BACKGROUND/OBJECTIVES:Parkinson's disease (PD) is associated with systemic molecular alterations that extend beyond the central nervous system, including changes in peripheral blood transcriptomic profiles. While prior studies have focused predominantly on coding-gene expression, the longitudinal behavior of the peripheral blood repeatome following clinical diagnosis remains poorly characterized. Here, we investigated temporal remodeling of repetitive-element transcription over 36 months post-diagnosis by integrating repeat subfamily- and locus-specific analyses. METHODS:Repeatome expression was quantified using SalmonTE and DESeq2 in peripheral blood RNA-seq data from 1560 PD and control individuals at diagnostic baseline (BL) and four follow-up visits (6, 12, 24, and 36 months). Differential expression was assessed at the subfamily level, with additional locus-specific validation in a representative subset. RESULTS:A total of 259 repeat subfamilies were differentially expressed (padj < 0.05), of which 224 (86.5%) were already detected at baseline. Enrichment of differential expression was significantly higher at baseline than at later visits (odds ratio = 30.9, p < 2.2 × 10-16), with limited additional divergence over time. Longitudinal analyses revealed non-linear trajectories in selected repeat families, including Alu and SVA subfamilies. Locus-specific analysis identified 237 significantly regulated elements, demonstrating heterogeneous, site-specific transcriptional changes, including clusters of differentially expressed loci and instances within PD-relevant genomic regions (e.g., SNCA and IKZF2). CONCLUSIONS:Peripheral blood repeatome expression differs between PD and control groups, with the dominant signal established at clinical diagnosis and modest longitudinal modulation thereafter. Integration of locus-level analysis indicates that subfamily level patterns arise from discrete genomic events rather than uniform regulation. These findings support a model of systemic, immune-associated transcriptomic remodeling in circulating blood cells and position the peripheral repeatome as a dynamic framework for biomarker discovery and future mechanistic investigation.

To investigate whether antidiabetic drugs have a biological basis to be repurposed in PD prevention, we applied a drug target Mendelian randomization framework to assess associations between genetic variation in antidiabetic drug targets and PD risk or age at onset (AAO). Instrumental variables (IVs) were derived from GWAS summary statistics on fasting glucose (FG), glycated hemoglobin (HbA1c), and gene expression data from GTEx. Apart from SGLT2 inhibitors, all other antidiabetic drugs of interest could be instrumented through our methods. Positive and negative control analyses were carried out to validate 20 IVs in the FG arm and 23 IVs in the HbA1c arm. DPP-4 inhibitors failed the positive control. GWAS summary statistics for PD risk and AAO data were sourced from the IPDGC and COURAGE-PD consortia, resulting in 42 083 cases/457 090 controls for risk and 37 103 PD cases for AAO. MR analyses showed no significant associations across consortia or in meta-analysis. These findings do not support a causal role of genetic variation in antidiabetic drug targets in PD risk or AAO.

Wolfram syndrome is a rare childhood neurodegenerative disease characterized by diabetes followed by severe and rapid optic atrophy leading to blindness before the age of 20. Patients often develop other symptoms, such as deafness and neurological dysfunction. Wolfram syndrome is caused by mutations in the WFS1 gene, which encodes wolframin protein. Despite decades of intensive research, the complex mechanisms of optic neuropathy are not fully understood, and there are currently no therapies to prevent vision loss in Wolfram patients. Here, we showed that the Wfs1 knockout mice produced by the Estonian group, in which exon 8 of the Wfs1 gene was disrupted, exhibit a progressive loss of visual acuity, optic disc pallor and severe optic nerve damage. We tested the efficiency of gene therapy using AAV2 to deliver human WFS1 to retinal ganglion cells in Wfs1 knockout mice. Our results provide the first evidence that intravitreal injection of human WFS1 has significant neuroprotective effects on retinal ganglion cells and their axons and slows the loss of visual acuity. These results demonstrate that WFS1 is able to provide both functional and structural protection to retinal ganglion cells in Wfs1 knockout mice and provide important evidence for the efficacy of WFS1 as a neuroprotective treatment for Wolfram syndrome. These results demonstrate the promising effects of gene therapy for Wolfram syndrome and encourage future research aimed at conducting clinical trials in patients.

