ABSTRACT Background The Progressive Supranuclear Palsy Clinical Deficits Scale (PSP-CDS) is a brief rating scale of clinical severity in PSP. However, its longitudinal performance has not been evaluated. We aimed to assess the ability of the PSP-CDS to track disease progression over time and to compare progression across PSP phenotypes in a real-world Asian cohort. Methods Patients who met the Movement Disorder Society PSP diagnostic criteria and underwent at least 2 PSP-CDS assessments were recruited from movement disorders clinics in Malaysia. Longitudinal progression was evaluated using linear mixed-effects models. Domain-specific progression and subtype-specific trajectories were also analyzed. Associations between annualized changes in PSP-CDS and Barthel Index (BI) scores were examined. Results 104 patients (including 59 with PSP-Richardson’s syndrome [PSP-RS], 28 with predominant parkinsonism [PSP-P], and 14 with progressive gait freezing [PSP-PGF]) contributed 394 PSP-CDS assessments over a median follow-up of 33.2 months (range, 8.7– 73.1 months). PSP-CDS scores increased significantly over time (β=0.126 points/month), corresponding to estimated increases of 1.13 points over 9 months and 2.27 points over 18 months. Subtype-specific analyses demonstrated the fastest progression in PSP-RS (0.156 points/month), followed by PSP-PGF (0.081 points/month) and PSP-P (0.077 points/month). Exploratory domain-level analyses showed that finger dexterity, communication, and dysphagia were the most rapidly worsening domains. Annualized PSP-CDS progression correlated significantly with annualized decline in BI scores (Spearman’s ρ=-0.474, P<0.001). Conclusions The PSP-CDS is sensitive to longitudinal disease progression in PSP and captures clinically-meaningful functional decline. Its brevity and ability to distinguish differential progression across PSP phenotypes support its utility as a pragmatic outcome measure for routine clinical practice and research.

Young onset Parkinson's disease may be caused by biallelic mutations in PRKN or other autosomal recessive Parkinson's disease genes, but the majority of patients do not carry known monogenic variants. Previous studies have found an increased cumulative burden of common genetic risk variants for Parkinson's disease in young onset patients, but the specific genetic architecture of non-monogenic young onset Parkinson's disease is not well characterized. We conducted a genome-wide association study of 1,528 Parkinson's disease patients with symptom onset between 18 and 40 years and 20,408 controls of European ancestry using data from The Global Parkinson's Genetic Program, the International Parkinson's Disease Genomics Consortium, and the NeuroGenetics Research Consortium. We performed meta-analyses of additive and recessive regression models and investigated associations between age at onset groups and different polygenic risk scores. An additive model meta-analysis identified six independent loci passing a genome-wide significance threshold, including three loci identified in previous genome-wide association studies (near SNCA, GBA1, and HIP1R) and two loci not previously associated with Parkinson's disease (rs74950462, P = 1.24x10-8 and rs72848817, P = 4.89x10-8). Furthermore, we identified a significant signal at the PRKN locus, prompting a follow-up analysis employing a recessive model. The recessive genome-wide association meta-analysis identified nine loci passing a genome-wide significance threshold, including SNCA, PRKN, and seven novel variants. Patients with onset between 18 and 40 years had significantly higher polygenic risk scores than later onset patients when the score was modelled specifically on genome-wide association statistics from independent young onset Parkinson's disease participants versus healthy controls. This increased polygenic burden was driven in part by loci harbouring mitochondrial pathway genes. Our results indicate that previously unidentified common and low-frequency variants contribute specifically to the young onset subgroup of Parkinson's disease. Association signals detected uniquely with a recessive model suggest that genetic susceptibility to young onset Parkinson's disease may be partially driven by homozygous variation, in line with previous reports of increased runs of homozygosity in this particular group of patients and may be consistent with a loss of function mechanism. The findings support the notion of young onset Parkinson's disease as a partly distinct subphenotype and highlight the mitochondrial pathway. These results may have implications for future precision medicine but should be interpreted with caution pending independent replication.

