Micro-diffusely abnormal white matter: An early multiple sclerosis lesion phase with intensified myelin blistering.

OBJECTIVE: Multiple sclerosis (MS) is a chronic central nervous system disease whose white matter lesion origin remains debated. Recently, we reported subtle changes in the MS normal appearing white matter (NAWM), presenting with an increase in myelin blisters and myelin protein citrullination, which may recapitulate some of the prodromal degenerative processes involved in MS pathogenesis. Here, to clarify the relevance of these changes for subsequent MS myelin degeneration we explored their prevalence in WM regions characterized by subtly reduced myelination (dubbed as micro-diffusely abnormal white matter, mDAWM). METHODS: We used an in-depth (immuno)histochemistry approach in 27 MS donors with histological presence of mDAWM and 5 controls. An antibody panel against degenerative markers was combined and the presence of myelin/axonal aberrations was analyzed and compared with the NAWM from the same cases/slices/regions. RESULTS: mDAWM-defined areas exhibit ill-defined borders, no signs of Wallerian degeneration, and they associate with visible veins. Remarkably, such areas present with augmented myelin blister frequency, enhanced prevalence of polar myelin phospholipids, citrullination, and degradation of myelin basic protein (MBP) when compared with the NAWM. Furthermore, enhanced reactivity of microglia/macrophages against citrullinated MBP was also observed in this tissue. INTERPRETATION: We report a new histologically defined early phase in MS lesion formation, namely mDAWM, which lacks signs of Wallerian pathology. These results support the prelesional nature of the mDAWM. We conceptualize that evolution to pathologically evident lesions comprises the previously documented imbalance of axo-myelinic units (myelin blistering) leading to their degeneration and immune system activation by released myelin components.

Evolution and advancements in genomics and epigenomics in OA research: How far we have come.

OBJECTIVE: Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease. DESIGN: In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients. RESULTS: Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease. CONCLUSIONS: Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

Longitudinal fibre-specific white matter damage predicts cognitive decline in multiple sclerosis.

During the course of multiple sclerosis, many patients experience cognitive deficits which are not simply driven by lesion number or location. By considering the full complexity of white matter structure at macro- and microstructural levels, our understanding of cognitive impairment in multiple sclerosis may increase substantially. Accordingly, this study aimed to investigate specific patterns of white matter degeneration, the evolution over time, the manifestation across different stages of the disease and their role in cognitive impairment using a novel fixel-based approach. Neuropsychological test scores and MRI scans including 30-direction diffusion-weighted images were collected from 327 multiple sclerosis patients (mean age = 48.34 years, 221 female) and 95 healthy controls (mean age = 45.70 years, 55 female). Of those, 233 patients and 61 healthy controls had similar follow-up assessments 5 years after. Patients scoring 1.5 or 2 standard deviations below healthy controls on at least two out of seven cognitive domains (from the Brief Repeatable Battery of Neuropsychological Tests, BRB-N) were classified as mildly cognitively impaired or cognitively impaired, respectively, or otherwise cognitively preserved. Fixel-based analysis of diffusion data was used to calculate fibre-specific measures (fibre density, reflecting microstructural diffuse axonal damage; fibre cross-section, reflecting macrostructural tract atrophy) within atlas-based white matter tracts at each visit. At baseline, all fixel-based measures were significantly worse in multiple sclerosis compared with healthy controls (P < 0.05). For both fibre density and fibre cross-section, a similar pattern was observed, with secondary progressive multiple sclerosis patients having the most severe damage, followed by primary progressive and relapsing-remitting multiple sclerosis. Similarly, damage was least severe in cognitively preserved (n = 177), more severe in mildly cognitively impaired (n = 63) and worst in cognitively impaired (n = 87; P < 0.05). Microstructural damage was most pronounced in the cingulum, while macrostructural alterations were most pronounced in the corticospinal tract, cingulum and superior longitudinal fasciculus. Over time, white matter alterations worsened most severely in progressive multiple sclerosis (P < 0.05), with white matter atrophy progression mainly seen in the corticospinal tract and microstructural axonal damage worsening in cingulum and superior longitudinal fasciculus. Cognitive decline at follow-up could be predicted by baseline fixel-based measures (R2 = 0.45, P < 0.001). Fixel-based approaches are sensitive to white matter degeneration patterns in multiple sclerosis and can have strong predictive value for cognitive impairment. Longitudinal deterioration was most marked in progressive multiple sclerosis, indicating that degeneration in white matter remains important to characterize further in this phenotype.

