Neurology Neuroimmunology & Neuroinflammation

Multiple sclerosis (MS), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and neuromyelitis optica spectrum disorder (NMOSD) are immune-mediated inflammatory disorders of the central nervous system (CNS). The temporal relationship between disease-specific autoantibodies and biomarkers of CNS injury before diagnosis remains unclear and is relevant for understanding early pathobiology. Here, we conducted a multicentre retrospective longitudinal case-control study using prediagnostic plasma from 362 individuals who later developed MS, 145 who developed MOGAD, and 60 who developed NMOSD. Plasma IgG levels against CNS antigens, MOG, and AQP4, as well as neurofilament light chain (pNfL), were quantified, and temporal relationships between immune activation, neuroaxonal injury, and clinical disease onset were modelled using linear mixed-effects models and survival analyses. In MS, EBNA-1-specific and CNS-cross-reactive IgG were elevated up to 77.8 months before diagnosis, preceding pNfL increases by 44.9 months. In NMOSD, AQP4-IgG seroconversion occurred 32.5 months before diagnosis and preceded pNfL elevations by 40.4 months. In MOGAD, pNfL elevations preceded MOG-IgG seroconversion by 11.2 months. Thus, in MS and NMOSD, humoral autoimmunity precedes detectable CNS injury, whereas in MOGAD, neuroaxonal injury occurs before circulating MOG-IgG. These distinct temporal patterns suggest differing early immunopathological trajectories and may provide a framework for future studies of early disease biology and biomarker-guided risk stratification.

BackgroundExtracellular matrix (ECM) remodeling is increasingly recognized as an important component of neuroinflammatory pathology in multiple sclerosis (MS), yet the mechanisms by which CNS cells sense and respond to alterations in their mechanical environment and the spatial across which mechanical changes can influence cellular behavior remain poorly understood. Piezo1 is a mechanosensitive ion channel that regulates cellular responses to mechanical stimuli and has recently emerged as a potential modulator of neuroinflammation. MethodsExperimental autoimmune encephalomyelitis (EAE) was induced in C57BL/6 wildtype mice using myelin oligodendrocyte glycoprotein (MOG):35-55. Immunohistochemical analyses were performed in spinal cord gray matter (GM), normal-appearing white matter (NAWM), and white matter lesion (LES) regions to assess ECM remodeling, total Piezo1 expression, and astrocyte-specific Piezo1 expression during acute and chronic EAE stages. Correlations with clinical EAE severity were determined. In parallel, mixed primary murine glial cultures were exposed to substrates of different stiffness and analyzed by transcriptomic profiling to investigate mechanobiological responses in vitro. ResultsECM-associated proteins, including glial fibrillary acidic protein (GFAP), fibronectin-1 and matrix metalloproteinase-3 (MMP3), were regionally upregulated during EAE, indicating widespread tissue remodeling beyond focal inflammatory lesions. Total Piezo1 expression was increased within lesions and transiently elevated in GM, whereas astrocyte-specific Piezo1 remained persistently upregulated during both acute and chronic EAE. Astrocytic Piezo1 expression correlated closely with ECM remodeling and clinical EAE severity, particularly in GM and NAWM. Notably, both total and astrocyte-specific Piezo1 showed stronger associations with clinical disability than classical inflammatory markers. Transcriptomic analysis revealed pronounced stiffness-dependent responses in glial cells, including alterations in extracellular matrix organization, cytokine signaling, cell adhesion, and proliferative pathways. ConclusionsOur findings identify astrocytic Piezo1 as a prominent component of neuroinflammatory tissue remodeling during EAE. The close association of Piezo1 with ECM alterations, clinical disease severity, and stiffness-dependent glial responses supports a link between neuroinflammation and mechanosensory signaling. These results highlight mechanosensation as a potentially important contributor to CNS pathology and establish Piezo1 alteration as a candidate biomarker for neuroinflammatory disease.

