Journal of Parkinson’s Disease

Importance: Dementia is a common and disabling complication of Parkinson's disease (PD). Blood-based biomarkers that identify individuals at higher risk of future dementia could improve prognostication and trial stratification. Objective: To determine whether blood-based proteins are associated with future risk of dementia in PD. Design, Setting, and Participants: Prospective longitudinal cohort study with discovery and replication analyses in the Oxford Parkinson's Disease Centre (OPDC) Discovery cohort and the Parkinson's Progression Markers Initiative (PPMI). A total of 1,335 participants with PD and 431 healthy controls, with serum, plasma, or cerebrospinal fluid proteomic data and follow-up of up to 12 years, were included. Main Outcomes and Measures: Incident dementia, defined using a composite of MoCA scores, MDS-UPDRS items, and clinician diagnosis. Associations between baseline protein levels and time to dementia were evaluated. Results: Among 1,335 participants with PD, 168 developed incident dementia across cohorts (OPDC Discovery [serum], n = 108; PPMI Project 293 [plasma], n = 23; PPMI Project 181 [CSF], n = 37). In the OPDC cohort, GFAP was the only protein (of 5,408 tested) significantly associated with incident dementia (HR = 2.43; 95% CI: 1.79-3.30; p-adjust =1.35 x 10-4). Higher GFAP tertiles were associated with greater cumulative dementia incidence. Findings were replicated in the PPMI plasma project (HR = 2.42; 95% CI: 1.12-5.22; p = 0.024) but not in the CSF project (HR = 0.96; 95% CI: 0.66-1.39; p = 0.82). Higher baseline GFAP was significantly associated with lower baseline cognitive performance and greater longitudinal cognitive decline but no significant association with motor progression. In both cohorts, GFAP levels increased over time but showed no group-level differences. Conclusions and Relevance: Circulating GFAP is a robust and reproducible predictor of future dementia in PD, detectable early in the disease course. While the lack of differential longitudinal trajectories between PD patients with and without dementia suggests that GFAP does not act as a dynamic marker of cognitive decline, its relative stability supports its role as an early indicator of underlying biological vulnerability or subclinical pathology. These findings support serum GFAP as a promising, accessible biomarker for early dementia risk stratification.

Background: Motor complications, such as motor fluctuations and Levodopa-induced dyskinesias (LID), significantly impair quality of life in persons with Parkinson's disease (PD) on long-term Levodopa treatment. Predicting their onset is crucial for tailored patient care. Objectives: To develop and evaluate machine learning (ML) models to forecast the onset of new motor fluctuations and LID in PD patients within three years from baseline assessment, and to assess how training cohort composition influences performance. Methods: A comprehensive ML workflow with repeated Nested Grid Search Cross-Validation was applied to real-world clinical data from a multicentric cohort of 247 PD patients. ML models were rigorously evaluated on the clinically relevant subgroup free of motor complications at baseline. SHAP analysis provided model explainability. Results: Models achieved moderate predictive power for both LID (SVC: MCC 0.28 {+/-} 0.14) and motor fluctuations (Voting MCC = 0.32 {+/-} 0.18). For LID prediction, the strongest predictors were the Levodopa Equivalent Daily Dose (LEDD), baseline motor fluctuations, and duration of Levodopa therapy, with risk increasing significantly above a LEDD threshold of 300-400 mg. A critical ablation study revealed that excluding patients with pre-existing complications caused a collapse in model sensitivity, highlighting their essential role in defining the upper bound of predicted risk. Conclusions: The model-based risk assessment is consistent with established clinical factors. Inclusion of the full spectrum of disease severity, including patients with pre-existing motor complications, in the training set is essential for achieving a robust probabilistic risk scale and reliable model calibration for new-onset prediction.

