Annals of Neurology

BackgroundThe International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) is a consensus-based, empirically-driven approach to standardize cognitive phenotyping in epilepsy research that has quickly garnered interest within the epilepsy community. However, manually generating IC-CoDE phenotypes in group data is laborious and time-consuming, particularly in datasets containing heterogenous cognitive measures or batteries, limiting the widespread adoption of IC-CoDE phenotypes to further multicenter epilepsy research. Methods/ResultsTo remove this barrier, we developed the IC-CoDE portal (https://ic-code-portal.ccf.org/), an interactive and user-friendly, web-based platform to support the scientific community in performing IC-CoDE individual level classification through web interface or bulk classification through upload of data files. The portal also allows the user to generate and visualize cohort summary statistics of cognitive phenotypes in their dataset, with the option of filtering the data interactively by specified demographic or clinical variables of interest. We further made the resulting IC-CoDE phenotypes downloadable as a spreadsheet to foster offline analysis of cognitive data by members of the epilepsy research community. SignificanceAscertainment of cognitive profiles is key to understanding the natural heterogeneity in the clinical presentation of the epilepsies and their comorbidities. The IC-CoDE taxonomy can be applied to any comprehensive neuropsychological battery, regardless of the specific test measures and normative data used or the language and culture in which the assessment took place, making it an ideal tool to accelerate international multi-center studies on cognition in epilepsy. We hope that by eliminating some of the barriers associated with cognitive phenotyping, the IC-CoDE portal will springboard large-scale collaborative efforts to further our understanding of the neuropsychology of the epilepsies.

BackgroundUse of digital sensors to passively collect long-term offers a step change in our ability to screen for early signs of disease in the general population. Smartwatch data has been shown to identify Parkinsons disease (PD) several years before the clinical diagnosis, however, has not been evaluated in comparison to biological and pathological markers such as dopaminergic imaging (DaTscan) or cerebrospinal fluid (CSF) alpha-synuclein seed amplification assay (SAA) in an at-risk cohort. MethodsTo address this, we performed a cohort study using longitudinal clinical assessment data from the Parkinsons Progression Marker Initiative (PPMI) cohort collected between 2010 and 2020 with additional long-term (mean: 485 days) at-home digital monitoring data (collected 2018-2020) from the Verily Study Watch. We derived a digital risk score and evaluated it in an at-risk cohort (N = 109) consisting of people with genetic markers (LRRK2, GBA) or prodromal symptoms (hyposmia, polysomnography-proven Rapid-Eye-Movement behavioral sleep disorder) without a diagnosis of PD for whom all modalities were available (digital, DaTscan, SAA). The digital risk score was compared to the Movement Disorder Society (MDS) research criteria for prodromal PD, alpha-synuclein SAA and DaTscan. FindingsIn the at-risk cohort (N=109, mean age = 64.62{+/-}6.86, 37% male), the digital risk correlated with the MDS research criteria for prodromal PD (r = 0.36, p-value = 1.46x10-4) and was increased in individuals with subthreshold Parkinsonism (UPDRS III > 6) (p-value = 4.99x10-6) and hyposmia (p-value = 3.77x10-2). Notably, the digital risk was correlated with DaTscan putamen binding ratio (r = -0.32, p-value = 6.64x10-4) and CSF SAA (r = 0.2, p-value = 3.9x10-2). The digital risk achieved higher sensitivity in identifying people with SAA positivity (0.71 vs 0.43) or DaTscan positivity (0.43 vs 0.14) than the MDS prodromal score but performed on-par or worse than hyposmia (SAA+: 0.71 vs 0.71, DaT+: 0.48 vs 0.57). InterpretationA digital risk score from smartwatch data could be used as a sensitive screening tool for early detection of PD followed by more specific tests.

BackgroundMutations in the E3 ubiquitin ligase Parkin (encoded by PRKN) are the most frequently known cause of recessively inherited Parkinsons disease. In addition to the loss of dopaminergic neurons, microglial activation is another pathological feature observed in Parkinsons disease. While postmortem brain samples show the end stage of the disease, neurons and glia derived from patients induced pluripotent stem cells (iPSCs) provide a model for detecting early pre-degenerative disease trajectories. However, mixed cell populations often confound these cultures, leading to heterogeneous disease phenotypes. MethodsHere, we tease apart the cell type-specific phenotypes underlying Parkin-linked Parkinsons disease by performing single-nucleus RNA sequencing in iPSC-derived co-cultures of dopaminergic neurons and microglia from PRKN mutation carriers and healthy controls. We validated our transcriptomic key findings through inflammatory cytokine profiling and live-cell calcium imaging. ResultsSingle-nucleus RNA sequencing identified seven major cell types composed of neuronal, glial, and precursor cells, with dopaminergic neurons accounting for the largest cell population. Pathway analysis revealed cell type-specific dysregulated biological processes in Parkin-deficient cells, including gene expression differences in dopaminergic neurons that control mitophagy and dopamine homeostasis, whereas microglia showed changes in calcium homeostasis and inflammatory signaling. Functional analysis verified elevated secretion of monocyte chemotactic protein 1 in PRKN-mutant co-cultures compared with controls, linking Parkin deficiency to increased microglial chemotactic signaling. Furthermore, lower intracellular calcium levels and diminished calcium release following treatment confirmed impaired calcium homeostasis in PRKN-mutant microglia. ConclusionsProfiling at the single-cell level resolved distinct cell subpopulations, enabling us to identify cell type-specific pathway disturbances underlying Parkin deficiency. This unique dataset provides a basis for understanding the impairment of individual cell types and the impact of cellular crosstalk in Parkinsons disease pathology.