Introduction- Choroid plexus (CP) enlargement on brain MRI has been identified as an emerging neuroinflammatory biomarker in multiple sclerosis (MS), yet its relationship to downstream parenchymal neurochemical abnormalities remains unknown. Proton magnetic resonance spectroscopy (1H MRS) enables non-invasive in vivo quantification of neurometabolites, making it well-suited to probe downstream consequences of CP pathology in MS. Methods- Ultra-high-field 7T 1H MRS was performed in 45 people with MS (pwMS) (28 Relapsing Remitting MS, RRMS; 17 Progressive MS, PMS) and 43 age- and sex-matched healthy controls (HCs) in the posterior cingulate cortex (PCC) and centrum semiovale white matter (CSWM). CP volume, EDSS, and MS Functional Composite measures were also acquired. Group differences in metabolite concentrations were evaluated using Mann-Whitney U tests with correction for multiple comparisons, and associations between CP volume, altered metabolites, and clinical disability and functional measures were investigated. Results- Myo-inositol (mI) was significantly elevated and total N-acetylaspartate was reduced in both MS subtypes, in the CSWM. In PMS, CP volume was positively associated with CSWM mI/total creatine (tCr) ({rho} = 0.63, p = 0.008), an association absent in RRMS. Across the combined MS cohort, CP volume correlated significantly with EDSS ({rho} = 0.40, p = 0.006). Conclusions- WM mI/tCr was elevated and tNAA/tCr was reduced across MS phenotypes compared with controls, reflecting a dual metabolic signature consistent with concurrent glial overactivation and neuroaxonal compromise. Increased CP volume was associated with greater neurological disability across MS phenotypes. The association of CP enlargement with CSWM mI/tCr in PMS suggests a potential link between CP-mediated periventricular inflammation and progressive WM glial pathology. Collectively, these findings support CP volume as a clinically relevant, non-invasive biomarker and restoring CP integrity as a potential therapeutic target in PMS, where effective treatments remain limited.

Background: Serum neurofilament light chain (NfL) indexes axonal injury and glial fibrillary acidic protein (GFAP) astrocytic pathology in multiple sclerosis (MS). GFAP rises disproportionately as relapsing-remitting MS (RRMS) shifts to progressive forms on research-grade SIMOA. The commercial Roche Elecsys ECLIA platform reads six-fold lower and is undescribed across subtypes. Objective: To describe both markers by MS subtype on ECLIA. Methods: Retrospective single-center analysis of 603 MS patients (2022-2026). NfL and GFAP were measured by LabCorp Roche Elecsys ECLIA; subtype came from ICD-10 codes and notes. We examined both markers by subtype, their correlation, and NfL against gadolinium-enhancing (Gd+) MRI lesions. Results: Median NfL was 1.32 pg/mL (IQR 1.01-1.91). Both rose with stage, steeper for GFAP: NfL 1.18 (RRMS), 1.54 (SPMS, p<0.001), 1.78 (PPMS, p=0.001); GFAP 41.90, 63.80 (p<0.0001), 75.75 (p=0.08, n=6). SPMS and PPMS GFAP did not differ (p=0.83). The markers correlated moderately (r=0.569). Of 34 Gd+ encounters with NfL within 30 days, 3 (9%) were elevated. Conclusion: On ECLIA, both markers rose with MS stage, GFAP more steeply, and both progressive subtypes exceeded RRMS. NfL rarely flagged a recent Gd+ lesion, consistent with its delayed kinetics. The two index distinct processes and reproduce on an orderable assay a profile once confined to research-grade SIMOA.

Neurodegeneration is a major determinant of disability progression in multiple sclerosis (MS), yet the pathophysiological mechanisms associating inflammation to neuronal insult remain poorly understood. We recently identified Dendritic Syntaphilin Intrusion (DSI), a novel excitoxicity pathway in which the axonal mitochondrial anchor syntaphilin (SNPH) aberrantly translocates into dendrites, causing neurodegeneration in a non-inflammatory model of MS. However, whether this protein intrudes abruptly into dendrites in inflammatory MS pathology is still not clear. Here, we investigated the role of synaptic and extrasynaptic NMDA receptors (NMDAR) in regulating the intrusion of Syntaphilin into dendrites. Using primary hippocampal neuronal cultures, we examined how the balance between synaptic GluN2A-containing and extrasynaptic GluN2B-containing NMDARs influences DSI under inflammatory conditions. Pharmacological and viral-mediated approaches were employed to manipulate NMDAR subtype activity and evaluate their impact on DSI. Inflammatory cytokines discernibly sensitized neurons to DSI. Our results revealed that blockade of synaptic NMDARs significantly increased DSI, whereas inhibition of extrasynaptic NMDARs reduced DSI. These findings demonstrate opposing roles of NMDAR subtypes, with GluN2A-containing synaptic receptors inhibiting DSI and fostering neuronal survival, while GluN2B-containing extrasynaptic receptors enhancing DSI and neurodegenerative signaling. Manipulation of the GluN2A/GluN2B balance showed opposite effect on DSI, suggesting a relationship between NMDAR subtype signaling and SNPH mislocalization. Overall, our findings extend the relevance of DSI from non-inflammatory MS to inflammatory MS and identify DSI as a downstream convergence point linking inflammatory cytokines and excitotoxic NMDAR signaling to neuronal insult. These results reveal DSI as a potential mechanistic link between inflammatory signaling and excitotoxic neuronal injury and indicate that modulation of GluN2B-dependent pathways warrants further investigation in inflammatory neurodegenerative disorders.

