Brain

BackgroundGangliogliomas (GGs) are low-grade glioneuronal tumors that frequently present with drug-resistant epilepsy. Although their indolent course contrasts with their high epileptogenic potential, the oncogenic mechanisms sustaining neuronal precursor-like populations within the tumor microenvironment remain poorly defined. MethodsWe performed spatial transcriptomic profiling on eight histologically confirmed GGs and matched healthy cortex to map the cellular and molecular architecture of the tumor microenvironment. Integrated analysis with weighted gene correlation network analysis (WGCNA) defined recurrent oncogenic programs and spatially resolved tumor-stroma interactions. ResultsEight conserved gene modules emerged, encompassing physiological cortical, reactive glial, and oncopathological programs. The latter captured extracellular matrix (ECM) remodeling, vascular-immune signaling, and persistence of immature, proliferative neuronal-like states. Spatial modeling revealed that these oncopathological programs form structured niches at the tumor-brain interface, where radial glia-derived neuronal-like tumor cells coexist with immune and stromal elements engaged in ECM turnover and cytokine signaling. ConclusionsGanglioglioma represents a hybrid glioneuronal neoplasm in which developmental neuronal programs are co-opted by tumor-associated stromal and immune cues. This convergence establishes a permissive oncogenic niche that sustains precursor-like tumor cells and provides a mechanistic basis for both the tumors benign growth and its intrinsic epileptogenicity. Key PointsO_LISpatial transcriptomics identifies reproducible transcriptional programs that define the ganglioglioma microenvironment. C_LIO_LITumor-associated regions show transcriptional programs consistent with immature neuronal states together with ECM remodelling and immune activity. C_LIO_LISingle-cell reference data indicate that immature neuronal programs in ganglioglioma resemble radial glia-derived developmental states. C_LI Importance of the StudyGanglioglioma is a low-grade glioneuronal tumor that combines benign growth with pronounced epileptogenicity, yet the molecular basis of this dual behavior remains poorly understood. Through spatial transcriptomics integrated with single-cell analysis, we reveal that ganglioglioma architecture is defined by two interacting transcriptional axes: a residual glioneuronal network and a tumoral niche enriched for extracellular-matrix, vascular, and immune programs. Within these niches, immature neuronal-like tumor cells persist in a developmentally arrested state maintained by ECM-immune signaling. This spatially organized interplay between physiological and pathological programs explains both the low oncologic aggressiveness and high excitability of these lesions. Our findings provide molecular signatures that may refine diagnostic classification within the LEAT spectrum, delineate epileptogenic zones, and identify candidate pathways for therapeutic modulation of the ganglioglioma microenvironment.

ObjectiveIn individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatiotemporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. MethodsIn this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board-certified epileptologists. ResultsOverall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. SignificanceOverall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.

Motor neuron (MN) loss is a hallmark of neurodegenerative disorders, yet its assessment remains variable, confounding mechanistic and therapeutic interpretation. To address this, we conducted a systematic review and meta-analysis of spinal muscular atrophy (SMA) mouse studies, revealing 60% variability in reported MN loss, largely attributable to nonspecific spinal cord sampling. Using a whole-segment approach with tissue clearing, MN tracing, and multimodal imaging, we confirmed segment-dependent differences in MN counts. Common MN markers (SMI-32, Nissl) lacked specificity, whereas choline acetyltransferase (ChAT) provided robust labeling in murine and human spinal cords. Deep learning-based whole-mount segmentation enabled unbiased MN quantification and validated manual counts. Integrating analysis with computational modeling established segment sampling as a key driver of variability and revealed degeneration patterns: widespread MN loss in amyotrophic lateral sclerosis (ALS), selective MN loss in severe SMA, and preservation in mild SMA models. These findings establish a framework for reproducible MN quantification. HighlightsO_LISpinal cord segment-specific analysis reduces variability and allows accurate MN quantification C_LIO_LIChAT is the most reliable MN marker in murine and human spinal cords C_LIO_LIDeep learning-based segmentation enables unbiased MN quantification in intact spinal cords C_LIO_LIMN degeneration is widespread in ALS but restricted to pools innervating proximal muscles in severe SMA C_LI