Isolated cognitive impairment in people with multiple sclerosis: frequency, MRI patterns and its development over time.

OBJECTIVES: To study the frequency of isolated (i.e., single-domain) cognitive impairments, domain specific MRI correlates, and its longitudinal development in people with multiple sclerosis (PwMS). METHODS: 348 PwMS (mean age 48 ± 11 years, 67% female, 244RR/52SP/38PP) underwent neuropsychological testing (extended BRB-N) at baseline and at five-year follow-up. At baseline, structural MRI was acquired. Isolated cognitive impairment was defined as a Z-score of at least 1.5 SD below normative data in one domain only (processing speed, memory, executive functioning/working memory, and attention). Multi-domain cognitive impairment was defined as being affected in ≥ 2 domains, and cognitively preserved otherwise. For PwMS with isolated cognitive impairment, MRI correlates were explored using linear regression. Development of isolated cognitive impairment over time was evaluated based on reliable change index. RESULTS: At baseline, 108 (31%) PwMS displayed isolated cognitive impairment, 148 (43%) PwMS displayed multi-domain cognitive impairment. Most PwMS with isolated cognitive impairment were impaired on executive functioning/working memory (EF/WM; N = 37), followed by processing speed (IPS; N = 25), memory (N = 23), and attention (N = 23). Isolated IPS impairment was explained by a model of cortical volume and fractional anisotropy (adj. R2 = 0.539, p < 0.001); memory by a model with cortical volume and hippocampal volume (adj. R2 = 0.493, p = 0.002); EF/WM and attention were not associated with any MRI measure. At follow-up, cognitive decline was present in 11/16 (69%) of PwMS with isolated IPS impairment at baseline. This percentage varied between 18 and 31% of PwMS with isolated cognitive impairment in domains other than IPS at baseline. CONCLUSION: Isolated cognitive impairment is frequently present in PwMS and can serve as a proxy for further decline, particularly when it concerns processing speed. Cortical and deep grey matter atrophy seem to play a pivotal role in isolated cognitive impairment. Timely detection and patient-tailored intervention, predominantly for IPS, may help to postpone further cognitive decline.

Elevated secretion of pro-collagen I-alpha and vascular endothelial growth factor as biomarkers of acetabular labrum degeneration and calcification in hip osteoarthritis: An explant study.

Background: Hip osteoarthritis (OA) involves structural degeneration of different joint compartments, including femoral head cartilage, periarticular ligaments and the acetabular labrum. However, the molecular mechanisms underlying labrum degeneration in hip OA remain poorly understood. Aim: To assess secretion of putative biomarkers for OA from explanted human labrum tissues under basal and inflammatory conditions and to determine whether these could differentiate between OA and calcification status compared to fracture controls. Methods: Intact labrum specimens were collected from patients undergoing joint arthroplasty for primary hip OA (n â€‹= â€‹15, mean age 70) or non-OA femoral neck fracture (n â€‹= â€‹5, mean age 64). Tissues were dissected in equal-sized samples and explanted for one week. To mimic activation of inflammatory signaling by endogenous damage-associated molecular patterns (DAMP) tissue were stimulated with a toll-like receptor 4 (TLR4) agonist (1 â€‹µg/mL LPS). The involvement of transforming growth factor-beta (TGF-beta) signaling was evaluated by treatment with a TGF-beta type 1 receptor inhibitor (10 â€‹µM SB-505124). Secretion of aggrecan (ACAN), pro-collagen-I alpha (Pro-Col-Iα), cartilage oligomeric matrix protein (COMP), interleukin-6 (IL-6) and vascular endothelial growth factor (VEGF) was assessed by enzyme-linked immunosorbent assay (ELISA). Labrum calcification was evaluated by 3D whole mount fluorescent microscopy of ethyl cinnamate-based optically cleared tissues stained with Alcian blue/Alizarin red. Results: Whole mount microscopy revealed non-OA fracture controls were non-calcified, whereas six OA labra (40%) were partially calcified or ossified. Basal secretion of Pro-Col-Iα and VEGF was increased four-fold in OA versus non-OA labra. Pro-Col-Iα levels were correlated with those of VEGF (r â€‹= â€‹0.65) and COMP (r â€‹= â€‹0.54). Stimulation of DAMP signaling through TLR4 affected secretion of IL-6, VEGF, COMP and Pro-Col-Iα, with distinct responses between non-OA and OA tissues. Inhibition of TGF-beta signaling specifically reduced elevated secretion of Pro-Col- Iα and VEGF in calcified OA labrum. Conclusions: Secretion of the putative OA biomarkers Pro-Col-Iα and VEGF is elevated in degenerated human acetabular labrum and may serve as indicators of OA and calcification status. Secretion of both factors was partially regulated by TGF-beta signaling in calcified OA labrum tissues.The Translational potential of this article:Our findings suggest that a biomarker panel consisting of Pro-Col-Iα/VEGF/COMP may be valuable for assessing subradiographic labrum degeneration and calcification in hip OA. Targeting TGF-beta signaling may offer a means to reduce vascular invasion and fibrosis in acetabular labrum tissue.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies.

