Journal of Parkinson's Disease

Background: Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common genetic risk factor for Parkinson's disease (PD). G2019S, the most common pathogenic variant, has been linked to milder motor symptoms, but the effects of other LRRK2 variants on disease trajectory remain incompletely characterized. R1441G, the second most common pathogenic variant, co-occurs with the PD risk variant M1646T on a shared haplotype. Whether this haplotype confers a distinct rate of motor progression has not been established. Methods: We analyzed up to 12 years of longitudinal data from 603 participants in the Parkinson's Progression Markers Initiative (PPMI) with PD and available whole-genome sequencing data: 394 sporadic PD, 169 G2019S carriers, 20 R1441G+M1646T carriers, and 20 M1646T carriers. Motor symptom progression (MDS-UPDRS III) was assessed using linear mixed-effects models with genotype-by-time interactions, adjusted for age at onset, disease duration at baseline, sex, race, baseline score, and levodopa equivalent daily dose. Results: R1441G+M1646T carriers exhibited 76% slower progression in OFF-state MDS-UPDRS III than sporadic PD (0.50 vs. 2.04 points/year; {beta}=-1.54 [95% CI: -2.48, -0.60]; p=0.001). G2019S carriers exhibited 26% slower progression (1.52 points/year; {beta}=-0.52 [-0.99, -0.06]; p=0.03). M1646T carriers did not differ from sporadic PD (p=0.60). Slower progression in R1441G+M1646T carriers was characterized by attenuated bradykinesia (64% slower; p=0.008), axial decline (76% slower; p=0.002), and a lack of orofacial symptom progression (p<0.001). R1441G+M1646T carriers also exhibited 55% slower self-reported motor decline (MDS-UPDRS II; p=0.04) Conclusions: R1441G+M1646T carriers exhibit substantially slower motor progression than sporadic PD while M1646T carriers do not.

Dopamine replacement therapy (DRT) alleviates motor symptoms in Parkinson's disease (PD) but can trigger hallucinations in a subset of patients, yet the neural basis of this selective vulnerability is unknown. Hallucinations are among the most disabling non-motor symptoms of PD, linked to social isolation, dementia and institutionalization. Using a validated robotic paradigm to induce and quantify hallucinations in real-time, combined with resting-state fMRI in a crossover On/Off DRT design, we studied patients with PD with (PD-H) and without (PD-nH) hallucinations. DRT selectively amplified sensitivity to robot-induced hallucinations in patients with pre-existing hallucinatory phenotype (PD-H, but not PD-nH) and was accompanied by cortico-striatal and large-scale network hyperconnectivity. Rather than supporting a uniform hallucinogenic effect of dopamine in PD, these findings indicate that DRT interacts with an intrinsic neural vulnerability that varies in patients. Prospective studies will establish whether this pharmacological-behavioural signature identifies patients at risk before clinical hallucinations emerge.

Objective and scalable approaches for detecting subtle motor impairment in isolated REM sleep behavior disorder (iRBD), a prodromal stage of Parkinson's disease, remain limited. We investigated whether markerless motion capture from single RGB-camera videos can identify gait abnormalities in people living with iRBD and provide interpretable digital biomarkers. We retrospectively analyzed 93 standardized walking videos from three clinical sites. Human pose estimation extracted 12 body markers and 14 kinematic time series. Thirty-five machine learning approaches classified healthy controls (HC) and people with iRBD. The Movement Disorder Society Unified Parkinson's Disease Rating Scale Part 3 (MDS-UPDRS III) served as the clinical baseline. The best-performing model (tsfresh+XGBoost) achieved an AUROC of 0.739, significantly outperforming the MDS-UPDRS III sum score when trained on data from all three sites. Harmonized multi-site training improved performance. SHAP identified hip-related temporal features as key contributors, which differed between groups and showed stronger associations with regional dopaminergic deficits than clinical scores. Single-camera gait analysis may provide scalable digital biomarkers for low-cost screening and monitoring of prodromal PD.