Comprehensive biomarkers of multiple sclerosis (MS) capable of simultaneously diagnosing the condition, capturing symptom severity and predicting treatment efficacy remain elusive. Although several studies have highlighted the pivotal role played by demyelinating lesions in determining MS structural pathology, their relationship with symptom severity is limited. Here, we combined personalized computational brain modeling with magnetoencephalography (MEG) recordings from 17 MS patients and 20 healthy controls (CTR) to derive personalized brain network excitability parameters, which we tested as MS biomarkers. Personalized parameters discriminated between CTR and MS participants with high accuracy, also classifying between progressing and remitting MS patients. Notably, they also predicted MS clinical scales across multiple domains. In all clinical tasks, personalized parameters consistently outperformed standard clinical measures and total lesion loads. Together, these results highlight the potential of personalized brain modelling in deriving integrative MS biomarkers, capable of simultaneously identifying the condition, classifying MS subtypes and predicting symptom severity. d brain modelling in deriving integrative MS biomarkers, capable of simultaneously identifying the condition, classifying between MS subtypes and predicting the severity of symptomatology.

Introduction: Progressive multiple sclerosis (MS), including primary progressive MS (PPMS) and non-active secondary progressive MS (nSPMS), remains an unmet need, as few treatments target innate immune pathways. Masitinib (AB1010) is a selective tyrosine kinase inhibitor that targets c-Kit and colony-stimulating factor 1 receptor pathways. This mechanism disrupts mast cell-microglia interactions, key innate immune effectors in progressive MS pathogenesis, reducing neuroinflammation and neuronal damage. In the phase 3 AB07002 trial, masitinib (4.5 mg/kg/d) over 96 weeks met its primary endpoint. Comparable signals in PPMS and nSPMS indicated masitinib benefited both phenotypes. Secondary analyses showed that masitinib lowered the progression to wheelchair dependence (EDSS [&ge;]7, 12 weeks) and reduced the 12-week confirmed EDSS progression risk by 37% versus placebo, although the results were underpowered for these endpoints. Methods: This study aimed to confirm that oral masitinib achieves central nervous system (CNS) concentrations sufficient to modulate CSF1R and wild-type c-Kit, thereby underpinning its neuroprotective potential. Male Sprague Dawley rats (n=12, ~200 g) were administered a single oral dose (30 mg/kg). Plasma and brain samples were collected at 2, 4, 8, and 24 hours post-dose (n=3 per time point). Masitinib (AB1010) and its metabolite (AB3280) were quantified in plasma and brain homogenates using LC-MS/MS. Results: Masitinib reached a brain Cmax of 223.5 ng/mL (~450 nM), exceeding IC50 values for CSF1R and wild-type c-KIT by ~5-fold and 2-fold, respectively, indicating effective CNS target engagement. The active metabolite AB3280 also achieved brain Cmax levels with full inhibitory activity. Masitinib demonstrated consistent CNS penetration supported by a proportional plasma-to-brain exposure relationship. Conclusion: The favorable CNS penetration and safety profile of masitinib, alongside its unique mast cell inhibition, position it as a compelling candidate for progressive MS treatment, either as monotherapy or in combination with other agents. This multifaceted immunomodulatory approach addresses critical unmet needs in progressive MS and supports further clinical development.

Depression and anxiety are highly prevalent in multiple sclerosis (MS), yet tools for predicting mental health trajectories from clinical data remain limited. We investigated what structured electronic health record data can predict about depression and anxiety progression in MS, and where its limits lie. We developed gradient boosting models to predict PHQ-9 (depression) and GAD-7 (anxiety) score change using EHR data from 2,163 MS patients (7,327 observations) and 1,465 patients (3,319 observations), respectively. Models achieved R^2 of 0.22 (PHQ-9) and 0.28 (GAD-7). Baseline score was the dominant predictor, but this largely reflects regression to the mean: patients with high baseline scores tend to improve, while those with low scores tend to worsen. Age emerged as a consistent secondary predictor across both models: younger patients showed smaller improvements independent of baseline severity. Feature importance differed between models---PHQ-9 prediction relied on symptom subscales while GAD-7 incorporated pain and disease duration. These results suggest that structured clinical data alone capture only a fraction of what drives mental health trajectories, and that richer data sources---clinical notes, patient-reported outcomes, digital phenotyping---will be needed to enable meaningful individual-level prediction.

