Annals of Neurology

Magnetic Resonance guided High Intensity Focused Ultrasound (MRgHIFU) has been demonstrated to be a safe and effective minimally invasive therapy for essential tremor (ET). However, it is not clear whether older adults ([&ge;]70 years old) or individuals with comorbidities exhibit similar safety and efficacy. This IRB approved project collected EPIC EMR data on patients that underwent MRgHIFU at Parkview Regional Medical Center from January 2023 to November 2025. 68 patients were assessed for tremor severity using Clinical Rating Scale for Tremor (CRST), quality of life using Quality of life in ET Questionnaire (QUEST), and safety profile via reported post-procedure side effects. CRST and QUEST scores improved up to 1 year from baseline in our patient cohort and efficacies in older ([&ge;]70 years of age) and younger (<70 years of age) patients up to 3 months post MRgHIFU were not statistically different. Effects of comorbidities on CRST or QUEST scores improvements were all transient or did not affect endpoints. Older patients showed fewer total side effects at 3 months (1.17 (95% CI: 0.47-1.87) vs 0.21 (95% CI: -0.09-0.51), p=0.017) as did patients with pulmonary disease at 1 month (1.9 (95% CI: 1.6-2.2) vs 1.1 (95% CI: 0.9-1.3), p=0.036) while patients with family history of tremor showed more side effects at day 1 (1.5 (95% CI: 0.8-2.2) vs 2.5 (95% CI: 2.1-2.9), p=0.025). Age and comorbidities were not detected to adversely affect safety or efficacy following MRgHIFU in ET patients.

Peripheral inflammation in Parkinson's disease (PD) remains poorly characterised among carriers of Asian-prevalent LRRK2 G2385R and R1628P variants. We investigated plasma immunoinflammatory markers (i.e., IL-6, TNF-, CCL2, CX3CL1, CCL5, and VCAM-1) via multiplex immunoassay in 240 participants: PD-G2385R (n=53), PD-R1628P (n=58), PD-G2385R+R1628P (n=5), idiopathic PD (iPD; n=62), and controls (n=62), and their clinicobiological correlates including monocyte LRRK2 kinase activity (pRab10Thr73). Compared with iPD and/or controls, TNF-, CCL2, CX3CL1, and CCL5 were lower in PD-G2385R, while IL-6, TNF-, CCL2, and CCL5 were lower in PD-R1628P. Higher LRRK2 kinase activity correlated with lower TNF-. CX3CL1 correlated with greater motor severity in iPD but less disability in both variant groups. CCL5 correlated with less motor complications in PD-G2385R, while IL-6 and VCAM-1 correlated with worse disability and/or cognition in PD-R1628P. These findings suggest that immunoinflammatory profiles and their clinical relevance in PD differ by genotype, with implications for stratification in future immunomodulatory trials.

Progressive multiple sclerosis (PMS) lacks blood-based biomarkers of the neurodegenerative processes driving disability. We measured synaptopodin, a postsynaptic protein, in neuronal-enriched extracellular vesicles (NEVs) across two independent cohorts: the SPRINT-MS trial (n=184) and a real-world validation cohort (n=268). A one SD increase in baseline synaptopodin was associated with ~32% lower risk of confirmed disability progression in PMS (p=0.011), with the strongest effect in secondary PMS (SPMS) (~57% lower odds, p=0.019). This SPMS association was replicated in the validation cohort (~60% lower odds, p=0.009). Higher baseline synaptopodin was associated with future slower whole-brain atrophy and preserved microstructural integrity across MRI metrics (p=0.007-0.013). Longitudinal changes in NEV synaptopodin were associated with disability worsening (p=0.007) and paralleled MRI microstructural changes. NEV synaptopodin, but not NfL, was associated with confirmed disability progression in PMS participants with both biomarkers measured (HR 0.71 vs 1.12, p=0.007 vs 0.22 for NEV synaptopodin and NfL, respectively) and SPMS (HR 0.58 vs 1.10, p=0.003 vs 0.50). Adding synaptopodin, but not NfL, to a base model improved discrimination for disability progression in SPMS in both cohorts (e.g. validation AUC 0.755 to 0.838, p=0.005). These findings identify NEV synaptopodin as a prognostic and longitudinal, blood biomarker of synaptic integrity in PMS, particularly SPMS, complementing NfL.