Parkinsons disease (PD) arises through disruption of multiple interconnected cellular processes, but the genetic contributions to these processes may differ across ancestries. We investigated functional convergence among genes harboring pathogenic or likely pathogenic (P/LP) variants and variants of uncertain significance (VUS) in a multicenter Indian cohort recruited through the Genetics of Parkinsons Disease in India Young Onset Parkinsons Disease project (GOPI YOPD). The cohort included 668 participants (463 males 69.3%) with a mean age at motor onset of 39.4+/-8.8 years. P/LP variants and VUS identified through previously reported whole-exome or whole genome sequencing were retained as separate evidential categories. The P/LP-associated gene set comprised 11 unique genes and the VUS associated set comprised 40 unique genes. Separate STRING functional-enrichment analyses evaluated Gene Ontology Biological Process, Molecular Function and Cellular Component terms, KEGG pathways, WikiPathways and STRING local network clusters. Terms meeting a Benjamini Hochberg false discovery rate threshold of <0.05 were organized into eight non-mutually-exclusive ontology/pathway categories. Gene to pathway mappings were subsequently projected to individual participants to estimate pathway representation and examine clinical associations. At least one reportable P/LP variant or VUS was identified in 336/668 participants (50.3%): 35 had a P/LP variant alone, 282 had VUS alone and 19 had a P/LP variant together with VUS in one or more additional genes. The most frequently represented categories were mitochondrial organization (247/336, 73.5%), autophagy related processes (228/336, 67.9%) and regulation of synaptic vesicle transport (201/336, 59.8%). PRKN was the most frequent P/LP-associated gene, occurring in 29/54 P/LP carriers, followed by PLA2G6 and PINK1. Lysosomal transport was represented exclusively by VUS-associated genes, particularly GBA1, VPS13C and LRRK2. Among P/LP carriers, additional VUS in distinct genes were not associated with age at onset (P = 0.81) or family history (52.6% versus 31.4%; P = 0.15). No pathway phenotype association remained significant after correction for multiple testing. Genetic findings in this Indian cohort converged across an interconnected mitochondrial autophagic lysosomal vesicular network, with different contributions from P/LP-associated and VUS associated gene sets. This study provides the first pathway resolved South Asian genetic profile and a framework for comparative studies across populations.

Background: Statins have gained increasing interest for their potential therapeutic effect in Parkinson's disease (PD). Beyond their cholesterol-lowering effect, statins decrease synthesis of isoprenoids, which is believed to account for their pleiotropic effects. Isoprenylation is important for proper membrane localization and function of the Rho GTPases, including RhoA. RhoA signalling has emerged as a possible underlying signalling pathway involved in the pathogenesis of PD and other neurodegenerative diseases. Methods: In the present study, we investigated the effects of simvastatin on neurodegeneration-associated phenotypes using human induced pluripotent stem cell-derived dopaminergic (DA) neurons from both PD patients and isogenic PARK2-/- cell lines. The dependence on RhoA was confirmed using direct RhoA inhibition using rhosin. Assessed phenotypes included structural integrity, mitochondrial and lysosomal characteristics, cytokine secretion, and cell viability. To understand the relevance of RhoA in PD, RhoA activity was measured in 32 PD patient iPSC-derived lines with different familial PD-related mutations and in healthy controls. Results: Simvastatin rescued multiple PD-associated phenotypes, including impaired DA neurite outgrowth, mitochondrial and lysosomal alterations, cytokine release, and cell death. RhoA inhibition was associated with changes in mitophagy- and autophagy-related markers, suggesting improved autophagic and mitophagic turnover. Furthermore, we performed the first systematic screen of RhoA activity across 32 iPSC-derived DA neuron lines representing multiple genetic forms of PD (PINK1 loss of function, parkin loss of function, LRRK2 (G2019S), LRRK2 (R1441C), GBA (L44P), GBA (N370S), A53T, and SNCA triplication) and healthy controls. RhoA activity was perturbated across several genetic forms of PD subtypes and was significantly increased in many, although not all, patient lines compared with healthy controls, highlighting disease heterogeneity and supporting RhoA dysregulation as a shared pathogenic mechanism in a subset of PD. Conclusions: Our findings identify aberrant RhoA signalling as a convergent pathogenic mechanism across multiple forms of genetic PD and demonstrate that simvastatin ameliorates PD-associated phenotypes through RhoA inhibition. These results support RhoA as a promising therapeutic target while emphasizing the importance of patient stratification based on RhoA activity.