BackgroundPostoperative delirium is the most common postoperative complication in older individuals. Genome-wide association studies (GWAS) can provide insights into how genetic factors influence postoperative risk. We examined the genetic architecture of postoperative delirium after major surgery and its relationship with related cognitive conditions (delirium of any type and Alzheimers disease, including the APOE {varepsilon}4 allele). Methods and FindingsA GWAS was performed in UK Biobank to identify genetic variants associated with postoperative delirium. These results were then used in genetic correlation and polygenic risk score analyses to investigate shared genetic risk between postoperative delirium and a) delirium of all causes, and b) Alzheimers disease. The GWAS (1016 cases, 139,148 controls) identified seven Single Nucleotide Polymorphisms (SNPs) that mapped to four genes (APOE, TOMM40, APOC1 and PVRL2); p <5 x 10-8. Five SNPs remained significant after excluding pre-existing dementia, and two after excluding subsequent dementia. The lead SNP was rs429358, a missense variant of APOE. Genetic correlation and polygenic risk score analyses revealed evidence of shared genetic architecture and risk between postoperative delirium and Alzheimers disease (rho = 0.68, p<0.001). The APOE {varepsilon}4 isoform had a dose-response effect on risk (OR [95% CI] for one and two copies 1.75 [1.53 - 2.0] and 4.19 [3.25 - 5.41] respectively, p <0.001). ConclusionsWe identified genetic variants associated with increased risk of postoperative delirium. We also found evidence of shared genetic liability with Alzheimers disease via APOE, complementing recent large-scale studies in all-cause delirium. If validated the findings have potential clinical applications including preoperative risk stratification and early identification of pre-clinical Alzheimers disease risk. Author SummaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIPostoperative delirium is the most common postoperative complication in older individuals. C_LIO_LILittle is known about the genetic basis of postoperative delirium. C_LIO_LIKnowledge of the genetic risk factors could help treatment or prevention in the future. C_LI What did the researchers do and find?O_LIWe performed a genome-wide association study of postoperative delirium including 1016 cases and 139,148 controls. C_LIO_LIWe found genetic variants associated with increased postoperative delirium risk. C_LIO_LIWe also found genetic similarity between postoperative delirium, all-cause delirium, and Alzheimers disease. C_LI What do these findings mean?O_LIPostoperative delirium has shared biology with Alzheimers disease and may represent unmasking of pre-clinical disease. C_LIO_LIIndividuals with genetic risk for Alzheimers disease have increased risk of postoperative delirium and vice versa. C_LIO_LIGiven the limitations of the data source used we were unable to identify small or modest genetic effects and any findings require validation before consideration of clinical use. C_LI

Background and ObjectivesIndividuals with disease-causing variants in STXBP1 frequently have epilepsy onset in the first year of life with a variety of seizure types, including epileptic spasms. However, the impact of early-onset seizures and anti-seizure medication (ASM) on the risk of developing epileptic spasms and impact on their trajectory is poorly understood, limiting informed and anticipatory treatment, as well as trial design. MethodsWe retrospectively reconstructed seizure and medication histories in weekly intervals for individuals with STXBP1-related disorders with epilepsy onset in the first year of life and quantitatively analyzed longitudinal seizure histories and medication response. ResultsWe included 61 individuals with early onset seizures, 29 of whom had epileptic spasms. Individuals with neonatal seizures were likely to have continued seizures after the neonatal period (25/26). The risk of developing epileptic spasms was not increased in individuals with neonatal seizures or early infantile seizures (21/41 vs. 8/16; OR 1, 95% CI 0.3-3.9, p = 1). We did not find any ASM associated with the development of epileptic spasms following prior seizures. Individuals with prior seizures (n = 16/21, 76%) had a higher risk to develop refractory epileptic spasms (n = 5/8, 63%, OR =1.9, 95% CI 0.2-14.6, p = 0.6). Individuals with refractory epileptic spasms had a later onset of epileptic spasms (n = 20, median 20 weeks) compared to individuals with non-refractory epileptic spasms (n = 8, median 13 weeks; p = 0.08). When assessing treatment response, we found that clonazepam (n = 3, OR 12.6, 95% CI 2.2-509.4; p < 0.01), clobazam (n=7, OR 3, 95% CI 1.6-6.2; p < 0.01), topiramate (n=9, OR 2.3, 95% CI 1.4-3.9; p < 0.01), and levetiracetam (n=16, OR 1.7, 95% CI 1.2-2.4; p < 0.01) were more likely to reduce seizure frequency and/or to maintain seizure freedom with regards to epileptic spasms than other medications. DiscussionWe provide a comprehensive assessment of early-onset seizures in STXBP1-related disorders and show that the risk of epileptic spasms is not increased following a prior history of early-life seizures, nor by certain ASM. Our study provides baseline information for targeted treatment and prognostication in early-life seizures in STXBP1-related disorders.

