Beach, Thomas G.

Abstract Background Cerebrospinal fluid (CSF) seed amplification assays (SAAs) for detecting α‐synuclein (αsyn) seeds have recently emerged as robust in vivo biomarkers of Lewy body pathology (LBP). However, CSF sampling is invasive, costly, and time‐consuming, limiting its widespread use. We aimed to develop and evaluate a neuropathologically‐validated two‐step workflow, leveraging smell function and CSF αsyn SAA to accurately determine postmortem LBP status. This approach could reduce the number of confirmatory lumbar punctures needed (Figure 1). Methods The study included 358 individuals from the Arizona Study of Aging and Neurodegenerative Disorders with antemortem smell testing, CSF αsyn SAA results, and postmortem neuropathological assessments of regional LBP burden. Step‐1 of the two‐step workflow involved a risk‐stratification model predicting postmortem cortical LBP‐positivity (LBP ctx , defined as at least mild pathology in any cortical region) using logistic regression models with University of Pennsylvania Smell Identification Test (UPSIT) scores (smell testing), age, and sex as predictors. In step‐2, confirmatory CSF αsyn SAA testing was applied only to participants identified as high‐risk in step‐1. Workflow performance ‐ accuracy, positive predictive value (PPV), negative predictive value (NPV), and reduction in CSF testing ‐ was evaluated in (i) the entire study cohort; (ii) patients with clinical parkinsonism; (iii) patients with an Alzheimer's disease (AD) clinical syndrome; and (iv) clinically unimpaired (CU) individuals. Results Participants had a mean age at death of 86.2±7.8 years, 42.6% were female, 35.2% had LBP ctx , and the average time between UPSIT and death was 3.2±2.3 years (Table 1). Using a 95% sensitivity cut‐off for the UPSIT‐based algorithm, the two‐step workflow achieved high accuracy in identifying LBP ctx (whole cohort=94%; clinical parkinsonism=95%; clinical AD=94%; CU=93%; Figure 2a), while reducing CSF testing (whole cohort=‐43%; clinical parkinsonism=‐23%; clinical AD=‐35%; and CU=‐80%; Figure 2d). PPVs ranged from 75‐96% and were highest in the clinical parkinsonism subgroup (96%) where LBP ctx + was highest (62.7%). NPVs ranged between 95‐98% and were highest in the clinical AD subgroup (98%) (Figure 2b‐c). The two‐step approach reached accuracies similar to using CSF tests in all participants. Conclusions Implementing a two‐step workflow in different clinical scenarios may reduce invasive testing with CSF, minimizing the burden for individuals and costs for healthcare providers.

Abstract Background The amygdala is closely connected to the olfactory bulb and involved in olfactory processing as well. It is a particularly susceptible region that accumulates a‐synuclein pathology in Parkinson's disease (PD). Our previous work revealed olfactory bulb gene alterations related to neuroinflammation, and neurotransmitter dysfunction to be associated with olfactory function. We aimed to extend this work and assess gene expression changes, affected pathways and co‐expression networks by transcriptomic profiling of the amygdala in subjects with and without clinicopathologically defined PD. Method Bulk RNA sequencing was performed on frozen human amygdala of 20 PD and 20 controls without dementia or any other neurodegenerative disorder, from the Arizona Study of Aging and Neurodegenerative Disorders. Result Differential expression analysis, corrected for age, sex and post‐mortem interval revealed 40 significantly differentially expressed genes (DEGs) in PD. Downregulated genes were mainly related to altered hemoglobin expression while upregulated genes included inflammatory markers and glutamine transporter. Significantly enriched pathways were involved in oxygen and carbon dioxide transport, cellular oxidant detoxification and regulation of glutamine secretion. Cell enrichment revealed these genes to be mainly expressed in neurons. Co‐expression network analysis using Weighted correlation network analysis (WGCNA ) subsequently identified four significant modules correlated with both PD and premortem olfactory dysfunction which were involved in pathways related to neuroinflammatory processes, mitochondrial, endoplasmic reticulum and lysosomal dysfunction. Conclusion These preliminary results suggest cellular alterations in the amygdala related to mitochondrial dysfunction, altered oxygen homeostasis, oxidative stress, inflammation as well as glutamatergic neurotransmitter dysfunction that may contribute to neurodegeneration in PD.

Abstract Bioinformatics methods can be used to quantify mitochondrial DNA copy number from whole genome sequencing (WGS) data. We evaluated mitochondrial DNA copy number from human brain-derived WGS data using the fastMitoCalc tool. 341 Parkinson’s Disease cerebellum samples were compared with 74 age-matched controls from the North American Brain Expression Consortium. Parkinson’s Disease cerebellum had significantly higher mitochondrial DNA copy number compared with controls (P = 4.15e–7), and this effect was reproducible in four of five brain banks when analysis was restricted to each resource that contributed Parkinson’s Disease samples to this genetic dataset. Follow-on analyses of 128 Parkinson’s Disease cerebellum samples and 33 controls that had paired neuropathology data and clinical scores demonstrated a significant increase in mitochondrial DNA copy number with Unified Staging System for Lewy Body disorders stages and Unified Parkinson’s Disease Rating Scale (off meds) motor scores. Analysis of Lewy Body scores from ten brain regions showed cerebellum mitochondrial DNA copy number increased upon pathological infestation of α-synuclein aggregates in the brainstem and limbic system but did not increase after late-stage neocortical involvement. This genetics dataset supports previous observations of cerebellum activation in Parkinson’s Disease and suggests mitochondrial DNA copy number may increase to support this regional activation as a compensatory mechanism to pathology or motor symptoms.

