Brain

Hyperpolarization-activated cyclic nucleotide-gated 1 channels (HCN1) mediate the Ih cationic current and play a central role in regulating neuronal excitability and synaptic integration. HCN1 is predominantly expressed in the neocortex and hippocampus. Pathogenic variants in HCN1 have been increasingly identified in individuals presenting with a broad spectrum of epileptic disorders, ranging from severe developmental and epileptic encephalopathy (DEE) to milder epilepsies. Here, we used patch-clamp electrophysiology in combination with confocal imaging in HEK293 cells to functionally characterize 43 HCN1 variants found in patients presenting with neurodevelopmental disorders, with or without epilepsy. Based on their biophysical properties, we defined four functional classes: (I) low or no current, (II) hyperpolarizing (i.e. left) shift in voltage dependence, (III) depolarizing (i.e. right) shift in voltage dependence, and (IV) generation of an instantaneous current. Integration of this functional classification with detailed clinical data from a cohort of 49 patients revealed a striking genotype-phenotype correlation. Loss-of-function variants were strongly enriched among individuals without epilepsy or with milder generalized phenotypes, whereas gain-of-function and mixed variants were predominantly associated with epilepsy, including all cases of DEE. Notably, non-epileptic cases clustered within a subgroup of loss-of-function variants affecting the selectivity filter. We further show that allosteric modulators, including the peptides NB6 and TRIP8bnano and the small molecule J&J12e, normalize the functional properties of mutant HCN1 channels in three classes. These findings establish a clinically relevant framework for interpreting HCN1 gain- and loss-of-function variants suggesting that the direction of channel dysfunction is a major determinant of epilepsy risk and severity.

Epileptic seizures exhibit marked phenotypic heterogeneity that reflects distinct underlying network mechanisms, yet these differences are incompletely captured by current clinical classifications. Computational models offer a principled approach to infer latent excitation-inhibition dynamics from intracranial EEG, enabling mechanism-informed seizure characterization. We analyzed 205 seizures from 15 patients with drug-resistant epilepsy from the European Epilepsy Database, covering seven clinically annotated seizure onset patterns. Using the Wendling neural mass model, we fitted five-second iEEG segments by optimizing synaptic excitation and inhibition parameters across four temporal windows spanning 60 s before to 25 s after seizure onset. Model-derived excitation-inhibition changes distinguished seizure types significantly above chance. Classification performance was strongest when combining excitation and inhibition parameters, with peridendritic inhibition being the single most discriminative parameter. Seizure-type-specific signatures were detectable not only during seizure onset and within seizure onset zones, but already during interictal periods and in non-onset channels, indicating that seizure mechanisms are preconfigured tens of seconds before clinical onset and extend beyond focal onset regions. Although all seizure types showed increases in both excitation and inhibition during seizure transition, their timing and magnitude differed systematically. In particular, our study supports and extends prior evidence that high-amplitude slow (HAS) seizures are driven by localized hyperexcitation within the seizure onset zone, whereas low-amplitude fast (LAF) seizures arise from inhibition-driven network mechanisms. Excitation-inhibition signatures were further linked to individual patient characteristics and surgical outcomes, highlighting their potential clinical relevance.

Hippocampal sclerosis is a frequent finding in pediatric epilepsy surgery and has traditionally been regarded as an acquired lesion. It commonly co-occurs with focal cortical dysplasia (FCD IIIa), yet whether hippocampal injury is secondary to seizures or reflects a shared underlying etiology remains unresolved. Here we identified somatic variants activating the RAS-MAPK pathway in 40% of patients with hippocampal sclerosis, but in none with non-sclerotic hippocampus. Gain-of-function variants in PTPN11 were the most common finding, with mutations present in both cortex and hippocampus and enriched in hippocampal neurons, consistent with a shared developmental origin. In mice, Ptpn11D61Y mutants developed profound hippocampal degeneration and gliosis following subthreshold kainic acid exposure, whereas wild-type controls were unaffected. p38-dependent stress pathways were upregulated in patients and mice, suggesting a mechanism through which ERK-p38 crosstalk lowers the threshold for seizure-induced injury. These results provide a genetic explanation for FCD IIIa, elucidate the role of somatic mutations within the RAS-MAPK pathway in driving hippocampal sclerosis, and provide a target for pathway-specific interventions for intractable seizures.

Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy is an established thermoablative treatment for tremor. Although outcomes in Essential Tremor approach those of deep brain stimulation, efficacy in tremor-dominant Parkinsons disease (TDPD) is often less durable, with tremor relapse reported in 30-50% of cases. Previous associations with lesion size or age remain descriptive and do not explain why anatomically similar lesions yield divergent long-term outcomes. We retrospectively analyzed 20 patients with TDPD who underwent unilateral MRgFUS. Lesions were used as seeds for normative structural and functional connectivity analyses. Durable tremor control was associated with lesion showing stronger functional connectivity to primary motor (M1), primary somatosensory (S1), and supplementary motor areas, as well as inferior frontal and occipital cortices. In contrast, relapse was linked to greater connectivity with cerebellar motor and associative regions. Structurally, optimal lesions converged at the triangular interface of the nuclei ventralis intermedius, ventralis oralis, and ventro caudalis. Streamlines associated with better outcomes projected posteriorly towards S1, with M1 delineating an anterior functional boundary beyond which outcomes declined. Structural fingerprints emphasized posterior sensorimotor areas as critical therapeutic outputs. Findings define a connectivity-based substrate of durable tremor suppression and support the development of individualized, network-guided targeting strategies for MRgFUS in TDPD

Cognitive difficulties are increasingly recognized in juvenile myoclonic epilepsy (JME), but scalable biomarkers linking resting-state brain dynamics to general mental ability remain limited. Here, we combined topological data analysis, graph signal processing, machine learning, inverse Langevin modeling, and biophysical simulations to test whether EEG-derived network dynamics capture individual differences in general mental ability in JME. We studied 54 patients with JME and 45 healthy controls using resting-state high-density EEG and the raw estimated full-scale score derived from the Wechsler Abbreviated Scale of Intelligence (WASI), used here as an index of general mental ability. Subject-specific low-alpha activity was reconstructed with generalized eigendecomposition, and graph-derived features were extracted from the projection of topological and alpha-power signals onto the functional connectome, providing a graph-harmonic description of large-scale brain-state dynamics. In controls, dynamic EEG-derived features significantly predicted general mental ability, whereas the same framework failed in JME. Because prediction in controls was driven mainly by dynamic measures of smoothness (Dirichlet energy), we next examined the temporal organization of alpha-power smoothness using an inverse Langevin framework. Within the patient group, greater thermodynamic rigidity--that is, stronger confinement of fluctuations around preferred network states--was associated with lower general mental ability. Relative to controls, patients also showed lower thermodynamic noise, indicating a reduced tendency to explore alternative network regimes. Biophysical simulations suggested that reduced dendritic arborization can generate rigidity directly, whereas pharmacological stabilization of hyperexcitable circuits can shift the system toward a more rigid, lower-noise regime. Together, these findings suggest that cognition in JME is linked not only to altered resting-state network dynamics but also to stronger confinement of network-state fluctuations, with both intrinsic circuit abnormalities and treatment-related stabilization representing plausible routes to this rigid phenotype.