Postoperative delirium is the most common postsurgical complication in older adults and is associated with an increased risk of long-term cognitive decline and Alzheimers disease (AD) and related dementias (ADRD). However, the neurological basis of this increased risk-- whether postoperative delirium unmasks latent preoperative pathology or leads to AD-relevant pathology after perioperative brain injury--remains unclear. Recent advancements in neuroimaging techniques now enable the detection of subtle brain features or damage that may underlie clinical symptoms. Among these, Neurite Orientation Dispersion and Density Imaging (NODDI) can help identify microstructural brain damage, even in the absence of visible macro-anatomical abnormalities. To investigate potential brain microstructural abnormalities associated with postoperative delirium and cognitive function, we analyzed pre- and post-operative diffusion MRI data from 111 patients aged [&ge;]60 years who underwent non-cardiac/non-intracranial surgery. Specifically, we investigated preoperative variation in diffusion metrics within the posterior cingulate cortex (PCC), a region in which prior work has identified glucose metabolism alterations in the delirious brain, and a key region in the early accumulation of amyloid beta (A{beta}) in preclinical AD. We also examined the relationship of preoperative PCC NODDI abnormalities with preoperative cognitive function. Compared to patients who did not develop postoperative delirium (n=99), we found increased free water (FISO) and neurite density index (NDI) and decreased orientation dispersion index (ODI) in the dorsal PCC before surgery among those who later developed postoperative delirium (n=12). These FISO differences before surgery remained present at six weeks postoperatively, while these NDI and ODI differences did not. Preoperative dorsal PCC NDI and ODI values were also positively associated with preoperative attention/concentration performance, independent of age, education level, and global brain atrophy. Yet, these diffusion metrics were not correlated with cerebrospinal fluid A{beta} positivity or levels. These results suggest that preoperative latent brain abnormalities within the dorsal PCC may underlie susceptibility to postoperative delirium, independent of AD-related (i.e., A{beta}) neuropathology. Furthermore, these preoperative microstructural differences in the dorsal PCC were linked to preoperative deficits in attention/concentration, a core feature of postoperative delirium. Our findings highlight microstructural vulnerability within the PCC, a key region of the default mode network, as a neuroanatomic locus that can help explain the link between preoperative attention/concentration deficits and increased postoperative delirium risk among vulnerable older surgical patients.

ImportanceSeizures significantly impact outcomes after stroke, underscoring the need for accurate predictors of post-stroke epilepsy. ObjectiveTo evaluate whether electrographic biomarkers detected early after acute ischemic stroke enhance the prediction of post-stroke epilepsy. DesignMulticenter cohort study with data collected from 2002 to 2022 and final data analysis completed in July 2024. SettingEleven international cohorts from tertiary referral centers, six with available EEG data. Participants1,105 stroke survivors with neuroimaging-confirmed ischemic stroke (mean age 71, 54% male) who underwent EEG within the first 7 days post-stroke. ExposurePresence of electrographic biomarkers detected through EEG. Main Outcome and MeasuresOccurrence of post-stroke epilepsy. The impact of electrographic biomarkers on the risk of post-stroke epilepsy was assessed using Cox proportional hazards regression, adjusted through inverse probability weighting. ResultsAmong 1,105 participants, 119 (11%) developed post-stroke seizures. Epileptiform activity (lateralized periodic discharges, interictal epileptiform discharges, and electrographic seizures; (odds ratio [OR] 2.0, 95% confidence interval [CI]: 1.3-3.0, p=0.001)) and regional slowing (OR 1.9, 95% CI: 1.2-2.9, p=0.004) were independently associated with developing post-stroke epilepsy. The novel SeLECT-EEG prognostic model, specifically developed for stroke survivors without acute symptomatic seizures (ASyS),, outperformed the previous gold-standard model (SeLECT2.0; 0.71 [95% CI: 0.65-0.76]) with a concordance statistic of 0.75 (95% CI: 0.71-0.80; p < 0.001). Conclusions and RelevanceElectrographic findings significantly enhance the prediction of post-stroke epilepsy beyond previously known clinical risk factors and may serve as prognostic biomarkers. The integration of these biomarkers into the SeLECT-EEG model in patients without acute symptomatic seizures provides a more accurate prognostic tool for early post-stroke epilepsy prediction. Key pointsO_ST_ABSQuestionC_ST_ABSCan early detection of electrographic biomarkers after acute ischemic stroke improve the prediction of post-stroke epilepsy? FindingsAmong 1,105 stroke survivors who received early EEG ([&le;] 7 days after stroke), post-stroke seizures occurred in 119 (11%). Stroke survivors with epileptiform activity had a 42% risk (95% CI 30%-49%) of developing post-stroke epilepsy 5 years after stroke, compared to a 13% risk (95% CI 9%-16%) in those without. Additionally, the 5-year risk of post-stroke epilepsy was twice as high in those with regional slowing (24%, 95% CI 18%-29%) compared to those without it (11%, 95% CI 5%-15%). Beyond known clinical risk factors, epileptiform activity and regional slowing were independently associated with developing post-stroke epilepsy. We integrated these findings into a novel prognostic model (SeLECT-EEG; concordance statistic 0.75 [95% CI: 0.71-0.80]), which outperformed the previous gold-standard model (SeLECT2.0; concordance statistic 0.71 [95% CI: 0.65-0.76]; p < 0.001). MeaningEarly electrographic biomarkers improve the prediction of post-stroke epilepsy and may inform counseling and management strategies for stroke survivors at risk of seizures.