We showed before that the endogenous peptide Nociceptin blocks the premature differentiation of oligodendrocytes (OLGs), preventing untimely precocious myelination in the developing brain. Consistent with this early function, Nociceptin brain expression is developmentally regulated, sharply decreasing with the initiation and progression of myelination. However, we now found that at difference with controls and relapsing-remitting multiple sclerosis (RRMS), Nociceptin levels are highly elevated in cerebrospinal fluid from patients with the most severe progressive MS (PMS) forms. This questioned whether Nociceptin early developmental effects could be latter recapitulated, interfering with remyelination in PMS. This possibility was tested by inducing experimental autoimmune encephalomyelitis in older mice, at an age equivalent to that with increased risk of RRMS transition into PMS. Older animals develop persistently highly debilitating clinical symptoms, and display both brain and spinal cord demyelination. Importantly, these mice exhibit elevated brain Nociceptin levels, and their treatment with an antagonist of the Nociceptin receptor (NOR) elicits a regression of clinical scoring that is accompanied by higher ratios of OLGs/OLG progenitor cells, increased myelination, and reduction of reactive astrocytes. These findings suggest that Nociceptin may be a crucial player in the age-related progression of MS; interfering with OLG maturation and remyelination, and perhaps further exacerbating neurological dysfunction by targeting astrocyte populations. The upregulation of Nociceptin secretion by human astrocytes in response to proinflammatory cytokines, also points to this peptide as a mediator of microglia-astrocyte interactions supporting MS progression with aging. NOR may offer a novel pharmacological target for ameliorating the devastating effects of MS progression.

Background. Early diagnosis and intervention are crucial in multiple sclerosis (MS), yet diagnostic delays are common. Large language models (LLMs) such as generative pre-trained transformers (GPTs) may help streamline diagnostic workflows by extracting MS diagnostic signals from clinical notes. Objective. To derive MS diagnosis status from the first neurology note using a computable algorithm based on the 2017 McDonald criteria and applying GPT-4 for node-level reasoning within a structured decision framework. Methods. We analyzed first neurology notes from 125 randomly selected patients (including those with MS, related disorders, and controls) enrolled in a clinic cohort between 2017 and 2023. We included the clinical history and diagnostic testing sections but redacted the assessment and plan. We converted the 2017 McDonald criteria into a decision tree and provided expert-curated clinical knowledge to guide GPT-4 reasoning at each decision node. GPT-4 generated binary decisions at each node to traverse the tree and classified MS diagnoses at terminal nodes. We evaluated performance against neurologist-assessed diagnoses and characterized hallucinations (non-factual, incongruent, irrelevant, over-reliant, and logical reasoning errors). Results. In this study cohort (mean age 40{+/-}13 years; 81% women) representative of the clinic population, GPT-4 performed well in predicting MS diagnosis (84% accuracy, 79% precision, 74% recall, 91% specificity) using first neurology notes. Hallucinations occurred in 32 cases (26%), most commonly incoherence (75%) and overreliance (47%). Conclusion. A structured, LLM-guided decision framework can flag MS diagnoses from early clinical documentation. Large-scale studies are needed to mitigate hallucinations, validate this approach, and test implementation in clinical settings.

Abstract The association between COVID-19 vaccination and Guillain-Barre syndrome (GBS) has been previously investigated with inconsistent results, largely due to limited data and lack of concurrent controls. To address this problem, a large longitudinal cohort study was conducted using National COVID Cohort Collaborative (N3C) data. While COVID-19 infection was associated with increased GBS occurrence, COVID-19 vaccination was associated with significantly reduced GBS risk relative to unexposed (unvaccinated and uninfected) control, corresponding to a 61% lower 30-day risk (incidence risk ratio: IRR = 0.39, P < 0.01), consistent with multivariable Cox regression showing a similar reduction (adjusted hazard ratio: aHR = 0.41, P < 0.01). This protective association was observed only among recipients of mRNA vaccines (BNT162b2: IRR = 0.38, P < 0.01; mRNA-1273: IRR = 0.24, P < 0.01), but not among recipients of adenoviral-vector vaccines (IRR = 1.38, P > 0.05). Prior COVID-19 vaccination also reduced infection-associated GBS risk. Additional factors associated with GBS risk included sex, vaccine dose, and pre-existing comorbidities such as stroke, neurological disorders, and autoimmune diseases. Overall, our N3C large-scale study provides evidence that COVID-19 mRNA vaccination reduces GBS risk, supporting the safety profile of mRNA vaccines and warranting further mechanistic investigation.