Pathogenic mutations in STXBP1, which encodes Munc18-1, a synaptic protein essential for synaptic vesicle exocytosis and neurotransmission, and in SCN2A, which encodes the voltage-gated sodium channel Nav1.2 (II subunit), have been identified in patients with epilepsy. Although haploinsufficiency of either Stxbp1 or Scn2a in cortical excitatory neurons induces epileptic phenotypes in mice and a reduction of cortico-striatal, especially cortico-striatal parvalbumin-expressing fast-spiking interneurons (FSIs), excitatory transmission has been suggested to be the basis, the subcortical circuits remain poorly understood. In this study, we investigated which striatal subregions FSIs are responsible for the epileptic seizures. Using chemogenetic approach, we selectively suppressed FSI activity in either the nucleus accumbens (NAc) or the dorsal striatum (caudate-putamen, CPu) of mice. Suppression of FSIs in the NAc induced outwardly-recognized convulsive seizures accompanied by epileptiform discharges in the electrocorticographic (ECoG) analysis, whereas inhibition of FSIs in the CPu resulted in epileptiform discharges without overt convulsions. Notably, focal suppression of FSIs in either the anterior or medial region of the NAc shell (NAcSh), but not in other NAc subregions, was sufficient to trigger convulsive seizures. These findings identify FSIs in the anteromedial shell of the NAc as a critical hub for convulsive seizure generation and provide new insights into the striatal circuit mechanisms underlying STXBP1- or SCN2A-associated epilepsies.

Resting-state electroencephalography (EEG) has been proposed as a scalable source of biomarkers for chronic pain, but its clinical potential remains uncertain. To systematically evaluate this potential, we benchmarked nine modeling strategies, spanning conventional machine learning with handcrafted features to state-of-the-art deep learning. Across 72 configurations of signal representations and model architectures, we trained models to predict self-reported pain intensity, using chronological age decoding as a positive control. Pain prediction performance was limited (R=0.15), with the best results achieved by conventional connectivity-based models. In contrast, age was robustly decoded from the same dataset (R=0.53), confirming technical efficacy. These findings indicate that resting-state EEG contains limited information about inter-individual differences in chronic pain intensity, making it unlikely to yield clinically actionable biomarkers in cross-sectional settings. Instead, its potential may lie in intra-individual modeling of pain dynamics, which could advance individualized mechanistic insights and more personalized treatment of chronic pain.

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy is the most common drug-resistant epilepsy, with surgical resection offering the primary path to seizure freedom. Despite standardized approaches, a substantial proportion of patients experience seizure recurrence, and the neurobiological substrates underlying these divergent outcomes remain unclear. We applied an individualized normative modeling framework to multimodal preoperative MRI data in a group that subsequently underwent surgical resection, to characterize patient-specific structural deviations and identify disease epicenters. Patients who became seizure-free exhibited spatially coherent abnormalities localized to the hippocampus and ipsilateral association regions, anchored in agranular limbic territories and enriched for genes linked to calcium-dependent signaling. Non-seizure-free patients, on the other hand, showed a more heterogeneous and distributed pattern of deviations, consistent with a "temporal-plus" network organization, and broader neuromodulatory dysregulation. Crucially, overlap between resected tissue and network-defined epicenters was closely associated with seizure freedom, independent of total resection volume. These findings provide a multiscale framework for precision surgical planning, shifting the focus from standardized tissue removal to targeted disconnection of patient-specific pathological hubs.

Multiple system atrophy (MSA) is an atypical Parkinsonian disorder marked by oligodendroglial -synucleinopathy and selective neurodegeneration. Although MRI can capture regional atrophy and microstructural alterations in MSA brain, the molecular substrates underlying these phenotypes remain poorly defined. Imaging transcriptomics provides a computational framework to relate spatial imaging patterns to brain-wide gene expression. While this approach has been applied to human MSA, interpretation is constrained by limited experimental control and lack of disease-matched molecular validation. Here, we apply imaging transcriptomics in a controlled preclinical setting by integrating high-resolution ex vivo multimodal MRI with transcriptomic mapping in the PLP-Syn mouse model of MSA. Structural and diffusion MRI revealed distinct patterns of regional atrophy and microstructural abnormalities. Atlas-based analyses associated imaging phenotypes to gene programs related to oligodendrocyte biology, energy metabolism, and neuroinflammation, with modality-specific signatures. These associations were supported by independent RNA-sequencing and showed convergence with human MSA findings. Our work benchmarks MRI-transcriptomic relationships in MSA and provides a translational framework for interpreting imaging biomarkers in synucleinopathies.