Background. Nigrostriatal dopaminergic dysfunction, a biological anchor of Parkinson's disease (PD), is routinely assessed using single-photon emission computed tomography of the dopamine transporter (DaT-SPECT). Dopa decarboxylase (DDC) in cerebrospinal fluid (CSF) is a promising biomarker of dopaminergic dysfunction, but its association with DaT-SPECT has to be demonstrated. Objectives. To investigate the association of CSF DDC with DaT-SPECT. Methods. We first analysed proteomic and DaT-SPECT data from the Parkinson's Progression Markers Initiative (PPMI), including PD (n=891), prodromal PD (n=867) and healthy controls (n=161). We then verified this association in a single-center clinical cohort (UNIPG), including PD/Dementia with Lewy Bodies (DLB) (n=78), atypical parkinsonisms (AP, n=11), other neurodegenerative diseases (OND, n=25) and controls (CTRL, n=40). Here, CSF DDC was measured by a novel fully automated quantitative immunoassay. Results. In PPMI, among 129 proteins assessed, DDC showed the strongest association with DaT-SPECT ({beta} = -0.132, FDR = 6.92 x 10-33). Across PPMI and UNIPG cohorts, DDC correlated with striatal binding ratio (SBR) ({rho} = -0.377, P < 0.001; {rho} = -0.466, P < 0.001, respectively) and accurately discriminated positive from negative scans (AUC 0.811, 95% CI 0.762-0.859; AUC 0.870, 95% CI 0.777-0.963, respectively). In PPMI prodromal cases, higher DDC predicted faster motor progression. In UNIPG, DDC distinguished PD/DLB and AP from OND and CTRL groups (AUC 0.830, 95% CI 0.764-0.896), independently of dopaminergic treatment. Conclusion. CSF DDC reflects nigrostriatal dopaminergic dysfunction, representing a potential quantitative biochemical alternative to DaT-SPECT that might be readily implemented via automated immunoassays.

Importance: Blood biomarkers for Alzheimer disease(AD), Parkinson disease(PD), and amyotrophic lateral sclerosis(ALS) are typically developed as disease-specific single-analyte tests. Whether one shared plasma panel can support disease-selective classification remains unclear. Objective: To test whether the Olink Target 48 Neurodegeneration plasma panel, analyzed with disease-specific Elastic Net models, can discriminate AD, PD, and ALS in a heterogeneous neurological cohort. Design, Setting, and Participants: Single-center diagnostic cohort study at Keio University Hospital, Tokyo, Japan. After quality control and one consent withdrawal, 302 participants were analyzed(healthy controls n = 62; AD continuum n = 93; PD n = 39; ALS n = 27; other neurological disorders n = 81) and allocated by diagnosis-stratified sampling into a discovery training set(n = 211) and a locked hold-out test set(n = 91). Exposures: Plasma normalized protein expression from 42 assays retained after protein quality control. Plasma DOPA decarboxylase was excluded a priori from all classifiers because blood levels primarily reflect dopaminergic treatment exposure. Main Outcomes and Measures: Hold-out receiver operating characteristic area under the curve(AUC). Sensitivity and specificity at a training-set Youden threshold locked for Test. Results: Hold-out AUCs were 0.974(95% CI, 0.942-0.995) for AD, 0.926(0.820-1.000) for PD, and 0.995(0.980-1.000) for ALS. At locked Youden cutoffs, sensitivity was 0.929 (95% CI, 0.765-0.991) and specificity was 0.921 (95% CI, 0.824-0.974) for AD, 0.833 (95% CI, 0.516-0.979) and 0.975 (95% CI, 0.912-0.997) for PD, and 1.000 (95% CI, 0.631-1.000) and 0.940 (95% CI, 0.865-0.980) for ALS. Conclusions and Relevance: A single plasma neurodegeneration panel supported disease-selective classification of AD, PD, and ALS in internal validation. Multicenter external validation is needed before clinical application.