Background Lipid metabolism is increasingly implicated in Parkinson's Disease (PD) pathology, yet the specific lipid classes and acyl chain compositions involved, and their relationship with PD clinical symptoms, remain poorly characterised. Objectives We aimed to identify serum lipid signatures that differentiate people with PD (PwPD) from healthy controls and to evaluate associations with levodopa-induced dyskinesia (LID). Methods Serum collected from 58 PwPD and 58 age- and sex-matched non-PD controls was analysed using targeted liquid chromatography - mass spectrometry (LC-MS). Group differences were assessed using univariate and multivariate approaches. Logistic regression was used to identify lipids associated with LID among PwPD. Results Significantly lower levels of glycerolipids and glycerophospholipids were observed in PwPD compared to controls, alongside higher levels of lysophosphatidylethanolamines (LPE) and lysophosphatidylcholines (LPC). Analysis of individual lipid species revealed a lipid remodelling of the acyl chain composition of glycerolipids and glycerophospholipids, with decreased esterified arachidonic, adrenic, docosapentaenoic, and docosahexaenoic acids. Non-esterified arachidonic acid (p = 5.80e-6) and eicosapentaenoic acid (p = 3.65e-10) were elevated in PwPD. In secondary analyses, no lipids discriminated between PwPD with and without LID; however, these models were constrained by modest subgroup sizes and clinical heterogeneity between groups, limiting conclusions regarding lipid-based discrimination of LID status. Conclusions These findings demonstrate disease-associated remodelling of acyl chain composition across multiple lipid classes in PD, particularly selective depletion of esterified polyunsaturated fatty acids from glycerolipids and glycerophospholipids. Replication in independent cohorts is warranted to establish whether these pathways represent viable therapeutic targets.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterised by progressive muscle weakness in both bulbar and extremity muscles, leading to a diverse clinical phenotype with motor and non-motor symptoms. Approximately 85% of ALS cases are sporadic (sALS), while the remaining 10%-15% are familial (fALS). Biological biomarkers of sporadic ALS remain poorly understood, hindering precise patient screening, delaying diagnosis and negatively affecting prognosis. This study aims to identify potential proteomic biomarkers by comparing the cerebrospinal fluid (CSF) of sALS patients with that of patients suffering from other neurological diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used for proteomic profiling of CSF samples from 24 sALS patients and 26 patients with other neurological diseases. The complete protein expression profiles were compared using a two-tailed Student's t-test, with a p < 0.05 considered statistically significant with additional FDR correction at the 0.1 level. Proteomic analysis of CSF samples identified significant quantitative changes in 96 proteins with threshold p < 0.05 and 74 proteins with FDR < 0.1 between sALS and non-ALS patients, including alterations in proteins associated with neurodegenerative processes, such as amyloid precursor proteins and inflammatory markers. CSF proteomic analysis reveals altered inflammatory and neurodegenerative metabolic pathways, providing valuable insights into the proteomic landscape of sALS. Several dysregulated proteins were consistent with the disease mechanisms highlighted in previous studies. These findings represent a step forward in developing personalised approaches for diagnosing and managing the disease.