Purpose: The purpose of this study was to identify subgroups of talkers with Parkinsons disease (PD) with shared tongue, lip, and jaw articulatory amplitude behaviors. The study also sought to identify demographic and clinical features that can distinguish the identified kinematic subgroups. Methods: 53 talkers with PD and 54 controls participated. Articulatory amplitudes of the tongue, lip, and jaw were measured during a paragraph reading task using three-dimensional electromagnetic articulography. Amplitude performance profiles of the tongue, lip, and jaw were established for each talker with PD by referencing their performance to that of controls. These profiles were submitted to a hierarchical cluster analysis to identify kinematic-based subgroups. Amplitude performances were compared across subgroups to determine between-group patterns. Demographic and clinical features (e.g., age, sex, disease duration, selected perceptual speech characteristics, dysarthria severity) were compared across the identified kinematic subgroups. Results: Four main kinematic subgroups with differing amplitude performance profiles were identified. One subgroup exhibited normal to mildly exaggerated or mildly reduced amplitudes and was labeled preclinical subgroup (n = 16). Three subgroups exhibited pronounced amplitude reductions of either the tongue (n = 10), the tongue and lips (n = 12), or the tongue, lips, and jaw (n = 10). In addition, there were five talkers with PD whose performance profiles did not align with the identified four subgroups. Their performance was characterized by either pronounced amplitude exaggerations or mildly reduced jaw and lip amplitudes and exaggerated tongue amplitudes. None of the demographic or clinical features differed significantly between the main four subgroups. Conclusion: Findings suggest that the extent to which hypokinesia manifests within the articulatory subsystem can vary in talkers with PD. Longitudinal studies are needed to determine if these subgroups represent different stages of disease progression or distinctly different manifestations of the disease within the articulatory subsystem.

INTRODUCTION: Parkinson's disease (PD) presents with motor and non-motor symptoms, including dementia, but the severity and rate of cognitive decline are heterogeneous and difficult to predict clinically. METHODS: We quantified baseline serum proteins with the high-throughput SomaScan(R) assay in 834 PD individuals and performed Cox regression to identify proteins associated with subsequent development of dementia. Candidate biomarker proteins were replicated in 371 individuals from an independent cohort and meta-analysed. RESULTS: Protein targets significantly associated with progression to dementia were predominantly involved in synaptic plasticity, protein degradation/lysosomal function and extracellular matrix organisation. Mendelian Randomisation further revealed that changes in the Nogo receptor RTN4R may be causally associated with the development of Lewy body dementia. DISCUSSION: We identified several proteins predicting progression to dementia in PD, indicating changes in blood proteome that precede the development of clinical symptoms by several years, providing a window of opportunity to identify at-risk individuals early on.

Background. L-Dopa remains the primary treatment for Parkinson's disease (PD), but chronic administration frequently leads to L-Dopa-induced dyskinesia (LID). While D1 and D2 medium spiny neuron (MSN) specific structural changes on the spine level have been observed in the striatum of PD and LID, studying microglia mediated synapse loss has not been done to date. Methods. Here we generated novel reporter mice by crossing floxed PSD95c(mCherry/eGFP) mice with D1-Cre and D2-Cre lines, producing D1-PSD95-EGFP and D2-PSD95-EGFP strains for MSN-specific synapse visualization. Using the 6-OHDA mouse model of PD and LID we assessed microglia mediated MSN subtype specific synapse loss in these mice while PLX3397 was used to investigate effects of microglia depletion and repopulation on LID development and synapse loss. Results. Both D1- and D2-MSNs exhibited significant PSD95 synapse loss in PD, with D1-MSN loss further exacerbated in LID. Microglia displayed increased phagocytic activity and accumulated PSD95 material within lysosomes, particularly in LID. PLX3397-mediated microglial depletion reduced LID severity and preserved D1-MSN synapses. A depletion and repopulation paradigm attenuated LID severity, preserved D1-MSN synapses, and reduced synaptic material within microglia. Conclusions. Microglia-mediated synapse loss in MSN subtypes contributes to PD and LID pathogenesis. Pharmacological microglial depletion and repopulation mitigate synapse loss and dyskinesia, highlighting microglial turnover as a promising therapeutic strategy for LID.