A prominent radiological manifestation of cerebral amyloid angiopathy (CAA) is enlargement of perivascular spaces (EPVS), which is suggested to result from fluid stagnation due to impaired perivascular clearance. Here, we report a novel observation of hypointense rims in cerebral white matter surrounding EPVS near haemorrhages on in vivo 7T Gradient Echo MRI. We hypothesised that the observed black rim pattern denotes iron accumulation that may be caused by incomplete clearance following bleeding. We investigated the occurrence and localisation of this marker on in vivo and ex vivo MRI and examined its histopathological correlates. From MRI data of the prospective longitudinal natural history study of hereditary Dutch-type CAA (D-CAA) at Leiden University Medical Centre, we selected the first 20 consecutive patients who underwent 7T imaging and assessed the presence of black rims on MRI. Post-mortem material was available from one donor with black rims on in vivo scans. Formalin-fixed coronal brain slabs were scanned at 7T MRI, including a high-resolution T2*-weighted sequence. Guided by ex vivo MRI, tissue blocks from representative areas with black rims were sampled for histopathological analysis. Serial sections were stained for iron, calcium, myelin, and general tissue morphology. On in vivo 7T MRI, 9 out of 20 participants exhibited one or several black rims, all located close to a haemorrhage. In the D-CAA donor, ex vivo MRI signal loss matched the in vivo contrast changes. Thirty-six vessels with ex vivo-observed black rims were retrieved and histopathologically examined, showing iron accumulation surrounding perivascular spaces, but the pattern and severity of iron deposition varied. Across groups, vessels displayed microvascular degeneration, including hyaline vessel wall thickening, adventitial fibrosis, and perivascular inflammation. We identified black rims on in vivo 7T MRI and confirmed their correspondence on ex vivo imaging. Iron deposition was determined as the underlying correlate of black rims, but the histopathology appears heterogeneous. The preferential deposition of iron around EPVS may indicate incomplete clearance of iron-positive blood-breakdown products after bleeding. The varied pattern of iron accumulation and microvascular alterations may reflect different pathophysiological mechanisms related to the formation and maintenance of black rims in D-CAA.

Alzheimer's disease (AD) is increasingly recognized to have systemic physiological correlates alongside central neurodegeneration. Here, we explored brain-organ network (BON) connectivity in AD (n=28) and healthy controls (n=23) using time-resolved quasi-dynamic analysis of plateau-phase total-body 18F-tau-PET. We found that AD-related pathophysiology was linked not only to cerebral tau aggregation, but also to altered signal synchronization across the brain-organ network, despite comparable body tracer distribution. Network topology analyses revealed the occipitotemporal cortex and the spinal cord as key nodes in this altered systemic network. Furthermore, exploratory mediation analyses demonstrated that BON dysregulation is cross-sectionally linked to cognitive deficits, with statistical associations observed for both cortical tau burden and imaging markers of impaired glymphatic clearance. This total-body PET study provides first-ever direct evidence repositioning AD as a multi-organ disorganization disease. These findings provide a novel framework for investigating brain-body interactions and systemic vulnerabilities in neurodegenerative disorders.

Multiple sclerosis (MS) is a debilitating disease affecting more than 1 million Americans, and today is assessed primarily through magnetic resonance imaging (MRI) and observational clinical symptoms. Given the autoimmune nature of MS, we hypothesized that high-dimensional gene expression data from peripheral blood mononuclear cells (PBMCs), when analyzed with the assistance of AI, may collectively serve as valuable biomarkers for the real-time risk and progression of MS. Here, we present PBMC RNA sequencing (RNAseq) results from N=997 samples, including 540 MS, 221 neuromyelitis optica (NMO), and 149 healthy controls. We constructed and optimized ensemble models for three clinical outcomes: (1) discrimination of early MS (EDSS [≤] 2.0) from healthy individuals with 74% AUC at 100% coverage, (2) differential diagnosis of MS from NMO with 91% AUC at 80% coverage, and (3) subtyping RRMS from progressive MS with 79% AUC at 80% coverage. To our knowledge, no prior molecular test has been reported for any of these three MS clinical tasks, and these results may have immediate impact on clinical management of MS patients. Two innovations that improved the stratification accuracy of our models: selection of gene sets based on expression variance in disease states, and use of non-linear rank sort and conviction weighting in the ensemble score calculation.

