Annals of Neurology

Background and Objectives: Older adults with epilepsy are at increased risk for Alzheimer's disease (AD), yet the mechanisms underlying this association remain poorly understood. We applied a validated AD neuroimaging signature to older adults with epilepsy to examine 1) whether older adults with epilepsy mirror AD-related changes, 2) associations with clinical, cognitive, and plasma biomarker outcomes, and 3) utility for identifying subgroups at heightened risk for cognitive decline. Our multicenter, prospectively enrolled cohort allowed for direct examination of differences in AD signatures between those with early-onset and late-onset unexplained epilepsy. Methods: Participants included 449 older adults: 87 with focal epilepsy from the multicenter Brain Aging and Cognition in Epilepsy (BrACE) cohort (age=66.10 [SD=6.86], including early-onset (<55 years at seizure onset) and late-onset ([&ge;]55 years at seizure onset) epilepsy); 362 from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including cognitively unimpaired (CU) healthy controls and individuals with mild cognitive impairment (MCI) or AD dementia. An AD signature was derived from regional cortical thickness and hippocampal volume weighted by their sensitivity to AD-related neurodegeneration in prior work. Associations between the AD signature, epilepsy characteristics, plasma biomarkers ({beta}-amyloid 42/40, phosphorylated tau [pTau217, pTau181], neurofilament light chain [NfL]), and cognition were evaluated in BrACE. Results: Participants with epilepsy demonstrated more AD-like signatures compared to ADNI CU controls ({beta}= -0.43, p<0.001), reflecting reduced thickness/volume in AD-vulnerable regions. This effect was stronger among early-onset ({beta}= -0.57) versus late-onset ({beta}= -0.26) epilepsy. In BrACE, the AD signature correlated with NfL ({beta}= -0.30, p=0.050), memory performance ({beta}= 0.30, p=0.006), and predicted greater odds of cognitive impairment specifically among those with early-onset, but not late-onset, epilepsy (interaction p=0.043). Further, among those with early-onset epilepsy, the AD signature significantly improved identification of cognitive impairment over and beyond the effects of plasma AD biomarkers (p=0.041). Findings were similar when examining the effects of epilepsy duration rather than epilepsy onset age. Discussion: AD neuroimaging signatures may help identify clinically meaningful subgroups among older adults with epilepsy, particularly when integrated with AD biomarkers. Findings support a multimodal framework for assessing AD-related risk in epilepsy and highlight interactive effects of epilepsy chronicity and AD-related processes that can influence cognitive outcomes.

Introduction: Variants in the polymerase gamma (POLG) gene are associated with a wide range of mitochondrial disorders. Emerging evidence suggests a potential link between POLG variants and Parkinson's disease (PD); yet, results remain inconclusive. Objectives: To investigate the genetic spectrum and prevalence of POLG variants in PD across diverse ancestries. Methods: We leveraged multi-ancestry genetic data from the Global Parkinson's Genetics Program (GP2), including genotyping data from 98,589 and short-read sequencing data from 36,022 individuals. We performed a POLG rare variant screen, case-control association, and gene-level burden analyses. Results: Five PD cases carried potentially biallelic rare pathogenic/likely pathogenic POLG variants. Additionally, 228 individuals (<1%; 161 PD cases, 28 individuals with other neurological disorders, and 39 controls) carried 34 distinct rare pathogenic/likely pathogenic heterozygous variants, with no significant frequency differences between cases and controls, except for the p.Ala467Thr variant in the European population. The co-inherited pathogenic variants p.Thr251Ile and p.Pro587Leu were present in <1% of both cases and controls, with no significant group differences. Burden and variant-level association analyses showed no association between rare POLG variant burden or common POLG variant enrichment and PD. Conclusions: POLG variants are overall rare in PD. The identification of rare pathogenic variants among PD cases suggests that POLG-related mitochondrial dysfunction may contribute to PD in isolated instances, particularly under recessive inheritance. Our findings support a role for POLG variants in select cases and underscore the need for larger-scale sequencing and functional studies.