Background Alzheimer’s disease (AD) pathology, particularly amyloid-β (Aβ) deposition, occurs years before clinical symptoms. Modifiable risk factors may influence cognitive trajectories during this preclinical stage, but whether amyloid status alters their effects remains unclear. Objectives To investigate interactions between amyloid pathology and modifiable risk factors in predicting longitudinal cognitive decline among cognitively unimpaired older adults. Design and Setting This study was a secondary analysis of data derived from two large multicenter longitudinal cohort studies, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study. Participants A total of 1707 cognitively unimpaired adults aged 65–85 years were included, comprising 1169 amyloid-positive participants from the A4 Study (Aβ+) and 538 amyloid-negative participants from the LEARN Study (Aβ–). Measurements Cognitive function was assessed every six months using the Preclinical Alzheimer’s Cognitive Composite (PACC) over a mean follow-up of 4.9 years. Eight established modifiable risk factors—low education, alcohol use, diabetes, high cholesterol, high blood pressure, obesity, depressive symptoms, and physical inactivity—were evaluated. Linear mixed-effects models were applied to examine associations between each risk factor and longitudinal PACC decline, and to test interactions with amyloid status, adjusting for demographic and genetic covariates. Results Significant interactions between amyloid status and modifiable risk factors were observed for diabetes (adjusted β = −0.206, p = 0.032), high cholesterol (adjusted β = −0.155, p < 0.001), and physical inactivity (adjusted β = −0.161, p = 0.046), indicating combined effects rather than additive effects on cognitive decline among Aβ+ individuals. In the A4 study (Aβ+), low education, diabetes, high cholesterol, and physical inactivity were independently associated with accelerated cognitive decline, whereas obesity was linked to slower decline. In contrast, in the LEARN study (Aβ-), these associations were not statistically significant. Conclusions In conclusion, the significant interactions with amyloid status were observed for diabetes, high cholesterol, and physical inactivity, indicating that these risk factors were associated with faster cognitive decline specifically in Aβ+ individuals. The results suggest that consideration of amyloid status may be important when evaluating the potential role of metabolic and lifestyle risk factors in preclinical cognitive decline. In Aβ+ individuals, obesity was associated with slower cognitive decline, while low education was linked to lower baseline cognition or a reduced symptom threshold, without a significant interaction with amyloid status. Future studies should incorporate amyloid status and longitudinal biomarkers to assess whether modifying these factors can slow preclinical cognitive decline.

Elucidating the genetic contributions to Parkinson's disease aetiology across diverse ancestries is a critical priority for the development of targeted therapies in a global context. We conducted the largest sequencing characterization of potentially disease-causing, protein-altering and splicing mutations in 710 cases and 11 827 controls from genetically predicted African or African admixed ancestries. We explored copy number variants (CNVs) and runs of homozygosity in prioritized early onset and familial cases. Our study identified rare GBA1 coding variants to be the most frequent mutations among patients with Parkinson's disease, with a frequency of 4% in our case cohort. Of the 18 GBA1 variants identified, 10 were previously classified as pathogenic or likely pathogenic, four were novel and four were reported as of uncertain clinical significance. The most common known disease-associated GBA1 variants in the Ashkenazi Jewish and European populations, p.Asn409Ser, p.Leu483Pro, p.Thr408Met and p.Glu365Lys, were not identified among the screened Parkinson's disease cases of African and African admixed ancestry. Similarly, the European and Asian LRRK2 disease-causing mutational spectrum, including LRRK2 p.Gly2019Ser and p.Gly2385Arg genetic risk factors, did not appear to play a major role in Parkinson's disease aetiology among West African ancestry populations. However, we found three heterozygous novel missense LRRK2 variants of uncertain significance, with two (p.Glu268Ala and p.Arg1538Cys) displaying higher frequencies in the African ancestry population reference datasets. Structural variant analyses revealed the presence of PRKN CNVs with a frequency of 0.7% in African and African admixed cases, with 66% of CNVs detected being compound heterozygous or homozygous in early-onset cases, providing further insights into the genetic underpinnings in early-onset juvenile Parkinson's disease in these populations. Short tandem repeat analysis also identified ATXN3 CAG repeat expansions within the pathogenic range (CAGn > 45) in three patients with Parkinson's disease of African ancestry. Novel genetic variation among screened genes warrants further replication and functional prioritization to unravel their pathogenic potential. Here, we created the most comprehensive genetic catalogue of both known and novel coding and splicing variants potentially linked to Parkinson's disease aetiology in an underserved population and further conducted global and local ancestry analyses to further explore population-specific effects. Our study has the potential to guide the development of targeted therapies in the emerging era of precision medicine. By expanding genetics research to involve underrepresented populations, we hope that future Parkinson's disease treatments are not only effective but also inclusive, addressing the needs of diverse ancestral groups.