Heat stroke is characterized by profound central nervous system dysfunction and vascular abnormalities. Previous studies have demonstrated the marked vulnerability of the CNS to thermal stress, resulting in neuronal injury and glial activation. However, the metabolic mechanisms linking acute injury to chronic neurological long-term effects remain understood. The neuropathological changes are closely associated with neuroinflammatory and metabolic disturbances, including dysregulation of the kynurenine pathway, whose metabolites modulate neurotoxicity, neuroprotection, and immune responses. Here, we present the first comprehensive characterization of kynurenine pathway metabolomic profile across both plasma and brain tissue in a mouse model of heat stroke. Using a validated and sensitive LC-MS/MS method, we simultaneously measured and quantified 13 analytes (kynurenine, kynurenic acid, quinolinic acid, nicotinic acid, picolinic acid, xanthurenic acid, anthranilic acid, 3-hydroxykynurenine, 3-hydroxyanthranilic acid, indole-3-acetic acid, indole-3-lactic acid, 5-hydroxyindoleacetic acid and neopterin). The findings reveal a biphasic metabolic response, characterized by an acute serotonergic disruption and reduced neuroprotective capacity, followed by chronic activation of the kynurenine pathway, depletion of central serotonin metabolites, and metabolic signatures consistent with gut microbiota dysbiosis. The acute phase is marked by a transient imbalance favoring neurotoxic kynurenine pathway metabolites, whereas the chronic phase reflects sustained pathway activation. Notably, the plasma-brain dissociation of 5-hydroxyindoleacetic acid emerged as the most prominent cross-compartment finding, suggesting a potential biomarker of central serotonergic depletion and a mechanistic link between peripheral and central metabolic changes, with implications for therapeutic targeting during the subacute recovery phase.

Recurrent inflammatory attacks in AQP4-antibody-seropositive neuromyelitis optica spectrum disorder (AQP4-IgG+NMOSD) can lead to devastating disabilities such as visual and motor dysfunction, pain, and cognitive impairment. However, the mechanisms driving the long-term effects of attacks and potential for subsequent recovery are still not well understood after patients enter a relapse-free disease phase. Here, we leveraged advanced structural and diffusion-weighted imaging analyses in a longitudinal cohort of patients with "stable" AQP4-IgG+NMOSD (retrospectively assessed, [&ge;]12 months without attack, n=33, 31/33 female, mean age 49.7 years (SD 14.2)). Brain changes over a median of 4 annual visits (range 2-6) were evaluated using FreeSurfer-based volumetry, regional damage profiles of white matter fibre bundles, cognitive testing (BRB-N), and neuropsychiatric self-reports. Our analysis revealed four key findings: (1) In the absence of new attacks, pre-existing symptoms persisted and contributed to motor impairment, fatigue, and lower visual function. By contrast, cognitive impairment - selective to higher attention and processing speed - improved over time (PASAT3s, PFDR=0.007). (2) On a macroscopic brain level, the continued decline of whole brain volumes (PFDR=0.037) was mainly driven by loss of cortical grey matter (PFDR=0.013) and linked to poorer motor outcomes (9-hole peg test: {rho}s=-0.55, PFDR=0.021) and higher pain levels (PD-Q: {rho}s=-0.51, PFDR=0.021) at last follow-up. Large-scale age- and sex-stratified reference curves (Braincharts) confirmed that cortical atrophy exceeded normal ageing. (3) Thalamic volumes, by contrast, were significantly higher compared to those of healthy participants (PFDR=0.044) throughout the entire follow-up period and predicted more favourable long-term attention (SDMT: {rho}s=0.63, PFDR=0.003) and spatial memory outcomes (SPART sum score: {rho}s=0.62, PFDR=0.029) as early as at the first MRI. Larger thalamic volumes were mainly seen in a subgroup of younger patients with lower disability burden, fewer comorbidities, and better integrity of thalamus-adjacent white matter tracts. (4) On a microstructural level, tract-specific longitudinal patterns emerged: decreasing regional fractional anisotropy (FA) in the optic radiation, thalamo-prefrontal and thalamo-occipital projections was linked to worse cognitive outcomes (e.g., SDMT: {rho}s=0.62, PFDR=0.012), while increasing FA, particularly in the corticospinal tract and inferior fronto-occipital fasciculus, predicted more favourable long-term cognitive and visual functions (e.g., NEI VFQ-25: {rho}s=0.64, PFDR=0.011). Collectively, our data suggest that even in relapse-free AQP4-IgG+NMOSD there is evidence for declining cortical volume, thalamic reserve in some patients, and white matter microstructural damage in distinct regions. Our clinically relevant findings elucidated in the "stable" disease phase highlight longitudinal mechanisms contributing to the long-term prognoses of patients with AQP4-IgG+NMOSD.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by death of upper and lower motor neurons, usually presented with clinical heterogeneity. Fluid biomarker development remains dominated by neurofilament light chain (NEFL), a marker of neuroaxonal injury. NEFL is however unspecific to ALS and its phenotypes and there is currently a lack of biomarkers that capture ALS heterogeneity such as onset site and ALS-frontotemporal spectrum disorder (ALS-FTSD). Therefore, we investigated whether plasma proteomics could reveal pathway-level signatures that stratify and explain ALS heterogeneity. Methods: We profiled ~5,400 plasma proteins (Olink Explore HT) in 299 patients with ALS and 50 age- and sex comparable healthy controls. We used two complementary analytic frameworks: (i) differential protein abundance analysis to identify altered proteins in ALS and across clinical subgroups, and (ii) weighted gene correlation network analysis (WGCNA) to identify coordinated protein modules and relate them to ALS diagnosis and to ALS-specific clinical traits (site of onset, ALS-FTSD, ALS functional rating scale-revised (ALSFRS-R) score, and plasma NEFL). Results: Differential abundance analysis identified 56 proteins altered in ALS versus controls, of which 40 were increased. WGCNA identified 11 co-expression modules, with ALS samples having the strongest correlation to a protein module (n=51) highly enriched for muscle-related proteins. Out of the 40 proteins that had increased expression levels, 29 overlapped with the muscle-enriched protein module, indicating that muscle related proteins are the dominant circulating proteomic signature in ALS. This signal extended to clinical stratification: spinal-onset patients showed a strong positive association with the muscle-module. Further, differential abundance analysis of spinal- versus bulbar-onset ALS identified changes that mapped predominantly to the same module, supporting a molecular signature of onset phenotype. In contrast, cognitive status (ALS-FTSD) mapped to distinct modules enriched for extracellular matrix/cell-adhesion pathways, consistent with a separable biological axis of disease heterogeneity. Although multiple modules correlated with NEFL, trait-specific signatures were not fully explained by neuroaxonal injury. Notably, the muscle-enriched module increased with higher NEFL and lower ALSFRS-R, supporting its interpretation as a severity-linked, muscle-involvement proxy. Conclusions: Large-scale plasma proteomics reveals that heterogeneity in ALS reflects underlying biological structures. We identified a dominant muscle-associated protein network that distinguished ALS patients from controls and correlated with disease onset phenotype and severity, alongside distinct protein networks linked to ALS-FTSD. By integrating differential protein abundance with network-based analysis, we defined pathway-level biomarker signatures that extend beyond NEFL, enabling biologically informed patient stratification and improved therapeutic monitoring.