OBJECTIVE: Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades. DESIGN: We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease. RESULTS: Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues. CONCLUSIONS: Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

The Impact of Interventional Weight Loss on Bone Marrow Adipose Tissue in People Living with Obesity and Its Connection to Bone Metabolism.

This review focuses on providing physicians with insights into the complex relationship between bone marrow adipose tissue (BMAT) and bone health, in the context of weight loss through caloric restriction or metabolic and bariatric surgery (MBS), in people living with obesity (PwO). We summarize the complex relationship between BMAT and bone health, provide an overview of noninvasive imaging techniques to quantify human BMAT, and discuss clinical studies measuring BMAT in PwO before and after weight loss. The relationship between BMAT and bone is subject to variations based on factors such as age, sex, menopausal status, skeletal sites, nutritional status, and metabolic conditions. The Bone Marrow Adiposity Society (BMAS) recommends standardizing imaging protocols to increase comparability across studies and sites, they have identified both water-fat imaging (WFI) and spectroscopy (1H-MRS) as accepted standards for in vivo quantification of BMAT. Clinical studies measuring BMAT in PwO are limited and have shown contradictory results. However, BMAT tends to be higher in patients with the highest visceral adiposity, and inverse associations between BMAT and bone mineral density (BMD) have been consistently found in PwO. Furthermore, BMAT levels tend to decrease after caloric restriction-induced weight loss. Although weight loss was associated with overall fat loss, a reduction in BMAT did not always follow the changes in fat volume in other tissues. The effects of MBS on BMAT are not consistent among the studies, which is at least partly related to the differences in the study population, skeletal site, and duration of the follow-up. Overall, gastric bypass appears to decrease BMAT, particularly in patients with diabetes and postmenopausal women, whereas sleeve gastrectomy appears to increase BMAT. More research is necessary to evaluate changes in BMAT and its connection to bone metabolism, either in PwO or in cases of weight loss through caloric restriction or MBS, to better understand the role of BMAT in this context and determine the local or systemic factors involved.

Multimodal multilayer network centrality relates to executive functioning.

Executive functioning (EF) is a higher order cognitive process that is thought to depend on a network organization facilitating integration across subnetworks, in the context of which the central role of the fronto-parietal network (FPN) has been described across imaging and neurophysiological modalities. However, the potentially complementary unimodal information on the relevance of the FPN for EF has not yet been integrated. We employ a multilayer framework to allow for integration of different modalities into one 'network of networks.' We used diffusion MRI, resting-state functional MRI, MEG, and neuropsychological data obtained from 33 healthy adults to construct modality-specific single-layer networks as well as a single multilayer network per participant. We computed single-layer and multilayer eigenvector centrality of the FPN as a measure of integration in this network and examined their associations with EF. We found that higher multilayer FPN centrality, but not single-layer FPN centrality, was related to better EF. We did not find a statistically significant change in explained variance in EF when using the multilayer approach as compared to the single-layer measures. Overall, our results show the importance of FPN integration for EF and underline the promise of the multilayer framework toward better understanding cognitive functioning.

Cognitive performance in multiple sclerosis: what is the role of the gamma-aminobutyric acid system?