In the Global Parkinson's Genetics Program (GP2) we aim to advance precision medicine by integrating large-scale clinico-genetic data from diverse populations worldwide. We investigated potentially trial-eligible carriers of pathogenic and high-risk GBA1 and LRRK2 variants and conducted a global precision-medicine survey across GP2 sites. Among 65,509 individuals with Parkinson's disease, we identified 9,019 (13.8%) potentially trial-eligible genetic variant carriers, including 6,789 GBA1, 2,084 LRRK2, and 146 dual GBA1-LRRK2 carriers. Individuals were distributed across multiple global regions, many of which currently lack active gene-targeted trials, highlighting a global disparity between relevant variant carriers and the availability of disease modifying treatment trials. GP2's unified framework supports equitable recruitment for gene-targeted therapeutic studies and helps address critical gaps in Parkinson's disease genetics and future therapeutic development.

We demonstrate how Large Language Models (LLMs) accelerate biomedical data harmonization through automated Common Data Element (CDE) generation. We processed 31 datasets including clinical taxonomies and research data dictionaries through OpenAI's Generative Pre-trained Transformer - 4 (API Model gpt-4-0613), generating comprehensive metadata for each element using a template-based system. Subject-matter experts validated outputs, finding 94% of generated metadata fields required no revision overall, with an unweighted accuracy of 83.8%, unweighted, for semi-structured sources. Dramatically faster than manual approaches. Our system uses ElasticSearch with weighted field matching to identify semantic equivalences between variables, avoiding duplicate CDEs while building a standardized repository. Testing with Alzheimer's Disease Neuroimaging Initiative (ADNI) and Global Parkinson's Genetic Program (GP2) datasets showed 32.4% of previously unseen headers successfully mapped to our CDEs, with interoperability scores averaging 53.8/100 based on matching, completeness, and compliance metrics. This approach automates the most tedious aspects of data integration, reducing barriers to cross-study collaboration in biomedical research.

Background:α-Synucleinopathies are clinically and biologically heterogeneous disorders lacking reliable biomarkers to assist with early diagnosis, disease progression, patient stratification, and therapeutic targeting. Genetic variation is known to impact biomarker levels, influencing their utility and interpretation in research and clinical settings. We aimed to identify common genetic modulators of biomarker levels implicated in α-synucleinopathy pathogenesis. Methods:63 CSF, plasma, and urine biomarkers were analyzed in 581 individuals from the Parkinson's Progression Markers Initiative (PPMI). GWAS was performed to test for associations with common variants, while regressions and area under the curve (AUC) analysis was used to assess predictive power. Analyses were adjusted for age, sex, disease status, and principal components. PD- and DLB-risk loci associations were separately assessed for each GWAS. Results:We confirm strong associations between urine bis(monoacylglycerol)phosphate (BMP) isoforms and the variants LRRK2 p.G2019S and GBA1 p.N370S, while providing support for BMPs use as a LRRK2-PD biomarker. CSF Aβ was significantly associated with an APOE ε4 allele, reinforcing its central role in amyloid regulation. Novel associations were detected between CSF ceramide isoforms the MCF2L2 and GMNN loci, and between CSF tau and the TP63 locus. Multiple PD risk loci, including MAPT, SIPA1L2, MCCC1, and RAB29, were associated with lysosomal lipid biomarkers, highlighting pathway-level convergence. Conclusions:The present study reveals established and novel genetic modulators of potential α-synucleinopathy biomarkers, demonstrating that genetic background significantly shapes biomarker levels. These genetic influences should be accounted for when conducting biomarker-based research, clinical trials, or therapeutic development to ensure accurate interpretation and improve their translational relevance.