BackgroundPostoperative delirium (POD) is a frequent and severe neurocognitive complication following cardiac surgery, associated with poor long-term outcomes. The underlying mechanisms are unclear, and objective biomarkers are urgently needed. MethodsWe used pre- and post-operative plasma samples from 59 patients undergoing cardiac surgery in three separate studies with rigorous delirium assessment using the Confusion Assessment Method in a case-control design. Small extracellular vesicles (sEVs) were isolated from plasma, and their miRNA cargo was profiled using RNA sequencing. Target miRNAs were validated by qRT-PCR, and digital PCR (dPCR). The functional impact of the lead candidate miRNA was investigated in vitro by assessing tau phosphorylation and cell viability in HT22 neuronal cell line. ResultsThere were no differences in sEV morphology or numbers between patients with and without POD. While three candidate miRNAs were initially validated by qRT-PCR, subsequent dPCR analysis confirmed that only the perioperative change in plasma sEV-cargo miR-330-3p expression was significantly greater in patients who developed POD (n = 20) compared with those who did not (n = 20) (5.22 copies/L plasma; 95% Confidence Interval (CI), 1.187 to 9.256; p = 0.0139). Receiver operating characteristic curve analysis for this change yielded an area under the curve of 0.745 (95% CI, 0.589 to 0.901). In vitro overexpression of miR-330-3p in a neuronal cell line significantly increased the phosphorylation of tau at Ser199 (p < 0.0001) and Ser396 (p < 0.001) and reduced cell viability (p < 0.001). ConclusionsOur findings suggest that sEV-bound miR-330-3p increases in patients with POD after cardiac surgery. In vitro results suggest a potential pathogenic role for miR-330-3p, linking a systemic signal to tau-related neuronal injury. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study identifies a specific perioperative increase in small extracellular vesicle (sEV)-cargo miR-330-3p in patients with postoperative delirium (POD) following cardiac surgery. C_LIO_LIWe provide the first evidence that miR-330-3p directly induces tau hyperphosphorylation and reduces neuronal viability in vitro, establishing a potential mechanistic link between systemic sEV signaling and neurodegeneration. C_LI What Are the Clinical Implications?O_LIThe measurement of perioperative change in miR-330-3p could serve as an objective biological marker to assist in the early identification and risk stratification of patients at high risk for POD. C_LIO_LIThe identified miR-330-3p/tau pathway represents a potential new therapeutic target; future interventions aimed at inhibiting this specific miRNA might help prevent or mitigate POD-related neuronal injury. C_LIO_LIThese findings emphasize the importance of monitoring dynamic sEV-cargo changes to better understand and manage perioperative neurocognitive disorders. C_LI

Parkinsons disease (PD) presents with considerable clinical heterogeneity, spanning motor and non-motor symptoms with variable progression trajectories. To investigate the molecular drivers of this variability and identify therapeutic opportunities, we conducted a multi-omics, network-based analysis of the Parkinsons Progression Markers Initiative (PPMI) cohort, with independent validation in the Parkinsons Disease Biomarkers Program (PDBP) cohort. By integrating genetic and longitudinal transcriptomic data, we constructed progression-endotype networks, each capturing trait-specific molecular signatures. These networks showed significantly greater connectivity than expected by chance and converged on established PD-associated genes, including Glucosylceramidase Beta 1 (GBA1), Apolipoprotein E (APOE) haplotype, and Leucine Rich Repeat Kinase 2 (LRRK2). Using these phenotype-informed modules, we applied a network proximity approach to systematically assess 1,595 FDA-approved drugs for repurposing potential. We prioritized 25 candidates, including Zolpidem, Alprazolam, Duloxetine and Primidone. Analysis of real-world clinical data from two large research networks further revealed consistent associations between use of these drugs and reduced incidence of PD-related outcomes. Together, these findings demonstrate the utility of progression-endotype networks for capturing PD progression biology and guiding drug repurposing. This integrative framework connects molecular mechanisms with clinical impact and may inform precision therapeutic strategies for this neurodegenerative disease.

OBJECTIVEStructural and functional metabolism are closely linked in the cholinergic system, and associations between cholinergic neurotransmission and atrophy of cholinergic nuclei, i.e., the nucleus basalis of Meynert (NBM), have been described for neurodegenerative conditions. Perioperative drug administration significantly impacts cholinergic neurotransmission, as shown by alterations in cholinesterase (ChE) activity of patients undergoing anaesthesia and may contribute to perioperative disorders of cognition. In this work, we hypothesised that there is an association between perioperative ChE activity and postoperative NBM atrophy and studied its potential role in postoperative delirium (POD) and cognitive dysfunction (POCD). METHODSWe studied a subsample from the BioCog cohort study. N=170 cognitively healthy (MMSE[&ge;]24) patients [&ge;]65 years provided blood samples for ChE activity measurement before elective surgery and on the first postoperative day, as well as magnetic resonance imaging data before surgery and at follow-up three months after surgery for volumetry of the NBM. Patients were screened for delirium until the 7th postoperative day. POCD was assessed three months after surgery and was defined according to the reliable change index. The data were analysed in linear regression models of postoperative NBM volume adjusted for age, sex, MMSE score and preoperative NBM volume. RESULTSLower postoperative activity of butyryl-ChE was associated with lower baseline-adjusted NBM volume, which was driven by the perioperative change in butyryl-ChE activity rather than preoperative activity. Significant associations were not observed for preoperative butyryl-ChE activity or pre- or postoperative acetyl-ChE activity. Postoperative NBM volumes were not altered in patients with POD or POCD, and associations between butyryl-ChE and postoperative NBM volume were not altered in patients with POD or POCD compared with patients without postoperative cognitive disorder. DISCUSSIONWe observed an association between plasma butyryl-ChE activity and postoperative NBM atrophy. Our findings may point toward a role of surgery and anaesthesia for neurodegenerative diseases and toxic encephalopathies. However, the involvement of this mechanism in postoperative cognitive disorders could not be proven.