Cognitive impairment occurs in 40-65% of persons with multiple sclerosis and may be related to alterations in glutamatergic and GABAergic neurotransmission. Therefore, the aim of this study was to determine how glutamatergic and GABAergic changes relate to cognitive functioning in multiple sclerosis in vivo. Sixty persons with multiple sclerosis (mean age 45.5 ± 9.6 years, 48 females, 51 relapsing-remitting multiple sclerosis) and 22 age-matched healthy controls (45.6 ± 22.0 years, 17 females) underwent neuropsychological testing and MRI. Persons with multiple sclerosis were classified as cognitively impaired when scoring at least 1.5 standard deviations below normative scores on ≥30% of tests. Glutamate and GABA concentrations were determined in the right hippocampus and bilateral thalamus using magnetic resonance spectroscopy. GABA-receptor density was assessed using quantitative [11C]flumazenil positron emission tomography in a subset of participants. Positron emission tomography outcome measures were the influx rate constant (a measure predominantly reflecting perfusion) and volume of distribution, which is a measure of GABA-receptor density. Twenty persons with multiple sclerosis (33%) fulfilled the criteria for cognitive impairment. No differences were observed in glutamate or GABA concentrations between persons with multiple sclerosis and healthy controls, or between cognitively preserved, impaired and healthy control groups. Twenty-two persons with multiple sclerosis (12 cognitively preserved and 10 impaired) and 10 healthy controls successfully underwent [11C]flumazenil positron emission tomography. Persons with multiple sclerosis showed a lower influx rate constant in the thalamus, indicating lower perfusion. For the volume of distribution, persons with multiple sclerosis showed higher values than controls in deep grey matter, reflecting increased GABA-receptor density. When comparing cognitively impaired and preserved patients to controls, the preserved group showed a significantly higher volume of distribution in cortical and deep grey matter and hippocampus. Positive correlations were observed between both positron emission tomography measures and information processing speed in the multiple sclerosis group only. Whereas concentrations of glutamate and GABA did not differ between multiple sclerosis and control nor between cognitively impaired, preserved and control groups, increased GABA-receptor density was observed in preserved persons with multiple sclerosis that was not seen in cognitively impaired patients. In addition, GABA-receptor density correlated to cognition, in particular with information processing speed. This could indicate that GABA-receptor density is upregulated in the cognitively preserved phase of multiple sclerosis as a means to regulate neurotransmission and potentially preserve cognitive functioning.

The longitudinal relation between executive functioning and multilayer network topology in glioma patients.

Many patients with glioma, primary brain tumors, suffer from poorly understood executive functioning deficits before and/or after tumor resection. We aimed to test whether frontoparietal network centrality of multilayer networks, allowing for integration across multiple frequencies, relates to and predicts executive functioning in glioma. Patients with glioma (n = 37) underwent resting-state magnetoencephalography and neuropsychological tests assessing word fluency, inhibition, and set shifting before (T1) and one year after tumor resection (T2). We constructed binary multilayer networks comprising six layers, with each layer representing frequency-specific functional connectivity between source-localized time series of 78 cortical regions. Average frontoparietal network multilayer eigenvector centrality, a measure for network integration, was calculated at both time points. Regression analyses were used to investigate associations with executive functioning. At T1, lower multilayer integration (p = 0.017) and epilepsy (p = 0.006) associated with poorer set shifting (adj. R2 = 0.269). Decreasing multilayer integration (p = 0.022) and not undergoing chemotherapy at T2 (p = 0.004) related to deteriorating set shifting over time (adj. R2 = 0.283). No significant associations were found for word fluency or inhibition, nor did T1 multilayer integration predict changes in executive functioning. As expected, our results establish multilayer integration of the frontoparietal network as a cross-sectional and longitudinal correlate of executive functioning in glioma patients. However, multilayer integration did not predict postoperative changes in executive functioning, which together with the fact that this correlate is also found in health and other diseases, limits its specific clinical relevance in glioma.

A multimodal marker for cognitive functioning in multiple sclerosis: the role of NfL, GFAP and conventional MRI in predicting cognitive functioning in a prospective clinical cohort.