Expanded short tandem repeats contribute to a broad spectrum of neurodegenerative diseases, yet their roles in Parkinson's disease (PD) and parkinsonism remain incompletely characterized, especially across diverse ancestries. We analyzed short-read whole-genome (WGS) and clinical exome sequencing (CES) data from 38,365 individuals (28,861 WGS; 9,504 CES), encompassing 23,242 patients with PD, 4,729 patients with atypical parkinsonism and 10,394 healthy controls from 11 genetic ancestries. To determine carrier frequencies and characterize repeat structures across diverse ancestries, we genotyped 12 established pathogenic loci where normal, intermediate, and pathogenic alleles can be reliably differentiated using short-read sequencing data. Additionally, we conducted threshold-based associations to determine the minimum threshold associated with increased PD risk in 15,995 individuals (8,591 PD, 7,404 controls) of European ancestry. Pathogenic repeat expansions were detected in 62 patients (56 PD and 6 atypical parkinsonism) and 5 controls across seven loci (AR, ATXN1, ATXN2, ATXN3, CACNA1A, HTT and THAP11), spanning seven ancestries. Among these, ATXN2 expansions were the most frequently observed in PD and were present in African, East Asian, European and Middle Eastern ancestries. Additionally, intermediate ATXN2 repeat expansions exhibited a strong, length-dependent association with PD risk in the European population, with individuals with ≥32 repeats having a more than four-fold increased risk (odds ratio 4.25, 95% confidence interval 1.80-12.05). Overall, >92% of expanded alleles harbor CAA interruptions within the CAG tract. Pathogenic expansions at other loci, such as ATXN3 and THAP11, showed more ancestry-specific distributions. Clinically, individuals with pathogenic ATXN2 and ATXN3 expansions most often presented with typical PD features but frequently showed earlier disease onset and a strong family history of PD. This large-scale, multi-ancestry study comprehensively maps the genetic landscape of pathogenic and intermediate repeat expansions in PD. Our findings confirm a length- and structure-dependent risk association for ATXN2 with PD in the European population and highlight the pleiotropic effects of repeat expansions across the parkinsonian spectrum.