Background and objectivesContinuous full-channel EEG is the gold standard for electrocortical activity assessment in critically ill children, but its implementation faces challenges, leading to a growing use of amplitude-integrated EEG (aEEG). While suppressed aEEG amplitudes have been linked to adverse outcomes in preterm infants and adults after cardiac arrest, evidence for critically ill children remains limited. This retrospective study aimed to evaluate the association between suppressed aEEG amplitudes in critically ill children and death or poor functional neurological outcomes. Methods235 EEGs derived from individual patients < 18 years in the pediatric intensive care unit (PICU) at the University Hospital Essen (Germany) between 04/2014 and 07/2021 were retrospectively converted into aEEGs and amplitudes analyzed with respect to previously defined age-specific percentiles. Adjusted odds ratios for death and poor functional outcome at hospital discharge in patients with bilateral upper or lower amplitude suppression below the 10th percentile were calculated accounting for neurological injuries, acute disease severity, sedation levels, and functional neurological status before acute critical illness. ResultsThe median time from neurological insult to EEG recording was 2 days. PICU admission occurred due to neurological reasons in 43 % and patients had high overall disease severity. Thirty-three (14 %) patients died and 68 (29 %) had poor outcomes. Amplitude depression below the 10th percentile was frequent (upper amplitude: 27 %, lower amplitude: 34 %) with suppression of only one amplitude less frequent than bilateral suppression. Multivariable regression analyses yielded odds between 6.63 and 15.22 for death, neurological death, and poor neurological outcomes if both upper or both lower amplitudes were suppressed. Model discrimination was excellent with areas under the curve above 0.92 for all models. DiscussionThis study found a high prevalence of suppressed aEEG amplitudes in critically ill children early after PICU admission, with suppression being highly associated with death and poor functional outcomes at hospital discharge. These findings emphasize the potential of early identification of high-risk PICU patients through aEEG monitoring if conventional EEG is unavailable, potentially guiding neuroprotective therapies and early neurorehabilitation.

Background and ObjectivesPost-ischemic stroke epilepsy (PISE) reduces quality of life, and early risk prediction can guide prevention strategies and anti-epileptogenesis treatment trials. Stroke severity predicts both PISE and mortality, and ignoring mortality can overestimate epilepsy risk. We sought to enhance PISE risk stratification by modeling death as a competing outcome, integrating quantitative clinical, neuroimaging, and electroencephalography (EEG) biomarkers to distinguish shared and distinct predictors of epilepsy and mortality. MethodsWe developed a PISE prediction model using retrospective data from Yale-New Haven Hospital. The training cohort included patients from 2014-2020; the testing cohort from 2021-2022. Eligible patients were adults with acute ischemic stroke who underwent neuroimaging and EEG monitoring <7 days post-stroke and had follow-up >7 days. ResultsOf 280 patients, 53 developed PISE first, 104 died first, and the rest were censored. Quantitative PISE biomarkers included greater 72h stroke severity (HR{Delta}3 [95%CI], 1.2 [1.1-1.4]), infarct volume (HR{Delta}10mL, 1.06 [1.04-1.08]), EEG epileptiform abnormality burden (HR{Delta}10%, 1.2 [1.1-1.3]), and EEG power asymmetries (HR{Delta}10%, 2.0 [1.4-2.9]). Death predictors included older age (HR{Delta}10years, 1.7 [1.4-2.0]), worse pre-stroke functional status (HR, 1.4 [1.2-1.7]), atrial fibrillation history (HR, 2.4 [1.6-3.7]), cardioembolism etiology (HR, 1.9 [1.2-3.0]), anterior cerebral artery involvement (HR, 2.2 [1.2-3.7]), and greater EEG global theta-band powers (HR{Delta}10{micro}V, 6.2 [2.3-17]). Our model, CRIMEPISE, integrating these features, allows prediction of PISE-first and death-first risk scores with AUC of 0.72 (95%CI, 0.60-0.83) and 0.79 (0.72-0.85), respectively. Compared with the benchmark SeLECT model, CRIMEPISE better predicted PISE in patients with [&ge;]4 SeLECT points (AUC, 0.72 vs 0.58) but not those with <4 points (AUC, 0.33 vs 0.52). In the testing cohort, CRIMEPISE identified a more selective group (n=18 vs 44 per SeLECT) with a higher PISE rate (39% vs 20%) and a lower mortality rate (22% vs 45%). DiscussionCRIMEPISE enhances PISE prediction by accounting for mortality as a competing outcome and incorporating multimodal quantitative biomarkers. Because its benefits over SeLECT are most pronounced in high-risk patients, a two-stage approach--SeLECT screening followed by CRIMEPISE in SeLECT-positive cases--may better target candidates for anti-epileptogenesis trials by prioritizing patients likely to survive long-term and develop epilepsy.