Background: Motor disturbances are common in neurologic and neurodegenerative syndromes. A standard motor speed and dexterity measure is the finger tapping test (FTT). The FTT has traditionally been administered in clinic using a mechanical FTT, limiting accessibility and early motor change quantification. This study assessed the validity of a smartphone app-based FTT, which may expand access and enable more frequent testing. Methods: The cohort was diagnostically diverse, including participants with frontotemporal dementia (FTD), progressive supranuclear palsy (PSP), corticobasal syndrome, primary progressive aphasia, multiple sclerosis, and clinically unimpaired controls. Participants completed a 20-second ALLFTD Mobile App (mApp)-FTT with each hand. Tapping speed metrics were extracted. Participants completed the gold-standard mechanical FTT, a neurologist-administered finger tapping exam, the PSP Rating Scale (PSPRS) and the Unified Parkinson`s Disease Rating Scale (UPDRS). Correlations assessed mApp-FTT and mechanical FTT relationships; regressions evaluated associations with neurologist-rated finger tapping impairment, PSPRS and UPDRS, adjusting for age and sex. Results: The mApp-FTT showed moderate-to-strong correlations with the mechanical FTT (dominant: r=0.63, p<0.001; non-dominant: r=0.55, p<0.001). Taps per second were associated with PSPRS motor severity (dominant hand: std. {beta}=-0.59, 95% CI [-0.91, -0.27], p<0.001) and the UPDRS (dominant hand: std. {beta}=-0.41, 95% CI [-0.82, 0.00], p=0.049). Flight time was modestly associated with neurologist-rated finger tapping impairment (dominant hand: std. {beta}=0.15, 95% CI [0.00, 0.29], p=0.044). Conclusion: These findings support mApp-FTT validity as a measure of motor function across neurodegenerative conditions. Validation in longitudinal and unsupervised remote settings is warranted to understand scalability and evaluate change over time.

Background: Hallucinations, ranging from minor (MH) to structured, are a common non-motor symptom in Parkinson's disease (PD). Structured hallucinations have been associated with altered functional connectivity (FC) between dorsal/ventral attention (DAN, VAN) and default mode (DMN) networks. As structured hallucinations are linked to rapid cognitive decline and MH are often viewed as their precursor, it is imperative to understand the neural basis of MH, and its relationship with cognitive alterations. Objectives: We aimed to identify a whole-brain FC pattern associated with MH and alterations in attention-executive functioning in PD, leveraging a robotic procedure inducing presence hallucinations (riPH) experimentally, to which patients with hallucinations previously showed increased sensitivity. Methods: Non-demented PD patients (N = 53) were categorized into three subgroups based on their hallucination symptoms: no hallucinations (nH; n = 19), MH (n = 18), and structured hallucinations, with or without MH (SMH; n = 16). We combined results from the riPH procedure and neuropsychological tests and applied multivariate methods capturing their shared variance in resting-state fMRI data across the three subgroups. Results: We identified a distributed FC pattern more strongly expressed in patients with hallucinations (MH, SMH), and equally so across both groups, significantly associated with alterations in attention-executive functions and differences in riPH sensitivity. The pattern was primarily driven by FC between subcortical areas and visual network, DAN and DMN, and within-cerebellar and within-subcortical FC. Conclusions: Our results highlight the role of subcortical-cortical connectivity in PD hallucinations, associated with cognitive alterations and already present in less advanced MH patients.

There is growing interest and need for non-invasive stimulation approaches for the treatment of Parkinson's disease (PD) and other neurological conditions. Pilot studies indicate that vibrotactile stimulation on the fingertips may reduce PD motor symptoms (Pfeifer et al., 2021; Syrkin-Nikolau et al., 2018). PD motor symptoms (e.g., rigidity, bradykinesia) are correlated with exaggerated beta power in the subthalamic nucleus (STN), where neurons are excessively synchronized (Brown 2003; Kuhn et al., 2006; Neumann et al., 2016; Yin et al., 2021), but the effect of vibrotactile stimulation on the STN has not been determined. Here, in 12 PD participants in the OFF deep brain stimulation (DBS) and OFF medication state, we investigated how unilateral vibrotactile stimulation applied to the fingertips affects local field potential (LFP) power in STN. We used a within-participants design to expose each participant to a treatment stimulation pattern, termed randomized vibrotactile stimulation (RVS), and a control stimulation pattern, with the order randomized and with intermittent acquisition of STN LFP. RVS yielded a modest but statistically significant 12% (SEM 4.6%) reduction in mean normalized STN beta power and a 48% (SEM 19%) reduction in peak beta power compared to the DBS-off baseline condition and was significantly different when compared to our control stimulus. Furthermore, we identified a biomarker in STN beta power that predicts which participants may benefit from RVS. We observed that participants that exhibited prominent beta peaks had stronger reductions in mean beta power (17% reduction, SEM 6.1%) and peak beta power (55% reduction, SEM 10%). Regressing against the magnitude of the peak in beta provides a moderate prediction of change in mean and peak beta power due to RVS (R2 = 0.58 for mean and 0.52 for peak). We then used our observations to construct a computational model where beta peaks in a simulated STN varied from prominent to diminished. We found that the efficacy of randomized treatments was dependent on the magnitude of beta peaking, mirroring our clinical findings, and showing that RVS may act by reducing intra-neuronal synaptic strengths in STN. Despite robust changes in STN LFP in our study population, we did not observe a significant change in motor symptoms. These results suggest that peripheral vibrotactile stimulation can reduce STN beta power and motivate additional studies to investigate its long-term effects on motor symptoms across a large population of participants.