Isolated rapid eye movement sleep behavior disorder (iRBD) is characterized by nigro-striatal deficits, comprising dopaminergic denervation of the striatum and loss of dopaminergic cells in the substantia nigra (SN), that may herald phenoconversion to clinically manifest synucleinopathy. While phenoconversion has repeatedly been shown to relate to pre-synaptic dopaminergic deficits in the striatum, potential involvement of loss of dopaminergic cells in the SN remain unclear. In addition, phenoconversion may independently relate to noradrenergic deficits, stemming from cell loss in the locus coeruleus/subcoeruleus (LC/LsC) complex. Fifty-six iRBD patients were included and clinically followed over an 11-years as part of the ICEBERG study. Putamen dopamine denervation was quantified using 123I-FP-CIT single-photon emission computed tomography. Cell loss in the SN and LC/LsC was quantified using neuromelanin-sensitive magnetic resonance imaging (MRI). SN cell loss was additionally characterized as free water, derived from diffusion-weighted MRI. The primary outcome was time to phenoconversion. Cox proportional hazards regression was used to investigate relationships between phenoconversion risk and imaging predictors, estimated as hazard ratios (HRs). Out of 56 patients, 24 (41%) converted to a clinically manifest synucleinopathy [PD=14 (58%), DLB=8 (33%), MSA=2 (8%)] over a maximum period of 11 years. We replicated the well-established finding that reduced putamen DaT confers an increased phenoconversion risk [HR (95%CI)=3.1 (1.7-5.5), P<0.001]. We extend on this by showing a similar relationship for SN neuromelanin [HR (95%CI)=2.5 [1.3-4.6], P=0.004], SN free water [HR (95%CI)=1.54 (1.06-2.24), P=0.025], and LC/LsC neuromelanin [HR (95%CI)=2.1 (1.2-3.7), P=0.011], demonstrating involvement of the broader nigro-striatal dopaminergic system along with potential involvement of noradrenergic neurotransmission. When adjusting for putamen DaT, the relationship between phenoconversion risk and SN neuromelanin was attenuated [P=0.16], suggesting partial overlap between the metrics. In contrast, when modelled together, SN neuromelanin [HR (95%CI)=2.8 (1.4-5.6), P=0.003] and LC/LsC neuromelanin [HR (95%CI)=2.3 (1.1-4.8), P=0.037] contributed to phenoconversion risk independently of each other, indicating a differential contribution of dopaminergic and noradrenergic neurotransmitter deficits to iRBD phenoconversion. We demonstrate that phenoconversion in iRBD relates similarly to dopaminergic denervation of the putamen and cell loss in the SN. This opens possibilities for using NM-MRI, which can simultaneously capture dopaminergic and noradrenergic deficits, as an alternative to nuclear imaging techniques when estimating phenoconversion risk in iRBD.

BackgroundLocomotor adaptation is essential for adjusting walking patterns to complex environments. This study investigated locomotor adaptation deficits in people with Parkinsons disease (PD) and examined oscillatory activity in the globus pallidus internus (GPi) during walking adaptation. We hypothesized that elevated beta-band activity in the GPi is associated with reduced locomotor adaptability in PD. MethodsTwelve PD patients with GPi deep brain stimulation (DBS) (eleven bilateral and one unilateral) were included. Local field potentials (LFPs) were recorded from DBS electrodes during split-belt treadmill walking. Patients were tested in the medication-off, DBS-off state. Locomotor adaptation was measured as the change in step length asymmetry during split-belt walking, with smaller changes indicating greater adaptation deficits. ResultsWe found that GPi high beta (20-30 Hz) and low gamma (30-60 Hz) oscillations were modulated during split-belt walking. Compared to adapters, non-adapters showed decreased movement-related beta suppression during walking. Across participants, beta activity in the GPi contralateral to the fast leg was negatively associated with adaptation magnitude (Spearmans {rho} = -0.65 to -0.75). ConclusionsGPi oscillations are dynamically modulated during locomotor adaptation in PD. Increased beta activity may underlie impaired sensorimotor adaptation during walking. These findings provide novel insight into basal ganglia mechanisms of gait adaptation in PD and suggest that elevated GPi beta activity may serve as a marker of locomotor adaptation deficits.