Striatal dopamine release defects are an early pathological feature observed in diverse models of Parkinsons disease. However, the underlying molecular mechanisms responsible, and potential links to disease aetiology in humans, have been elusive. Here, we tested the hypothesis that dopamine release deficits are a characteristic feature of disease-relevant human neurons, using human Parkinsons patient iPSC-derived dopamine neurons carrying the SNCA-triplication mutation. We reveal deficits in dopamine release from SNCA-triplication patient-derived neurons, and identify that this is due to reduced dopamine content arising from a lower capacity to store dopamine through reduced expression and function of vesicular monoamine transporter 2 (VMAT2) compared to healthy controls. In turn, by imaging VMAT substrate FFN206, and reporters for synaptic vesicular dynamics, SynaptopHluorin and CypHer5E, we reveal corresponding deficits in the size of either VMAT-containing, presynaptic releasing or recycling vesicle pools. Consistent with diminished synaptic vesicle loading and recycling, the cytosolic turnover of dopamine indicated by the ratio of concentrations of dopamine metabolite DOPAC to dopamine was elevated. By contrast, glutamate release events and VGLUT2 levels in neurons in the same preparations were not disturbed, demonstrating that vesicular dysfunction is limited to vesicles for dopamine. These findings therefore reveal dopamine loading into vesicles as a locus of dysfunction in human Parkinsons-derived neurons. These disturbances will not only drive deficits in dopamine release but could potentially also be detrimental to dopamine neuron viability through an increased burden of oxidative stress associated with elevated cytosolic dopamine, thus contributing to both symptoms and aetiology of Parkinsons pathology and offering a strategic target for improved therapies.

YWHAG Syndrome (Developmental and Epileptic Encephalopathy 56, DEE56) is an ultra- rare childhood epilepsy associated with neurodevelopmental delays, with no therapeutic intervention available. Multiple de novo mutations in the YWHAG gene, encoding for the 14-3-3{gamma} protein, have been identified as causative for YWHAG Syndrome. 14-3-3{gamma} interacts with various targets, including major neurodevelopmental signaling proteins such as components of the ROCK pathway. Despite substantial evidence of the essential role of 14-3-3{gamma} in neurite outgrowth, cytoskeletal rearrangements, and neuronal migration during cortical development, little is known regarding the molecular consequences of YWHAG mutations and their effect on neuronal function and survival. Here, we characterized an isogenic, pluripotent stem cell (iPSC) model of YWHAGR132C/+ cortical neurons. The YWHAGR132C/+iPSC-derived neurons exhibited early cytoskeletal phenotypes, coupled with an elevated calcium baseline, lower frequency of calcium spikes, and reduced network activity. The widespread alterations in the transcriptome of mutant neurons revealed a biphasic dysregulation in the core genes and modulators associated with the ROCK pathway that resulted in maturation-dependent changes to cytoskeletal protein stability and calcium phenotypes. Direct inhibition of ROCK with Y27632 further increased the calcium baseline compared to the isogenic control. Exposure of YWHAGR132C/+ neurons to Trypsin-EDTA revealed underlying cytoskeletal instability, which was partially reversed by lovastatin treatment. Further, lovastatin partially rescued the elevated calcium baseline, but not the frequency or amplitude of calcium spikes. Together, these results suggest decoupling of calcium homeostasis and calcium signaling associated with cytoskeletal instability in YWHAGR132C/+ neurons. These findings lay the groundwork for future mechanistic studies of YWHAG function and molecular therapeutic targets for YWHAG Syndrome and YWHAG-associated conditions.