Progression from Parkinson's disease (PD) to Lewy body dementia is a major clinical concern. Although several progression-associated loci have been identified, their cumulative effects on cognitive decline have not been systematically evaluated. To assess the dose-dependent effect of five candidate progression loci linked to synaptic vulnerability (RIMS2, TMEM108, GBA1) and amyloid-tau pathology (APOE, WWOX), we analyzed 7745 participants from 24 cohorts with 28,737 longitudinal visits over 15 years using random-effects meta-analyses of cohort-specific Cox proportional hazards models. Dementia risk increased monotonically with the number of progression loci (0, 1, 2, or ≥3). A single locus conferred a 1.56-fold increase in risk (hazard ratio (HR) = 1.56, 95% CI: 1.28-1.89), rising to 3.21-fold for two loci (HR = 3.21, 95% CI: 2.19-4.70) and 7.49-fold for three or more loci (HR = 7.49, 95% CI: 4.98-11.28). Individually, GBA1 (HR = 2.09), APOE ε4 (HR = 1.71), RIMS2 (HR = 1.90), TMEM108 (HR = 2.05), and WWOX (HR = 1.56) were associated with dementia risk, but there was heterogeneity between clinical trials, biomarkers, and population-based cohorts. Multi-locus dosage increases dementia risk in a monotonic manner and may improve stratification and clinical trial design in PD.

We investigated the role of copy number variations (CNVs) in Parkinson's disease (PD) using genotyping data from 10,815 patients (2731 early-onset PD, EOPD) and 8901 controls from the COURAGE-PD consortium. CNVs were analyzed using a sliding window genome-wide association and burden approach. No genome-wide significant CNVs were detected in the overall cohort, but a robust deletion spanning exons 2-6 of PRKN was identified in EOPD cases, validated by MLPA, and replicated in the GP2 dataset (23,089 cases, 18,824 controls). CNV burden was significantly enriched in PD-related genes, primarily driven by PRKN, with the strongest effect observed in EOPD. PRKN CNV carriers showed earlier age at onset, confirmed by survival analysis. No association was observed for genome-wide or large CNV burden. Our findings reinforce the pivotal role of PRKN deletions in early-onset PD and highlight the need for high-resolution CNV analysis in large cohorts to uncover additional rare contributors to PD risk.

Epilepsy is one of the most common neurological diseases in the world, but it is also complex and difficult to study. There is a significant genetic component to epilepsy and more information is being published frequently. It is difficult to group and summarise all of this information in a way that is beneficial for both researchers and clinicians. The aim of this paper is to create a summary of all currently known epilepsy associated genes in order to aid epilepsy research to better understand the aetiology of the disease. This was achieved through gathering genetic data from three databases: Online Mendelian Inheritance in Man (OMIM), Clincal Genome (ClinGen), and PubMed. Genes were filtered based on specific criteria and were summarised into three tables: Epilepsy genes, Epilepsy associated genes and Predicted epilepsy associated genes. A fourth table was produced to showcase all epilepsy genes that were identified in all three databases. A total of 2,536 genes were identified to have some level of association with epilepsy. A total of 238 genes were classified as Epilepsy genes, 1,317 genes were classified as Epilepsy associated genes and 981 genes were classified as Predicted epilepsy genes. Finally, 86 genes were identified to be epilepsy genes that were found in all three genetic databases and represent the highest confidence in association with epilepsy. The significance of this study involves the ability to give researchers an up-to-date list of genes that have an association to epilepsy and a summary of information about said genes.

Introduction:GCH1 has been implicated in Parkinson's disease (PD), but its risks variants and associations are not well defined. Objectives:To investigate the clinical relevance and PD risk associated with the GCH1 p.Ser80Asn variant. Methods:We first identified a segregating GCH1 p.Ser80Asn variant in a Malaysian Chinese PD family via whole genome sequencing (WGS). We assessed its risk association using multi-ancestry WGS data from the Global Parkinson's Genetics Program (GP2) (n=22,372PD vs n=8,826Controls) and meta-analysis of East Asian (EAS) cohorts (n=4,712PD vs 38,733Controls). Clinico-demographic details of affected variant carriers were collated. Results:The GCH1 p.Ser80Asn variant was enriched in GP2 EAS PD populations (n=9/2,757; 0.33%) but not detected in other ancestries. Meta-analysis revealed increased PD risk in EAS populations (odds ratio:5.1; 95%CI:2.3-10.7; p=2.89×10-5). Affected carriers (mean age at onset:56.3±12.5 years) had additional occurrence of dystonia, while dementia was rare. Conclusions:The GCH1 p.Ser80Asn variant is a rare, EAS-enriched risk variant for PD.