Tissue-based assays provide broad screening for neural autoantibodies but remain vulnerable to technical and reader-dependent variability. We evaluated an integrated workflow combining automated 3,3'-diaminobenzidine tissue-based assay processing, digital whole-slide imaging, and interpretable deep learning. Model development used 2,357 retrospective serum and cerebrospinal fluid images referred from more than 80 institutions and processed in a centralized laboratory, with reference labels established by expert-consensus tissue-based assay interpretation. A prospective validation cohort included 200 images from 200 unique patients (154 positive and 46 negative; 100 serum and 100 cerebrospinal fluid). The same images were evaluated by two expert and two novice readers in a fixed-order two-round study, with unaided interpretation followed by artificial-intelligence-assisted interpretation after a washout of at least two weeks. The standalone binary classifier achieved an area under the receiver operating characteristic curve of 0.922, accuracy of 86.5%, sensitivity of 85.7%, and specificity of 89.1% in prospective validation. Pooled reader accuracy was 90.4% in the unaided round and 97.4% in the artificial-intelligence-assisted round (McNemar P < 0.001), with specificity of 82.6% and 99.5%, respectively. Novice-reader accuracy was 83.3% unaided and 96.5% with artificial-intelligence assistance (P < 0.001), approaching unaided expert accuracy of 97.5%. Among tissue-based-assay-positive cases, reader accuracy for cytoplasmic/nuclear antigen-associated versus neural surface antigen-associated staining-pattern subclassification was 88.8% unaided and 94.0% with artificial-intelligence assistance (P < 0.001). These findings support further multicentre, cross-platform evaluation of artificial-intelligence-assisted neural autoantibody tissue interpretation.

Purpose Dynamic [11C]UCB-J PET can simultaneously provide information about synaptic density and relative perfusion in Parkinson's disease (PD). We investigated whether these complementary biomarkers could explain a higher percentage of motor symptom severity variation in PD and inform other PD-specific physiological alterations and symptomatology. Methods Binding potential (BPND) and relative perfusion (R1) images were derived 30 PD and 30 controls imaged with [11C]UCB-J PET. A spatial covariance analysis was used on R1 to derive PDRP-a known metabolic network alteration in PD. Linear models related PD-motor symptom severity to PDRP expression and nigral synaptic losses. Next, whole-brain cluster analyses identified physiological correlates for PD-tremor severity, a prominent motor symptom that does not correlate with dopaminergic losses. Lastly, inter-individual regional correlation alterations in PD were examined for both BPND and R1. Results PDRP was identified from R1, with higher expression in PD (p=1.7x10-5, Cohen's d=1.2), and its expression correlated with MDS-UPDRS III (r=0.57, p=0.0009). Combining PDRP expression scores with synaptic density in the substantia nigra explained 48% of the total variation in MDS-UPDRS Part III, twice as much as previously reported using nigral synaptic density alone. Two significant large clusters (pk<1x10-6) were identified in the occipital-parietal areas where R1 was negatively correlated with tremor severity (r ~ -0.65, p<0.001). Extensive correlation alterations were observed in synaptic density (prominently involving pallidum) and perfusion (prominently involving thalamus). Conclusions Combining synaptic and perfusion outcomes for [11C]UCB-J PET explains more physiological alterations associated with PD.

Objectives: Genotype-phenotype studies in rare epilepsies typically relate a pathogenic DNA sequence change to clinical outcome, without considering the broader molecular context of a given variant. Here we ask whether clinical heterogeneity in SCN8A-related disorders (SCN8A-RD) is patterned along molecular dimensions that go beyond the specific genetic alteration, to include position in the linear channel topology, proximity to post-translational modification (PTM) and structural sites, and predicted effects on mRNA splicing. Using the International SCN8A Registry, we map these features against seizure, developmental, and treatment-response phenotypes to identify the regions and molecular feature classes with which clinical variability is associated. Methods: We identify "hot-spots" across the coding sequence for seizure types and severity of developmental disability (DD). We then test for enrichment of clinical features near sites related to PTM and protein structure, identify variants that may alter mRNA splicing, and evaluate the interaction between these features and clinical subgroups. Results: We expand on previous work identifying regions of coding DNA sequence that are pathogenic or benign "hot-spots". We show regional enrichment of numerous seizure types and severities of DD. Enrichment analysis of PTM and protein structural sites shows distinct enrichment profiles for developmental, seizure, and medication-response features. Finally, we identify 14 variants that are likely to alter RNA splicing. Significance: We provide a higher-resolution map of pathogenic variation across SCN8A and show that seizure types, developmental severity, and medication response are regionally organized along the coding sequence. Proximity to structural and glycosylation sites distinguishes phenotypic subgroups is associated with differential drug response, including a glycosylation-gabapentin relationship, and 14 missense variants are flagged as likely splice-altering, nominating targets for splice-directed therapy and providing candidates for experimental validation of dual pathogenic mechanisms.