Objective: Spinocerebellar ataxia type 1 (SCA1) is a rare, inherited neurodegenerative disease characterised by progressive deterioration of motor and cognitive function. Here, we illustrate the pattern and evolution of brain atrophy in people with SCA1 using a large multisite dataset. Methods: Structural magnetic resonance imaging data from SCA1 (n=152) and healthy control (n=131) participants from seven sites and two consortia were analyzed using voxel-based morphometry. Cross-sectional stratification and correlations were undertaken with ataxia severity and duration to profile disease evolution. Cerebrocerebellar structural covariance analysis was used to understand the relationship between cerebral and cerebellar tissue atrophy. Results: Atrophy in SCA1 first manifests in the lower brainstem and cerebellar white matter (WM), before progressing to the pons, anterior cerebellum, and cerebellar lobule IX. The midbrain and peri-thalamic WM and the remainder of the cerebellar cortex are then affected, with preferential involvement of specific motor and cognitive areas. Finally, degeneration in the striatum and cerebral WM corresponding to the corticospinal tract become apparent. Atrophy and correlations with ataxia severity are most pronounced in the cerebellar WM and pons. Structural covariance analysis showed reduced correlations between cerebellar and cerebral WM volume in SCA1 participants. Interpretation: Cross-sectional stratification of a large SCA1 cohort by ataxia severity indicates a pattern of atrophy spread across the brainstem, cerebellum, and subcortical grey and white matter. Ongoing volume loss throughout the disease course is most evident in a core set of infra-tentorial brain regions. Atrophy of cerebellum spans both motor and cognitive functional zones. Cerebellar degeneration is not directly mirrored by downstream effects in the cerebrum.

Traumatic brain injuries (TBIs) are more than mere lesions and generate a persistent secondary pathology. This, combined with functional reorganization of circuits post-injury, may explain the increased risk for psychiatric disorders in patients with TBI. In the current studies, we demonstrate that frontal TBI changed the Pavlovian behavioral response to reinforcer-predicting cues and reduced the motivational value of cues. TBI also chronically impaired decision-making on a gambling-like task with reinforcer-paired cues. To investigate how these changes occur, we evaluated the nucleus accumbens (NAc) core. At a subacute time point (14 days), we confirmed reduced input to the NAc with optogenetics and evaluated electrophysiological and transcriptional changes. TBI increased neuronal excitability and the single nucleus RNA sequencing profile indicated a substantial stress and inflammatory response, but also high indicators of plasticity, particularly in D1- and D2-positive medium spiny neurons. To evaluate how these subacute changes transitioned to chronic NAc dysfunction, we measured immunohistochemical surrogates of activity post-mortem and recorded calcium activity from the NAc after TBI during Pavlovian conditioning. TBI reduced histological markers of activity and reduced cue-evoked calcium activity. Overall, these data indicate that substantial reorganization of the NAc occurs following frontal brain injury. A primary effect of this is to reduce the salience of environmental cues linked to outcomes. The inability to properly process outcomes could contribute to broader psychiatric symptoms after TBI, including impairments in decision-making, behavioral flexibility, and impulsivity but also presents a potential treatment target.