Parkinson disease (PD) progression is highly heterogeneous. Deeply phenotyped longitudinal research cohorts have enabled characterization of PD progression trajectories. Early prediction of these progression patterns can help us better understand patient disease conditions and manage appropriately. However, the sample sizes of these cohorts are typically too small to build robust early predictors, and it is usually challenging to translate them to real-world patients because of differences in the population as well as information availability. In this paper we present MedStitcher, a graph-based machine learning framework that stitches individual multimodal data across research cohorts and real-world data (RWD) using a biomedical knowledge graph-anchored architecture. This design enables predictive modeling under modality missingness and cross-dataset population heterogeneity. On the research cohort data combining PPMI and PDBP, MedStitcher achieved an AUROC of 0.819 +/- 0.040 for predicting rapid PD progressors, outperforming existing machine learning approaches. Graph-based model interpretation revealed clinical and molecular signals involving cognitive vulnerability, alpha-synuclein biology, vesicle trafficking and neuroinflammation. Importantly, MedStitcher-predicted rapid progressors in the RWD cohort demonstrated elevated risks of dementia, falls, mild cognitive impairment, and gait impairment, which also enabled identification of early indicators of rapid PD progression in real-world patient populations.

Study Objectives To develop and initially validate the Circadian Disruption Index (CDI), a self-report measure of circadian disruption, and obtain preliminary evidence of its responsiveness to circadian health education. Methods In Study 1, 244 participants completed a 22-item CDI version and external measures. The sample was randomly divided for exploratory and confirmatory factor analyses. Internal consistency, external associations, and discrimination of poor sleep quality were examined. In Study 2, 72 postgraduate students completed the CDI before and 1 week after a 16-hour circadian health education program in an uncontrolled pre-post design. Results Analyses yielded a 15-item, three-factor structure comprising rhythm stability and light exposure, behavioral habits and diet, and sleep quality and subjective complaints. Total-score internal consistency was acceptable (Cronbach's = 0.871). Confirmatory factor analysis showed a comparative fit index of 0.902 and a root mean square error of approximation of 0.072, although the Tucker-Lewis index was 0.882. CDI scores correlated with sleep quality, chronotype, corrected midsleep on free days, depression, and anxiety, but not social jetlag. The area under the curve for poor sleep quality was 0.807 (95% confidence interval, 0.753-0.862), with an exploratory cutoff of [&le;] 23. In Study 2, CDI scores decreased from 22.26 to 19.88 (p = 0.002; Cohen's dz = 0.36). Conclusions The CDI demonstrated satisfactory internal consistency, a meaningful multidimensional structure, and responsiveness to short-term changes following circadian health education, supporting its potential utility for assessing circadian disruption and monitoring circadian-related behavioral changes.

Relatively little is known regarding suicide among older adults in nursing homes. The aim of this study was to compare the incidence of suicide among older nursing home residents (NHR) with community-dwelling older people (CDP) using newly available, national, individual-level register data, and to assess differences with regard to socio-demographic characteristics. We obtained data on all older adults aged 65+ who were living in Austria at the end of October 2018 (n=1,665,450), including 155,020 NHR. Death by suicide was followed until the end of 2023. A total of 114 and 2,136 suicides were observed among NHR and CDP; corresponding to cumulative incidences of 14 and 27 per 100,000, respectively. Among NHR, suicide incidence was higher among males (28.0, 95% CI=22.1, 35.5), those aged 65-74 years (20.2, 95% CI=13.3, 30.6), with tertiary education (23.3, 95% CI=10.6, 50.6), divorced (25.0, 95% CI=16.2, 38.5), and residing in urban nursing homes (22.0, 95% CI=17.0, 28.4). Compared to CDP, more suicides in NHR occurred by poisoning and but few by firearms. In conclusion, we found that suicide incidence was lower among older NHR compared to CDP. More research on and preventive efforts against suicide among older NHR are needed.