Background: The primary neuroanatomical site of Huntington-s disease (HD) pathology resides in the striatum and its atrophy identifies important disease progression from HD-ISS Stage 0 to Stage 1. Immune-associated proteins may capture variation in HD that is incompletely represented by markers of neuroaxonal injury. Objectives: To determine whether cerebrospinal-fluid myeloperoxidase contributes information about striatal volume loss beyond genetic disease burden and neurofilament light. Methods: Cross-sectional data from 88 persons with HD were analyzed. Cerebrospinal-fluid myeloperoxidase and neurofilament light were measured with a nucleic acid-linked immunosandwich assay. Normalized putamen volume was derived from structural magnetic resonance imaging. Linear regression adjusted for genetic disease burden and sex. Results: Higher neurofilament light was associated with smaller normalized putamen volume (standardized {beta} = -0.322, (P=.0066)). Higher myeloperoxidase was associated with larger normalized putamen volume after adjustment for genetic disease burden, sex, and neurofilament light (standardized {beta} = 0.183, (P=.0386)). Adding myeloperoxidase increased explained variance in striatal loss. Conclusions: Cerebrospinal fluid myeloperoxidase contributed modest incremental information about striatal volume in this cross-sectional sample. Independent longitudinal studies are needed to determine its biological source, temporal behavior, and potential biomarker value. Findings advance efforts to characterize multicomponent biological markers of HD.

INTRODUCTION: Biomarkers for monitoring disease activity and treatment response in peripheral neuropathies remain limited. Big tau, a high-molecular-weight isoform of tau, is predominantly expressed in the peripheral nervous system (PNS). We investigated serum levels of big tau, brain-derived tau (BD-tau), and neurofilament light chain (NfL) in peripheral neuropathies, multiple sclerosis (MS), Alzheimer disease (AD), and healthy controls (HC). METHODS: Ultra-sensitive blood-based assays run on an HD-X Single Molecule Array analyser (Quanterix) were used to measure big tau and BD-tau in serum from patients with Guillain-Barr&eacute syndrome (GBS, n=81), Miller Fisher syndrome (MFS, n=20), Charcot-Marie-Tooth disease (CMT, n=102), chronic inflammatory demyelinating polyneuropathy (CIDP, n=43), MS (n=159), AD (n=20), and HC (n=41). NfL was measured in patients with neuropathies using an SR-X Single Molecule Array analyser (Quanterix). RESULTS: Serum big tau levels were higher in GBS than in AD (11.4 vs 2.4 pg/mL, p<0.0001) and MS (11.4 vs 9.0 pg/mL, p=0.01), and similar to CIDP and CMT. Contrarily, serum BD-tau levels in GBS were higher than in CIDP (3.0 vs 2.3 pg/mL, p=0.006) and MS (3.0 vs 1.7 pg/mL, p<0.0001), but similar to CMT, and lower than in AD (3.0 vs 9.8 pg/mL, p<0.0001). Serum NfL levels were higher in GBS than in CIDP (32.5 vs 13.0 pg/mL, p=0.0002), CMT (32.5 vs 12.3 pg/mL, p<0.0001), and HC (32.5 vs 7.6 pg/mL, p<0.0001). Compared with GBS, MFS patients showed higher BD-tau (12.7 vs 3.0 pg/mL, p=0.003), lower big tau (5.4 vs 11.4 pg/mL, p=0.002), and higher NfL levels, although the latter did not reach statistical significance (118.3 vs 32.5 pg/mL, p=0.16). The NfL/big tau ratio was significantly higher in MFS than in GBS, CIDP, and CMT. In GBS, BD-tau correlated with early clinical severity (MRC at 1 week; I-RODS at 4 weeks; maximum GBS-DS and GBS-DS at 4 weeks), whereas neither tau biomarker showed long-term clinical correlations. Higher BD-tau and big tau levels were associated with the need for mechanical ventilation (BD-tau: 8.6 vs 2.9 pg/mL, p=0.019; big tau: 19.7 vs 10.7 pg/mL, p=0.007), while higher BD-tau levels were associated with mortality (10.9 vs 2.9 pg/mL, p=0.003). CONCLUSIONS: Higher big tau levels in peripheral neuropathies than in CNS diseases support its role as a PNS-specific biomarker. In MFS, increased serum BD-tau, reduced big tau, and an elevated NfL/big tau ratio suggest CNS involvement with relative preservation of the PNS.