Hyperphosphorylated tau is a central pathological feature of Alzheimers disease and related tauopathies, and antibodies targeting the pSer396/pSer404 epitope region represent a promising therapeutic strategy. However, direct comparisons of pSer396- and pSer404-selective antibodies and the impact of humanization on their functional properties remain limited. We generated two new monoclonal antibodies (mAbs), 9E (pSer404-specific) and G10 (pSer396-specific), and evaluated them alongside 4E6 (pSer404) and PHF-1 (pSer396) in murine and partially humanized chimeric formats. Antibodies were assessed in mixed cortical cultures using extracellular (PHF + Ab) and intracellular (PHF [->] Ab) paradigms. Efficacy in preventing tau-induced toxicity and seeding differed substantially among antibodies and was variably altered by chimerization, despite identical variable regions. Antibodies targeting pSer404 were more effective than those targeting pSer396, and antibodies that preferentially bound soluble pathological tau species in competition ELISA were consistently more efficacious, whereas neuronal uptake was comparable across variants. To define structural determinants of phospho-epitope recognition, we determined the crystal structures of the Fab regions of 9E, G10, and PHF-1, and additionally solved the co-crystal structure of Fab PHF-1 in complex with a pSer396 tau peptide at 2.55 [A] resolution. The PHF-1 complex reveals a heavy-chain-dominant binding mode in which pSer396 is anchored within an electropositive pocket and Tyr394 adopts a flipped conformation that stabilizes a {beta}-strand-like motif, consistent with a phosphorylation-dependent conformational switch. These findings demonstrate that epitope selectivity, aggregate preference, structural binding mode, and Fc context collectively govern antibody efficacy, and that humanization can substantially alter therapeutic properties.

Background Friedreich ataxia (FRDA) is a rare neurodegenerative disorder with substantial heterogeneity in clinical presentation and progression, complicating prognosis and trial design. Neuroimaging offers objective biomarkers to track disease evolution, yet variability in progression patterns remains poorly understood. Objective To identify biologically meaningful FRDA progression subtypes using longitudinal multimodal MRI and assess their associations with demographic, genetic, and clinical factors. Methods Longitudinal structural and diffusion MRI data from 54 FRDA and 57 controls were analysed. Annualised progression rates of macrostructural (volumetric) and microstructural (diffusion) features across cerebellum, brainstem, and spinal cord regions were clustered using Gaussian Mixture Models. Cluster robustness was assessed using per-cluster Jaccard similarity and other validation metrics. Random Forest classification examined predictors of cluster membership. Results Three reproducible clusters/subtypes emerged: micro-dominant/dual progression, characterised by widespread microstructural deterioration with modest volumetric decline; macro-dominant, marked by pronounced volumetric decline with minimal microstructural change; and minimal/no progression, showing negligible change in all measures. FRDA participants predominated in the first two clusters. Random Forest prediction of cluster membership using clinical and demographic variables identified length of the trinucleotide repeat expansion in the FXN gene as key predictor. Conclusions Data-driven clustering of longitudinal MRI identified distinct FRDA subtypes with unique co-progression patterns, underscoring genetic burden as a key driver. Recognising such heterogeneity can improve patient stratification, enable personalised monitoring, and guide targeted therapeutic strategies. Future studies should validate these subtypes in larger, more diverse cohorts and integrate additional biomarkers for enhanced precision.

Cerebral amyloid angiopathy (CAA), a major vascular contributor to cognitive decline, is present in 85-95% of Alzheimers disease (AD) patients. Despite its high prevalence, the mechanisms by which CAA contributes to neurodegeneration remain poorly understood. Triggering receptor expressed on myeloid cells 2 (TREM2), an innate immune receptor expressed exclusively by microglia, regulates activation, phagocytosis, and amyloid clearance, thereby shaping neuroinflammation. Loss-of-function mutations in TREM2 markedly increase AD risk, but its role in CAA pathology remains unknown. To investigate this, we crossed the Familial Danish Dementia (Tg-FDD) mouse model, which accumulates robust vascular amyloid, with TREM2 knockout (TREM2KO) mice to generate Tg-FDD/TREM2KO animals. Histological and transcriptomic analyses revealed region-specific effects of TREM2 deficiency. In the cortex, TREM2 loss markedly reduced vascular amyloid deposition, accompanied by decreased tau pathology. In contrast, in the cerebellum, TREM2 deletion exacerbated vascular amyloid accumulation, promoted astrogliosis, and enhanced tau pathology. Transcriptomic profiling further identified distinct neuroinflammatory signatures between cortex and cerebellum, particularly in cytokine signaling, matrix remodeling, and lipid metabolism. Together, these findings demonstrate that TREM2 deficiency leads to region-specific effects on CAA, revealing extensive regional variability in vascular amyloid pathology and underscoring the importance of considering these differences when developing TREM2-based therapies.