Background: Sleep fragmentation and reduced sleep efficiency are markers of disrupted sleep architecture linked to cognitive and age-related decline. Current assessments rely on subjective reports prone to recall bias, limiting their effectiveness for longitudinal monitoring. Data-driven analysis of sleep using physiological signals such as EEG and EMG remains underutilised, particularly in mid-to-older adults. Objective: We present a deep learning pipeline for automated sleep staging and label-free abnormality scoring, with the primary objective of quantifying deviations in sleep architecture to capture progressive sleep disruption and longitudinal change. Methods: Temporal and attention-based models were benchmarked using datasets from the National Sleep Research Resource and PhysioBank. To improve class-specific performance, we introduce a stacking-based ensemble of sleep stage classifiers, each trained to specialise in a different stage. For longitudinal scoring, we develop a reconstruction loss-based abnormality metric using a temporal convolutional autoencoder trained on hypnograms generated by the sleep staging models. Results: Attention-based models, particularly AttnSleep, achieved the highest performance in both multimodal and single-channel settings (accuracy: 0.85 and 0.83; F1: 0.79 and 0.74, respectively). The encoder-decoder ensemble model improved overall classification accuracy by 3% compared to the best-performing biased base classifier, with a modest gain in N1-stage F1 score (0.444). The proposed abnormality score correlated with Pittsburgh Sleep Quality Index components and showed sensitivity to synthetic hypnogram degradation, highlighting its potential as a label-free indicator of sleep disruption. Conclusion: Automated classification and annotation-free scoring enable an end-to-end multimodal pipeline that supports scalable, objective sleep health monitoring, with relevance for future clinical deployment.

Mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE) is a recently recognized cause of drug-resistant focal epilepsy. It is often MRI-negative or shows imaging features mimicking focal cortical dysplasias, which makes recognition difficult and limits presurgical counseling. We aimed to identify an intracranial EEG (iEEG) biomarker that distinguishes MOGHE from other developmental brain lesions encountered in epilepsy surgery. In a retrospective multicenter test cohort of 38 patients (18 MOGHE, 20 non-MOGHE), we analyzed long-term stereo-EEG and subdural recordings. Only MOGHE patients showed highly stereotyped clusters of very brief low-voltage fast activity (LVFA) events, organized into status-like 3 to 12-minute episodes that often lacked clear clinical symptoms. LVFA clusters were present in 16/18 MOGHE and 0/22 non-MOGHE patients. We then tested diagnostic performance in an independent, blinded single-center validation cohort of 22 patients (11 MOGHE, 11 non-MOGHE), in which visual identification of LVFA clusters correctly classified 10/11 MOGHE and 10/11 non-MOGHE cases (Cohens kappa=0.82). Penalized logistic regression further confirmed MOGHE histology as the strongest predictor of LVFA clusters, independent of age and lobe localization. Because LVFA clusters can be recognized visually on routine intracranial EEG recordings without specialized software, this biomarker is readily applicable in clinical practice and may improve presurgical identification of MOGHE. Future prospective studies should determine whether its recognition influences surgical planning, improves outcome prediction, or facilitates selection of patients for mechanism-based therapies.

Background: Mono-allelic Dehydrodolichyl Diphosphate Synthase (DHDDS) variants are associated with juvenile Parkinsonism, developmental delay and seizures. Symptoms are progressive, and various mechanisms, such as defective glycosylation, lysosomal dysfunction and cholesterol accumulation have been hypothesized to underlie disease symptoms. There is no treatment for DHDDS-related disease. Methods: Patient-derived cortical forebrain organoids were created to elucidate disease mechanisms and evaluate potential treatments. In these neuronal models, glycosylation, lipidomics, proteomics, cholesterol/ganglioside accumulation, mitochondrial function and electrophysiological activity were assessed. Finally, we investigated the effects of nicotinamide mononucleotide (NMN), identified through a yeast-based drug screen, in neuronal cell models and in six patients in an off-label, N-of-1, observational series. Results: DHDDS-patient derived organoids showed visual signs of degeneration after four months of culturing. This was accompanied by significant cholesterol accumulation in astrocytes, decreased mitochondrial respiration and loss of deep-layer neurons. In addition, we identified glycosylation abnormalities, showing for the first time that glycosylation in human tissue is affected by monoallelic DHDDS variants. Proteomic analysis revealed altered protein expression of proteins involved in lipid metabolism, cytoskeletal organization and neuronal development. We found that oral Nicotinamide Mononucleotide supplementation led to significant improvement in mitochondrial respiration and electrophysiological parameters in organoids, concurring with clinical improvements in all of the treated patients, particularly regarding their ataxia and tremor. Conclusion: Our findings reveal a progressive phenotype in DHDDS-patient-derived brain organoids, with mitochondrial dysfunction and astrocyte-specific metabolic alterations contributing to disease pathology. Notably, NMN treatment led to clinical improvements in patients with heterozygous DHDDS variants, highlighting its potential as a therapeutic strategy.