Viral infections have long been proposed as environmental contributors to neurodegenerative diseases, including Parkinson's disease (PD), yet the molecular mechanisms linking infection and neurodegeneration are not well defined. Neuroinflammation and disruption of central nervous system (CNS) homeostasis have emerged as potential mediators. In this study, we used severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, as a model pathogen to investigate convergent molecular pathways between viral infection and PD. Single-nucleus RNA sequencing (snRNA-seq) was performed on post-mortem striatal tissue from 14 individuals stratified into four groups: COVID-19 only (COVID-19), PD only (PD), comorbid PD with COVID-19 (PD/COVID-19), and controls (Control). The PD/COVID-19 group exhibited an expanded astrocytic population and a pronounced interferon-associated molecular signature characterized by increased expression of canonical interferon-stimulated genes, including IFI44L (average log2FC= 3.9; adjusted p=2.3 x 10-373), IFI44 (average log2FC=2.9; adjusted p=8.0 x 10-266), ISG15 (average log2FC=3.1; adjusted p=1.2 x 10-197), and RSAD2 (average log2FC= 3.5; adjusted p=8.6 x 10-111). Pathway analyses demonstrated activation of innate immune and antiviral signaling pathways, particularly within microglia and astrocytes, including interferon signaling, pattern-recognition receptor pathways, and complement-associated responses. In parallel, genes involved in lipid metabolism, cholesterol homeostasis, synaptic maintenance, and neuronal signaling were reduced across disease groups. Proteomic analyses independently confirmed enrichment of antiviral and interferon-associated pathways and identified convergent suppression of sterol, cholesterol, and lipid metabolic processes. Our findings identify a convergent molecular signature linking PD and COVID-19, pronounced in comorbid individuals and characterized by interferon-driven innate immune activation, glial inflammatory responses, and dysregulation of lipid metabolic homeostasis. Collectively, the data support a model in which severe viral infection amplifies biological pathways already implicated in PD pathogenesis.

Objective: Whether a scheduled antiseizure medication (ASM) continues on schedule across the ICU-to-floor transfer has not been characterized. We quantified ASM administration-gap frequency across this transfer and compared it with gap frequency during matched non-transfer intervals in the same patient and drug. Methods: In this retrospective MIMIC-IV (version 3.1) cohort study, we identified epilepsy and status-epilepticus admissions with an ICU stay followed by floor transfer and a scheduled ASM order active at ICU departure. A gap was defined as an interval exceeding 1.5 times the expected dosing interval between the last ICU dose and first floor dose, or no further dose before discharge, and compared with a matched non-transfer control interval in the same patient and drug (paired McNemar test). A multivariable model evaluated six prespecified clinical predictors; sociodemographic variables were summarized descriptively. Results: Among 2,469 ASM transition-by-drug observations (1,583 admissions, 1,335 patients), an administration gap occurred in 251 (10.2%; 95% CI, 8.7%-11.7%). Gap frequency across the transfer exceeded frequency during matched non-transfer control intervals in the same patient and drug: a paired rate difference of 5.8 percentage points (95% CI, 4.4-7.1; 7.5% vs 1.7%; P = 7.3 x 10^-22) before the transfer and 6.4 percentage points (95% CI, 4.9-7.9; 8.9% vs 2.5%; P = 1.9 x 10^-23) after. Gap rates were similar for intravenous-available (9.9%) and oral-only (11.4%) drugs (rate difference, 1.5 percentage points; 95% CI, -1.6 to 4.5; P = .34). None of six prespecified predictors reached significance after correction. Significance: An antiseizure medication administration gap occurred in approximately 1 of every 10 drug-transition observations at the ICU-to-floor transfer, exceeding matched non-transfer gap rates by 5.8 to 6.4 percentage points. This transfer-associated excess, rather than any single medication or patient characteristic, supports a structured medication-continuity check.

Background: Plasma phosphorylated tau at threonine 217 (p-Tau217) is a leading blood-based biomarker for Alzheimer's disease (AD). Robust analytical characterization on high-throughput platforms is essential for research use and clinical translation. Objective: To evaluate the analytical performance of an automated plasma p-Tau217 immunoassay and characterize its discrimination of PET-defined amyloid status. Methods: We performed analytical validation of the Access Research Use Only (RUO) plasma p-Tau217 immunoassay on the Beckman Coulter DxI 9000 Access Immunoassay Analyzer and evaluated biomarker discrimination of PET-defined amyloid pathology in a subset of the Bio-Hermes-001 cohort spanning the symptomatic cognitive continuum (mild cognitive impairment or mild AD dementia; cognitively unimpaired participants excluded; n = 449). Analytical precision, sensitivity, linearity, specificity, interference, and sample stability were assessed per Clinical and Laboratory Standards Institute guidelines. Discrimination of PET-defined amyloid status was evaluated using receiver operating characteristic curve and indeterminate zone analyses. Results: The assay demonstrated high precision (within-laboratory CV </=7.1%), excellent sensitivity (limit of detection 0.018-0.021 pg/mL), linearity across the analytical measuring range (R-squared > 0.99), strong epitope specificity (</=1.0% cross-reactivity with other tau phosphoisoforms), and minimal interference from over 60 endogenous and exogenous substances. In 449 research participants plasma p-Tau217 showed strong discrimination between amyloid-positive and amyloid-negative groups (AUC 0.881; 95% CI 0.846-0.915). Application of indeterminate zones systematically improved classification metrics at the cost of fewer definitive classifications. Conclusions: These findings support the Access p-Tau217 (RUO) assay as a robust, high-throughput assay for plasma biomarker-based discrimination of PET-defined amyloid pathology in AD applications.