Parkinson’s disease (PD) is a complex neurodegenerative disorder with diverse molecular signatures that extend beyond the central nervous system. Peripheral blood serves as a minimally invasive source of transcriptomic biomarkers reflecting systemic inflammation, mitochondrial dysfunction, lysosomal impairment, and disrupted RNA processing—key pathways involved in PD. Long-read RNA sequencing with Oxford Nanopore Technologies (ONT) offers unprecedented detail of full-length transcripts, alternative isoforms, and RNA modifications, enabling more accurate detection of disease-related transcriptional changes. We conducted high-throughput ONT long-read RNA sequencing on blood samples from 145 individuals, including PD patients and age-matched healthy controls. RNA libraries were prepared using a cDNA-based protocol optimised for high-accuracy PromethION sequencing. Transcriptomes were quantified with ONT-specific pipelines, and analyses of differential gene expression (DGE), differential transcript expression (DEX), differential transcript usage (DTU), and alternative splicing were performed using ONT-aware tools such as DRIMSeq, DEXSeq, and stageR. Pathway enrichment linked disease-related changes to mitochondrial, lysosomal, and vesicle-trafficking pathways. Our analysis identified highly significant PD-associated transcriptional signatures in peripheral blood (SNCA, VPS13C, LRRK2, GRN, STAU1, NPTN, PARK7). Long-read sequencing uncovered extensive isoform-level dysregulation, including novel transcript variants (e.g., BCL2L2-PABPN1, SQSTM1) in pathways relevant to PD, such as autophagy and endolysosomal trafficking. DTU analyses revealed shifts in isoforms of LRRK2 and GBA1, indicating widespread disturbances in RNA processing. Enrichment analysis showed activation of molecular pathways linked to neurodegeneration. This study provides the largest long-read blood transcriptomic dataset in PD to date, demonstrating that ONT sequencing can resolve isoform-level changes and reveal systemic molecular signatures of PD. Our findings support the development of blood-based RNA biomarkers and the establishment of long-read transcriptomics as a transformative approach for genomic pathology in PD.

Bruck syndrome type 2 (BRKS2) is a rare disorder marked by congenital joint contractures and bone fragility, caused by variants in PLOD2, which encodes lysyl hydroxylase 2 essential for collagen stability. We report the first genetically confirmed BRKS2 cases from Indonesia and Ukraine, both showing fractures, skeletal deformities, and contractures. The Indonesian patient had compound heterozygous variants, while the Ukrainian patient had a homozygous missense variant, expanding the phenotypic and geographic spectrum of the disorder.

Epilepsy is one of the most common neurological diseases in the world, but it is also complex and difficult to study. There is a significant genetic component to epilepsy and more information is being published frequently. It is difficult to group and summarise all of this information in a way that is beneficial for both researchers and clinicians. The aim of this paper is to create a summary of all currently known epilepsy associated genes in order to aid epilepsy research to better understand the aetiology of the disease. This was achieved through gathering genetic data from three databases: Online Mendelian Inheritance in Man (OMIM), Clincal Genome (ClinGen), and PubMed. Genes were filtered based on specific criteria and were summarised into three tables: Epilepsy genes, Epilepsy associated genes and Predicted epilepsy associated genes. A fourth table was produced to showcase all epilepsy genes that were identified in all three databases. A total of 2,536 genes were identified to have some level of association with epilepsy. A total of 238 genes were classified as Epilepsy genes, 1,317 genes were classified as Epilepsy associated genes and 981 genes were classified as Predicted epilepsy genes. Finally, 86 genes were identified to be epilepsy genes that were found in all three genetic databases and represent the highest confidence in association with epilepsy. The significance of this study involves the ability to give researchers an up-to-date list of genes that have an association to epilepsy and a summary of information about said genes.