BACKGROUND:The genetic architecture of Parkinson's disease varies considerably across ancestries, yet most previous genetic studies have focused on individuals of European ancestry. We aimed to characterise the distribution of established Parkinson's disease causal variants, as well as risk-associated variants with clinical implications (ie, variants in genes involved in pathways targeted by ongoing clinical trials), across ancestrally diverse populations. METHODS:We conducted a multi-ancestry, observational, cross-sectional genetic study using retrospective data from the Global Parkinson's Genetics Program (GP2) release 11 (released in December, 2025). The study investigated causal and risk variants, including copy number variants, in established Parkinson's disease and parkinsonism-associated genes, following the recommendations of the Movement Disorder Society (MDS) Task Force on the Nomenclature of Genetic Movement Disorders, including GBA1, LRRK2, SNCA, VPS35, RAB32, PINK1, PRKN, PARK7, ATP13A2, DCTN1, DNAJC6, FBXO7, JAM2, RAB39B, SLC20A2, SYNJ1, VPS13C, and WDR45. Individuals with Parkinson's disease were diagnosed based on established clinical criteria, including the Parkinson's UK Brain Bank or MDS diagnostic criteria (or both), and healthy control participants were defined as individuals without evidence of neurodegenerative disease and unrelated to participants with Parkinson's disease. We analysed genome and exome sequencing and array genotyping data of 99 783 individuals, including 58 559 individuals with Parkinson's disease and 41 224 controls, from 11 genetically inferred ancestries (African, African admixed, Ashkenazi Jewish, Latino and Indigenous people of the Americas, central Asian, complex admixture, east Asian, European, Finnish, Middle Eastern, and south Asian), defined using reference population-based ancestry inference methods. We calculated allele frequencies for all investigated variants in individuals with Parkinson's disease and controls, both overall and stratified by ancestry. FINDINGS:Approximately 29% of individuals (29 001 of 99 783; 15 443 [26·4%] of 58 559 individuals with Parkinson's disease and 13 558 [32·9%] of 41 224 controls) were from under-represented populations (ie, non-European and non-Ashkenazi Jewish). Our findings indicated both shared genetic contributors across ancestries as well as ancestry-specific differences in variant frequencies and the spectrum of variants within Parkinson's disease-associated genes. Overall, 1217 (2·1%) of 58 559 individuals with Parkinson's disease carried a causal variant, with substantial variations across ancestries ranging from ten (0·4%) of 2844 African individuals to 251 (10·7%) of 2343 individuals of Ashkenazi Jewish ancestry. Risk variants in GBA1 and LRRK2 were identified in 6893 (11·8%) of 58 559 individuals with Parkinson's disease and 3578 (8·7%) of 41 224 controls. GBA1 risk variants were most frequent overall and identified across all ancestries, but variant frequency and spectra differed substantially between ancestries, from 195 (4·1%) of 4773 in the east Asian ancestry group to 1505 (52·9%) of 2844 in the African ancestry group. Similarly, LRRK2 causal and risk variants showed ancestry-specific enrichment, with the highest frequencies of causal variants in the Ashkenazi Jewish (250 [10·7%] of 2343) and Middle Eastern (59 [4·4%] of 1347) ancestry groups, whereas risk variants were predominantly identified in the east Asian ancestry group (601 [12·6%] of 4773). Carriers of biallelic causal variants in PRKN, commonly including deletions and duplications, were also identified across all ancestries except Ashkenazi Jewish; the highest frequency was in the Middle Eastern ancestry group (17 [1·3%] of 1347), and frequencies in all other ancestries were less than 1%. INTERPRETATION:This large-scale, multi-ancestry genetic study offers crucial insights into the population-specific genetic architecture of Parkinson's disease. Whereas clinical trials targeting GBA1 and LRRK2 variant carriers are primarily performed in Europe and the USA, increased ancestral diversity in Parkinson's disease research will be crucial to improve diagnostic accuracy, enhance our understanding of disease mechanisms across populations, and ensure equitable application of and access to emerging genetically informed therapies. FUNDING:Aligning Science Across Parkinson's (ASAP) through the Global Parkinson's Genetics Program (GP2).

Pathogenic GAA repeat expansions in FGF14 are an established cause of late-onset cerebellar ataxia, but have not been linked to Parkinson's disease (PD). Given emerging evidence that repeat expansions in ataxia-associated genes like RFC1, can contribute to atypical or familial forms of PD, we investigated whether FGF14 expansions might play a similar role. Using long-read whole-genome sequencing on 411 individuals with PD and 197 neurologically healthy controls from the PPMI cohort, alongside 1,429 additional controls from the NIH CARD initiative, the 1000 Genomes Project, and the All of Us program, representing globally diverse populations. We identified pathogenic FGF14 GAA repeat expansions in five individuals with PD and one control. All five individuals fit the clinical criteria of PD and showed typical patterns of neurodegeneration on DaTSCAN imaging; α-synuclein aggregation was confirmed by a positive seeding assay among four individuals with available data. These findings broaden the phenotypic spectrum of FGF14 repeat-associated disease and suggest a rare, previously unrecognized genetic contributor to PD. To our knowledge, this is the first report implicating FGF14 in PD and underscores the utility of long-read sequencing for detecting hidden forms of pathogenic variation in unresolved cases.