BackgroundEpidemiological studies show an inverse association between cigarette smoking and Parkinsons disease (PD), suggesting a potential protective effect of smoking on PD incidence, despite the well-established and overwhelming harms of smoking to human health. We integrated genomic and proteomic approaches to investigate the causality and molecular basis of this potential relationship. MethodsWe analyzed summary statistics from genome-wide association studies (GWAS) of smoking initiation (SmkInit), smoking intensity, and PD. Two-sample Mendelian randomization (MR) tested whether genetic liability to smoking behaviors causally influences PD risk. Shared genomic architecture was quantified using MiXeR, and conjunctional false discovery rate (conjFDR) analysis identified loci jointly associated with smoking and PD, which were then mapped to genes and tested for tissue enrichment. To identify mediating proteins, we integrated dorsolateral prefrontal cortex proteomic data with GWAS using proteome-wide association studies (PWAS), summary-based MR, heterogeneity in dependent instruments testing, and colocalization. Finally, the druggability of convergent genes was evaluated. ResultsMR analyses indicated a protective effect of genetic liability to SmkInit on PD risk (OR = 0.78, 95% CI: 0.67-0.91, P = 1.5 x 10-3), which was consistent across sensitivity analyses and not suggestive of directional pleiotropy. However, no significant effect of genetic liability to cigarettes per day (CigDay) on PD risk was found. MiXeR revealed modest polygenic overlap between SmkInit and PD (13.9%; genetic correlation rg = -0.16) and between CigDay and PD (22.9%; rg = -0.09). ConjFDR identified 95 shared loci for SmkInit-PD and 26 for CigDay-PD. SmkInit-PD loci mapped to genes involved in neurotrophic signaling, synaptic organization, microglial modulation, and mitochondrial stress responses, with expression enriched in substantia nigra, basal ganglia, and interconnected cortical regions. PWAS identified 11 proteins shared by PD and SmkInit and 5 shared with CigDay, several of which (AKT3, MAPT, RIT2, EXD2, and PPP3CC) were supported by both genomic and proteomic analyses. Druggability assessment highlighted six proteins with existing pharmacologic modulation potential, spanning neurotrophic, microglial, proteostatic, and ion-channel pathways. ConclusionsGenetic liability to smoking initiation appears to confer modest protection against PD. Integrative genomic and proteomic evidence converges on neurotrophic, synaptic, microglial, and mitochondrial pathways as shared mechanisms, identifying biologically coherent potential therapeutic targets for advancing smoke-free neuroprotective strategies in PD.

The spinocerebellar ataxias (SCAs) are a clinically heterogenous group of neurodegenerative disorders that affect movement, vision, speech and balance. Here, we reassign the linkage of SCA30 to 14q32.13 based on a cumulative LOD score >12. Within this interval we identified a 331 kb duplication, absent in population controls and not observed in >800 unrelated individuals with genetically unresolved cerebellar ataxia. RNASeq analysis of patient-derived lymphoblastoid cell lines revealed a splice-mediated chimeric transcript resulting from the duplication event. This transcript joined exon 1 of CLMN to exon 2 of SYNE3. In silico translation predicted that this chimeric transcript would produce a short N-terminal peptide corresponding to exon 1 of CLMN and the usually untranslated region of exon 2 of SYNE3 fused to the complete and in-frame SYNE3 protein. Transient overexpression of SYNE3 or the CLMN::SYNE3 fusion protein, in both HeLa cells and mouse primary cortical neurons, resulted in equivalent cellular outcomes including altered nuclear morphology and chromosomal DNA fragmentation. SYNE3 forms part of the linker of nucleoskeleton and cytoskeleton complex and is not usually expressed in cerebellar Purkyn[e] neurons while, CLMN has a Purkyn[e] specific expression pattern within the brain. Our data suggests that ectopic expression of SYNE3 in cerebellar Purkyn[e] neurons, mediated by the CLMN promoter, leads to cerebellar atrophy and causes spinocerebellar ataxia in the SCA30 family. This is an example of Mendelian disease arising from a novel, chimeric transcript with a likely dominant negative effect. Chimeric transcripts are commonly associated with cancers, but they are not often associated with monogenic disorders. Detection of chimeric transcripts as part of structural variant analysis could increase the genetic diagnostic yield of Mendelian disorders.