Introduction: Parkinson's disease (PD) and aging both disrupt hypothalamic-pituitary-adrenal (HPA) axis function and peripheral immune homeostasis. Whether aging or -synuclein (-syn) pathology alters glucocorticoid (GC) sensitivity of peripheral immune cells has not been investigated. Methods: Using an ex vivo GC sensitivity assay, we assessed the responsiveness of isolated and lipopolysaccharide (LPS)-stimulated splenocytes to the anti-inflammatory effects of increasing doses of corticosterone (CORT) in a wild-type (WT) aging cohort and in a PD -syn transgenic mouse model and respective age-matched controls. Results: Compared with splenocytes from 6-month-old WT mice, splenocytes from 20-month-old WT mice were less sensitive to 0.1 and 0.5 M CORT. Isolated splenocytes from PD vs. control mice were less sensitive to 0.05, 0.1, and 0.5 M CORT specifically at 16 months of age, but not at 6 or 20 months of age. As peripheral immune phenotyping revealed neither differences in HPA axis-related parameters nor in splenic GC receptor expression between PD and age-matched control mice at 6, 16, and 20 months, splenic GC resistance in PD mice at 16 months of age seems to be mediated by downstream GR signaling dysfunction. Conclusion: Together, our results support the hypothesis that -syn pathology accelerates an aging-associated decline in the peripheral sensitivity to anti-inflammatory GCs and may thereby sustain systemic and neuroinflammatory processes in PD.

Amyotrophic lateral sclerosis (ALS) is a motor neuron disease, leading to progressive muscle weakness and motor impairment. Growing evidence indicates that cerebellar Purkinje cells, which play a central role in motor coordination, are also affected in ALS. However, it is unclear whether the molecular events that initiate neurodegeneration in these ALS-relevant motor-controlling neurons are shared or distinct. Here, we used a MATR3 S85C knock-in (KI) mouse model of early-stage ALS with stage-specific motor phenotypes and selective vulnerability of motor neurons and Purkinje cells to decipher the molecular events underlying neurodegeneration in these two neuronal populations. We found that a profound reduction in detectable MATR3 S85C immunoreactivity (hereafter referred to as MATR3 loss) in both motor neurons and Purkinje cells precedes the onset of motor dysfunction and neuropathology, implicating MATR3 loss as the earliest detectable molecular event. Our bulk cerebellar RNA profiling and motor neuron-specific RNA profiling data at the onset of MATR3 loss revealed distinct molecular signatures. In the cerebellum, Ngfr expression emerged in Purkinje cells before the onset of neuronal loss and remained elevated throughout the disease course. This increase was accompanied by activation of the JNK-mediated cell death pathway. In the motor neurons, elevated Fgf21 and integrated stress response (ISR) gene expression were the first to be observed and persisted throughout disease progression, consistent with previous findings in SOD1 mouse models. Our findings provide mechanistic insights into the initiation of neurodegeneration in ALS-relevant motor-controlling neurons and implicate potential neuron type-specific targets for future therapeutics.