Levodopa (LD) remains the cornerstone of treatment for Parkinson’s disease (PD), but chronic LD therapy has been associated with elevated plasma homocysteine levels. Homocysteine reflects alterations in amino acid and one-carbon metabolism. Catechol-O-methyltransferase inhibitors (COMT-Is) reduce peripheral LD methylation; however, their association with homocysteine levels across different LD doses has not been fully characterized. In this prospective cross-sectional study, 262 patients with PD receiving oral LD/dopa decarboxylase inhibitor therapy were enrolled at two centers in Japan. Patients were stratified by COMT-I use (opicapone or entacapone). Plasma homocysteine and serum vitamin B6, vitamin B12, and folate levels were measured. Multivariable linear regression using log-transformed homocysteine as the outcome variable was performed, adjusting for demographic, clinical, pharmacological, and biochemical factors. Dose-stratified rolling range analyses examined LD dose–dependent associations. COMT-I use was independently associated with lower plasma homocysteine levels (β = −0.166, p = 0.00024). Higher vitamin B12 and folate levels were also inversely associated with homocysteine. In dose-stratified analyses, the homocysteine-lowering effect of COMT inhibition became apparent at LD doses above approximately 450 mg/day, whereas no significant differences were observed at lower doses. COMT inhibitor use is independently associated with lower plasma homocysteine levels in patients with PD receiving LD therapy, particularly at higher LD doses, supporting a metabolic role of COMT-mediated LD methylation.

Type 2 diabetes (T2D) risk prediction remains a challenge, particularly in underrepresented populations, including people living with HIV (PWH) and those of non-European ancestry. We evaluated the performance of two metaPRS (polygenic risk score) models, integrating genetic markers related to inflammation and lipid metabolism, in predicting T2D risk across ancestry groups (African and European), with and without HIV. The metaPRS were generated in a subset from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (6,034 Black; 11,972 White) and validated in 7,580 (4,120 Black; 3,460 White) PWH from the Centers for AIDS Research of Integrated Clinical Systems (CNICS), as well as an additional 4,152 (2,586 Black; 1,566 White) seronegative participants from REGARDS. Incorporating the metaPRS into models provided non-significant improvements in T2D risk prediction compared to single-trait T2D PRS and clinical risk factors. Performance was similar in PWH and in people without HIV, suggesting that these general population-derived genetic scores are transferable to PWH. Future studies should focus on refining PRS models in diverse populations and exploring genetic factors specific to PWH regarding T2D risk.

ObjectivesEmerging evidence suggests that the genetic architecture of Alzheimer disease (AD) and Parkinson disease (PD) risk varies across ancestries. This study seeks to explore distinct and universal genetic targets across individuals of Latino, African/African-admixed, East Asian, and European populations by implementing population attributable risk (PAR) comparisons using summary statistics from genome-wide association studies (GWASs). MethodsPAR was calculated for the most significant disease variants using summary statistics derived from select multi-ancestry GWAS meta-analyses, followed by fine-mapping analysis to validate genetic contribution of disease variants to European, African/African-admixed, East Asian, and Latino individuals. ResultsFor AD, APOE4 PAR estimates were universally high across all ancestries, with TSPAN14 and PICALM emerging as other common targets. Attributable risk varied across PD-related major risk loci, including variation nearby GBA1 and LRRK2. By contrast, SNCA, MCCC1, VPS13C, and MAPT loci demonstrated comparable attributable risk across ancestries. DiscussionThis cross-ancestry evaluation of PAR reinforces the genetic heterogeneity of AD and PD. In consideration of the complex etiology of these diseases, these findings may inform the strategic prioritization of therapeutic targets and improve global health outcomes.

Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this research gap, we introduce CARDBiomedBench, a large-scale question-and-answer benchmark for evaluating LLMs in biomedical science. This pilot release focuses on neurodegenerative disease research, a field requiring the integration of genomics, pharmacology, and statistical reasoning. CARDBiomedBench includes more than 68 000 curated question-answer pairs generated through expert annotation and structured data augmentation. The questions spanned ten biological categories and nine reasoning types, based on publicly available resources, such as genome-wide association studies, summary data-based mendelian randomisation results, and regulatory drug databases. We assessed model responses using BioScore, a rubric-based evaluation system that measures response accuracy (response quality rate, RQR) and the ability to abstain from incorrect answers (safety rate). Testing 18 state-of-the-art LLMs revealed considerable gaps. Claude-3.5-Sonnet achieved high caution but low accuracy (safety rate 75%, RQR 24%), whereas GPT-4.1 showed the opposite trade-off (safety rate 7%, RQR 51%). No model showed a successful balance of both metrics. CARDBiomedBench provides a new standard for benchmarking biomedical LLMs, revealing key limitations in existing models and offering a scalable path towards safer, more effective artificial intelligence systems in scientific research.

Although large-scale genetic association studies have proven opportunistic for the delineation of neurodegenerative disease processes, we still lack a full understanding of the pathological mechanisms of these diseases, resulting in few appropriate treatment options and diagnostic challenges. To mitigate these gaps, the Neurodegenerative Disease Knowledge Portal (NDKP) was created as an open-science initiative with the aim to aggregate, enable analysis, and display all available genomic datasets of neurodegenerative disease, while protecting the integrity and confidentiality of the underlying datasets. The portal contains 218 genomic datasets, including genotyping and sequencing studies, of individuals across ten different phenotypic groups, including neurological conditions such as Alzheimer's disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson's disease. In addition to securely hosting large genomic datasets, the NDKP provides accessible workflows and tools to effectively utilize the datasets and assist in the facilitation of customized genomic analyses. Here, we summarize the genomic datasets currently included within the portal, the bioinformatics processing of the datasets, and the variety of phenotypes captured. We also present example use-cases of the various user interfaces and integrated analytic tools to demonstrate their extensive utility in enabling the extraction of high-quality results at the source, for both genomics experts and those in other disciplines. Overall, the NDKP promotes open-science and collaboration, maximizing the potential for discovery from the large-scale datasets researchers and consortia are expending immense resources to produce and resulting in reproducible conclusions to improve diagnostic and therapeutic care for neurodegenerative disease patients.

Among LRRK2-associated parkinsonism cases with nigral degeneration, over two-thirds demonstrate evidence of pathologic alpha-synuclein, but many do not. Understanding the clinical phenotype and underlying biology in such individuals is critical for therapeutic development. Our objective was to compare clinical and biomarker features, and rate of progression over 4 years of follow-up, among LRRK2-associated parkinsonism cases with and without in vivo evidence of alpha-synuclein aggregates. Data were from the Parkinson's Progression Markers Initiative, a multicentre prospective cohort study. The sample included individuals diagnosed with Parkinson disease with pathogenic variants in LRRK2. Presence of CSF alpha-synuclein aggregation was assessed with seed amplification assay. A range of clinician- and patient-reported outcome assessments were administered. Biomarkers included dopamine transporter scan, CSF amyloid-beta1-42, total tau, phospho-tau181, urine bis(monoacylglycerol)phosphate levels and serum neurofilament light chain. Linear mixed-effects (LMMs) models examined differences in trajectory in CSF-negative and CSF-positive groups. A total of 148 LRRK2 parkinsonism cases (86% with G2019S variant), 46 negative and 102 positive for CSF alpha-synuclein seed amplification assay, were included. At baseline, the negative group was older than the positive group [median (inter-quartile range) 69.1 (65.2-72.3) versus 61.5 (55.6-66.9) years, P < 0.001] and a greater proportion were female [28 (61%) versus 43 (42%), P = 0.035]. Despite being older, the negative group had similar duration since diagnosis and similar motor rating scale [16 (11-23) versus 16 (10-22), P = 0.480] though lower levodopa equivalents. Only 13 (29%) of the negative group were hyposmic, compared with 75 (77%) of the positive group. The negative group, compared with the positive group, had higher per cent-expected putamenal dopamine transporter binding for their age and sex [0.36 (0.29-0.45) versus 0.26 (0.22-0.37), P < 0.001]. Serum neurofilament light chain was higher in the negative group compared with the positive group [17.10 (13.60-22.10) versus 10.50 (8.43-14.70) pg/mL; age-adjusted P-value = 0.013]. In terms of longitudinal change, the negative group remained stable in functional rating scale score in contrast to the positive group who had a significant increase (worsening) of 0.729 per year (P = 0.037), but no other differences in trajectory were found. Among individuals diagnosed with Parkinson disease with pathogenic variants in the LRRK2 gene, we found clinical and biomarker differences in cases without versus with in vivo evidence of CSF alpha-synuclein aggregates. LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates as a group exhibit less severe motor manifestations and decline. The underlying biology in LRRK2 parkinsonism cases without evidence of alpha-synuclein aggregates requires further investigation.