BackgroundPostoperative delirium (POD) in elderly patients is a common and serious complication after surgery with an unclear pathogenesis at the molecular level. Perioperative untargeted high-throughput proteomic profiling may provide insights into underlying mechanistic molecular patterns and help identify patients at high risk, guiding preventative and therapeutic measures. MethodsThis study is a monocentric substudy of the European BioCog project, a prospective multicentre observational study involving elderly patients aged [&ge;]65 undergoing elective surgery. Patients with preexisting cognitive impairment (Mini-Mental State Examination score [&le;]23) were excluded. POD was assessed twice daily for up to seven days using the Nursing Delirium Screening Scale (Nu-DESC) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), along with patient chart reviews. Proteomic profiling was conducted using high-throughput liquid chromatography mass spectrometry on sequential pre- and postoperative plasma samples. Data were analysed using a matched case-control design, employing both cross-sectional and longitudinal approaches, along with pathway enrichment analysis as a functional approach. ResultsA total of 226 highly abundant proteins were investigated in 168 patients (50% POD incidence). Multiple pathways, particularly those involved in the activation of the innate immune response and the complement system, were associated with POD in both cross-sectional and longitudinal analyses. Butyrylcholinesterase showed the most robust regulation, with preoperative downregulation and postoperative upregulation in patients with POD, while further downregulated in those without POD. Enzyme activity showed significant decrease in both groups. Additionally, a set of eight preoperative proteins distinguished between patients with and without POD with 86% sensitivity and 79% specificity. ConclusionUntargeted high-throughput proteomics is a feasible approach to characterize pathways involved in POD pathogenesis. This case-control study identified a protein signature associated with POD, emphasizing the need for larger cohorts to confirm these observations and improve the mechanistic understanding of POD. HighlightsO_LIThe complex pathophysiology of postoperative delirium is poorly understood C_LIO_LIHigh-throughput proteomics uncovered distinct regulated features in delirium patients C_LIO_LIEnrichment analysis showed differential regulation of pathways in multiple domains C_LIO_LILogistic regression separates delirium patients using 8 proteins with 86% sensitivity C_LI

Delirium is a severe postoperative complication associated with poor overall and especially neurocognitive prognosis. Altered brain mineralization is found in neurodegenerative disorders but has not been studied in postoperative delirium and postoperative cognitive decline. We hypothesized that mineralization-related hypointensity in susceptibility-weighted magnetic resonance imaging (SWI) is associated with postoperative delirium and cognitive decline. We analyzed a subsample of cognitively healthy patients [&ge;]65 years presenting for elective major surgery who underwent SWI before (N=65) and three months after surgery (N=33) as part of a subproject in the BioCog study. We measured relative SWI intensities in basal ganglia, hippocampus, and posterior basal forebrain cholinergic system (pBFCS). A post-hoc analysis of two pBFCS subregions (Ch4, Ch4p) was conducted. Patients were screened for delirium until the seventh postoperative day. Cognitive testing was performed before and three months after surgery. Preoperative relative SWI hypointensities in the basal ganglia and pBFCS were associated with increased risk for postoperative delirium after adjustment for surgery duration. After additional adjustment for age, sex, preoperative MMSE and region volume, only the association of pBFCS hypointensity and postoperative delirium remained significant. Adjusted for surgery duration, perioperative change in relative SWI intensities of the pBFCS was associated with cognitive decline three months after surgery. This association remained at a trend level after adjustments for age, sex, and region volume, but a significant independent association especially with pBFCS-subregion Ch4p was found in a post-hoc analysis. Brain mineralization, particularly in the cerebral cholinergic system, could be a pathomechanism in postoperative delirium and cognitive decline.

BackgroundThe gold standard anesthesia for deep brain stimulation (DBS) surgery is the "awake" approach, using local anesthesia alone. While it offers high-quality microelectrode recordings and clinical assessment of the stimulation therapeutic window, it potentially causes patients extreme stress and might result in suboptimal surgical outcomes. However, the alternative of general anesthesia or deep sedation dramatically reduces reliability of physiological navigation and therapeutic window assessment, thus potentially diminishing the accuracy of lead localization. We therefore designed a prospective double-blinded randomized controlled trial to investigate a novel anesthesia regimen of ketamine-induced conscious sedation for DBS surgery. MethodsPatients with Parkinsons disease undergoing subthalamic nucleus DBS surgery were enrolled. Patients were randomly assigned to either the experimental or control group. During the physiological navigation phase, the experimental group received ketamine infusion at a dosage of 0.25 mg/kg/hr, while the control group received normal saline. Both groups received moderate propofol sedation before and after the physiological navigation phase. Primary outcomes were non-inferiority of electrophysiological quality, including multiunit recordings, EEG, EMG, bispectral index and lead localization accuracy according to postoperative CT scans. Secondary outcomes included patients satisfaction level measured using Iowa satisfaction with anesthesia scale for awake procedures. Potential side effects and adverse events were also monitored, including hemodynamics (blood pressure, heart rate) and cognition (hallucinations during surgery and early post-operative cognition using Montreal Cognitive Assessment). ResultsThirty patients, 15 from each group, were included in the study and analysed. Intra-operatively, the electrophysiological signature of the subthalamic nucleus was similar under ketamine and saline. Tremor amplitude was slightly lower under ketamine (p = 0.002). The accuracy of lead position was comparable in both groups. Postoperatively, patients in the ketamine group reported significantly higher satisfaction with anesthesia. The improvement in Unified Parkinsons disease rating scale part-III was similar between the groups. No negative effects of ketamine on hemodynamic stability or cognition were reported perioperatively. Additionally, no procedure-related complications were reported in either group, besides one case of peri-lead edema in the control group. ConclusionThis study demonstrates that ketamine induced conscious sedation during physiological navigation in DBS surgery resulted in non-inferior intra-operative, post-surgical and patient satisfaction outcomes compared to the commonly used standard awake protocol, without major disadvantages. Future studies should investigate the applicability of this protocol in other awake neurosurgical procedures, such as DBS for other targets and indications, and awake craniotomy for tumor resection and epilepsy.

