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Abstract Objective Perineuronal nets (PNN) are specialized extracellular matrix (ECM) components of the central nervous system, frequently accumulating at the surface of inhibitory GABAergic interneurons. While an altered distribution of PNN has been observed in neurological disorders including Alzheimer's disease, schizophrenia and epilepsy, their anatomical distribution also changes during physiological brain maturation and aging. Such an age‐dependent shift was experimentally associated also with hippocampal engram formation during brain maturation. Our aim was to histopathologically assess PNN in the hippocampus of adult and pediatric patients with temporal lobe epilepsy (TLE) compared to age‐matched post‐mortem control subjects and to compare PNN‐related changes with memory impairment observed in our patient cohort. Methods Sixty‐six formalin‐fixed and paraffin‐embedded tissue specimens of the human hippocampus were retrieved from the European Epilepsy Brain Bank. Twenty‐nine patients had histopathologically confirmed hippocampal sclerosis (HS), and eleven patients suffered from TLE without HS. PNN were immunohistochemically visualized using an antibody directed against aggrecan and manually counted from hippocampus subfields and the subiculum. Results PNN density increased with age in both human controls and TLE patients. However, their density was significantly higher in all HS patients compared to age‐matched controls. Intriguingly, TLE patients presented presurgically with better memory when their hippocampal PNN density was higher (p

Abstract Focal Cortical Dysplasia (FCD) is a frequent cause of drug-resistant focal epilepsy in children and young adults. The international FCD classifications of 2011 and 2022 have identified several clinico-pathological subtypes, either occurring isolated, i.e., FCD ILAE Type 1 or 2, or in association with a principal cortical lesion, i.e., FCD Type 3. Here, we addressed the DNA methylation signature of a previously described new subtype of FCD 3D occurring in the occipital lobe of very young children and microscopically defined by neuronal cell loss in cortical layer 4. We studied the DNA methylation profile using 850 K BeadChip arrays in a retrospective cohort of 104 patients with FCD 1 A, 2 A, 2B, 3D, TLE without FCD, and 16 postmortem specimens without neurological disorders as controls, operated in China or Germany. DNA was extracted from formalin-fixed paraffin-embedded tissue blocks with microscopically confirmed lesions, and DNA methylation profiles were bioinformatically analyzed with a recently developed deep learning algorithm. Our results revealed a distinct position of FCD 3D in the DNA methylation map of common FCD subtypes, also different from non-FCD epilepsy surgery controls or non-epileptic postmortem controls. Within the FCD 3D cohort, the DNA methylation signature separated three histopathology subtypes, i.e., glial scarring around porencephalic cysts, loss of layer 4, and Rasmussen encephalitis. Differential methylation in FCD 3D with loss of layer 4 mapped explicitly to biological pathways related to neurodegeneration, biogenesis of the extracellular matrix (ECM) components, axon guidance, and regulation of the actin cytoskeleton. Our data suggest that DNA methylation signatures in cortical malformations are not only of diagnostic value but also phenotypically relevant, providing the molecular underpinnings of structural and histopathological features associated with epilepsy. Further studies will be necessary to confirm these results and clarify their functional relevance and epileptogenic potential in these difficult-to-treat children.

Abstract Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks.

The human brain has a highly complex structure both on the microscopic and on the macroscopic scales. Increasing evidence has suggested the role of mechanical forces for cortical folding – a classical hallmark of the human brain. However, the link between cellular processes at the microscale and mechanical forces at the macroscale remains insufficiently understood. Recent findings suggest that an additional proliferating zone, the outer subventricular zone (OSVZ), is decisive for the particular size and complexity of the human cortex. To better understand how the OSVZ affects cortical folding, we establish a multifield computational model that couples cell proliferation in different zones and migration at the cell scale with growth and cortical folding at the organ scale by combining an advection-diffusion model with the theory of finite growth. We validate our model based on data from histologically stained sections of the human fetal brain and predict 3D pattern formation. Finally, we address open questions regarding the role of the OSVZ for the formation of cortical folds. The presented framework not only improves our understanding of human brain development, but could eventually help diagnose and treat neuronal disorders arising from disruptions in cellular development and associated malformations of cortical development.