Background In a retrospective online survey, we assessed the extent to which people with symptomatic hypermobility are at risk of Long COVID with a high degree of post-exertional symptom exacerbation, a form of Long COVID similar to myalgic encephalomyelitis. Methods Participants were 1,816 adults with prior COVID-19 infection; 19.4% reported Long COVID, defined as symptoms persisting [&ge;]3 months. Survey measures identified Long COVID with high post-exertional symptom exacerbation, generalized joint hypermobility (GJH), extreme hypermobility, and a pre-COVID orthostatic/neurocognitive symptom burden (ONS profile). Logistic regression assessed whether ONS profile and hypermobility, together defined as symptomatic hypermobility, were associated with increased risk of Long COVID with post-exertional symptom exacerbation. Results In the full sample, both extreme hypermobility (OR 3.15, 95 % CI 2.00-4.95) and an ONS profile pre-COVID (OR 3.29, 95% CI 2.34-4.61) were strongly predictive of Long COVID with high post-exertional symptom exacerbation. These effects were cumulative, leading to an OR of 9.46 (95% CI 4.93-18.17) for people with both conditions. People who both had an ONS profile pre-COVID and had generalized joint hypermobility also had a higher risk of Long COVID with high post-exertional symptom exacerbation (OR 5.54, 95% CI 3.51-8.75). Conclusions In this dataset, people with symptomatic hypermobility were at high risk of Long COVID with high levels of post-exertional symptom exacerbation. Further research is needed to understand the biological mechanisms of viral-onset illness to promote more effective and targeted treatments tailored to the disease pathways shared by groups of individuals with common vulnerabilities.