Background: Peripheral inflammation has been implicated in the pathophysiology of Parkinson's disease (PD), but its relationship with autonomic dysfunction remains unclear. Objectives: To explore the association between peripheral inflammation, assessed by the neutrophil-to-lymphocyte ratio (NLR), and autonomic function in patients with PD. Methods: We retrospectively analyzed 97 patients with PD who underwent 123I-metaiodobenzylguanidine (MIBG) cardiac scintigraphy and differential blood cell counts. Associations of NLR with early and delayed heart-to-mediastinum (H/M) ratios, washout ratio, and the coefficient of variation of R-R intervals (CVRR) were assessed using Spearman's rank correlation and multivariable linear regression adjusted for age, sex, and disease duration. Results: No significant univariable correlations were observed between NLR and the autonomic measures. In multivariable analysis, higher NLR was associated with a lower early H/M ratio (B = -0.802, 95% CI -1.598 to -0.005, P = 0.049), whereas no significant associations were observed with the delayed H/M ratio, washout ratio, or CVRR. Sensitivity analyses showed a generally consistent direction of association, although the effect estimate was attenuated after exclusion of two influential observations and statistical significance was not consistently retained. Conclusions: Higher NLR was associated with lower early cardiac MIBG uptake after adjustment for age, sex, and disease duration in patients with PD. This exploratory finding raises the possibility of an association between systemic inflammation and sympathetic dysfunction in PD and requires confirmation in larger prospective studies.

Frontotemporal lobar degeneration (FTLD) encompasses clinically and biologically heterogeneous syndromes that are unlikely to be captured by a single blood biomarker. Although plasma neurofilament light (NfL) chain reflects neuroaxonal injury, multiplex profiling may identify complementary inflammatory, vascular and proteostatic processes relevant to clinical phenotype and progression. We characterised plasma CNS-related and inflammatory proteomic signatures across FTLD-related clinical syndromes and tested their associations with neuroaxonal injury, clinical severity, regional brain atrophy and survival. Plasma samples from 177 participants with behavioural variant frontotemporal dementia (bvFTD), primary progressive aphasia (PPA), progressive supranuclear palsy (PSP) or corticobasal syndrome (CBS) and 67 healthy controls were analysed using the high-sensitivity nucleic acid-linked immuno-sandwich assay (NULISA) platform. We quantified 130 CNS-related and 250 inflammation-related proteins. Differential expression and multivariate classification analyses were complemented by hierarchical clustering, penalised regression and survival analyses. Canonical correlation analysis tested multivariate associations between disease-associated proteins and regional MRI brain volumes. Sixty-one CNS-related and 61 inflammation-related proteins differed between participants with FTLD-related syndromes and controls after false-discovery-rate correction. NfL was the strongest individual discriminator between all patients and controls, with an area under the receiver operating characteristic curve of 0.91. In exploratory full-cohort models, the multivariate CNS signature achieved an area under the curve of 0.93, compared with 0.82 for the multivariate inflammation signature. However, inflammatory proteins provided stronger discrimination for selected syndrome comparisons, including PPA versus PSP. Among inflammation-related proteins, SPP1 and CD276 showed the strongest positive associations with NfL. Higher CD276 and SPP1 were associated with increased mortality, whereas higher amyloid-{beta}42 was associated with lower mortality. A multivariate protein signature weighted towards tumour necrosis factor and immune signalling was associated with lower regional brain volumes across predominantly frontotemporal and limbic regions (canonical correlation 0.43; permutation p=0.018). Plasma multiplex proteomics identified complementary dimensions of neuroaxonal injury and immune dysregulation across frontotemporal lobar degeneration-related syndromes. CNS-related proteins, particularly NfL, predominantly captured case-control neurodegeneration, whereas inflammatory signatures provided additional information about syndrome heterogeneity, structural brain changes and survival. SPP1, CD276 and broader immune-related signatures are candidates for independent biomarker validation and mechanistic investigation.