BackgroundAcute symptomatic seizures (ASyS) increase the risk of epilepsy and mortality after a stroke. The impact of the timing and type of ASyS remains unclear. MethodsThis multicenter cohort study included data from nine centers between 2002 and 2018, with final analysis in February 2024. The study included 4,552 adults (2,005 female; median age 73 years) with ischemic stroke and no seizure history. We examined ASyS occurring within seven days after stroke. Main outcomes were all-cause mortality and epilepsy. Validation in three separate cohorts included 74 adults with ASyS. ResultsThe ten-year risk of post-stroke epilepsy ranged from 41% to 94%, and mortality from 36% to 100%, depending on ASyS type and timing. ASyS on stroke onset day had a higher epilepsy risk (aHR 2.3, 95% CI 1.3-4.0, p=0.003) compared to later ASyS. Status epilepticus had the highest epilepsy risk (aHR 9.6, 95% CI 3.5-26.7, p<0.001), followed by focal to bilateral tonic-clonic seizures (aHR 3.4, 95% CI 1.9-6.3, p<0.001). Mortality was higher in those with ASyS presenting as focal to bilateral tonic-clonic seizures on day 0 (aHR 2.8, 95% CI 1.4-5.6, p=0.004) and status epilepticus (aHR 14.2, 95% CI 3.5-58.8, p<0.001). The novel SeLECT-ASyS model, available as an app, outperformed a previous model in the derivation cohort (concordance statistic 0.68 vs. 0.58, p=0.02) and in the validation cohort (0.70 vs. 0.50, p=0.18). ConclusionsASyS timing and type significantly affect epilepsy and mortality risk after stroke, improving epilepsy prediction and guiding patient counseling.

ObjectiveWe evaluated whether the combination of epileptiform spikes and ripples (spike ripples) outperformed other leading biomarkers in identifying the epileptogenic zone across subjects in a multicenter international study. MethodsWe validated and applied an automated spike ripple detector on intracranial EEG recordings in subjects from 4 centers who subsequently underwent surgical resection with known 1-year seizure outcomes. We evaluated the spike ripple rate in subjects cured after resection (ILAE 1 outcome) and those with persistent seizures (ILAE 2-5) across sites and recording types. We also evaluated spike, wideband HFO (80-500 Hz), fast ripple (250-500 Hz), and ripple (80-250 Hz) rates using validated automated detectors. The proportion of resected events was computed and compared across subject outcomes and biomarkers. Results109 subjects were included. The majority of spike ripples were removed in subjects with ILAE 1 outcome (p = 1e-6), and this was qualitatively observed across the four sites (p = 0.032, p = 0.092, p = 0.0005, p = 0.003) and the two electrode types (p = 0.01, p = 7e-6). A higher proportion of spike ripples were removed in subjects with ILAE 1 outcomes compared to ILAE 2-5 outcomes (p = 0.02). Among ILAE 1 subjects, the proportion of spike ripples removed was higher than the proportion of spikes (p = 0.0004), wideband HFOs (p = 0.0004), fast ripples (p = 0.008), and ripples (p = 0.008) removed. At the individual level, more subjects with ILAE 1 outcome had the majority of spike ripples removed (40/48, 83%) than spikes (69%, p = 0.04), wideband HFOs (63%, p = 0.009), fast ripples (36%, p = 2e-5), or ripples (45%, p = 0.0007) removed. InterpretationWhen surgical resection was successful, the majority of spike ripples were removed. Automatically detected spike ripples have improved specificity for epileptogenic tissue compared to spikes, wideband HFOs, fast ripples, and ripples.

IntroductionScalp electroencephalography (EEG) is a cornerstone in the diagnosis and treatment of epilepsy, but routine EEG is often interpreted as normal without identification of epileptiform activity during expert visual review. The absence of interictal epileptiform activity on routine scalp EEGs can cause delays in receiving clinical treatment. These delays can be particularly problematic in the diagnosis and treatment of people with drug-resistant epilepsy (DRE) and those without structural abnormalities on MRI (i.e., MRI negative). Thus, there is a clinical need for alternative quantitative approaches that can inform diagnostic and treatment decisions when visual EEG review is inconclusive. In this study, we leverage a large population-level routine EEG database of people with and without focal epilepsy to investigate whether normal interictal EEG segments contain subtle deviations that could support the diagnosis of focal epilepsy. Data & MethodsWe identified multiple epochs representing eyes-closed wakefulness from 19-channel routine EEGs of a large and diverse neurological patient population (N=13,652 recordings, 12,134 unique patients). We then extracted the average spectral power and phase-lag-index-based connectivity within 1-45Hz of each EEG recording using these identified epochs. We decomposed the power spectral density and phase-based connectivity information of all the visually reviewed normal EEGs (N=6,242) using unsupervised tensor decompositions to extract dominant patterns of spectral power and scalp connectivity. We also identified an independent set of routine EEGs of a cohort of patients with focal epilepsy (N= 121) with various diagnostic classifications, including focal epilepsy origin (temporal, frontal), MRI (lesional, non-lesional), and response to anti-seizure medications (responsive vs. drug-resistant epilepsy). We analyzed visually normal interictal epochs from the EEGs using the power-spectral and phase-based connectivity patterns identified above and evaluated their potential in clinically relevant binary classifications. ResultsWe obtained six patterns with distinct interpretable spatio-spectral signatures corresponding to putative aperiodic, oscillatory, and artifactual activity recorded on the EEG. The loadings for these patterns showed associations with patient age and expert-assigned grades of EEG abnormality. Further analysis using a physiologically relevant subset of these loadings differentiated patients with focal epilepsy from controls without history of focal epilepsy (mean AUC 0.78) but were unable to differentiate between frontal or temporal lobe epilepsy. In temporal lobe epilepsy, loadings of the power spectral patterns best differentiated drug-resistant epilepsy from drug-responsive epilepsy (mean AUC 0.73), as well as lesional epilepsy from non-lesional epilepsy (mean AUC 0.67), albeit with high variability across patients. SignificanceOur findings from a large population sample of EEGs suggest that normal interictal EEGs of patients with epilepsy contain subtle differences of predictive value that may improve the overall diagnostic yield of routine and prolonged EEGs. The presented approach for analyzing normal EEGs has the capacity to differentiate several diagnostic classifications of epilepsy, and can quantitatively characterize EEG activity in a scalable, expert-interpretable, and patient-specific fashion. Further technical development and clinical validation may yield normal EEG-derived computational biomarkers that could augment epilepsy diagnosis and assist clinical decision-making in the future.