BACKGROUND:The catechol-O-methyltransferase (COMT) gene is involved in brain catecholamine metabolism, but its association with Parkinson's disease (PD) risk remains unclear. OBJECTIVE:Our aim was to investigate the relationship between COMT genetic variants and PD risk across diverse ancestries. METHODS:We analyzed COMT variants in 2251 PD patients and 2835 controls of European descent using whole-genome sequencing from the Accelerating Medicines Partnership-Parkinson Disease (AMP-PD), along with 20,427 PD patients and 11,837 controls from 10 ancestries using genotyping data from the Global Parkinson's Genetics Program (GP2). RESULTS:Using the largest case-control datasets to date, no significant enrichment of COMT risk alleles in PD patients was observed across any ancestry group after correcting for multiple testing. Among Europeans, no correlations with cognitive decline, motor function, motor complications, or time to levodopa-induced dyskinesia onset were observed. CONCLUSIONS:This study highlights the need for increased representation of diverse ancestries to better understand the role of COMT variants in PD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Emerging evidence suggests that the genetic architecture of Alzheimer's (AD) and Parkinson's diseases (PD) risk varies across ancestries. This study seeks to explore distinct and universal genetic targets across individuals of Latino, African/African Admixed, East Asian, and European populations by implementing Population Attributable Risk (PAR) comparisons on summary statistics from genome-wide association studies (GWAS). PAR was calculated for the most significant disease variants using summary statistics derived from select multi-ancestry GWAS meta-analyses, followed by fine-mapping analysis to validate genetic contribution of disease variants to European, African/African Admixed, East Asian, and Latino individuals. For both AD, APOE4 PAR estimates were universally high across all ancestries, with TSPAN14 and PICALM emerging as other common targets. Attributable risk varied across PD-related major risk loci including variation nearby GBA1 and LRRK2. In contrast, SNCA, MCCC1, VPS13C, and MAPT loci demonstrated comparable attributable risk across ancestries. This cross-ancestry evaluation of PAR reinforces the genetic heterogeneity of AD and PD. In consideration of the complex etiology of these diseases, these findings may inform the strategic prioritization of therapeutic targets and improve global health outcomes.

Alzheimer's disease (AD) and Parkinson's disease (PD) are influenced by genetic and environmental factors. We conducted a biobank-scale study to (i) identify endocrine, nutritional, metabolic, and digestive disorders with potential causal or temporal associations with AD/PD risk before diagnosis; (ii) assess plasma biomarkers' specificity for AD/PD in the context of co-occurring gut related traits and disorders; and (iii) integrate multimodal datasets to enhance AD/PD prediction. Our findings show that several disorders were associated with increased AD/PD risk before diagnosis, with variation in the strength and timing of associations across conditions. Polygenic risk scores reveal lower genetic predisposition for AD/PD in individuals with co-occurring disorders. Moreover, the proteomic profile of AD/PD cases was influenced by comorbid gut-brain axis disorders. Last, our multimodal prediction models outperform single-modality paradigms in disease classification. This endeavor illuminates the interplay between factors involved in the gut-brain axis and the development of AD/PD, opening avenues for therapeutic targeting and early diagnosis.