Background and Objectives: Vascular contributions to cognitive impairment and dementia (VCID) represent the second leading cause of dementia and a common comorbidity for reduced functional capacity in many individuals, but clinical management and clinical trial readiness are severely hindered by extreme phenotypic and mechanistic heterogeneity. This study establishes the baseline clinical, functional, and multimodal biomarker characteristics of the first United States (US) cohort of Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL), serving as a single-cause, monogenic small vessel disease model for sporadic VCID. Methods: Cross-sectional analysis of baseline data collected from October 2022 through January 2025 from a longitudinal cohort at 12 US enrollment sites. Adults from families with a documented NOTCH3 variant were recruited through clinical referrals, medical record review, advocacy organizations, and community outreach. Exclusion criteria included other conditions that prevented interpretation of findings and modified Rankin Scale (mRS) scores greater than 3. Central genetic characterization assigned persons with a pathogenic or likely pathogenic NOTCH3 variant to low-, medium-, or high-risk tiers based on epidermal growth factor-like repeat domains. Standardized assessments included clinical histories, exams, objective cognitive and physical assessments, self-reported, companion-reported, and clinician-rated measures, MRI, genetics, and proteomics acquired under harmonized protocols. Group comparisons used Fishers exact and Kruskal-Wallis tests. Multivariable regression used adjustment for age, sex, race, and education. Results: Of 560 participants completing baseline visits, 46 had variants of unknown significance, and 55 had pending genetic analyses. The analytic cohort included 343 persons with a CADASIL-causing NOTCH3 variant and 116 non-carrier family controls. Median age was 47.9 years (IQR 38.7-59.1), median education was 16 years (IQR 14-17), 62.5% were female, and 91.4% were White. Carriers were classified in CADASIL risk tiers: low (7.0%), medium (18.4%), or high (74.6%). Compared with controls, adjusted odds of classification into a more impaired CDR category were higher in all tiers (OR 2.55-5.08, 95% CI 1.22-11.34). Discussion: The US CADASIL Consortium has established a large, genetics-confirmed cohort spanning presymptomatic to moderate disease stages, providing a robust, harmonized platform to define early biomarker signatures and endpoints for targeted VCID therapies.

Background: Dopamine replacement reshapes subthalamic activity in Parkinson's disease, but whether this response reflects anatomically organized network reconfiguration remains unclear. Objectives: To determine whether levodopa preferentially reorganizes dorsal subthalamic spectral activity and cortico-subthalamic directionality. Methods: Twelve participants undergoing bilateral subthalamic deep brain stimulation contributed 30 contacts (14 dorsal, 16 ventral). Recordings obtained OFF and ON medication underwent spectral parameterization and multiband state-space analysis. Simultaneous electroencephalography in six participants enabled assessment of directional cortico-subthalamic coupling using the phase slope index. Results: Levodopa suppressed beta power more strongly dorsally than ventrally (-2.473 versus -0.120 dB; p=0.0438). Dorsal theta power increased, with a trend toward an increase after baseline normalization (p=0.07). Dorsal contacts exhibited greater theta-beta (+5.904 versus +1.610 dB; p=0.006) and gamma-beta (+2.516 versus +0.384 dB; p=0.0188) state-space shifts, principally driven by beta suppression. Gamma changes did not differ regionally. Concurrently, dorsal low-beta and beta interactions shifted toward cortical leading at selected electrodes, whereas ventral responses were less consistent. Conclusions: Levodopa produces a topographically organized subthalamic response, combining preferential dorsal beta suppression with altered cortico-subthalamic directionality. These findings position contact anatomy as a key consideration in characterizing dopaminergic network responses and motivate clinical validation of spatially informed multiband biomarkers for adaptive stimulation.