BackgroundTemporal lobe epilepsy (TLE) is the most common form of focal epilepsy and is characterized by a pathological cascade of excitotoxicity that leads to neuroinflammation, progressive neuronal loss, and subsequent cognitive decline. Despite its prevalence, effective disease-modifying therapies remain lacking. Previous studies have demonstrated that the endocannabinoid system contributes to epileptic activity. In particular, inactivation of monoacylglycerol lipase (MAGL), the key rate-limiting enzyme responsible for the degradation of the endocannabinoid 2-arachidonoylglycerol (2-AG), an endogenous lipid mediator with anti-inflammatory and neuroprotective properties, suppresses seizures and reduces neuroinflammation. However, the cellular and molecular mechanisms underlying these protective effects remain unclear. MethodsTo dissect the cellular mechanisms underlying MAGL-mediated neuroprotection, we employed a kainic acid (KA)-induced status epilepticus model in mice with global, astrocyte-specific (aKO), and neuron-specific (nKO) deletion of mgll. We combined single-nucleus RNA sequencing (snRNA-seq) to map the transcriptomic landscape of glial responses with pharmacological interventions to validate key signaling pathways, as well as behavioral assays to assess functional recovery. ResultsWe demonstrated that astrocyte-specific, but not neuron-specific, mgll deletion was sufficient to attenuate seizure susceptibility and hippocampal neurodegeneration, thereby recapitulating the protective phenotype observed in global knockouts. Transcriptomic profiling revealed that astrocytic MAGL deficiency fundamentally reshaped the glial response to injury by preventing the transition to pro-inflammatory reactive astrocyte states and suppressing the activation of disease-associated microglia (DAM). Mechanistically, we identified a signaling pathway in which the neuroprotective effects of MAGL inhibition depend on cannabinoid receptor 1 (CB1) activation and are mediated by downstream peroxisome proliferator-activated receptor {gamma} (PPAR-{gamma}) signaling. Either genetic deletion of CB1 or pharmacological blockade of PPAR-{gamma} abolished the protective effects. Furthermore, aKO mice exhibited reduced neuronal loss, preserved synaptic structural integrity and protection against post-seizure cognitive deficits. ConclusionThese findings reveal astrocytic MAGL as a crucial regulatory node in the epileptic brain and demonstrated that enhancing 2-AG signaling in astrocytes orchestrates neuroprotection via CB1-PPAR-{gamma} signaling pathways, thereby attenuating neuroinflammation, preserving synaptic function, and preventing the cognitive comorbidities associated with epilepsy.

BackgroundNeuroinflammation is a common hallmark of primary tauopathies, and is associated with worse clinical outcomes over time. However, accurate prognosis in these disorders remains challenging, and current fluid biomarkers provide limited insight into the contribution of peripheral immune cells to PSP/CBS pathogenesis. Our study aims to characterise blood-based immune cell profiles in patients with progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), and test their associations with neurodegeneration and clinical outcomes. MethodsPeripheral blood immune cells from fresh whole blood were characterized with high-dimensional mass cytometry (29 markers) in n=60 people with PSP/CBS and n=21 age- and sex-matched controls. Cell type abundance was defined as the ratio of counts for each gated population divided by total live cells. Hierarchical clustering of cell types and principal component analysis were used to derive data-driven immune clusters. Correlation network analysis and diffusion-based network propagation integrated cell counts with plasma inflammation markers to prioritise mediators of intercellular signalling. Associations between immunological markers, plasma concentrations of neurofilament light chain (NfL), cognition, and survival were assessed using regression and Cox proportional hazards models. ResultsPatients with PSP/CBS showed a global increase in covariance among immune cell populations, indicating heightened coordination within the peripheral immune network. A monocyte-driven cluster (Cluster 1) showed higher scores in PSP/CBS, reflecting impaired phenotypic transition from classical to nonclassical monocytes, and was associated with higher NfL levels, poorer cognitive performance, and worse prognosis. In contrast, a Treg-driven cluster (Cluster 2) showed lower scores in PSP/CBS, and was associated with better cognition and longer survival. Integrated multimodal networks identified a small set of immune-regulatory molecules and cytokines mediating crosstalk between Treg/Th17-like cells and monocytic populations, supporting a dysregulated Treg-monocyte axis in PSP/CBS. ConclusionsWe identified peripheral blood-based immunophenotypic profiles of individuals with PSP/CBS that are associated with neurodegeneration, cognitive decline, and survival. Dysregulated monocyte maturation and reduced Treg-related immune configurations are enriched in patients with worse outcomes, suggesting that specific peripheral immune cell subsets may serve as fluid biomarkers and potential immunotherapy targets in primary tauopathies.