Rationale: Reliable electroencephalography (EEG) biomarkers of cortical excitability could improve diagnosis and longitudinal monitoring in epilepsy, yet it remains unclear which metrics best balance sensitivity across individuals with intra-individual stability over time. Methods: We analyzed scalp EEG recordings from the open-access Temple University Hospital EEG Epilepsy Corpus, comprising 1,404 recordings from 96 individuals with neurologist-confirmed epilepsy and 85 healthy controls across multiple sessions. Eight global measures were computed: aperiodic exponent and offset, sample entropy, detrended fluctuation analysis exponent and derived index, spatial gamma-band phase consistency, and absolute and relative alpha power. Group differences were assessed by permutation tests with false discovery rate correction at recording, session, and subject levels. Associations with antiseizure medication burden, temporal stability, and cross-metric correlation structure were evaluated as secondary analyses. Results: Aperiodic parameters showed the most robust case-control separation, remaining significant after subject-level averaging (exponent: median difference = 0.20, q = 0.010; offset: median difference = 0.25, q = 0.011). Entropy and alpha power distinguished groups at the recording and session levels, while gamma-band phase consistency was significant at the session level only; none of these survived subject-level averaging, suggesting greater state-dependency. Higher medication burden was associated with reductions in alpha power and detrended fluctuation analysis, and adjusting for it substantially attenuated group differences, though residual effects in the aperiodic exponent persisted. Cross-metric correlation structure was preserved between groups but modestly reorganized by medication burden. Conclusions: Aperiodic spectral parameters are the most robust EEG markers of epilepsy, reflecting stable trait-like network properties. Complexity and synchrony measures capture complementary, state-sensitive dimensions. Medication burden substantially influences multiple metrics, underscoring the need to account for pharmacological effects when interpreting EEG biomarkers in epilepsy.

Adapting ongoing gait patterns to environmental challenges is essential for safe navigation through the environment. Impairment of gait adaptation is common in many neurodegenerative disorders, such as Parkinson's disease (PD), where it hampers mobility and limits quality of life. The neural control of gait adaptation remains largely unclear, thereby limiting the development of targeted treatments, such as deep brain stimulation of the subthalamic nucleus (STN-DBS). We integrated clinical, kinematic, brain metabolic imaging, and electrophysiological data, obtained during a fully immersive virtual reality overground walking task, to characterize the neural underpinnings of gait adaptation performance during dynamic obstacle avoidance and its improvement with STN-DBS. Movement kinematics, brain oscillatory activity, and metabolic activation were simultaneously acquired in 12 patients with PD during rest and gait adaptation, under active or paused STN-DBS, using inertial measurement units, electroencephalography, and three separate [18F]fluorodeoxyglucose positron emission tomography scans. Eight age-matched healthy subjects completed the same task for comparative kinematic analyses. All patients showed significant clinical improvement with STN-DBS. During the gait adaptation task with paused stimulation, patients exhibited increased metabolic activity in the cerebellum and sensorimotor cortex. Active STN-DBS selectively enhanced thalamic and superior frontal gyrus (SFG) metabolism, while concomitantly reducing cerebellar uptake. Right-lateralized SFG metabolism correlated with gait adaptation performance, with DBS-driven shifts toward greater right SFG activity predicting the magnitude of gait adaptation improvement. This correlation was independent of baseline asymmetry in clinical impairment, electrode placement, or structural connectivity to the SFG. Of note, STN-DBS amplitude asymmetry emerged as an independent predictor of right-lateralization of SFG metabolism. EEG recordings confirmed this lateralized network modulation, with theta-band asymmetry paralleling PET findings. Our findings identify a lateralized thalamo-cortical network supporting gait adaptation in PD and highlight a distinctive role for the SFG. We further show that effective STN-DBS acts as a lateralized regulator, dynamically rebalancing cortico-thalamic circuits to support context-appropriate gait control. The observed right-hemispheric lateralization may foster novel image-guided programming strategies to enhance the consistency and effectiveness of gait control in PD.