Hippocampal sclerosis (HS) is the most common pathology in drug-resistant temporal lobe epilepsy (TLE). However, clinical diagnosis, prevalent epileptogenicity, and drug drug-resistance in individuals with HS remain an ongoing challenge demanding multidisciplinary research efforts. In this study, we examined the mechanical properties of neurosurgically en bloc resected HS specimens (n=8) ex vivo under compression, tension, and torsional shear. We fitted a two-term Ogden hyperelastic model to the measured mechanical responses to quantify nonlinear mechanical tissue properties. The resulting parameters revealed higher strain stiffening under compression in HS compared to hippocampus obtained post mortem (n=7). The distinction was most noticeable in the large-strain regime, which has important implications for using mechanical tissue properties as valuable diagnostic biomarker. Furthermore, we correlated the tissue microstructure with mechanical parameters. We trained a deep-learning histopathology classifier to detect and classify neurons and glial cells from hematoxylin-stained whole slide images (WSI). We identified a strong association between the small-strain stiffness (shear modulus {micro}) and the overall cell density as well as the glial cell density. The negative relationship between the neuron-to-glia ratio and shear modulus is consistent with the hypothesis that neuronal cell loss and gliosis drives tissue stiffening, respectively. Magnetic resonance imaging (MRI) analysis of the specimens confirmed the previously reported negative association between MRI-derived fractional anisotropy and shear modulus {micro}. Taken together, our study establishes a direct link between tissue mechanics and microstructure, suggesting nonlinear continuum mechanics models as promising new tools for clinical diagnosis and novel research strategies.

Multi-consistency testing during flexible endoscopic evaluation of swallowing (FEES) is clinically necessary but introduces selection bias: worst scores inflate severity because the number of consistencies tested covaries with disease severity. In this retrospective observational study of hospitalized neurological patients, we derived and validated the FEES Dysphagia Index (FDI) in two temporally independent cohorts (Cohort 1: 2013-2018, N=1,257; Cohort 2: 2021-2025, N=1,686) from a single center. FDI-S averages Penetration-Aspiration Scale (PAS) scores across tested consistencies (0-100 scale); FDI-E uses Yale Pharyngeal Residue scores; FDI-C combines both. Selection bias was quantified using sequential branching-tree inverse probability weighting (IPW). Worst PAS overestimated severity by 24%; FDI deviated by <2%. FDI-C was significantly superior to Worst PAS for hospital-acquired pneumonia (HAP; AUC 0.70 vs. 0.60, p<0.001), mortality (0.71 vs. 0.62, p=0.040), and restricted oral intake (0.90 vs. 0.74, p<0.001), and statistically equivalent to clinician-rated severity. FDI-C mapped linearly onto ordinal Functional Oral Intake Scale values (FOIS; proportional odds RCS p=0.99). With functional status and diagnosis, FDI-C reconstructed the clinicians oral intake recommendation with AUC up to 0.93. The FDI-C-mortality relationship was sigmoidal with a clinically relevant transition zone between [~]50 and [~]85. FDI-C is a bias-resilient, bedside-calculable score with interval-scale properties that captures expert clinical judgment, suitable as both a clinical decision support tool and a continuous research endpoint.

