multiple Sclerosis remains unclear. Here, we tested the hypothesis that altered functional connectivity could provide a missing link between structural findings, such as thalamic atrophy and white matter lesion load, and clinical and cognitive dysfunction. Resting-state magnetoencephalography recordings from 21 MS patients and 17 gender- and age matched controls were projected onto atlas-based regions-of-interest using beamforming. Average functional connectivity was computed for each ROI and literature-based resting-state networks using the phase-lag index. Structural measures of whole brain and thalamic atrophy and lesion load were estimated from MRI scans. Global analyses showed lower functional connectivity in the alpha2 band and higher functional connectivity in the beta band in patients with Multiple Sclerosis. Additionally, alpha2 band functional connectivity was lower for the patients in two resting-state networks, namely the default mode network and the visual network. Higher beta band functional connectivity was found in the default mode network and in the temporo-parietal network. Lower alpha2 band functional connectivity in the visual network was related to lower thalamic volumes. Beta band functional connectivity correlated positively with disability scores, most prominently in the default mode network, and correlated negatively with cognitive performance in this network. These findings illustrate the relationship between thalamic atrophy, altered functional connectivity and clinical and cognitive dysfunction in MS, which could serve as a bridge to understand how neurodegeneration is associated with altered functional connectivity and subsequently clinical and cognitive decline.
| S-EPMC3729968 | biostudies-literature
Project description:ObjectiveWe investigated white matter lesion load and global and regional brain volumes in relation to domain-specific cognitive performance in the stroke-free Northern Manhattan Study (NOMAS) population.MethodsWe quantified white matter hyperintensity volume (WMHV), total cerebral volume (TCV), and total lateral ventricular (TLV) volume, as well as hippocampal and cortical gray matter (GM) lobar volumes in a subgroup. We used general linear models to examine MRI markers in relation to domain-specific cognitive performance, adjusting for key covariates.ResultsMRI and cognitive data were available for 1,163 participants (mean age 70 ± 9 years; 60% women; 66% Hispanic, 17% black, 15% white). Across the entire sample, those with greater WMHV had worse processing speed. Those with larger TLV volume did worse on episodic memory, processing speed, and semantic memory tasks, and TCV did not explain domain-specific variability in cognitive performance independent of other measures. Age was an effect modifier, and stratified analysis showed that TCV and WMHV explained variability in some domains above age 70. Smaller hippocampal volume was associated with worse performance across domains, even after adjusting for APOE ε4 and vascular risk factors, whereas smaller frontal lobe volumes were only associated with worse executive function.ConclusionsIn this racially/ethnically diverse, community-based sample, white matter lesion load was inversely associated with cognitive performance, independent of brain atrophy. Lateral ventricular, hippocampal, and lobar GM volumes explained domain-specific variability in cognitive performance.
| S-EPMC4534076 | biostudies-literature
Project description:BackgroundBrain volume loss is an important surrogate marker for assessing disability in MS; however, contribution of gray and white matter to the whole brain volume loss needs further examination in the context of specific MS treatment.ObjectivesTo examine whole and segmented gray, white, thalamic, and corpus callosum volume loss in stable patients receiving natalizumab for 2-5 years.MethodsThis was a retrospective study of 20 patients undergoing treatment with natalizumab for 24-68 months. Whole brain volume loss was determined with SIENA. Gray and white matter segmentation was done using FAST. Thalamic and corpus callosum volumes were determined using Freesurfer. T1 relaxation values of chronic hypointense lesions (black holes) were determined using a quantitative, in-house developed method to assess lesion evolution.ResultsOver a mean of 36.6 months, median percent brain volume change (PBVC) was -2.0% (IQR 0.99-2.99). There was decline in gray (p = 0.001) but not white matter (p = 0.6), and thalamic (p = 0.01) but not corpus callosum volume (p = 0.09). Gray matter loss correlated with PBVC (Spearman's r = 0.64, p = 0.003) but not white matter (Spearman's r = 0.42, p = 0.07). Age significantly influenced whole brain volume loss (p = 0.010, multivariate regression), but disease duration and baseline T2 lesion volume did not. There was no change in T1 relaxation values of lesions or T2 lesion volume over time. All patients remained clinically stable.ConclusionsThese results demonstrate that brain volume loss in MS is primarily driven by gray matter changes and may be independent of clinically effective treatment.
| S-EPMC6303064 | biostudies-literature
Project description:Thalamic atrophy is known to be one of the most important predictors for clinical dysfunction in multiple sclerosis (MS). As the thalamus is highly connected to many cortical areas, this suggests that thalamic atrophy is associated with disruption of cortical functional networks. We investigated this thalamo-cortical system to explain the presence of physical and cognitive problems in MS. Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) were performed in 86 MS patients and 21 healthy subjects. We computed cortical functional networks for fMRI and MEG by respectively the Pearson's correlation coefficient and the phase lag index using the same automated anatomical labeling atlas for both modalities. Thalamo-cortical functional connectivity was only estimated using fMRI. We computed conventional network metrics such as clustering coefficient and path length and analyzed the minimum spanning tree (MST), a subnetwork and backbone of the original network. MS patients showed reduced thalamic volumes and increased thalamo-cortical connectivity. MEG cortical functional networks showed a lower level of integration in MS in terms of the MST, whereas fMRI cortical networks did not differ between groups. Lower integration of MEG cortical functional networks was both related to thalamic atrophy as well as to increased thalamo-cortical functional connectivity in fMRI and to worse cognitive and clinical status. This study demonstrated for the first time that thalamic atrophy is associated with global disruption of cortical functional networks in MS and this global disruption of network activity was related to worse cognitive and clinical function in MS. Hum Brain Mapp 36:603-618, 2015. © 2014 Wiley Periodicals, Inc.