Circadian disruption, notably sleep disturbances, serves as an early indicator of Alzheimers disease (AD), preceding cognitive symptoms like memory loss. The suprachiasmatic nucleus (SCN) governs biological rhythms and receives direct retinal input via melanopsin-expressing retinal ganglion cells (mRGCs) to synchronize with environmental light cycles. The anatomical and functional basis for circadian disruption in AD remains unclear. Here, we explored the multi-level relationships between gene expression, the SCN connectome, and regulations of sleep and circadian rhythms in the APP/PS1 mouse model. The sleep architecture of APP/PS1 mice displayed significantly reduced rapid eye movement sleep (REM), associated with a reduced daily core body temperature amplitude and locomotor hyperactivity. Lastly, APP/PS1 mice showed an impaired response to acute light pulse stimulation and present hyperactivity of mRGCs at a young age and hypoactivity of these cells at older ages. These physiological functions are known to be, at least in part, regulated by the SCN, the main target of mRGCs. We noted several modifications in SCN connectomics using serial blockface electron microscopy (SBEM), including a reduction of the dendro-dendritic chemical synapse (DDCS) network that receives a large part of the retinal input and is thought to be crucial for synchronicity between SCN neurons. In addition, we observed multiple signs of dystrophy, including modifications of the shape of dendrites and cell soma, accumulation of aggregated lysosomes, and swelling of axons. At the same time, we investigated the changes in gene expression using spatial transcriptomics. The SCN presents changes in the expression of genes associated with synapse formation, cell adhesion, and neurite growth. These results suggest that, despite the absence of amyloid plaques in the ventral hypothalamus, the SCN of APP/PS1 mice still undergo profound gene expression changes, impacting connectomics and physiological functions. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/744599v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@ceedb0org.highwire.dtl.DTLVardef@156cfaaorg.highwire.dtl.DTLVardef@5bc262org.highwire.dtl.DTLVardef@36df4d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background. In Europe, first-trimester combined screening with the Fetal Medicine Foundation (FMF) algorithm identifies women at increased risk of preeclampsia who may benefit from personalized aspirin prophylaxis. However, a substantial proportion of early-onset preeclampsia (EOPE) remains undetected at clinically acceptable specificity. Objective. To evaluate the first-trimester performance of MaiRa for early-onset preeclampsia (EOPE) risk stratification by benchmarking it against FMF screening in the same women, characterizing discordant patient-level classification profiles and exploring potential implementation strategies. Study Design. This secondary case-control analysis was nested within the prospective, multicentre PREMOM cohort [NCT04990141], which enrolled women with singleton pregnancies across 14 tertiary hospitals in Spain. First-trimester MaiRa and FMF risk estimates were evaluated in the same 126 pregnant women, comprising 99 uncomplicated controls and 27 EOPE cases, defined by disease onset before 34 weeks. Discrimination was compared using a stratified paired bootstrap analysis of the areas under the receiver-operating-characteristic curves. Performance was assessed at prespecified clinical thresholds, and detection rates were evaluated at fixed false-positive rates. Universal and contingent MaiRa implementation strategies were also evaluated. Results. MaiRa showed greater first-trimester discrimination for EOPE than FMF combined screening (AUC, 0.974 vs 0.900; P=.040) and consistently achieved higher detection rates across fixed false-positive rates. At false-positive rates of 5% and 10%, MaiRa detected 85.2% and 92.6% of EOPE cases, compared with 44.4% and 70.4% for FMF, respectively. Patient-level analysis demonstrated that MaiRa identified 12 of 27 EOPE cases (44.4%) classified as low risk by FMF; these pregnancies generally exhibited less abnormal conventional first-trimester profiles, including fewer maternal risk factors, lower mean arterial pressure and lower uterine artery pulsatility index, yet 8 of 12 (66.7%) subsequently developed severe EOPE. Exploratory implementation analyses showed that universal MaiRa screening achieved the highest EOPE detection, whereas a contingent strategy using FMF for triage and reflex MaiRa testing reduced molecular testing to 35.7% of pregnancies while maintaining 77.8% sensitivity and 97.0% specificity. Conclusion. MaiRa provided greater first-trimester discrimination for EOPE than conventional combined screening and detected additional pregnancies that later developed severe disease despite less abnormal conventional screening profiles. The findings suggest that maternal plasma cfRNA profiling captures biological alterations not fully reflected by combined first-trimester screening and support further prospective evaluation in an independent, unselected obstetric population. Key words: early-onset preeclampsia; first-trimester screening; cell-free RNA; liquid biopsy; Fetal Medicine Foundation algorithm; combined screening; risk stratification; aspirin prophylaxis.