Evidence indicates phenotypic and biological overlap between psychiatric and neurodegenerative disorders. Further identification of underlying mutual and unique biological mechanisms may yield novel multi-disorder and disorder-specific therapeutic targets. The metabolome represents an important domain for target identification as metabolites play critical roles in modulating a diverse range of biological processes. We used Mendelian randomisation (MR) to test the causal effects of 1000 plasma metabolites and 300 metabolite ratios on anxiety, bipolar disorder, depression, schizophrenia, amyotrophic lateral sclerosis, Alzheimer’s disease, Parkinson’s disease and multiple sclerosis. Follow-up analyses were conducted using statistical colocalisation, multivariable Bayesian model averaging MR (MR-BMA) and polygenic risk score analysis in the UK Biobank. MR analyses identified 85 causal effects involving 77 unique metabolites passing FDR correction and robust sensitivity analyses (IVW-MR OR range 0.73–1.48; pFDR < 0.05). No evidence of reverse causality was identified. Multivariable MR-BMA analyses implicated sphingolipid metabolism in psychiatric disorder risk and carnitine derivatives in risk for amyotrophic lateral sclerosis and multiple sclerosis. Although polygenic risk scores for prioritised metabolites showed limited prediction in the UK Biobank, those nominally significant were directionally consistent with MR estimates. Downstream colocalisation in regions containing influential variants identified greater than suggestive evidence (PP.H4 ≥ 0.6) for a shared causal variant for 29 metabolite/psychiatric disorder trait-pairs on chromosome 11 at the FADS gene cluster. Most of these metabolites were lipids containing linoleic or arachidonic acid. Additional colocalisation was identified between the ratio of histidine-to-glutamine, glutamine, Alzheimer’s disease and SPRYD4 gene expression on chromosome 12. Although no single metabolite had a causal effect on both a psychiatric and a neurodegenerative disease, results suggest a broad effect of lipids across brain disorders, with a particular role for lipids containing linoleic or arachidonic acid in psychiatric disorders. The metabolites identified here may help inform future targeted interventions.

Objective:To investigate the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data and explore their role in sporadic PD. Methods:We analyzed CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium using a sliding window CNV-GWAS and genome-wide burden analysis. The independent dataset from the Global Parkinson Genetics Program (GP2) consisted of 23,089 cases and 18,824 controls were used to validate our initial findings. Results:The exploratory dataset identifies multiple CNV regions associated with PD risk. The nominated CNV loci were not confirmed in an independent dataset, except that only a deletion in the PRKN gene, a well-established EOPD locus, remained genome-wide significant and robustly supported. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. Interpretation:The largest CNV-based GWAS on PD highlights both the promise and pitfalls of array-based CNV detection in PD and underscores the relevance of whole-genome sequencing approaches in resolving the role of CNV in PD. The array-based findings are prone towards false positive findings that might arise either from platform limitations and/or cohort biases. Future studies require improved genotyping resolution and rigorous cross-cohort validation to reliably assess CNV contributions to PD risk.