Background and Objective: For their acceptance as endpoints in clinical trials, biomarkers and clinical outcome assessment (COA) measures should show reliability by being reproducible (precise) and responsive to change. We evaluated precision and responsiveness of MRI-derived brain volume metrics and various COAs in ceroid-lipofuscinosis, neuronal-3 (CLN3) disease. Methods: This longitudinal observational study (NCT03307304) included 44 individuals with CLN3-related disease (ages 0.5-29.1 years, 48% female). Brain volumetric measures were computed using SynthSeg-v2.0 from T1-weighted 3D MPRAGE images acquired at 3T (Median [Q1, Q3] total MRI follow-up duration from baseline: 2.04 [0.00, 3.69] years). Compartmental tissue volumes were normalized to a model-adjusted total intracranial volume and scaled to the tissue-specific volume fraction expected in healthy adolescent brains to extract measures of brain atrophy. COAs included the Vineland Adaptive Behavior Scales, verbal IQ, and the Unified Batten Disease Rating Scale (UBDRS). Analysis of linear mixed-effects models included only CLN3 participants with syndromic presentation, having three or more visits per measurement to estimate slope, its relative standard error (RSE), and the minimum inter-visit interval (Tmin) for statistically significant progression for each participant. Tmin to detect progression in 75% of the population (Tmin,75%) was computed for each metric. Results: Among brain volumetric measures, brain parenchyma volume (BPV) and gray matter volume (GMV) were the most precise and responsive metrics. BPV showed an overall intra-individual decline with age of -1.32%/year (95% CI: -1.64% to -0.99%), low RSE of 12.5%, and short Tmin,75% of 0.85 years (95% CI: 0.47-1.24). Amongst COAs, the UBDRS Clinical Global Impression (CGI) score was the most precise and responsive with an overall intra-individual increase of 1.26 units/year (95% CI: 1.03-1.49), RSE of 24.10%, and Tmin,75% of 2.56 years (95% CI: 1.73-3.46), though with lower precision (RSE higher) and lower responsiveness (Tmin,75% longer) than BPV. Discussion: MRI-derived metrics, in particular BPV and GMV, detected change in brain atrophy with high precision and responsiveness suggesting that they would be informative for evaluating potential neuroprotective therapies in CLN3 disease. These findings support incorporating MRI-derived volumetric measurements alongside clinical assessments in future clinical trials in CLN3.

The upper cervical spinal cord is essential for motor, sensory and autonomic function, yet its normative morphometric trajectories and disease-related deviations remain unclear. Using three-dimensional T1-weighted images from 10,159 healthy individuals aged 8-85 years, we established normative references for averaged and level-specific upper cervical spinal cord morphometry, revealing measure-specific trajectories with peak ages of 29.7-44.1 years. These references were applied to 2,394 patients with seven neurological disorders: mild cognitive impairment, Alzheimer' s disease, Parkinson' s disease, cerebral small vessel disease, multiple sclerosis, neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody-associated disease to derive individualized deviation scores. These deviation scores captured disease-specific abnormalities, enabled disease classification, and were associated with cognition, physical disability and disease progression. Finally, a personalized upper cervical spinal cord report was developed to support individualized imaging interpretation. Together, these findings provide a normative framework for quantifying upper cervical spinal cord morphometry and advancing personalized assessment across neurological disorders.

Multimodal Parkinson disease models can improve internally while obscuring why patients differ and whether a gain is deployable. We separated clinical trajectories, dated biological sources, observation process and cohort-relative, age-weighted evidence for dopaminergic, injury/glial, cognitive co-pathology and lysosomal burden across 5,404 cutoffs in 1,058 Parkinson's Progression Markers Initiative participants. DaT-SPECT and MoCA history produced a small 12-month motor-change gain (Delta R^2=0.015; delta MAE=-0.060) that failed prespecified magnitude and strict-calendar criteria. Continuous evidence retained overlapping support but showed no detectable predictive increment beyond raw sources. Source-aware intervals achieved 90.6% simultaneous participant coverage yet failed selective prediction, yielding ABSTAIN. In 8,000 semisynthetic experiments, the gate limited null promotion to 0.35%, detected leakage and blocked 94.75% of calendar reversals; PDBP clinical transport and multimodal eligibility failed. The framework reveals state support, stale or missing evidence, and unjustified prognostic, uncertainty or transport claims.