BACKGROUND: Cognitive impairment in people with MS (PwMS) has primarily been investigated using conventional imaging markers or fluid biomarkers of neurodegeneration separately. However, the single use of these markers do only partially explain the large heterogeneity found in PwMS. OBJECTIVE: To investigate the use of multimodal (bio)markers: i.e., serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and conventional imaging markers in predicting cognitive functioning in PwMS. METHODS: Eighty-two PwMS (56 females, disease duration = 14 ± 9 years) underwent neuropsychological and neurological examination, structural magnetic resonance imaging, blood sampling and lumbar puncture. PwMS were classified as cognitively impaired (CI) if scoring ≥ 1.5SD below normative scores on ≥ 20% of test scores. Otherwise, PwMS were defined as cognitively preserved (CP). Association between fluid and imaging (bio)markers were investigated, as well as binary logistics regression to predict cognitive status. Finally, a multimodal marker was calculated using statistically important predictors of cognitive status. RESULTS: Only higher NfL levels (in serum and CSF) correlated with worse processing speed (r = - 0.286, p = 0.012 and r = - 0.364, p = 0.007, respectively). sNfL added unique variance in the prediction of cognitive status on top of grey matter volume (NGMV), p = 0.002). A multimodal marker of NGMV and sNfL yielded most promising results in predicting cognitive status (sensitivity = 85%, specificity = 58%). CONCLUSION: Fluid and imaging (bio)markers reflect different aspects of neurodegeneration and cannot be used interchangeably as markers for cognitive functioning in PwMS. The use of a multimodal marker, i.e., the combination of grey matter volume and sNfL, seems most promising for detecting cognitive deficits in MS.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection.

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Sensorimotor network dynamics predict decline in upper and lower limb function in people with multiple sclerosis.

BACKGROUND: Upper and lower limb disabilities are hypothesized to have partially independent underlying (network) disturbances in multiple sclerosis (MS). OBJECTIVE: This study investigated functional network predictors and longitudinal network changes related to upper and lower limb progression in MS. METHODS: Two-hundred fourteen MS patients and 58 controls underwent functional magnetic resonance imaging (fMRI), dexterity (9-Hole Peg Test) and mobility (Timed 25-Foot Walk) measurements (baseline and 5 years). Patients were stratified into progressors (>20% decline) or non-progressors. Functional network efficiency was calculated using static (over entire scan) and dynamic (fluctuations during scan) approaches. Baseline measurements were used to predict progression; significant predictors were explored over time. RESULTS: In both limbs, progression was related to supplementary motor area and caudate efficiency (dynamic and static, respectively). Upper limb progression showed additional specific predictors; cortical grey matter volume, putamen static efficiency and posterior associative sensory (PAS) cortex, putamen, primary somatosensory cortex and thalamus dynamic efficiency. Additional lower limb predictors included motor network grey matter volume, caudate (dynamic) and PAS (static). Only the caudate showed a decline in efficiency over time in one group (non-progressors). CONCLUSION: Disability progression can be predicted using sensorimotor network measures. Upper and lower limb progression showed unique predictors, possibly indicating different network disturbances underlying these types of progression in MS.

Inhibitory synaptic loss drives network changes in multiple sclerosis: An ex vivo to in silico translational study.

BACKGROUND: Synaptic and neuronal loss contribute to network dysfunction and disability in multiple sclerosis (MS). However, it is unknown whether excitatory or inhibitory synapses and neurons are more vulnerable and how their losses impact network functioning. OBJECTIVE: To quantify excitatory and inhibitory synapses and neurons and to investigate how synaptic loss affects network functioning through computational modeling. METHODS: Using immunofluorescent staining and confocal microscopy, densities of glutamatergic and GABAergic synapses and neurons were compared between post-mortem MS and non-neurological control cases. Then, a corticothalamic biophysical model was employed to study how MS-induced excitatory and inhibitory synaptic loss affect network functioning. RESULTS: In layer VI of normal-appearing MS cortex, excitatory and inhibitory synaptic densities were significantly lower than controls (reductions up to 14.9%), but demyelinated cortex showed larger losses of inhibitory synapses (29%). In our computational model, reducing inhibitory synapses impacted the network most, leading to a disinhibitory increase in neuronal activity and connectivity. CONCLUSION: In MS, excitatory and inhibitory synaptic losses were observed, predominantly for inhibitory synapses in demyelinated cortex. Inhibitory synaptic loss affected network functioning most, leading to increased neuronal activity and connectivity. As network disinhibition relates to cognitive impairment, inhibitory synaptic loss seems particularly relevant in MS.

Regional healthy brain activity, glioma occurrence and symptomatology.