An individual’s genetics contributes to their risk of developing amyotrophic lateral sclerosis (ALS); however, there is still a large proportion of the heritability of ALS to be understood. Part of this missing heritability may lie in complex variants, such as the long interspersed element 1 (L1) retrotransposon, which have yet to be evaluated. The majority of L1 insertions in the human genome are no longer able to retrotranspose, but to date 279 retrotransposition-competent (RC) L1s have been reported. Many RC-L1s are polymorphic for their presence/absence; therefore, each individual will have a different number and complement of RC-L1s. These elements have been hypothesized to be involved in disease processes by multiple mechanisms such as somatic mutation by retrotransposition, the triggering of neuroinflammation and DNA damage. We hypothesize that L1s may influence disease development either through their effects on endogenous genes or through the properties that enable them to retrotranspose. Whole genome sequencing data from the New York Genome Center ALS consortium were used to characterize L1 variation identifying 2,803 polymorphic L1 elements and association analysis was performed in European individuals (ALS/ALS with other neurological disorder (ALSND) n = 2,653, controls n = 320). There were no individual L1 elements associated with disease, but we did identify a significant increase in the number of RC-L1s in ALS/ALSND genomes (p = 0.01) and the presence of ≥46 RC-L1s showed the most significant association (OR = 1.09 (1.02–1.16), p = 0.01) with disease. Analysis of individual L1s and their association with age at onset and survival identified one L1 whose presence was significantly associated with a lower age at onset (52.7 years) compared to homozygous absent individuals (59.2 years) (padj = 0.009). Our study has identified novel genetic factors for both disease risk and age at onset in ALS providing further evidence for the role of L1 retrotransposons in neurodegenerative diseases.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disorder leading to upper and lower motoneurons degeneration. Although several mechanisms potentially involved in disease development have been identified, its pathogenesis is not fully understood. From the patient side, ALS diagnosis, still based on clinical criteria, can be difficult and may take up to 1 year. More than 30 genes have been associated to genetically inherited ALS, among which four (C9ORF72, SOD1, TARDBP and FUS) would explain around 60–70% of cases. However, familial ALS represents only 5–10% of ALS cases while the remaining are sporadic, with genetics explaining 6–10% of such cases only. In this context, short tandem repeats (STRs) expansions, have recently been found in clinically diagnosed ALS patients. In this review, we discuss the recent discoveries on ALS associated STRs and their potential as biomarkers as well as prognosis and therapy targets.

BACKGROUND:Loss of Y chromosome (LOY), an age-related somatic mutation, is associated with various age-related diseases, but its role in the onset and progression of Parkinson's disease (PD) remains unclear. This study investigated the relationship between blood LOY levels and the risk of PD onset and progression. METHODS:We estimated the LOY level for each male participant based on genome-wide arrays or whole genome sequencing data. We performed Cox proportional hazards regression analysis among 222,598 male participants in the UK Biobank and linear mixed model analysis involving 2574 male individuals with PD across 14 cohorts, encompassing 19,562 visits. In the Parkinson's Progression Markers Initiative (PPMI) cohort, we further compared brain structure using T1-weighted magnetic resonance imaging (MRI) scans, and carried out brain network functional connectivity analysis based on resting-state functional MRI (rs-fMRI) datasets. Additionally, we assessed the LOY status in single-nucleus RNA sequencing (snRNA-seq) data, which included 1,303,531 cells from 279 post-mortem samples across five brain regions, and performed temporal dynamic gene expression analysis. FINDINGS:Male participants with LOY had a slightly higher risk of developing PD during follow-up (HR = 1·16, 95% CI = 1·01-1·34, P = 0·04). Among males affected by PD, LOY carriers experienced accelerated neurodegenerative progression, manifesting as more rapid motor impairment (P = 0·0072) and cognitive decline (P = 0·0005) compared to non-LOY carriers. Patients with PD carrying LOY also exhibited decreased network functional connectivity in certain brain regions. Notably, LOY cells were particularly enriched in microglia/immune and vascular/epithelial cells, and a subset of genes in LOY-Mic P2RY12 cells were associated with PD progression. INTERPRETATION:This data-driven study highlights the potential association of LOY with the onset and progression of PD through the analysis of multi-scale data, including clinical phenotypes, brain neuroimaging maps, and molecular profiles from single-nucleus transcriptome across multi-brain regions. These findings suggest that LOY may be an accomplice to the onset and progression of PD. FUNDING:G.L.'s work is supported by the Shenzhen Fundamental Research Program (JCYJ20240813151132042), National Natural Science Foundation of China (32270701, 32470708), Young Talent Recruitment Project of Guangdong (2019QN01Y139), the Science and Technology Planning Project of Guangdong Province (2023B1212060018) and Shenzhen Key Laboratory for Systems Medicine in Inflammatory Diseases (ZDSYS20220606100803007). This study is supported by High-performance Computing Public Platform (Shenzhen Campus) of Sun Yat-sen University. C.R.S.'s work is supported by NIH grants NINDS/NIA R01NS115144, the U.S. Department of Defense, and the American Parkinson Disease Association Center for Advanced Parkinson Research. C.R.S.'s research work was funded in part by Aligning Science Across Parkinson's 000301 through the Michael J. Fox Foundation for Parkinson's Research (MJFF). The study was made possible in part by a philanthropic support for Illumina MEGA chip genotyping (to Brigham & Women's Hospital and C.R.S.). CHWG received funding support from an RCUK/UKRI Research Innovation Fellowship awarded by the Medical Research Council (MR/R007446/1; MR/W029235/1) and from the NIHR Cambridge Biomedical Research Centre (NIHR203312). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. For the purpose of open access, the author has applied a CC BY public copyright licence to all Author Accepted Manuscripts arising from this submission.