Background: Neurological, neuropsychiatric, and neurodevelopmental disorders cluster in ALS families, sharing a common genetic architecture with ALS. Pathogenic variants in genes associated with other neurological, neurodevelopmental, or neuropsychiatric disorders may also co-occur in ALS and modify phenotype. We have sought to determine the prevalence and clinical pattern of likely-pathogenic/pathogenic (LP/P) non-ALS neurological, neurodevelopmental, and neuropsychiatric variants, alone and in combination with ALS-gene variants, in two large ALS cohorts. Methods: Whole-genome sequencing (WGS) of 469 Irish and 774 Answer ALS people with ALS (pwALS) was analysed for ClinVar LP/P variants associated with other neurological (n = 15541), neurodevelopmental (n = 9761), and neuropsychiatric (n = 321) phenotypes. Inheritance patterns for associated genes (autosomal recessive/autosomal dominant) along with the associated phenotype were validated using OMIM. Standardised clinical data included family history, site and age of onset, El Escorial category, survival, motor decline, and cognitive and behavioural assessments. Known ALS-gene variants and C9orf72 repeat expansion status were included for each cohort. Results: Non-ALS neurological variants were identified in 47/469 (10.0%) Irish and 69/774 (8.9%) Answer ALS participants, most frequently in hereditary spastic paraplegia-associated genes (3.2% Irish; 2.8% Answer ALS). Irish neurological variant carriers showed higher frequency of respiratory onset (10.6% vs 1.2%, Fisher's exact p = 0.002, {Phi} = 0.20) and fewer premorbid behavioural symptoms (0.92 +/- 0.56 vs 3.08 +/- 0.97, Cohen's d = -0.40). Neurodevelopmental variants occurred in 12/469 (2.6%) Irish and 20/774 (2.6%) Answer ALS participants. In the Irish cohort, neurodevelopmental variant carriers had significantly shorter survival in Cox proportional hazards model (log-rank p = 0.005), corresponding to a more than two-fold increased hazard of death (HR = 2.25, 95% CI 1.26-4.00), and had significantly increased familial burden of neuropsychiatric disorders among first- and second-degree relatives (negative binomial IRR for carriers = 2.41, 95% CI: 1.12-5.18, p = 0.025). Across combined cohorts, 18 individuals (Irish n = 8; Answer ALS n = 10) carried [&ge;]2 LP/P variants spanning ALS and non-ALS genes. Conclusion: Rare LP/P variants in genes associated with other neurological and neurodevelopmental disorders occur in up to 12% of pwALS across two independent cohorts. Carriers show distinct phenotypes, shorter survival, and characteristic family history patterns. These findings suggest that extended pleiotropic and oligogenic architectures may contribute to ALS heterogeneity.

Background: Cognitive impairment in Parkinson's disease (PD) is linked to degeneration of the cholinergic basal forebrain, particularly cholinergic nucleus 4 (Ch4) in the nucleus basalis of Meynert. Structural and diffusion MRI separately detect this degeneration, but few studies have combined these modalities across the PD cognitive spectrum. Methods: We analyzed 92 participants: 14 healthy controls (HC), 35 PD with normal cognition (PD-NC), 33 with mild cognitive impairment (PD-MCI), and 10 with dementia (PDD). For Ch4 and cholinergic nuclei 1, 2, and 3 (Ch1-3) in the medial septal/diagonal band complex, we determined TIV-normalized gray matter density (GMD) and free-water (FW) fraction. We evaluated group differences, cognitive correlations, adjusted multivariable regression, and exploratory ROC discrimination. Results: Ch4 GMD was significantly lower in PDD compared to PD-MCI (p=0.007), PD-NC (p<0.001), and HC (p<0.001). Ch4 GMD was also lower in PD-MCI versus HC (p=0.028); the PD-MCI versus PD-NC difference was not significant after correction (p=0.074). Ch1-3 GMD was lower in PDD versus PD-NC (p=0.008) and HC (p=0.009). Ch4 and Ch1-3 FW were elevated in PDD versus all other groups (all p<0.01). Among PD patients (n=78), MoCA was positively correlated with Ch4 GMD ({rho}=0.49) and Ch1-3 GMD ({rho}=0.42) and negatively correlated with Ch4 FW ({rho}=-0.51) and Ch1-3 FW ({rho}=-0.40; all p<0.001). In the full four-metric model, Ch4 GMD and Ch4 FW were the only independent basal forebrain predictors (Ch4 GMD {beta}=+2.04, p<0.001; Ch4 FW {beta}=-1.46, p=0.005) of MoCA score. The combined Ch4 GMD + Ch4 FW model showed high discrimination for PDD versus non-demented PD (AUC=0.934; optimism-corrected AUC=0.925). Conclusions: Structural and free-water diffusion MRI provide complementary information about Ch4 degeneration in PD. The combined Ch4 model showed promising exploratory discrimination of PDD; validation in larger independent samples is needed.