Background: Growing evidence implicates the hypothalamus as a key structure in migraine pathophysiology; however, our understanding of its precise role and of the specific nuclei involved remains limited. We combined MRI data from our laboratory with publicly available MRI datasets from OpenNeuro to examine hypothalamic subunit volumes in episodic migraine and assess the specificity of these alterations relative to chronic pain conditions. Methods: Structural MRI combined with an automated atlas-based segmentation algorithm and a discovery-replication design was employed to investigate cross-sectional volumetric differences across 5 bilateral hypothalamic subunits in two independent migraine cohorts: DS1-MIG (DS1-MIG-base, n = 111 patients, n = 35 controls) and DS2-MIG (n = 27 patients, n = 31 controls). The adjusted volumes were compared between groups using MANOVA as an omnibus test, followed by Welch t-tests to test univariate follow-up. Longitudinal volumetric changes were additionally assessed in DS1-MIG participants with available follow-up scans using linear mixed models. To assess the specificity of findings to migraine, the same pipeline was applied to two chronic pain datasets, one including patients with fibromyalgia (DS-FM, n = 33 patients, n = 33 controls) and the other including patients with trigeminal neuralgia (n = 119 patients, n = 55 controls). Results: MANOVA revealed significant multivariate group differences in the discovery and replication migraine cohorts (DS1-MIG-base: = .006; DS2-MIG: = .008). Follow-up univariate analyses identified a consistent enlargement of the left anterior-superior subunit across both cohorts (FDR = .023 in DS1-MIG-base and FDR = .046 in DS2-MIG), representing the only cross-cohort replication finding. Beyond this shared signature, DS2-MIG exhibited additional significant enlargements of the right anterior-inferior and right tubular-inferior subunits. Longitudinal analyses in DS1-MIG showed that hypothalamic subunit volumes remained broadly stable over time within both migraine patients and control participants. No significant volumetric alterations were detected in the fibromyalgia or trigeminal neuralgia cohorts, either in multivariate or univariate analyses, underscoring migraine-specific findings. Conclusions: These findings provide evidence for subunit-specific hypothalamic structural alterations in migraine localized in the left anterior hypothalamic subunit. The stability of these differences over time and their absence in other chronic pain conditions suggest a migraine-specific structural organisation of hypothalamic circuitry.

Quantitative MRI enables the detection of subtle microstructural alterations in normal-appearing white matter (NAWM) associated with pathological conditions such as multiple sclerosis. Quantitative metrics including R1, R2, and the bSSFP asymmetry index (AI) were evaluated in the WM of 20 relapsing-remitting multiple sclerosis (RRMS) patients and 10 healthy controls (HC). A multi-parametric frame-work based on a phase-cycled balanced steady-state free precession (pc-bSSFP) sequence was used. Diffusion tensor imaging-derived measures, including fiber-to-field angle, number of fiber orientations, and fractional anisotropy, were incorporated to assess parameter anisotropy. Statistical analysis was performed using linear mixed-effects models to test for group, ROI, and group-by-ROI effects for each metric, with ROI-specific group comparisons derived from the model. Significant main effects of group, ROI, and group-by-ROI interaction were observed for both R1 and R2, whereas for AI only the ROI effect reached significance (group p= 0.462; group-by-ROI p = 0.786). Fourteen of sixteen ROIs demonstrated significantly lower R1 and R2 values in RRMS compared with HC. No ROI showed significant differences in AI. In conclusion, pc-bSSFP-based relaxometry reveals predominantly white matter alterations in RRMS, while enabling a comprehensive whole-brain assessment that also encompasses gray matter.

Importance: Neuroinflammation is a key component of the response to injury after concussion, but direct links between diffusion MRI metrics and specific plasma inflammatory pathways in human concussion have not been established. Objective: To examine associations between diffusion MRI metrics and pathway-level inflammatory proteomic signatures in adolescents during the subacute period after concussion. Design, Setting, and Participants: Cross-sectional analysis of data from the CARE4Kids Consortium, a six-site prospective study. Participants were English-speaking adolescents ages 11-17.99 with concussion and symptoms at 7-35 days post-injury. Data were collected between 2022-2024. Of 370 enrolled participants, 122 had both diffusion MRI and plasma proteomics available for analysis. Exposure: Advanced diffusion MRI metrics were converted to z-scores and participants were grouped by the spatial extent of outlier values (potholes and peaks) across 15 white matter regions of interest. Nine non-redundant groupings were selected for primary analysis. Main Outcomes and Measures: Pathway-level inflammatory profiles derived from gene set enrichment analysis (GSEA) of ~5,400 plasma proteins measured by Olink proximity extension assay, targeting nine hallmark inflammatory pathways spanning initiation through resolution. Persistent symptoms were assessed 64-115 days post-injury. Results: Diffusion metrics reflecting tissue disorganization were associated with upregulation of the coagulation pathway, consistent with hemostatic-inflammatory signaling. Metrics reflecting reduced tissue complexity and neurite density were associated with upregulation of interferon- and interferon-{gamma} response pathways, consistent with microstructural remodeling driven by cellular immune activation. Elevated free water content was associated with downregulation of most inflammatory pathways and trend-level transforming growth factor - {beta} upregulation, reflecting inflammatory resolution. Time since injury did not differ between groups based on free water (Kolmogorov-Smirnov p = 0.97), suggesting these differences reflect individual variability in recovery pace. Exploratory analyses showed a trend toward lower odds of persistent symptoms in the group with elevated free water content (odds ratio = 0.51, p = 0.18). Conclusions and Relevance: Multiple diffusion MRI metrics are differentially sensitive to distinct neuroinflammatory states in the subacute period after adolescent concussion. These findings suggest that diffusion imaging could serve as a non-invasive tool for inflammatory phenotyping, with potential implications for identifying patients who may benefit from targeted immunomodulatory intervention.