In 2022, Austria legalised physician-assisted suicide (PAS). Among 1,847,919 older adults, there were 92 PAS and 977 unassisted suicides (UAS) in 2022-2023. Compared to the general population, older adults who died by either PAS or UAS, were older and more likely to live alone. Compared with UAS, older adults who died by PAS were more likely to be female, higher-educated, live in urban areas, and diagnosed with cancer, or diseases of the nervous system, and less likely diagnosed with mental/ behavioural disorders. PAS and UAS among older adults in Austria showed different sociodemographic and comorbidity characteristics.

Synucleinopathies are a group of neurodegenerative disorders characterized by the accumulation of aggregated -synuclein (-syn), including Parkinson's disease, Dementia with Lewy Bodies, and Multiple System Atrophy. These diseases are marked by locomotor and non-motor impairments, as well as mitochondrial dysfunction and the loss of dopaminergic (DA) neurons. We have developed several anti--syn single-domain antibodies (sdAbs) and demonstrated the diagnostic imaging potential of two of them and the acute therapeutic benefit of one in clearing -syn in a mouse model. However, whether these sdAbs can suppress -syn-mediated neuronal loss and locomotor impairment in vivo remains unclear. We evaluated the therapeutic potential of five anti--syn sdAbs to clear pathological -syn in mouse neuronal culture and then demonstrated their in vivo efficacy in a Drosophila model of synucleinopathy. The sdAbs differed in their efficacy to lower levels of phospho-serine 129 -syn, prevent loss of DA neurons, alleviate mitochondrial dysfunction, improve motor function, and prolong survival in synucleinopathy flies. The most effective sdAb, 2H1, has not been reported before. It binds strongly to the aggregation prone region of -syn and robustly improves all these disease parameters. Additionally, that sdAb is associated with -syn in the fly neurons, as shown through proximity dependent turboID biotinylation assays. The sdAb-turboID also biotinylated -syn-associated proteins involved in synapse/vesicle trafficking pathways, pinpointing the location of their intracellular interaction. Our findings provide an insight into the therapeutic mechanism of action of these sdAbs and strongly support their clinical development.

By utilizing a targeted genetic assay within a Fox Insight cohort (N = 1,987), this research establishes a hybrid, transparent, and interpretable predictive framework. Initial modeling via Firth penalized logistic regression discovered enrichment regarding the GBA N370S locus (OR = 0.01, FDR < .001), highlighting the critical role of epidemiological evaluation in enriched, human study populations. Advanced ensemble learning methods, refined through a meta-learner gradient boosting machine, attained an out-of-sample AUC of 0.929 on 15% of the analysis dataset partitioned via random sampling and strictly held-out from model training. Both global, visual machine learning explanations and local-Shapley interpretations provide transparency into the models and individual predictions representative of practical, collaborative human-artificial intelligence efforts, offering a solution that supports classification while remaining accessible and economical.

The aggregation of -synuclein (Syn) is a molecular hallmark of Parkinson's disease (PD) and other synucleinopathies. Understanding the molecular mechanisms that determine the aggregation of this protein may thus facilitate the development of disease-modifying therapies. While Syn is most commonly expressed as a 140-residue protein (Syn-140), recent evidence suggests an involvement of alternatively spliced Syn isoforms in disease onset and progression. Here, we report and characterise the interaction between Syn-140 and the aggregation-prone Syn-112 variant, one of the most abundant Syn splice isoforms. We found that amounts as low as 1% of Syn-112 accelerate the nucleation and aggregation of Syn-140. To further investigate this phenomenon, we employed MALDI-MS and NMR spectroscopy, confirming that Syn-140 and Syn-112 monomers interact strongly with one another. Furthermore, to assess the association of Syn-112 with disease pathology, we performed immunohistochemical staining combined with confocal microscopy on PD brain samples. Thereby, we found an increase in the number as well as the area of Syn-112 immunoreactive aggregates compared to healthy controls. These results illustrate how low-abundance Syn splice isoforms can modulate the aggregation landscape of Syn-140 and in turn contribute to the molecular heterogeneity of synucleinopathies.