Background Sporadic Parkinson disease (PD) lacks a molecular taxonomy that stratifies patients by dominant molecular drivers, limiting enrollment for disease-modifying trials, especially anti-inflammatory agents targeting NLRP3/NF-{kappa}B. Methods We developed ORIGIN-PD, an interpretable whole-blood transcriptomic classifier comprising 34 gene-level features and a composite low-expression score, with gene-level contributions organized into eight prespecified functional modules: midbrain dopaminergic (mDA) neuron identity/development, pathway-related, oxidative/mitochondrial, proteostasis, inflammation/ immunity, microglia, ncRNA, and other. Using LASSO regression on stringently quality-controlled whole-blood RNA-seq data from the Parkinson Progression Markers Initiative (PPMI) (Training Set: 204 PD and 92 controls; Locked Test Set: 51 PD and 23 controls), we assigned each patient a module-contribution profile. Module dominance was defined as >30% of total score. Results ORIGIN-PD discriminated PD from controls with high accuracy (Locked Test Set AUC 0.944, sensitivity 0.843, specificity 0.913). Among 255 sporadic PD patients, 49.4% exhibited a dominant module-contribution pattern, most frequently mDA neuron identity/development (22.0%), followed by pathway-related (11.8%), microglia/glial (7.5%), and inflammation/immunity (3.5%). Among the 50.6% with multi-module contributions, mDA neuron identity/development ranked in the top three in 62.8% of patients versus 35.7% for inflammation/immunity, indicating broader involvement of mDA neuron identity genes than inflammatory genes. The model showed high specificity against Alzheimer disease, ALS, and inflammatory controls. Conclusions ORIGIN-PD enables rational enrichment for NLRP3/NF-{kappa}B inhibitor trials by identifying patients with inflammatory involvement. In addition, the predominant contribution of the mDA neuron identity/development module, centred on WNT1, MSX1, NPM1, and LMX1B, identifies a larger patient subgroup with altered expression of mDA neuron identity module genes, suggesting that ORIGIN-PD may also be useful for patient enrichment in future trials of Wnt/{beta}-catenin pathway agonists. This dual-purpose framework provides a transparent, interpretable basis for pathogenic subtyping and precision enrichment in sporadic PD, with the aim of guiding disease-modifying therapy.

Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative disorder lacking established biomarkers of underlying disease biology. Here, we identify lipidomic signatures of circulating extracellular vesicles (EVs) that distinguish ALS from neurologically healthy controls and related neuromuscular diseases. Using mass spectrometry-based profiling and multivariate modelling, we separate ALS (n=77) from healthy controls (n=89) with an area under the receiver operating characteristic curve (AUROC) of 0.90 (95% CI 0.85-0.94), rising to 0.92 (0.89-0.96) when low-confidence predictions are withheld, and retaining performance in an independent cohort (n=119; AUROC 0.78, 0.70-0.86). In Tofersen-treated SOD1-ALS patients, biomarker trajectories change in parallel with clinical measures while individuals with spinal muscular atrophy (n=50) exhibit a lipid fingerprint distinct from that observed in ALS, supporting disease specificity within a shared systemic framework of abnormal systemic lipogenesis. These findings establish EV-associated lipid signatures as a systemic, blood-based biomarker platform for ALS diagnosis, stratification, and treatment monitoring, with structurally distinct lipid species indicating widespread membrane remodelling.

Digital health technology (DHT) enables to detect and quantify charateristics motor dysfunction in Parkinsons disease (PD). However, the understanding of the relationship between dopaminergic nigrostriatal denervation and quantitative composite digital motor scores (DMS) captured by DHT remains largely limited to date. In this hybrid PET-MRI study, we used simultaneously acquired PET with 11C-d-threo-methylphenidate (11C-dMP-PET) - a tracer of presynaptic dopamine transporters - and resting-state-fMRI (rs-fMRI) to investigate this relationship and to explore associated neural network correlates in PD. Seventeen PD patients and 39 healthy controls underwent 11C-dMP-PET and rs-fMRI. Quantitative composite DMS for arm swing, gait and balance were calculated using DHT-derived parameters. Voxel-based correlation analysis of 11C-dMP-PET binding potential (BPND) was performed for each DMS and resulting clusters were used for seed-based functional connectivity analyses. We found that DMS of arm swing, gait and balance exhibit differential striatal representations associated with dopaminergic denervation as assessed by 11C-dMP-PET. Specifically, lower BPND correlated with more pathologic arm swing DMS in the central putamen and higher balance DMS in the right caudate, whereas the most robust correlation was observed for lower BPND with more pathologic gait DMS in the right caudate and anteromedial putamen. Seed-based functional connectivity analysis revealed lower functional connectivity in a frontostriatal network encompassing the basal ganglia and medial frontal regions associated to pathological gait DMS in PD. Taken together, our study demonstrates striatal representations of key domains of PD motor dysfunction captured by DHT. Highlighting the complex interplay of gait motor control, we show that gait dysfunction is associated with dopaminergic denervation in the anteromedial executive subregion of the striatum and frontostriatal connectivity changes in regions involved in planning and initiation of movement sequences. Therefore, our study provides first preliminary insights into the relationship of dopaminergic degeneration and DMS encouraging further investigation in larger cohorts and longitudinal studies to construct and validate digital motor biomarkers obtained from DHT as outcome measures in clinical trials in PD.