Abstract Focal malformations of cortical development (MCD) are linked to somatic brain mutations occurring during neurodevelopment. Mild malformation of cortical development with oligodendroglial hyperplasia in epilepsy (MOGHE) is a newly recognized clinico-pathological entity associated with pediatric drug-resistant focal epilepsy, and amenable to neurosurgical treatment. MOGHE is histopathologically characterized by clusters of increased oligodendroglial cell densities, patchy zones of hypomyelination, and heterotopic neurons in the white matter. The molecular etiology of MOGHE remained unknown so far. We hypothesized a contribution of mosaic brain variants and performed deep targeted gene sequencing on 20 surgical MOGHE brain samples from a single-center cohort of pediatric patients. We identified somatic pathogenic SLC35A2 variants in 9/20 (45%) patients with mosaic rates ranging from 7 to 52%. SLC35A2 encodes a UDP-galactose transporter, previously implicated in other malformations of cortical development (MCD) and a rare type of congenital disorder of glycosylation. To further clarify the histological features of SLC35A2-brain tissues, we then collected 17 samples with pathogenic SLC35A2 variants from a multicenter cohort of MCD cases. Histopathological reassessment including anti-Olig2 staining confirmed a MOGHE diagnosis in all cases. Analysis by droplet digital PCR of pools of microdissected cells from one MOGHE tissue revealed a variant enrichment in clustered oligodendroglial cells and heterotopic neurons. Through an international consortium, we assembled an unprecedented series of 26 SLC35A2-MOGHE cases providing evidence that mosaic SLC35A2 variants, likely occurred in a neuroglial progenitor cell during brain development, are a genetic marker for MOGHE.

Abstract Objective To comprehensively describe the pathological features of neurons in patients with ovarian teratomas and paraneoplastic anti-NMDAR encephalitis (anti-NMDARE), emphasizing on NMDA-receptor expression and infiltrating lymphocytes. Methods A retrospective study was performed in a large series of 159 patients from the West China Hospital. We retrospectively identified 12 patients with paraneoplastic anti-NMDARE (11 case with ovarian teratomas and 1 case with mixed germ cell tumor), which were compared to 35 patients with teratomas and no encephalitis and to 147 patients with anti-NMDARE and no evidence for tumors. Patient history and outcome were reviewed from the clinical charts and compared between all three groups. Histopathological examination, including double-immunofluorescence of NMDAR subunits and IgG was performed in all teratoma tissues. Magnetic Luminex Assay Human Premixed Multi-Analyte Kit was performed to investigate cytokines profile of CSF. Results Patients with paraneoplastic anti-NMDARE had a more severe clinical presentation, i.e. they required more mechanical ventilation and intensive care (p

Abstract Brain tumors represent the second most frequent etiology in patients with focal seizure onset before 18 years of age and submitted to epilepsy surgery. Hence, this category of brain tumors, herein defined as low-grade, developmental, epilepsy-associated brain tumors (LEAT) is different from those frequently encountered in adults as (A): 77% of LEAT occur in the temporal lobe; (B): the vast majority of LEAT are of low malignancy and classified as WHO I°; (C): LEAT are often composed of mixed glial and neuronal cell components and present with variable growth patterns including small cysts or nodules; (D): LEAT do not share common gene driving mutations, such as IDH1 or 1p/19q co-deletions. Characteristic entities comprise the ganglioglioma (GG), the dysembryoplastic neuroepithelial tumor (DNT), the angiocentric glioma (AG), the isomorphic diffuse glioma (IDG) and the papillary glio-neuronal tumor (PGNT), representing 73.2% of 1680 tumors collected in a large German series of 6747 patients submitted to epilepsy surgery. In the realm of exciting discoveries of genetic drivers of brain tumors new genes have been also reported for LEAT. BRAF V600E mutations were linked to GG with CD34 expression, FGFR1 mutations to DNT, MYB alterations to AG and also IDG and PRKCA fusions to PGNT, suggesting the possibility to also develop a genetically driven tumor classification scheme for LEAT. Rare availability of LEAT in a single center is a challenging obstacle, however, to systematically unravel the neurobiological nature and clinical behavior of LEAT. Other challenges in need of clarification include malignant tumor progression of LEAT entities, seizure relapse in patients following bulk tumor resection and the controversial issue of associated focal cortical dysplasia as additional pathomechanism. In order to advance our understanding and promote reliable diagnostic work-up of LEAT, we recommend, therefore, international collaboration to achieve our goals.