Background: Depressive and anxiety symptoms are prevalent among older adults and associated with increased dementia risk. In healthy older adults, higher step counts are associated with fewer depressive and anxiety symptoms; whether this holds in individuals with cognitive concerns (subjective cognitive decline [SCD] or mild cognitive impairment [MCI]) is unknown. In a randomised controlled trial, the 12-month APPLE-Tree group psychosocial lifestyle intervention produced small cognitive improvements but no change in step count. Objective: To test whether step count was associated with depressive and anxiety symptoms (cross-sectionally and over 24 months), and whether APPLE-Tree increased step count in participants with clinical anxiety or depression. Methods: We examined cross-sectional and longitudinal (12- and 24-month) associations between step count (two-week average from wrist-worn wearables) and depressive and anxiety symptoms (Hospital Anxiety and Depression Scale) using adjusted linear regressions, with a mediation analysis of self-perceived mobility. We also tested whether the intervention increased step count in those with baseline clinical anxiety or depression. Findings: We included 629 of 746 trial participants at baseline, of whom 376 contributed 12-month and 215 24-month data. At baseline, higher step counts were associated with fewer depressive symptoms ({beta} = -0.11, 95% CI -0.17 to -0.05, p < 0.001) but, counter to our hypothesis, more anxiety symptoms ({beta} = 0.12, 95% CI 0.06 to 0.19, p = 0.003). Over two years, change in step count was not associated with change in depressive or anxiety symptoms (all p [&ge;] 0.12). Self-perceived mobility problems mediated the association between step count and depressive but not anxiety symptoms. The intervention did not change step count in those with clinical anxiety or depression. Conclusions: This provides the first evidence in older adults with cognitive concerns that higher step counts are associated with fewer depressive but more anxiety symptoms. This may reflect heterogeneity of a population that includes those with prodromal dementia and cognitive health anxiety. Step count did not predict symptoms over time. Clinical implication: Step count may help distinguish anxiety and depressive symptoms in people presenting with cognitive concerns, or underlying reasons for cognitive concerns among those with functional cognitive disorders.

Parkinsons disease (PD) is a movement disorder characterized by the accumulation of alpha-synuclein aggregates leading to dopaminergic neuron loss in the substantia nigra. While PD has been associated with environmental and microbiome changes, our ability to assess the mechanistic impact of these factors on synuclein aggregation in cells has remained limited. Here, we designed and optimized a high-throughput optical screening system to assess the effect of metabolites and small molecules on synuclein aggregation in cell lines expressing a synuclein-fluorescent protein fusion and treated with pre-formed fibrils (PFFs). Using this assay, we identified several compounds that modulate synuclein aggregate accumulation in cells, including harman, a {beta}-carboline that led to reduced synuclein aggregation. We further investigated the transcriptional effect of harman and PFFs and identified changes in peroxiredoxins as a potential mechanism linking harman to aggregate accumulation. Altogether, this work establishes a pipeline to prioritize small molecules that can impact synuclein aggregate formation.