Polyhydramnios, Megalencephaly, and Symptomatic Epilepsy syndrome (PMSE/STRADA-related disorder) is a rare neurodevelopmental disorder characterized by megalencephaly (ME), early-onset drug-resistant epilepsy, neurocognitive impairment, and high early mortality, often due to status epilepticus. PMSE is caused by a multi-exon deletion in STRADA, encoding STRADA, which regulates the mechanistic target of rapamycin (mTOR) pathway. GABAergic inhibitory interneurons (INs) critically modulate the excitatory:inhibitory balance in cortical and hippocampal networks, and IN deficits contribute to epileptogenesis in several epileptic encephalopathies. However, no studies have investigated INs in PMSE. We used a multimodal approach to study INs in a Strada-/- mouse model engineered with the same causative 5-exon deletion identified in human PMSE. We demonstrate that Strada/STRADA loss causes a reduction of INs in the somatosensory cortex and a corresponding increase in the striatum, representative of remnant ganglionic eminence progenitor origin, in Strada-/- mice and a single PMSE brain tissue specimen. RNA sequencing comparing wildtype to Strada-/- cortex and striatum corroborated these findings, revealing increased IN-related gene expression (e.g., Dlx2) in the striatum and decreased IN-related gene expression (e.g., Pvalb) in the developing cortex. Cytoskeletal (e.g., Tpp3, Kank4, Map1a) and mTOR-associated genes (e.g., Rictor, Cryab) are differentially expressed in the developing cortex, mature striatum, and mature cortex of Strada-/- mice. Functional validation confirmed enlarged INs in mouse and human Strada/STRADA-deficient brain and enhanced S6 phosphorylation in Strada-/- striatum. Together, these findings suggest STRADA/Strada loss contributes to failed IN migration -- the first such report in a developmental, mTOR-associated megalencephaly syndrome -- highlighting INs as a therapeutic target for seizure prevention in PMSE. Key PointsO_LI- Reduced numbers of cortical inhibitory interneurons were observed in the cerebral cortex of Strada-/- mice, with striatal interneuron aggregation C_LIO_LI- Reduced numbers of cortical inhibitory interneurons, with an aggregation in striatum, were observed in human PMSE brain, supporting the observations in Strada-/- mouse C_LIO_LI- Transcriptomic analysis in Strada-/- mice reveals evidence of early developmental interneuron and cytoskeletal dysfunction C_LIO_LI- We introduce a loss of cortical interneurons as a salient feature of PMSE developmental pathogenesis, potentially contributing to a loss of inhibitory modulation C_LIO_LI- This is the first study proposing interneuron migration impairment in the developmental pathogenesis of an mTOR-associated megalencephaly syndrome C_LI

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.

Clinical progression is strongly linked to grey matter atrophy in multiple sclerosis (MS), detectable early on MRI and progressing non-randomly across the brain. However, the mechanisms driving its spatio-temporal progression and individual variability remain unclear. Using MRIs from 2,187 participants, alongside normative data, we systematically investigated network-based mechanisms underlying MS-related atrophy. Regional atrophy colocalised with functional cortical hubs, supporting the nodal stress hypothesis, and propagated along anatomical and functional connections, consistent with transneuronal degeneration. Lesional disconnection and transcriptomic vulnerability played marginal roles. Patient- and subgroup-level analyses revealed that network-based mechanisms are specifically linked to MS-related neurodegeneration and may operate differently in distinct subtypes or disease phases. Atrophy patterns were anchored to the connectivity profiles of disease epicentres involving the visual, sensorimotor, and temporal cortices, and the hippocampi and thalami. Network-based measures enhanced the prediction of future atrophy progression in individual with MS, providing a mechanistic framework to understand neurodegeneration in MS.