Blood-based proteomic profiling is now widely applied in neurodegenerative and neuroinflammatory disease, yet the choice between serum and plasma remains poorly characterised for high-multiplex platforms. Many legacy biobanks hold mainly serum, whereas most current NUcleic-acid-Linked Immuno-Sandwich Assay (NULISA) studies use plasma. We compared the 130-protein NULISAseq central nervous system (CNS) Disease Panel head-to-head in matched serum and plasma collected at the same draw from 62 participants (30 neurodegenerative, 19 demyelinating, 13 healthy controls). Agreement was measured with Spearman correlation (rho), Lin's concordance correlation coefficient (CCC), the intraclass correlation coefficient (ICC) and the mean paired serum-to-plasma difference (dNPQ). Concordance was moderate to high: 123 of 130 proteins reached significance and 18 reached rho >= 0.90, with a median rho of 0.72 (range 0.10-0.988). Proteins fell into three tiers. Cytoskeletal markers (NEFH rho=0.988; NEFL rho=0.947) and glial GFAP (rho=0.949, |dNPQ|<0.5) were interchangeable between matrices. Phosphorylated tau (pTau) species retained excellent rank concordance but carried a systematic plasma-greater-than-serum offset (pTau-181 rho=0.869, dNPQ=+0.67; pTau-217 rho=0.846, dNPQ=+0.64; pTau-231 rho=0.885, dNPQ=+0.89). Platelet-derived analytes (CD40LG rho=0.102, dNPQ=-4.74; BDNF rho=0.223, dNPQ=-2.69) and intracellular synaptic proteins (NRGN, SNAP25, ENO2) diverged markedly. For most clinically relevant neurodegeneration markers, especially cytoskeletal and glial proteins, serum is a valid substitute for plasma; absolute thresholds for phosphorylated tau and amyloid peptides require matrix-specific calibration, and platelet-sensitive analytes cannot be compared across matrices without strictly standardised pre-analytical conditions.

Guillain-Barre syndrome (GBS) is an autoimmune disorder that causes weakness, sensory loss, autonomic dysfunction, and chronic neuropathic pain. The mediators responsible for driving early autoimmune injury in the most common GBS variant, acute inflammatory demyelinating polyradiculoneuropathy (AIDP), remain incompletely understood. We performed single-cell and bulk RNA sequencing on peripheral blood mononuclear cells collected from early untreated AIDP-variant GBS patients and healthy controls to comprehensively deduce leukocyte transcriptome alterations and predict disease- and pain-driving interactions between pathogenic leukocytes and peripheral nervous system cells. We found that classical, intermediate, and non-classical monocytes were expanded and upregulated genes associated with type I and II interferons, JAK/STAT signaling, and NLRP3 inflammasome engagement. CD8+ T cells were highly proliferative and likewise upregulated JAK/STAT signaling. CD4+FOXP3+ regulatory T cells upregulated PRDM1 and CD74 in a signature that may indicate functional exhaustion. A subpopulation of highly activated intermediate monocytes upregulated genes related to angiogenesis and oncostatin M. Differential expression-based cell-cell interaction analysis between GBS leukocytes, Schwann cells, and sensory neurons predicted engagement of ligand-receptor pairs with nerve integrity and pain functions, including epiregulin, interferon-beta, adrenomedullin, clusterin, IL-6, IL-15, and CCL4. Functional validation demonstrated that CCL4 sensitizes human sensory neurons in vitro. These results unearth molecular interactions by which specific leukocyte populations in AIDP-variant GBS may participate in peripheral nerve injury and drive neuropathic pain. Many of these targets may be amenable to therapeutic modulation using available approved and investigational drugs, potentially providing drug repurposing opportunities.