Background: Stress-induced childhood-onset neurodegeneration with variable ataxia and seizures (CONDSIAS) is a rare autosomal recessive disorder caused by biallelic variants in ADPRHL2, which encodes ADP-ribosylhydrolase 3 (ARH3), a key enzyme involved in poly (ADP-ribose) (PAR) metabolism. Although Minocycline has been reported to attenuate PAR-mediated neurotoxicity primarily through modulation of PARP-dependent pathways, whether it may also interact with ARH3 or influence the structural behavior of pathogenic ARH3 variants remains unknown. This study was designed to explore this possibility by integrating clinical observation with computational structural analyses. Methods: Comprehensive clinical evaluation, targeted Sanger sequencing, and in silico pathogenicity analyses were performed. Protein modeling, molecular docking, and 100-ns molecular dynamics simulations were conducted to evaluate the predicted structural consequences of the p.Thr79Pro variant and to explore potential interactions between ARH3 and Minocycline. Results: A homozygous ADPRHL2 variant (NM_017825.3:c.235A>C; p.Thr79Pro) was identified in a child with CONDSIAS. Computational analyses predicted reduced structural stability and increased conformational flexibility of the mutant ARH3 protein relative to the wild-type structure. MM-GBSA calculations estimated differences in binding free energies between the wild-type (-34.51 kcal/mol) and mutant (-39.76 kcal/mol) ARH3-Minocycline complexes, suggesting subtle differences in their predicted energetic profiles. Clinically, neurological progression appeared stable, with improved motor function observed during approximately one year of follow-up and no notable treatment-related adverse effects. Conclusions: By integrating clinical observations with computational structural analyses, this study provides preliminary computational support for the hypothesis that Minocycline may influence ARH3 conformational behavior in addition to its proposed effects on PARP-dependent pathways. Although these findings do not demonstrate direct molecular binding or therapeutic efficacy, they provide a biologically plausible framework for future biochemical, cellular, and functional investigations. Keywords: CONDSIAS; ADPRHL2; ARH3; Minocycline; molecular docking; molecular dynamics simulation; structural bioinformatics; translational medicine

Smooth pursuit eye movement abnormalities are well established in psychosis, but the specific components of pursuit performance that vary across clinical states and symptom profiles remain insufficiently characterized. Here, we used a rapid smooth pursuit paradigm combining standard linear tracking (repeated short trials moving in different directions) with structured target occlusion to examine oculomotor performance in individuals with acute psychosis, chronic psychosis, and healthy controls. The occlusion condition allowed assessment of tracking when the target was temporarily hidden and gaze had to be maintained along the expected trajectory. Basic oculomotor measures, including full pursuit gain and initial catch-up saccade properties, were largely preserved in patients. In contrast, more specific trajectory-based measures revealed distinct abnormalities. Saccade-free smooth tracking gain was selectively reduced in acute psychosis, whereas tracking deviation during non-occluded pursuit was altered in both patient groups, reflecting reduced forward tracking relative to controls. During structured occlusion, patients showed reduced forward gaze progression along the expected trajectory, with a graded pattern across groups: controls showed the strongest predictive lead, chronic patients an intermediate response, and acute patients the weakest predictive lead. Tracking deviation and occlusion-related deviation were both associated with positive symptom severity, whereas smooth tracking gain was not. These findings suggest that smooth pursuit abnormalities in psychosis are measure-specific rather than uniform, involving both broader psychosis-related alterations in gaze-target alignment and state-sensitive disruptions in occlusion-related tracking. Structured occlusion may therefore offer a useful extension of conventional smooth pursuit paradigms for probing prediction-related sensorimotor control in psychosis and distinguishing acute from chronic clinical states.

Background: Compulsive alcohol use despite negative outcomes is a defining characteristic of alcohol use disorder. Rats exposed to long-term intermittent alcohol access (IAA) demonstrate sustained motivation for ethanol despite presence of the bitter additive quinine, offering a useful preclinical model of compulsive alcohol use. However, little is known about the role of habenular circuitry in the development of this phenotype. Here, we employed chemogenetic techniques targeting basal forebrain (BF) input to the lateral habenula (LHb) to probe the involvement of this neural circuitry in aversion-resistant alcohol consumption. Methods: Following long-term IAA or control conditions, male and female Long-Evans rats underwent surgery for the expression of designer receptors in BF-to-LHb projections. We then excited this pathway in rats with IAA history, or inhibited this pathway in rats with more limited ethanol history, before testing consumption of unadulterated and quinine-adulterated ethanol as well as unadulterated and quinine-adulterated sucrose. Results: Long-term IAA elevated ethanol drinking in all rats and aversion-resistant ethanol preference in males. Chemogenetic activation of BF-to-LHb neurons in rats with IAA history produced different effects in males and females: excitation enhanced ethanol intake in females, but reduced ethanol preference in males, regardless of quinine adulteration. Activation also led to a relative insensitivity to quinine-adulteration of sucrose when compared to controls, particularly in females. Chemogenetic inhibition in rats with limited prior ethanol exposure did not alter either ethanol or sucrose consumption with or without quinine. Conclusions: Our results suggest a differential role for BF-to-LHb circuitry in ethanol drinking based on sex, and a potential role for this circuitry in the sensitivity to quinine in the context of natural reward consumption.