Thalamic neuromodulation is clinically effective in drug{-}resistant epilepsy, suggesting critical contributions of the thalamus to the epileptogenic process. However, the underlying electrophysiologic mechanisms remain poorly characterized. Converging evidence implicates the thalamus in shaping large{-}scale functional interactions across the cortex. We hypothesized that ictal changes in thalamic activity track cortical network dynamics associated with seizure propagation. We analyzed stereo{-}electroencephalography recordings from 16 patients with focal epilepsy (255 seizures) with simultaneous sampling of the thalamus (anterior nucleus, N=14; pulvinar, N=11) and cortex. Cortical regions of interest included the seizure onset zone (SOZ), surrounding cortices (near{-}SOZ), and control regions from the contralateral hemisphere. We characterized seizure dynamics across spatial scales, from local activity within each region to network{-}level, inter{-}regional interactions. Local activity was decomposed into its periodic (oscillatory) and aperiodic components. Network interactions were characterized by directed functional connectivity computed with a multivariate method. Seizures were associated with increased broadband power (a proxy for neuronal population firing rates) and low{-}frequency rhythmic activity across the thalamocortical network relative to interictal baseline levels. In contrast, consistent changes in aperiodic slope (a putative marker of excitation{-}inhibition balance) were specific to the thalamus, which showed an early and sustained steepening (i.e., more negative slope). While local rhythms were heterogeneous across the canonical frequency bands, inter{-}regional interactions predominantly involved the beta band (13{-}30 Hz). Shortly after onset, both forward outflow from SOZ to near{-}SOZ and feedback inflow in the reverse direction were increased. These bidirectional effects were expressed via both a direct cortico{-}cortical pathway and an indirect transthalamic route, operating in parallel. These dynamics were further stratified based on seizure subtypes, leveraging the fact that there was minimal propagation of ictal activity to the near{-}SOZ in subclinical seizures. The ictal drop in thalamic aperiodic slope was primarily observed in clinical seizures. At the network level, whereas SOZ[->]near{-}SOZ outflow was present across seizure types, reverse feedback was particularly enhanced in clinical seizures. Multivariable regression showed that the degree of thalamic slope steepening uniquely tracked seizure{-}to{-}seizure fluctuations in the strength of near{-} SOZ[->]SOZ feedback, and further predicted seizure durations. Together these findings highlight thalamic aperiodic slope as an index of cortical network dynamics linked to seizure propagation, with potential clinical utility for further development of physiology{-}informed precision neuromodulation.

Epilepsy is among the most prevalent neurological disorders, affecting millions of individuals worldwide at every stage of life. Characterised by recurrent seizures, epilepsy can significantly disrupt daily functioning, education, employment, and overall quality of life. Despite advances in neuroimaging, current approaches often overlook the individualised nature of brain disruptions in epilepsy. Here, we introduce an individualised functional Magnetic Resonance Imaging (fMRI) framework, Adjusted Local Estimates of Connectivity (ALEC), to detect patient-specific brain local connectivity abnormalities across distinct clinical stages of epilepsy. To do so, we analysed movie-watching multi-echo fMRI in 102 heterogeneous epilepsy patients (34 with drug-resistant epilepsy; 34 with a new diagnosis of epilepsy; 34 after a first seizure) and 68 socioeconomically matched healthy controls. ALEC is a voxel-wise modified z-score and estimates deviations in Regional Homogeneity from healthy norms at the individual level. Our results show that whole-brain averaged ALEC scores were significantly higher in drug-resistant epilepsy compared to early-stage cohorts. Several drug-resistant individuals exhibited pronounced ALEC elevations in the hippocampus, thalamus and brainstem alongside widespread cortical decreases, although these patterns did not reach group-level significance. Age and seizure duration correlated positively with ALEC, but only within the drug-resistant group. We also highlight a subset of cases that demonstrated concordance with ALEC and the patients clinical history and investigations, including epileptogenic pathology. Combined, our findings highlight the importance of individualised neuroimaging approaches for understanding epilepsy. By revealing biologically concordant local connectivity patterns--marked by local hyperconnectivity in drug-resistant cases worsening with aging--ALEC provides a potential pathway for precision brain mapping of patients at risk for drug resistance.

A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). We screened individuals who received WGS analyses at Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significant phenotypic enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. We identified 14 individuals with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5 domains. All individuals presented with a highly concordant, severe DEE, characterised by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with paediatric epilepsy (two-sided Monte Carlo permutation test, p=0.005). RNA sequencing analyses in fibroblast tissues showed a clear separation of aberrant mutually exclusive exon and alternate 3 splice site events between RNU2-2 individuals and controls, which was not detectable in blood. In summary, we present deep phenotyping data and transcriptomic analyses which provide support for rare, 5 clustering biallelic RNU2-2 variants causing a novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