Synapse loss is an early feature of neurodegeneration and may provide sensitive biomarkers for experimental medicine. Positron emission tomography (PET) with the synaptic vesicle glycoprotein 2A radioligand [11C]UCB-J shows widespread signal reduction across dementias. However, it remains unclear which aspects of synaptic integrity [11C]UCB-J PET measures. We developed a histological-imaging pipeline to quantify structurally intact synapses in post-mortem brain tissue. We applied it to six donors with the tauopathy progressive supranuclear palsy (PSP) who had ante-mortem [11C]UCB-J-PET, alongside six controls across 11 brain regions. Synapse loss in PSP was widespread but region-specific across cortical, subcortical, and brainstem regions. Greater synapse loss was associated with higher tau burden and pathology, and cortical synaptic density correlated with ante-mortem cognition. Post-mortem synaptic density correlated with in vivo [11C]UCB-J-PET signal. This study provides validation of SV2A PET as a biomarker of synaptic density and supports integration of imaging with histopathology in neurodegenerative disease research.

Background: Most approaches to suicide risk assessment consider clinical conditions as independent risk factors, potentially overlooking prognostic information in the order in which conditions accumulate. We applied temporal sequence mining to linked claims and mortality data to identify ordered clinical diagnostic trajectories associated with suicide death. Results: The cohort included 3 647 059 insured Maryland residents aged 10 years or older with available claims records in the Maryland Suicide Data Warehouse from January 1, 2016, to December 31, 2020, among whom 768 suicide deaths were ascertained through medical examiner linkage. Sequential pattern mining of ICD-10-CM diagnoses grouped into Clinical Classifications Software Refined categories identified 89 221 candidate sequences, of which 1 816 remained significantly associated with suicide death in time-varying Cox models. Adjusted hazard ratios (AHRs) ranged from 2.4 to 134.1. Two-thirds of significant trajectories ended in physical conditions, and approximately half crossed from psychiatric to physical endpoints. Among suicide decedents, 62% were exposed to at least 1 significant sequence (median, 16 per case); median sequence duration was 18.7 months, and median time from completion to death was 13.1 months. In landmark analyses, among patients with depression who later developed suicidal ideation (n = 26 356), the path through anxiety, then anemia, was associated with higher risk (AHR, 4.6; 95% CI, 2.2-9.5), whereas the anxiety-only path was not (AHR, 1.3; 95% CI, 0.8-2.1). Among patients with anxiety who later developed hypertension (n = 149 215), the path through history of self-harm was associated with higher risk (AHR, 32.0; 95% CI, 16.6-61.6). Associations were generally consistent across sex and age. Conclusions: Temporal ordering of clinical conditions may carry prognostic information for suicide death. Clinical trajectories incorporating physical illness within psychiatric sequences identified higher-risk groups. These findings suggest that opportunities for risk detection may extend beyond psychiatric settings and that suicide risk signals may be fragmented across care settings and not apparent within isolated encounters.

Age-related hearing loss is a leading modifiable risk factor for dementia and is increasingly recognized as a non-motor feature of Parkinson's disease (PD). The apolipoprotein E (APOE) E4 allele is the strongest genetic risk factor for Alzheimer's disease and is associated with cognitive decline in PD, yet its relationship to hearing loss remains unclear. Therefore, we examined the independent and interactive effects of PD status and APOE E4 carrier status on age-related hearing loss using a validated web-based speech-in-noise (SIN) assessment in 239,620 23andMe Research Institute participants without PD and 4,361 PD cases. Generalized additive models for location, scale, and shape (GAMLSS) showed that both PD and APOE E4 independently exacerbated age-related hearing decline, with speech reception thresholds (SRTs) worsening non-linearly with advancing age, but without evidence of synergistic interaction. However, longitudinal analyses in a subcohort completing at least two assessments (1,434 PD cases; 36,242 controls) using GAMLSS mixed models showed a significant three-way interaction between PD status, APOE E4, and age2, such that SIN hearing loss accelerated more steeply with age in APOE E4 carriers with PD. Males and individuals with lower educational attainment also exhibited worse SIN hearing loss. These results identify APOE E4 carriers with PD as a priority population for hearing screening and intervention, and support the integration of SIN assessments into routine PD care to detect hearing decline that may compound cognitive and communicative burden in aging.