It is unclear why exactly gliomas show preferential occurrence in certain brain areas. Increased spiking activity around gliomas leads to faster tumour growth in animal models, while higher non-invasively measured brain activity is related to shorter survival in patients. However, it is unknown how regional intrinsic brain activity, as measured in healthy controls, relates to glioma occurrence. We first investigated whether gliomas occur more frequently in regions with intrinsically higher brain activity. Second, we explored whether intrinsic cortical activity at individual patients' tumour locations relates to tumour and patient characteristics. Across three cross-sectional cohorts, 413 patients were included. Individual tumour masks were created. Intrinsic regional brain activity was assessed through resting-state magnetoencephalography acquired in healthy controls and source-localized to 210 cortical brain regions. Brain activity was operationalized as: (i) broadband power; and (ii) offset of the aperiodic component of the power spectrum, which both reflect neuronal spiking of the underlying neuronal population. We additionally assessed (iii) the slope of the aperiodic component of the power spectrum, which is thought to reflect the neuronal excitation/inhibition ratio. First, correlation coefficients were calculated between group-level regional glioma occurrence, as obtained by concatenating tumour masks across patients, and group-averaged regional intrinsic brain activity. Second, intrinsic brain activity at specific tumour locations was calculated by overlaying patients' individual tumour masks with regional intrinsic brain activity of the controls and was associated with tumour and patient characteristics. As proposed, glioma preferentially occurred in brain regions characterized by higher intrinsic brain activity in controls as reflected by higher offset. Second, intrinsic brain activity at patients' individual tumour locations differed according to glioma subtype and performance status: the most malignant isocitrate dehydrogenase-wild-type glioblastoma patients had the lowest excitation/inhibition ratio at their individual tumour locations as compared to isocitrate dehydrogenase-mutant, 1p/19q-codeleted glioma patients, while a lower excitation/inhibition ratio related to poorer Karnofsky Performance Status, particularly in codeleted glioma patients. In conclusion, gliomas more frequently occur in cortical brain regions with intrinsically higher activity levels, suggesting that more active regions are more vulnerable to glioma development. Moreover, indices of healthy, intrinsic excitation/inhibition ratio at patients' individual tumour locations may capture both tumour biology and patients' performance status. These findings contribute to our understanding of the complex and bidirectional relationship between normal brain functioning and glioma growth, which is at the core of the relatively new field of 'cancer neuroscience'.

Investigating Functional Network Abnormalities and Associations With Disability in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: In multiple sclerosis (MS), functional networks undergo continuous reconfiguration and topography changes over the disease course. In this study, we aimed to investigate functional network to pography abnormalities in MS and their association with disease phenotype, clinical and cognitive disability, and structural MRI damage. METHODS: This is a multicenter cross-sectional study. Enrolled participants performed MRI and neurologic and neuropsychological assessment. Network topography was assessed on resting state fMRI data using degree centrality, which counted the number of functional connections of each gray matter voxel with the rest of the brain. SPM12 age-adjusted, sex-adjusted, scanner-adjusted, framewise displacement, and gray matter-volume adjusted analysis of variance and multivariable regressions were used (p < 0.05, family-wise error [FWE] corrected). RESULTS: We enrolled 971 patients with MS (624 female patients; mean age = 43.1 ± 11.8 years; 47 clinically isolated syndrome [CIS], 704 relapsing-remitting MS [RRMS], 145 secondary progressive MS [SPMS], and 75 primary progressive MS [PPMS]) and 330 healthy controls (186 female patients; mean age = 41.2 ± 13.3 years). Patients with MS showed reduced centrality in the salience and sensorimotor networks as well as increased centrality in the default-mode network vs controls (p < 0.05, FWE). Abnormal centrality was already found in CIS vs controls and in RRMS vs CIS (p < 0.001, uncorrected); however, it became more severe in SPMS vs RRMS (p < 0.05, FWE) and in PPMS vs controls (p < 0.001, uncorrected). Cognitively impaired patients (39%) showed reduced centrality in the salience network and increased centrality in the default-mode network vs cognitively preserved patients (p < 0.001, conjunction analysis). More severe disability correlated with increased centrality in the right precuneus (r = 0.18, p < 0.05 FWE). Higher T2 lesion volume and brain/gray matter atrophy were associated with reduced centrality in the bilateral insula and cerebellum (r = range -0.17/-0.15 and 0.26/0.28, respectively; p < 0.05, FWE). Higher brain/gray matter atrophy was also associated with increased centrality in the default-mode network (r = range -0.31/-0.22, p < 0.05, FWE). DISCUSSION: Patients with MS presented with reduced centrality in the salience and primary sensorimotor networks and increased centrality in the default-mode network. Centrality abnormalities were specific for different disease phenotypes and associated with clinical and cognitive disability, hence suggesting that voxel-wise centrality analysis may reflect pathologic substrates underpinning disability accrual.