The cerebellum rapidly integrates with cerebral networks during infancy and shows consistent structural and functional alterations in Autism Spectrum Disorder (ASD), suggesting that early cerebellar development may be consequential for later behavioral and psychiatric outcomes. Yet, little is known about the effect of ASD genetic liability on cerebello-cerebral functional connectivity in infancy or whether effects may differ by biological sex. Here, we leveraged neonatal functional magnetic resonance imaging, genetic, and behavioral follow-up data from the Developing Human Connectome Project (dHCP) to examine the relationship between ASD polygenic scores (PGS) and functional connectivity of cerebellar regions associated with sensorimotor and social-cognitive functions in 198 term-born neonates (mean age: 9.7 days). We report widespread sex differences in neonatal cerebello-cerebral connectivity that are regionally specific across cerebellar subdivisions. Across the full sample, elevated ASD PGS predicted alterations in cerebello-cerebral connectivity, with hemisphere-dependent differences in sensorimotor cerebellar connectivity with temporal cortex, and hyperconnectivity between the right social-cognitive seed and posterior cingulate. Notably, elevated ASD PGS predicted opposing patterns of cerebello-cerebral connectivity in males and females, including male hyperconnectivity between the right sensorimotor cerebellum and default mode areas, and female hyperconnectivity between the right social-cognitive seed and sensorimotor cortex. Connectivity associated with elevated ASD PGS showed nominal, sex-specific associations with 18-month language ability, attention problems, and emotional reactivity. Our findings show that ASD PGS influences the functional configuration of the cerebellum at birth and suggest that underlying cerebellar connectivity profiles associated with ASD may partially underlie distinct behavioral presentations in males and females.

Disability worsening is the critical long-term outcome in multiple sclerosis, yet the Expanded Disability Status Scale incompletely captures neurological deterioration and has limited sensitivity in the short time windows of clinical trials. Composite endpoints incorporating functional measures have been proposed to address these limitations, but whether they reliably improve detection of treatment effects has not been established across trials. We conducted a post-hoc analysis of individual patient data from ten phase III randomised controlled trials (ASCEND, BRAVO, CONFIRM, DEFINE, EXPAND, INFORMS, OLYMPUS, OPERA I/II, and ORATORIO; n = 9,369), spanning relapsing-remitting and progressive multiple sclerosis. Confirmed disability worsening was defined using harmonised criteria with the msprog package and confirmed at 24 weeks. Treatment effects were estimated using Cox proportional hazards models and combined across trials in a one-stage individual patient data framework. Composite endpoints were constructed from the Expanded Disability Status Scale, the timed 25-foot walk test, and the nine-hole peg test using logical unions (OR-type), intersections (AND-type), and majority-vote structures. Sensitivity to treatment effect was quantified using Z-scores (the ratio of the pooled log-hazard ratio to its standard error) and compared to the Expanded Disability Status Scale reference using interaction tests. Event rates varied across components: the timed walk test generated the highest rates (up to 46.8%) while the nine-hole peg test generated the lowest (as low as 2.1%). OR-type composite endpoints showed weaker treatment effects than the Expanded Disability Status Scale alone, with the largest reductions in sensitivity observed for endpoints incorporating the timed walk test ({Delta}Z up to +2.26; interaction p = 0.004). These findings were confirmed across disease subtypes and were pronounced in relapsing-remitting trials, where no composite endpoint outperformed the Expanded Disability Status Scale. In progressive multiple sclerosis, the combination of the Expanded Disability Status Scale and the nine-hole peg test showed numerically stronger treatment effects ({Delta}Z = -1.65), though interaction tests did not reach statistical significance (p = 0.051). Composite endpoints do not systematically improve treatment effect detection in multiple sclerosis trials. Increased event capture driven by the timed walk test introduces noise that dilutes the treatment signal rather than amplifying it, highlighting that event rate and endpoint quality are not interchangeable. Upper limb function assessed by the nine-hole peg test provides complementary and specific information, particularly in progressive disease. The combination of global disability and upper limb measures represents a promising direction for future endpoint development in progressive multiple sclerosis trials, warranting validation.