Abstract Introduction We investigated the frequency, neuropathology, and phenotypic characteristics of spastic paraplegia (SP) that precedes dementia in presenilin 1 (PSEN1) related familial Alzheimer's disease (AD). Methods We performed whole exome sequencing (WES) in 60 probands with hereditary spastic paraplegia (HSP) phenotype that was negative for variants in known HSP‐related genes. Where PSEN1 mutation was identified, brain biopsy was performed. We investigated the link between HSP and AD with PSEN1 in silico pathway analysis and measured in vivo the stability of PSEN1 mutant γ‐secretase. Results We identified a PSEN1 variant (p.Thr291Pro) in an individual presenting with pure SP at 30 years of age. Three years later, SP was associated with severe, fast cognitive decline and amyloid deposition with diffuse cortical plaques on brain biopsy. Biochemical analysis of p.Thr291Pro PSEN1 revealed that although the mutation does not alter active γ‐secretase reconstitution, it destabilizes γ‐secretase‐amyloid precursor protein (APP)/amyloid beta (Aβn) interactions during proteolysis, enhancing the production of longer Aβ peptides. We then extended our analysis to all 226 PSEN1 pathogenic variants reported and show that 7.5% were associated with pure SP onset followed by cognitive decline later in the disease. We found that PSEN1 cases manifesting initially as SP have a later age of onset, are associated with mutations located beyond codon 200, and showed larger diffuse, cored plaques, amyloid‐ring arteries, and severe CAA. Discussion We show that pure SP can precede dementia onset in PSEN1‐related familial AD. We recommend PSEN1 genetic testing in patients presenting with SP with no variants in known HSP‐related genes, particularly when associated with a family history of cognitive decline.