Mesial temporal lobe epilepsy (TLE) is the most common form of acquired epilepsy involving the hippocampus and is a frequent sequelae of head trauma. TLE is associated with refractory seizures and significant cognitive deficits. Yet, the gene expression patterns and cell types driving epileptogenesis and the associated cognitive deficits are poorly understood. To address this, we performed single nucleus RNA sequencing on hippocampal tissue from mice at 3 and 6 weeks following pilocarpine-induced status epilepticus, a robust model of TLE. At these early timepoints, epilepsy samples showed reductions in specific Cck and Lamp5-Lhx6 interneuron subclusters, alongside increases in Cajal-Retzius cells, dentate granule (DG) cell precursors, and a mature DG cell subcluster. Among glia, an astrocyte subcluster and a markedly expanded microglia sublcuster were increased. We term this microglia population epilepsy-associated microglia (EAM). The transcriptomic profile of EAM partially overlaps with microglia described in models of Alzheimers disease and traumatic brain injury, with enrichment of genes including Myo1e and Igf1. EAM display amoeboid morphology, can be found in dense clumps around pyramidal and granule cell body layers, and exhibit enlarged vesicles and mitochondria on electron microscopy. Cell-cell interaction analysis predict that DG cells are the main interaction partners of EAM. This dataset recapitulates known cellular alterations in TLE while defining their underlying transcriptomic programs, enabling mechanistic dissection of the key processes driving epileptogenesis.

Parkinsons disease is characterized by dopaminergic neuron loss and accumulation of -synuclein aggregates in the brain. G51D -synuclein knock-in mice provide a genetically and clinically relevant model of disease, exhibiting early olfactory deficits, age-dependent motor impairment, and progressive phospho--synuclein accumulation. In multiple Parkinsons disease models, striatal cholinergic and parvalbumin interneurons, as well as astrocytes, lose primary cilia and the neurotrophic signaling needed to sustain dopaminergic neurons. We show here that G51D--synuclein mice share these phenotypes. Phospho-Ser129 -synuclein accumulation correlates with cilia loss in cholinergic interneurons but not in medium spiny neurons that accumulate higher phospho--synuclein levels. In the piriform cortex, parvalbumin neurons lose primary cilia and downregulate Neurturin, potentially contributing to olfactory dysfunction. Within the peripheral olfactory epithelium, horizontal basal cells lose cilia, whereas multi-ciliated olfactory sensory neuron cilia remain intact. These findings reveal convergent cellular vulnerabilities across Parkinsons disease models and highlight a pathogenic role for impaired ciliary signaling. TeaserLoss of primary cilia may contribute to dopamine neuron loss in both inherited and common Parkinsons disease.

Parkinsons disease (PD) is a progressive movement disorder that affects over ten million individuals worldwide. While the involvement of genetically-driven cellular mechanisms in PD pathogenesis is well-established, there is increasing evidence that epigenetic dysregulation also plays a key role. We profiled genome-wide DNA methylation in isolated neuronal, oligodendrocyte and other glial nuclei populations from the prefrontal cortex of 71 PD and 56 control individuals. We identified seven significant differentially methylated positions in neuronal nuclei associated with PD. All these sites were hypermethylated in PD, with five of the differentially methylated positions located in the following genes: ROBO4, SSBP2, PDE4B, NPHP1, and HSD17B12. No differentially methylated positions were observed in oligodendrocyte or other glial nuclei, highlighting the neuronal specificity of PD-associated methylation changes. Comparison with a large bulk brain meta-analysis of Lewy body pathology confirmed concordant directionality for [~]79% of neuronal differentially methylated positions, indicating that bulk tissue signals primarily reflect neuronal alterations. Together, these findings provide the first cell type-resolved map of DNA methylation changes in the PD cortex, revealing neuronal-specific hypermethylation at novel loci and emphasizing the importance of cell type-specific analyses in disentangling the molecular heterogeneity of PD. This study lays the groundwork for future multi-omics and region-specific studies aimed at uncovering mechanisms underlying disease vulnerability and progression at the cellular level.