Background: Mucopolysaccharidosis type IIIB (MPS IIIB) is a devastating neurodegenerative lysosomal storage disorder caused by alpha-N-acetylglucosaminidase (NAGLU) deficiency. There is currently no approved therapy. We report the 3-month outcomes of a novel intracerebroventricular (ICV) gene therapy in a child with MPS IIIB. Methods: In an open-label, single-center, investigator-initiated trial (ChiCTR2600121466), a single dose of RDGT-101 (2.0E14; vg of an AAV9 vector encoding human NAGLU) was administered via ICV infusion. Primary outcomes were safety and tolerability. Secondary outcomes included serum NAGLU activity, urinary heparan sulfate (HS) excretion, and neurocognitive function. Exploratory analyses included hematological parameters. Results: The patient achieved serum NAGLU activity (17.06 nmol/mL/hour) approaching that of healthy controls (17.75 {+/-} 1.37 nmol/mL/hour) by Month 3, accompanied by a 58.4% reduction in urinary HS. Clinically, previously severe hand and toe contractures resolved, allowing for full extension. Neurocognitive improvements were observed, including clear articulation, logical conversation, and sustained eye contact. Hematological analyses revealed normalized red blood cell indices and improved iron utilization. No dose-limiting toxicities, serious adverse events, or clinically significant laboratory abnormalities were observed. Conclusions: A single ICV infusion of RDGT-101 was safe and well-tolerated in this patient with MPS IIIB. Early biochemical correction was accompanied by marked improvements in somatic, neurocognitive, and hematological parameters. These findings support further investigation of ICV AAV9 gene therapy for MPS IIIB.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

Background. Tethered cord syndrome (TCS) is classically associated with a low-lying conus medullaris, yet many surgically treated children have a normally positioned conus (occult TCS). Large-scale normative data on conus position in children, and the diagnostic value of quantitative conus assessment, are limited. Purpose. To establish a large-cohort reference distribution for conus medullaris termination level in children, to quantify conus position in children surgically treated for presumed (occult) TCS, and to test whether automated conus segmentation and radiomics can distinguish TCS from normal. Materials and Methods. In this retrospective single-center study, conus termination level was extracted from structured radiology reports of consecutive pediatric lumbosacral MRI examinations and encoded numerically (L1 = 1, L2 = 2, etc.). Children surgically treated for tethered cord were identified by linkage to an operative registry (name and date of birth) and restricted to preoperative examinations. A deep-learning model (nnU-Net) was trained for conus segmentation on axial T2-weighted images. IBSI-compliant radiomic features were extracted; reproducibility was assessed by intra- and inter-observer intraclass correlation (ICC). A case-control radiomics analysis used batch-only ComBat harmonization and cross-validated L1-penalized logistic regression; discrimination was compared with conus level by paired bootstrap. Results. Among 9,808 examinations with a parseable conus level (98.5% of reports; parser validated against dual blinded annotation, 99.4% agreement, weighted kappa 0.946), the conus terminated in the L1 region in 85.7% and the L2 region in 14.3% of the reference cohort (postoperative examinations excluded, n = 9,655); a low-lying conus (>=L3) occurred in only 0.05% (5/9,655), and remained rare (0.14%, 14/9,808) including operated examinations (median L1; mean 1.13 +/- 0.33). A slightly more cephalad position was seen with increasing age (negligible correlation). Among 475 preoperative children surgically treated for tethered cord, 99.6% had a normally positioned conus (<=L2) and only 0.4% were low-lying. Automated conus segmentation achieved a held-out Dice of 0.85. Conus radiomics likewise did not distinguish TCS from controls (equivalence-tested null; full segmentation/radiomics pipeline reported in the companion methodological paper). Conclusion. In children, the conus medullaris terminates at L1-L2 in more than 99% of cases and is normally positioned in virtually all children surgically treated for TCS. Within the conus, neither position nor texture (radiomics) identifies tethered cord; whether the filum terminale carries a diagnostic signal was not tested here.