Background: Recent findings have demonstrated that hippocampal subfields can be selectively affected in different disease states, which has led to efforts to segment the human hippocampus with in vivo magnetic resonance imaging (MRI). However, no studies have examined the histological accuracy of subfield segmentation protocols. The presence of MRI-visible anatomical landmarks with known correspondence to histology represents a fundamental prerequisite for in vivo hippocampal subfield segmentation. In the present study, we aimed to: 1) develop a novel method for hippocampal body segmentation, based on two MRI-visible anatomical landmarks (stratum lacunosum moleculare [SLM] & dentate gyrus [DG]), and assess its accuracy in comparison to the gold standard direct histological measurements; 2) quantify the accuracy of two published segmentation strategies in comparison to the histological gold standard; and 3) apply the novel method to ex vivo MRI and correlate the results with histology. Methods: Ultra-high resolution ex vivo MRI was performed on six whole cadaveric hippocampal specimens, which were then divided into 22 blocks and histologically processed. The hippocampal bodies were segmented into subfields based on histological criteria and subfield boundaries and areas were directly measured. A novel method was developed using mean percentage of the total SLM distance to define subfield boundaries. Boundary distances and subfield areas on histology were then determined using the novel method and compared to the gold standard histological measurements. The novel method was then used to determine ex vivo MRI measures of subfield boundaries and areas, which were compared to histological measurements. Results: For direct histological measurements, the mean percentages of total SLM distance were: Subiculum/CA1 = 9.7%, CA1/CA2 = 78.4%, CA2/CA3 = 97.5%. When applied to histology, the novel method provided accurate measures for CA1/CA2 (ICC = 0.93) and CA2/CA3 (ICC = 0.97) boundaries, but not for the Subiculum/CA1 (ICC = −0.04) boundary. Accuracy was poorer using previous techniques for CA1/CA2 (maximum ICC = 0.85) and CA2/CA3 (maximum ICC = 0.88), with the previously reported techniques also performing poorly in defining the Subiculum/CA1 boundary (maximum ICC = 0.00). Ex vivo MRI measurements using the novel method were linearly related to direct measurements of SLM length (r2 = 0.58), CA1/CA2 boundary (r2 = 0.39) and CA2/CA3 boundary (r2 = 0.47), but not for Subiculum/CA1 boundary (r2 = 0.01). Subfield areas measured with the novel method on histology and ex vivo MRI were linearly related to gold standard histological measures for CA1, CA2, and CA3/CA4/DG. Conclusions: In this initial proof of concept study, we used ex vivo MRI and histology of cadaveric hippocampi to develop a novel segmentation protocol for the hippocampal body. The novel method utilized two anatomical landmarks, SLM & DG, and provided accurate measurements of CA1, CA2, and CA3/CA4/DG subfields in comparison to the gold standard histological measurements. The relationships demonstrated between histology and ex vivo MRI supports the potential feasibility of applying this method to in vivo MRI studies.

Background and Objective: Patients with presumed nonlesional focal epilepsy-based on either MRI or histopathologic findings-have a lower success rate of epilepsy surgery compared with lesional patients. In this study, we aimed to characterize a large group of patients with focal epilepsy who underwent epilepsy surgery despite a normal MRI and had no lesion on histopathology. Determinants of their postoperative seizure outcomes were further studied., Methods: We designed an observational multicenter cohort study of MRI-negative and histopathology-negative patients who were derived from the European Epilepsy Brain Bank and underwent epilepsy surgery between 2000 and 2012 in 34 epilepsy surgery centers within Europe. We collected data on clinical characteristics, presurgical assessment, including genetic testing, surgery characteristics, postoperative outcome, and treatment regimen., Results: Of the 217 included patients, 40% were seizure-free (Engel I) 2 years after surgery and one-third of patients remained seizure-free after 5 years. Temporal lobe surgery (adjusted odds ratio [AOR]: 2.62; 95% CI 1.19-5.76), shorter epilepsy duration (AOR for duration: 0.94; 95% CI 0.89-0.99), and completely normal histopathologic findings-versus nonspecific reactive gliosis-(AOR: 4.69; 95% CI 1.79-11.27) were significantly associated with favorable seizure outcome at 2 years after surgery. Of patients who underwent invasive monitoring, only 35% reached seizure freedom at 2 years. Patients with parietal lobe resections had lowest seizure freedom rates (12.5%). Among temporal lobe surgery patients, there was a trend toward favorable outcome if hippocampectomy was part of the resection strategy (OR: 2.94; 95% CI 0.98-8.80). Genetic testing was only sporadically performed., Discussion: This study shows that seizure freedom can be reached in 40% of nonlesional patients with both normal MRI and histopathology findings. In particular, nonlesional temporal lobe epilepsy should be regarded as a relatively favorable group, with almost half of patients achieving seizure freedom at 2 years after surgery-even more if the hippocampus is resected-compared with only 1 in 5 nonlesional patients who underwent extratemporal surgery. Patients with an electroclinically identified focus, who are nonlesional, will be a promising group for advanced molecular-genetic analysis of brain tissue specimens to identify new brain somatic epilepsy genes or epilepsy-associated molecular pathways.