Background & Aims: Fatigue is a central symptom of chronic liver disease (CLD), substantially impacting health-related quality of life (HRQoL). This study aimed to further understand CLD symptomatology, including fatigue, and its impact on HRQoL from a patient perspective. Methods: Abbott Global Assessment of Patients unmet needs (aGAP) was a multinational, cross-sectional survey in adults with compensated CLD in China, India and Mexico, conducted between July and November 2024. Adult participants who self-reported that they had physician-diagnosed CLD and were experiencing fatigue completed a quantitative survey to assess symptom burden and included three HRQoL patient-reported outcome (PRO) questionnaires (Patient-Reported Outcomes Measurement Information System [PROMIS]-29+2, Work Productivity and Activity Impairment - Specific Health Problem version 2.0 [WPAI: SHP], Multidimensional Fatigue Inventory [MFI]). Results: Overall, 505 participants (China: 200; Mexico: 105; India: 200) completed the study. Participants reported that their CLD-related fatigue sometimes, often or always affected their self-esteem/confidence (45.1%) and ability to maintain or acquire new employment (38.6%). Most participants reported moderate (51.3%) or serious (26.9%) fatigue, with 33.5% experiencing fatigue every day or almost every day. Many participants felt their social life was negatively impacted by their fatigue (47.3%) and that there were related financial difficulties (53.9%). Use of validated PRO tools demonstrated severe fatigue (MFI: overall mean [SD] 13.9 [3.4] general fatigue and 13.4 [3.6] physical fatigue) as well as substantial levels of work and activity impairment (WPAI: SHP overall mean [SD] 53.0 [26.4]) and high levels of anxiety, pain interference, depression and sleep interference (PROMIS T-scores [&ge;]54). Conclusions: Fatigue has a substantial impact on HRQoL among adults with CLD across several countries, highlighting a global unmet need for targeted interventions to effectively identify and manage the condition.

Background: Consumer use of AI chatbots for health advice is rising, yet triage safety relative to established services remains unclear. Australia's Healthdirect, a government-backed symptom checker with 2.4 million uses in FY2024-25, remains unevaluated against frontier large language models (LLMs), and whether premium subscriptions improve triage safety remains unexplored. This study compared the triage accuracy and safety of Healthdirect against six LLM configurations across ChatGPT, Claude, and Gemini, assessed whether paid subscriptions improve triage safety, and characterised each system's error patterns. Methods: Forty-five clinical vignettes from the Semigran et al. benchmark spanning emergency, non-emergent, and self-care categories (15 each) were evaluated across seven systems. Healthdirect was tested following a seven-rule interaction protocol. LLMs were evaluated using first-person patient-language prompts under free-tier and paid-tier conditions. Outcomes were triage accuracy, emergency sensitivity, under-triage, and critical misses, analysed using Cochran's Q, Bonferroni-corrected McNemar tests, Cohen's kappa, and Wilson intervals. Findings: Triage accuracy differed significantly (Cochran's Q = 36.79, p < 0.001). Healthdirect achieved 48.9% accuracy (95% CI 35.0% to 63.0%; kappa = 0.233) versus 73.3% to 86.7% for LLMs (kappa = 0.600 to 0.800). Healthdirect operated under conservative interactive defaults while LLMs received complete information in a single prompt, which may have disadvantaged Healthdirect. Emergency sensitivity was 46.7% versus 80.0% to 86.7% for LLMs. Healthdirect produced two critical misses; no LLM produced any across 270 evaluations (95% CI 0% to 1.4%). When LLMs undertriaged, they recommended GP care rather than self-care. No tier differences were significant (all p > 0.05), and most systems over-triaged self-care cases. Interpretation: Frontier LLMs demonstrated higher triage accuracy and safer error profiles than Healthdirect. All LLMs avoided critical misses; Healthdirect did not. Premium subscriptions did not significantly improve triage safety. These findings support clinical governance decisions about whether LLMs warrant formal evaluation alongside government-backed symptom checkers.

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardiovascular outcomes. Whether ECGs can support prediction of multiple future diseases across organ systems remains unclear. We developed ECG-RISK, a multitask survival model for 67 incident three-character ICD-10 endpoints using ECG waveforms, demographic characteristics and routinely collected laboratory data from 86,673 MIMIC-IV patients. Discrimination was highest for heart, brain, kidney and lung endpoints, with organ-level C-indices ranging from 0.796 to 0.825, whereas liver and pancreatic endpoints showed lower discrimination. The ECG-only model achieved strong discrimination across most endpoints, whereas the incremental improvement gained by incorporating ECG and laboratory inputs beyond demographic information varied substantially across endpoints. Across the nine exploratory aggregated outcomes, Kaplan Meier curves showed clear separation among model-score tertiles. Discrimination was highest for dementia (C-index, 0.891) and heart failure (C-index, 0.857). These findings support the feasibility of ECG-based longitudinal risk prediction across multiple diseases. External validation and competing-risk analyses are required to assess generalisability and clinical utility.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.