Background Neuropsychiatric symptoms (NPS) are frequent in Alzheimer's disease (AD) dementia, but a higher NPS burden is found in dementia with Lewy bodies (DLB). Lewy body (LB) pathology frequently co-occurs with AD pathology and may not meet neuropathological criteria for DLB (ADLB). NPS trajectories over disease course in these subgroups is not well understood. Objective We investigated changes in NPS severity over time, at two time points, comparing clinicopathologically defined cohorts of AD (without LB), ADLB, DLB, and controls. Methods Cases with two available Neuropsychiatric Inventory-Questionnaire (NPIQ), at the time of enrollment and within 2.5 years of death, were selected from the Arizona Study of Aging and Neurodegenerative Disorders. Differences and rate of change in NPIQ scores were compared between AD (n = 75), ADLB (n = 48) DLB (n = 65), and controls (n = 32) with covariates for age, sex, and cognition. Results First NPIQ scores were highest in ADLB when compared to AD (p = 0.04) and controls (p = 0.01) but not different from DLB. A significant increase in NPS severity was observed in DLB and AD (p < 0.001) over a mean follow up time of 4.9 ± 3.0 years, and the rate of change was significantly greater in DLB when compared to other groups. Final NPIQ scores were highest in DLB when compared to AD (p = 0.03) but not ADLB, and in DLB, ADLB, and AD than controls ( all p < 0.001). Conclusions Early NPS burden as well as NPS severity progression rate, independently of cognitive status, might be useful clinical metrics and may help predict underlying pathological diagnoses.

AbstractBackgroundThe 17q21.31 region with various structural forms characterized by the H1/H2 haplotypes and three large copy number variations (CNVs) represents the strongest risk locus in progressive supranuclear palsy (PSP).ObjectiveTo investigate the association between CNVs and structural forms on 17q.21.31 with the risk of PSP.MethodsUtilizing whole genome sequencing data from 1684 PSP cases and 2392 controls, the three large CNVs (α, β, and γ) and structural forms within 17q21.31 were identified and analyzed for their association with PSP.ResultsWe found that the copy number of γ was associated with increased PSP risk (odds ratio [OR] = 1.10, P = 0.0018). From H1β1γ1 (OR = 1.21) and H1β2γ1 (OR = 1.24) to H1β1γ4 (OR = 1.57), structural forms of H1 with additional copies of γ displayed a higher risk for PSP. The frequency of the risk sub‐haplotype H1c rises from 1% in individuals with two γ copies to 88% in those with eight copies. Additionally, γ duplication up‐regulates expression of ARL17B, LRRC37A/LRRC37A2, and NSFP1, while down‐regulating KANSL1. Single‐nucleus RNA‐seq of the dorsolateral prefrontal cortex analysis reveals γ duplication primarily up‐regulates LRRC37A/LRRC37A2 in neuronal cells.ConclusionsThe copy number of γ is associated with the risk of PSP after adjusting for H1/H2, indicating that the complex structure at 17q21.31 is an important consideration when evaluating the genetic risk of PSP. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

AbstractBackgroundAlzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non‐Hispanic White (NHW) population. To address this, Accelerating Medicines Partnership in AD (AMP‐AD) aimed to promote inclusivity in multi‐omics AD research, to unravel unique molecular signatures and pathways. The study aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial groups.MethodDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (980 unique individuals), 322 were from African American donors, 214 from Latino Americans, 551 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG samples, 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag‐based mass spectrometry (TMT‐MS). Following quality control (QC), proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. Differential protein expression was conducted within and across races after adjusting for batch using regression‐analysis.ResultIn total, 9,180 proteins from the DLPFC, and 9,734 proteins from STG brain tissues were quantified by TMT‐MS. Further analysis identified approximately 3,000 differentially abundant proteins in AD brains compared to controls within race. The AD‐associated differentially abundant proteins were strongly correlated between DLPFC and STG regions and with CERAD and Braak. Protein levels of MAPT and APP demonstrated equivalent disease‐related elevations in both African American and NHW individuals with AD. Notably, after adjusting for AD, significant differences in protein levels were identified across race.ConclusionThe proteomics approach employed by AMP‐AD sheds light on the brain proteome in AD across diverse racial groups, emphasizing the importance of inclusive research in establishing robust and generalizable discoveries. The identified proteins here could underscore racial disparities beyond disease association, contributing to a more nuanced understanding of AD pathophysiology.