Polg mtDNA mutator mice reveal limited involvement of vertebral bone loss in premature aging-related thoracolumbar hyperkyphosis.

Background: Age-related hyperkyphosis is multifactorial and involves alterations of vertebral bone, intervertebral discs (IVD) and paraspinal muscles. The relative contribution of these tissues remains unclear. Here, we compared differences in vertebral bone microarchitecture and IVD thickness between prematurely aging mice with spinal hyperkyphosis and wild type littermates. Methods: Thoracolumbar vertebral columns were dissected from homozygous Polg D257A and age-matched wild type littermates. Micro-computed tomography was performed to quantify cortical and trabecular bone parameters at anterior and posterior portions of T8-L4 vertebrae. In addition, vertebral shape, transaxial facet joint orientation and IVD thickness were quantified. Differences in anterior/posterior ratios between genotypes were compared by Student's t-test and association between vertebral bone and IVD parameters was investigated using Pearson correlation analysis. Results: Hyperkyphotic homozygous mice displayed generalized osteopenia that was more pronounced at the posterior compared with anterior portion of thoracolumbar vertebrae. An increase in the anterior/posterior ratio of trabecular bone parameters was revealed at the thoracolumbar junction (T13-L1). Polg D257A displayed diffuse loss of cortical bone thickness, yet anterior/posterior ratios were unchanged. Despite generalized and regional bone loss, vertebral shape was unaffected. PolG D257A mice showed a 10-20 % reduction of IVD thickness at both thoracic and lumbar levels, with only minimal histopathological changes. IVD thickness was negatively correlated with anterior/posterior ratios of trabecular bone parameters, as well as with more coronally oriented facet joints, but negatively correlated with the anterior/posterior ratio of cortical bone thickness. Conclusions: Aging-induced regional changes of vertebral trabecular and cortical bone did not lead to altered vertebral shape in Polg D257A mice but may indirectly cause hyperkyphosis through reduction of IVD thickness. These findings suggest a limited role for aging-induced bone loss in spinal hyperkyphosis and warrants further research on the involvement of paraspinal muscle degeneration.

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

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.

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is a co mplex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods. NEW METHOD: We originated novel texture analysis and machine learning approaches for classifying MS pathology subtypes as compared with 2 common advanced MRI measures: magnetization transfer ratio (MTR) and fractional anisotropy (FA). Texture analysis used an optimized grey level co-occurrence matrix method with histology-informed 7T T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) from 15 MS and 12 control brain specimens. DTI analysis took an innovative approach that assessed the texture across diffusion directions upsampled from 30 to 90. Tissue types included de- and re-myelinated lesions and normal-appearing areas in both grey and white matter, and diffusely abnormal white matter. Data analyses were stepwise, including: (1) group-wise classification using random forest algorithms based on all or individual imaging parameters; (2) parameter importance ranking; and (3) pairwise analysis using top-ranked features. RESULTS: Texture analysis performed better than MTR and FA, with T2 texture performed the best. T2 texture measures ranked the highest in classifying most grey and white matter tissue types, including de- versus re-myelinated lesions and among grey matter lesion subtypes (accuracy=0.86-0.59; kappa=0.60-0.41). Diffusion texture best differentiated normal appearing and control white matter. COMPARISON WITH EXISTING METHODS: There is no established method in imaging for differentiating MS pathology subtypes. In combined texture analysis and machine learning studies, there is also no direct evidence comparing conventional with advanced MRI measures for assessing MS pathology. Further, this study is unique in conducting innovative texture analysis with DTI following data-augmentation using robust methods. CONCLUSIONS: T2 and diffusion MRI texture analysis integrated with machine learning may be valuable approaches for characterizing MS pathology.

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. Receiving operating curve 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 stronger 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 area under the curve (AUC) = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095). Long-range structure-function coupling was stronger in CI MS compared to HCs, but more research is needed to further explore this measure as biomarkers in MS.