Behavioral and psychological symptoms of dementia (BPSD) are common, profoundly troubling to patients and caregivers, and difficult to treat, yet their molecular underpinnings remain poorly understood. Here, we generated the first brain proteomic dataset with BPSD phenotyping, profiling the dorsolateral prefrontal cortex of 376 donors from three cohorts spanning nine BPSD domains assessed in life. Protein associations with BPSD were examined using complementary approaches - domain-specific BPSD, multi-domain BPSD, and latent factor modeling - and integrated via cross-cohort meta-analysis. Four proteins (NMT1, DCAKD, DNPH1, and HIBADH) were associated with anxiety in dementia and five proteins (ABL1, SAP18, PLXND1, CTRB2, and LDHD) with multi-domain BPSD or BPSD latent factors after adjusting for sex, age, and other covariates (FDR < 0.05). Additionally, eight protein co-expression networks were associated with BPSD across cohorts. These results link BPSD to dysregulation of synaptic signaling, protein folding, and humoral immune response, providing a molecular framework for therapeutic discovery.

Pain captures attention and interferes with executive and motor processes but task performance may be preserved at the cost of more effort. In a preregistered fMRI study, 40 participants performed a visuomotor force-matching task at two force levels under individually calibrated painful or non-painful thermal stimulation, while reporting the intensity of perceived effort. Maintaining task performance under pain was associated with increased perceived effort and recruited brain regions involved in pain modulation and cognitive control. Region-of-interest analysis showed perceived effort was consistently linked to decreased anterior midcingulate cortex activity, whereas supplementary motor area contributions varied depending on its role in motor execution or pain processing. Across experimental condition, motor, pain-modulatory and cognitive-control regions were associated with effort perception. Independently of condition, effort perception was modulated by ventromedial prefrontal cortex and ventral striatum. These findings indicate that effort perception reflects brain activity within areas involved in motor, executive and valuation processes.

Post-stroke cognitive recovery is difficult to predict using focal lesion characteristics alone. The brain's capacity to maintain cognitive function depends also on structural integrity of the whole brain. One way to measure brain health is through the severity of cerebral small vessel disease (CSVD) markers, which reflect aging-related pathologies that erode structural integrity. Here, we propose a composite measure of CSVD (cCSVD) integrating three independently validated biomarkers automatically quantified using T1-weighted MRIs: white matter hyperintensity volume (WMH; representing vascular injury), perivascular space count (PVS; putative glymphatic clearance), and brain-predicted age difference (brain-PAD; structural atrophy). We hypothesize that cCSVD, which captures the shared variance across these CSVD biomarkers, will be a robust indicator of whole-brain structural integrity and predict cognitive changes 3 months after stroke. We analyzed 65 early subacute stroke survivors with assessments within 21 days (baseline) and at 90 days (follow-up) post-stroke. WMH volume, PVS count, and brain-PAD were quantified from baseline T1-weighted MRIs, and then residualized for age, sex, days since stroke, and intracranial volume. Principal component analysis (PCA) of the residualized biomarkers was used to derive cCSVD. Beta regression with stability selection using LASSO was used to model three outcomes: baseline Montreal Cognitive Assessment (MoCA) scores, follow-up MoCA scores, and longitudinal change (follow-up score adjusted for baseline score). Logistic regression was used to test if baseline cCSVD predicted improvement in those with baseline cognitive impairment (MoCA < 26). The PCA revealed that the first principal component (PC1) explained 43.1% of the total variance among WMH volume, PVS count, and brain-PAD. The three biomarkers contributed nearly equally to PC1, which was subsequently used as the baseline cCSVD score. Lower baseline cCSVD was significantly associated with better MoCA scores at follow-up ({beta} = -0.19, p = 0.009), even after adjusting for baseline MoCA ({beta} = -0.12, p = 0.042), and, importantly, outperformed all individual biomarkers. Furthermore, lower cCSVD at baseline significantly increased the likelihood of improving to cognitively unimpaired status at three months (OR = 0.34, p = 0.036), independent of age and education. The composite CSVD captures the additive impact of vascular injury, glymphatic dysfunction, and structural atrophy on recovery in a way that individual measures do not. cCSVD accounts for shared variance across these domains, reflecting a patient's latent capacity for cognitive recovery, where relative integrity in one CSVD domain may mitigate effects of another. This automated, T1-based framework offers a scalable tool for predicting post-stroke recovery.