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by motor and neuropsychiatric symptoms resulting from the loss of dopamine-producing neurons in the substantia nigra pars compacta (SNc). Dopamine transporter scan (DATSCAN), based on single-photon emission computed tomography (SPECT), is commonly used to evaluate the loss of dopaminergic neurons in the striatum. This study aims to identify a biomarker from DATSCAN images and develop a machine learning (ML) algorithm for PD diagnosis. Using 13 DATSCAN-derived parameters and patient handedness from 1309 individuals in the Parkinson’s Progression Markers Initiative (PPMI) database, we trained an AdaBoost classifier, achieving an accuracy of 98.88% and an area under the receiver operating characteristic (ROC) curve of 99.81%. To ensure interpretability, we applied the local interpretable model-agnostic explainer (LIME), identifying contralateral putamen SBR as the most predictive feature for distinguishing PD from healthy controls. By focusing on a single biomarker, our approach simplifies PD diagnosis, integrates seamlessly into clinical workflows, and provides interpretable, actionable insights. Although DATSCAN has limitations in detecting early-stage PD, our study demonstrates the potential of ML to enhance diagnostic precision, contributing to improved clinical decision-making and patient outcomes.

Background: Besides conventional norms that recognize synovial fluid (SF) as a joint lubricant, nutritional channel, and a diagnostic tool in knee osteoarthritis (kOA), based on the authors previous studies, this study aims to define functional role of SF in kOA. Methods: U937, a monocytic, human myeloid cell line, was induced with progressive grades of kOA SF, and the induction response was assessed on various pro-inflammatory parameters. This ‘SF challenge test model’ was further extended to determine the impact of SF on U937 differentiation using macrophage-specific markers and associated transcription factor genes. Mitochondrial membrane potential changes in SF-treated cells were evaluated with fluorescent JC-1 probe. Results: a significant increase in nitric oxide, matrix metalloproteinase (MMP) 1, 13, and vascular endothelial growth factor (VEGF)-1 was noted in the induced cells. A marked increase was seen in CD68, CD86, and the transcription factors –activator protein (AP)-1, interferon regulatory factor (IRF)-1, and signal transducer and activator of transcription (STAT)-6 in the SF-treated cells indicating active monocytes to macrophage differentiation. Reduced mitochondrial membrane potential was reflected by a reduced red-to-green ratio in JC-1 staining. Conclusions: these results underline the active role of OA SF in stimulating and maintaining inflammation in joint cells, fostering monocyte differentiation into pro-inflammatory macrophages. The decline in the membrane potential suggestive of additional inflammatory pathway in OA via the release of pro-apoptotic factors and damaged associated molecular patterns (DAMPs) within the cells. Overall, biochemical modulation of SF warrants a potential approach to intervene inflammatory cascade in OA and mitigate its progression.