| S-EPMC6869443 | biostudies-literature
Project description:Brain structure and many brain functions are known to be genetically controlled, but direct links between neuroimaging measures and their underlying cellular-level determinants remain largely undiscovered. Here, we adopt a novel computational method for examining potential similarities in high-dimensional brain imaging data between siblings. We examine oscillatory brain activity measured with magnetoencephalography (MEG) in 201 healthy siblings and apply Bayesian reduced-rank regression to extract a low-dimensional representation of familial features in the participants' spectral power structure. Our results show that the structure of the overall spectral power at 1-90 Hz is a highly conspicuous feature that not only relates siblings to each other but also has very high consistency within participants' own data, irrespective of the exact experimental state of the participant. The analysis is extended by seeking genetic associations for low-dimensional descriptions of the oscillatory brain activity. The observed variability in the MEG spectral power structure was associated with SDK1 (sidekick cell adhesion molecule 1) and suggestively with several other genes that function, for example, in brain development. The current results highlight the potential of sophisticated computational methods in combining molecular and neuroimaging levels for exploring brain functions, even for high-dimensional data limited to a few hundred participants.
| S-EPMC6590382 | biostudies-literature
Project description:Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study.
| S-EPMC8148377 | biostudies-literature
Project description:BackgroundB cells and humoral immune responses play an important role in the pathogenesis and diagnosis of multiple sclerosis (MS). A characteristic finding in patients with MS is a polyspecific intrathecal B cell response against neurotropic viruses, specifically against measles virus, rubella virus, and varicella zoster virus, also known as an MRZ reaction (MRZR). Here, we correlated from the routine clinical diagnostics individual IgG antibody indices (AIs) of MRZR with magnetic resonance imaging (MRI) findings in patients with first MS diagnosis.Methods/resultsMRZR was determined in 68 patients with a clinically isolated syndrome (CIS) or early relapsing-remitting MS (RRMS). Absolute AI values for measles virus, rubella virus, and varicella zoster virus were correlated with T2 lesion load and gadolinium enhancing lesions on cerebral MRI (cMRI) and cMRI combined with spinal MRI (sMRI). Measles virus AI correlated significantly with T2 lesion load on cMRI (p = 0.0312, Mann-Whitney U test) and the sum of lesions on cMRI and sMRI (p = 0.0413). Varicella zoster virus AI also showed a correlation with T2 lesion load on cMRI but did not reach statistical significance (p = 0.2893).ConclusionThe results confirm MRZR as part of the polyspecific immune reaction in MS with possible prognostic impact on MRI and clinical parameters. Furthermore, the data indicate that intrathecal measles virus IgG production correlates with disease activity on cMRI and sMRI in patients with early MS.
| S-EPMC3261854 | biostudies-literature
Project description:Amyotrophic lateral sclerosis (ALS) is an age-related neurodegenerative disease characterized by selective loss of motor neurons in the brainstem and spinal cord. Several genetic factors have been associated to ALS, ranging from causal genes and potential risk factors to disease modifiers. Here, we applied an exon-centric aCGH method to investigate, in sporadic ALS patients, the load of CNVs in 131 genes previously associated to ALS. Our approach revealed that CNV load, defined as the total number of CNVs or their length, was significantly higher in ALS cases.
2024-08-28 | GSE239611 | GEO
Project description:IntroductionResting-state oscillatory activity has been extensively studied across a wide array of disorders. Establishing which spectrally- and spatially-specific oscillatory components exhibit test-retest reliability is essential to move the field forward. While studies have shown short-term reliability of MEG resting-state activity, no studies have examined test-retest reliability across an extended period of time to establish the stability of these signals, which is critical for reproducibility.MethodsWe examined 18 healthy adults age 23 - 61 who completed three visits across three years. For each visit, participants completed both a resting state MEG and structural MRI scan. MEG data were source imaged, and the cortical power in canonical frequency bands (delta, theta, alpha, beta, low gamma, high gamma) was computed. Intra-class correlation coefficients (ICC) were then calculated across the cortex for each frequency band.ResultsOver three years, power in the alpha and beta bands displayed the highest reliability estimates, while gamma showed the lowest estimates of three-year reliability. Spatially, delta, alpha, and beta all showed the highest degrees of reliability in the parietal cortex. Interestingly, the peak signal for each of these frequency bands was located outside of the parietal cortex, suggesting that reliability estimates were not solely dependent on the signal-to-noise ratio.ConclusionOscillatory resting-state power in parietal delta, posterior beta, and alpha across most of the cortex are reliable across three years and future MEEG studies may focus on these measures for the development of specific markers.
| S-EPMC8590732 | biostudies-literature