Brain-derived tau (BD-tau) is an emerging blood-based biomarker for neurodegeneration, yet there are currently limited well validated BD-tau assays available for research and clinical use. To enhance access to this vital biomarker for neurological disorders including traumatic brain injury (TBI), we developed a novel blood-based immunoassay for BD-tau on the ultra-sensitive Quanterix HD-X platform using Single Molecule Array technology. Analytical validation assessed dilution linearity, specificity, precision, detection limits, and spike recovery, each recording robust metrics in agreement with international expert recommendations. The assay demonstrated robust validation metrics, achieving between-run stability of 95% when analyzing aliquots from six independent plasma and serum samples across five analytical runs. It also showed strong dilution linearity when diluted four-fold and achieved over 90% recovery when spiked with cerebrospinal fluid. Next, we evaluated the clinical utility of the assay in cohorts of individuals with traumatic brain injury (TBI), where strong performances were recorded whether using the 2-step or 3-step assay formats ({rho}= 0.94; p < 0.0001). Furthermore, plasma BD-tau distinguished samples from TBI patients based on time from injury and severity (AUC=0.93). Plasma BD-tau differentiated between favorable and unfavorable functional outcomes in the acute-severe group. Our findings underscore the significant potential of the BD-tau assay as a biomarker for TBI in the severe phase.

Objective: Clinical phenotyping methods that rely on clinical and informatics expertise can be time-intensive and costly. We tested both manual and highly automated approaches using electronic health record (EHR) data to identify an FDA Sentinel Initiative health outcome of interest, acute pancreatitis. Materials and Methods: We trained and evaluated machine learning algorithms using EHR data with two approaches: a custom approach that included manually curated features and trained on outcomes data validated with medical record review, and a highly automated approach that greatly simplifies and automates feature engineering and relies on low-cost silver-standard outcomes for model training. Results: Custom algorithms using manually curated structured claims data discriminated cases from non-cases with a high degree of accuracy (cv-AUC 0.89 [95%CI 0.84-0.94]); the inclusion of natural language processing (NLP)-derived covariates from clinical notes increased performance slightly (cv-AUC 0.91[95%CI 0.86-0.97]). The automated algorithm trained on the outcome count of diagnosis codes performed less well (AUC 0.80 [95% CI 0.75-0.85]) but improved using maximum lipase value as an outcome (AUC 0.88 [95% CI 0.84-0.92]). At a positive predictive value of 90%, the custom algorithm had a sensitivity of 92%, the automated algorithm trained on diagnosis code count had a sensitivity of 45%, and the automated algorithm trained on maximum lipase value had a sensitivity of 84%. However, a prediction rule derived by clinicians during chart review was nearly as accurate (maximum lipase value [&ge;] 3 times upper limit of normal; AUC 0.86, PPV 85%, sensitivity 92%). Discussion: Machine learning algorithms with manually curated structured data and NLP features trained on validated outcomes data successfully identified validated events. Use of an outcome in the automated model based on specific phenotype knowledge (maximum lipase value) allowed for performance similar to the custom model and with considerably less resources.

Importance: As new treatments increase quality and length of life in people with multiple sclerosis (MS), effective prevention and management of common comorbidities, including Diabetes Mellitus (DM), is increasingly important. Objective: To compare incidence of DM and its associations with hospitalisation and mortality in adults with MS and matched controls. Design: Using English primary care data from the Clinical Practice Research Datalink (CPRD), linked to Hospital Episode Statistics and national mortality records, we matched adults with MS diagnosed between 2000 and 2023, with up to ten controls without MS by age, sex, and practice. We excluded individuals with preexisting DM, defined using diagnostic and management codes. Outcomes included all-cause hospitalisation (number and duration) and mortality. We used Poisson, negative binomial, linear, and Cox proportional hazards models, adjusting for demographic and socioeconomic factors, adding interaction terms to examine if ethnicity, deprivation, and urbanity were associated with outcomes. Results: We included 9,010 individuals with MS and 78,121 matched controls. Over a mean follow-up of 13.2 years, people with MS had over twice the incidence of DM compared with controls (adjusted incidence rate ratio [aIRR]=2.26, 95% CI: 1.96 to 2.61, p<0.001). Among people with MS, incident DM was associated with higher hospitalisation rates (aIRR=1.82, 95%CI: 1.47 to 2.28, p<0.001), longer hospitalisation duration (median 18 vs 4 days, adjusted beta;=0.53, 95%CI: 0.41 to 0.65, p<0.001), and increased all-cause mortality when incident DM was modelled as a time-varying exposure (adjusted hazard ratio=1.46, 95%CI: 1.17 to 1.82, p<0.001), compared to those who did not develop DM. Similar patterns were observed among controls (hospitalisation rates: aIRR = 2.96, 95% CI 2.63 to 3.23, p<0.001; hospitalisation duration: adjusted {beta} = 0.93, 95% CI: 0.86 to 0.99, p<0.001; mortality [time-varying]: HR = 1.50, 95% CI: 1.27 to 1.77, p<0.001). The relationship between DM and increased hospitalisation was stronger in rural areas among those with MS and stronger in White groups among controls. Conclusions: People with MS are more likely to be diagnosed with DM, resulting in greater all-cause hospitalisation and all-cause mortality. This highlights the importance of equitable screening, prevention, and management of DM in people living with MS, with particular attention to geographical health inequalities.