Background: Wearable sensing and machine learning can support objective assessment of Parkinson's disease (PD), but performance depends on sensor placement, modality, and analysis, and studies often target selected motor tasks, whereas clinical assessment integrates multiple standardized movements. How discriminative information is distributed across tasks and modalities remains unclear, limiting comparability and translation. Objectives: To quantify standardized Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III) tasks across complementary modalities, determine task- and modality-specific contributions to discrimination, and identify complementary, stable candidate digital biomarkers. Methods: Thirty-one participants with PD (Hoehn and Yahr stages I-III) and 30 age- and sex-matched healthy controls performed seven MDS-UPDRS III tasks (items 3.4-3.8, 3.10, 3.15). Unilateral surface electromyography from task-specific muscles and full-body inertial motion capture were acquired, which drove subject-specific musculoskeletal simulations. A leakage-free classification pipeline (in-fold feature selection, repeated cross-validation, permutation testing) was applied by task and modality, followed by sparse task fusion and stability-based biomarker selection. Results: Discrimination was concentrated in four upper-limb tasks, with pronation-supination (3.6) performing best (ROC-AUC 0.94; balanced accuracy 0.92). Multitask multimodal fusion maintained discrimination (ROC-AUC 0.93; balanced accuracy 0.92; sensitivity 0.87; specificity 0.97), retaining finger tapping (3.4), hand movements (3.5), pronation-supination (3.6), and postural tremor (3.15). Eighteen stable candidate biomarkers captured complementary alterations in movement execution, muscle activation, coordination, tremor, and proximal stabilization. Conclusions: In this cohort, discriminative information converged on a four-task upper-limb assessment and a physiologically interpretable multimodal biomarker profile. These findings support shorter, clinically anchored digital motor assessment, pending independent clinical validation.

Amyloid-targeting therapies (ATTs) substantially reduce amyloid PET signal and slow clinical decline in early symptomatic Alzheimer disease. As ATTs enter clinical practice, PET may assess target engagement and guide treatment management, but there is no consensus on how to measure treatment-related amyloid clearance (TRAC). We compared Centiloid quantification across pipelines and visual reads for interpreting pre- and post-ATT amyloid PET. Methods: We analyzed 18F-florbetapir or 18F-florbetaben PET from 101 patients treated with lecanemab or donanemab: 88 pre-ATT and 54 post-ATT scans, including 41 paired scans. Centiloids were derived using FDA-cleared MIMneuro and two research pipelines (rPOP, CapAIBL) and compared using intraclass correlation coefficients (ICC). Clearance rates were estimated using linear mixed-effects models. Full TRAC was defined on post-ATT scans quantitatively (<11 Centiloids) or based on visual interpretation by three expert readers. Results: Treated patients were 74+/-7 years old; 57% were female, 59% were apolipoprotein E4 carriers, and 78% had mild cognitive impairment (22% mild dementia). Centiloid agreement between pipelines was equally high pre- and post-ATT (both ICCs=0.90). Among paired scans (mean treatment duration, 16.7 +/- 4.6 months), clearance estimates were similar across pipelines and greater with donanemab (n=15 patients; between -62 and -60 Centiloids/year depending on the pipeline) than lecanemab (n=26; -38 to -36 Centiloids/year; all Ps<0.005). Among 54 post-ATT scans, between 44% and 57% were <11 Centiloids depending on pipeline, with 20 (37%) meeting this criterion across all three pipelines. In contrast, only 11% to 19% were visually negative across readers, with 4 (7%) unanimously read as negative. Of the 20 post-ATT scans <11 Centiloids across all pipelines, 13 (65%) were considered positive by all readers, commonly with residual occipital binding. Conclusion: Centiloid quantification was robust across pipelines before and after ATT initiation, yielding clearance rates consistent with clinical trials. However, quantitative and visual assessments were markedly discordant after ATT, with an unusually high proportion of scans <11 Centiloids remaining visually positive, warranting cautious interpretation of post-ATT Centiloid values. Larger studies should assess the clinical relevance of these findings and further develop robust approaches to establish full TRAC.