Background: Parkinson's disease (PD) is the second most common progressive neurological disorder that is pathologically characterized by the loss of dopaminergic neurons within the substantia nigra (SN). However, disease progression probably involves coordinated changes across both neuronal and glial cell populations. Although single-nucleus RNA-seq resolved cell-type-specific transcriptional profiling, differential expression and regulatory interpretation are commonly reported separately; however, they may limit the mechanistic prioritization to uncover novel therapeutic targets. Methods: Here, we performed sample-aware pseudobulk framework analysis on single-nucleus transcriptomes obtained SN of PD and control donors. Cell-type-specific differential expression for PD vs. control was identified using edgeR quasi-likelihood modeling (FDR < 0.05; |log2FC| > 0.5). Further, to quantify disease-specific remodelling, we computed one-vs-rest cell-type specificity scores in each condition and defined delta-specificity as the PD-control shift. We further prioritized the gene-set for dopaminergic neurons and microglia based on edge R significance and delta-specificity shifts, followed by upstream regulatory assessment using transcription factor enrichment and subnetwork visualization using ChEA-KG. Moreover, we used Cellchat to identify altered cell-cell communication networks to infer differences between both conditions. Results: Dopaminergic neurons demonstrated upregulation of neuronal-state remodeling transcriptional programs related gene sets in PD group, including receptor signaling and contact/guidance pathways (e.g., CHRM3, ROBO1, PLXNA4, UNC5D, EFNA5), neuronal excitability homeostatsis, RNA components, cellular traffickings and proteostasis, suggesting coordinated remodeling in surviving neuronal population. Microglia exhibited a compact PD-associated signature enriched for regulatory and activation state-related genes. TF networks analysis revealed distinct regulatory subnetwork in each population,including BNC2-centered network in microglia and an NPAS3-centered network in dopaminergic neurons with embedded ZNF804A and chromatin-associated components. Conclusions: In summary, integrating pseudobulk, delta-specificity scoring and TF-network enrichment analysis provides coherent dopaminergic and microglial programs in PD substantia nigra. This framework prioritizes cell-type-specific potential candidate mechanisms for downstream validation. The inferred regulatory networks and interactions are hypothesis generating and need orthogonal validation, such as spatial or proteomics approaches and independent cohorts.

PURPOSE: Alzheimer disease (AD) is associated with cognitive impairment, brain atrophy, and elevated amyloid-beta and tau. The study aimed to characterize regional atrophy associated with elevated amyloid-beta and tau, as measured by [18F]florbetapir (FBP) and [18F]flortaucipir (FTP) positron emission tomography (PET), respectively, and determine whether combining PET and atrophy data improves the prediction of cognitive impairment. METHODS: Alzheimer Disease Neuroimaging Initiative data (n = 381) were retrospectively analyzed. PET results were correlated with cortical thickness, gray matter (GM) volumes, Mini-Mental State Examination, and Montreal Cognitive Assessment. Linear/logistic regression and area under the curve (AUC) were used to evaluate for significant correlations and compare performances in distinguishing cognitive impairment, respectively. RESULTS: Incremental loss of cortical thickness and GM volume was observed from FBP-/FTP- (n = 205) to single PET-positive (FBP+/FTP-, n = 133; FBP-/FTP+, n = 5) and FBP+/FTP+ (n = 38) groups, particularly in the temporal and parietal lobes. FBP+/FTP+ showed the most severe cortical thickness loss in the entorhinal cortex, temporal lobe GM atrophy, and cognitive impairment. Adding brain atrophy as the third variable resulted in higher odds ratios and improved AUCs for cognitive impairment, with FBP+/FTP+/temporal GM or entorhinal cortical atrophy+ demonstrating the strongest associations with cognitive impairment. CONCLUSION: A multimodal approach combining PET and MRI may help improve the assessment of cognitive impairment in AD.