AbstractBackgroundAlzheimer’s disease (AD) is a devastating neurodegenerative disorder with few therapies to treat, mitigate or prevent its onset. Understanding of this disease is predominantly based on research in non‐Hispanic Whites (NHW) although AD disproportionately affects African Americans (AA) and Latin Americans (LA), underrepresented in AD research. To address this knowledge gap, the Accelerating Medicine Partnership for Alzheimer’s Disease (AMP‐AD) Diversity Working Group was launched to generate multi‐omics data from post‐mortem brain tissue from donors of predominantly AA and LA descent. Here, we focus on genomic and transcriptomics measures, made available through the AD Knowledge Portal (ADKP).MethodBrain tissue from dorsolateral prefrontal cortex (DLPFC), caudate nucleus (CN), superior temporal gyrus (STG) and temporal pole (TP) regions of AA (N = 299), LA (N = 344) and NHW (N = 532) donors was obtained through Mayo Clinic, Mt. Sinai School of Medicine, Emory, Columbia, Rush Alzheimer’s Disease Center, Banner Sun Health, and 1Florida. DNA extracted from DLPFC tissue samples (n = 641) was utilized for whole genome sequencing (WGS) at New York Genome Center (NYGC). RNAseq of 2,224 samples was conducted either at Mayo, Rush or NYGC. Sequencing reads were processed through GenomeGPS and MAPRseq pipelines for WGS and RNAseq data, respectively. Following quality control (QC), RNAseq data was normalized and assessed for sources of variation (SOV). Integration of WGS and RNAseq data to perform comparative eQTL analysis across multi‐ethnic populations and brain regions is ongoing.ResultWGS data for 621 donors, and RNAseq data generated at Mayo (n = 1,136 samples), Rush (n = 627), and NYGC (n = 779) sequencing centers, were deposited to the ADKP. Consensus processing of RNAseq data revealed site, sex, race/ethnicity, RIN, AD diagnosis, age at death and/or library batch as SOV across various sites and brain regions. Principal component analysis of gene expression measures revealed no major stratification by disease or brain region. Accompanying clinical metadata of donors have been distributed through ADKP.ConclusionThese multi‐omics data made available to the research community is expected to be an initial step towards bridging our data and knowledge gap to elucidate conserved and distinct AD related pathways across these underrepresented at‐risk populations.

AbstractBackgroundLewy body (LB) diseases can present with overlapping prodromal, cognitive, motor, autonomic or neuropsychiatric symptoms. Intuitively, greater symptom severity should correlate with greater pathological burden, but this has not been consistently shown. LB pathology does not translate to clinical expression in Incidental LB disease. While several composite scores/toolkits utilize overlapping schemes for diagnosis, a composite data‐derived score to predict LB pathologic burden is lacking. We aimed to utilize an autopsy‐confirmed cohort, and validated, brief, and standardized clinical, functional, pathologic assessments, and machine learning (ML)/quantitative modeling techniques to identify clusters and importance rankings among assessments/measures to predict LB pathologic severity and density.MethodA total of 234 subjects with neuropathological finding of LB at autopsy in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) who were classified as Cognitively Unimpaired or Mild Cognitive Impairment after their first study clinical evaluation were included. Of these, 145 subjects had complete scores for 32 of 46 measures (clinical, cognitive, behavioral and functional) that were utilized as predictors of LB pathology. Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). LB severity was assessed by the Unified Staging System for Lewy Body Disorders (USSLB). Several ML algorithms and quantitative prediction models were explored and compared: artificial neural network (ANN), partial least square regression (PLSR), support vector regression (SVR), relevance vector regression (RVR) and ensemble forest regression (EFR) with leave‐one‐out (LOO) scheme. Game‐theory based Shapley methods assessed the impact, including rankings, consistency and magnitude, of model predictors.ResultRVR predicted aggregate LB density with large effect size (R2 = 0.691, p<0.00001). ANN predicted USSLB severity stage with large effect size (R2 = 0.74, p<2.5e‐43). All other ML algorithms/models provided substantial prediction. Across all models, UPSIT was the most influential predictor (>65%), followed by Controlled Oral Word Association Test (COWAT) and age.ConclusionThese preliminary and exploratory results support the utilization of ML techniques/models to assess LB pathologic burden with key measures collected in relatively small samples. UPSIT was consistently ranked highest impactful among clinical and functional measures/predictors. Integrated together in ML/data‐derived composites, UPSIT, COWAT and other clinical characteristics may be of antemortem utility to predict USSLB stages.

AbstractBackgroundIdiopathic rapid eye movement sleep behavior disorder (RBD) is a strong known predictor of a final clinicopathological diagnosis of a Lewy type α‐synucleinopathy (LTS). Olfactory dysfunction is an early symptom of synucleinopathies and has been repeatedly associated with the presence of post‐mortem LTS.ObjectiveTo assess the combined value of a clinician diagnosis of probable RBD (PRBD) and hyposmia in predicting the post‐mortem presence of LTS in a broader, less‐selected, volunteer elderly population.MethodsWe studied 652 autopsied subjects from the Arizona Study of Aging and Neurodegenerative Disorders, which were evaluated for PRBD, had completed annual movement and cognitive assessments, and had at least one the University of Pennsylvania Smell Identification Test (UPSIT) olfactory test.ResultsHistological evidence of LTS was significantly more frequent in those who had PRBD (112/152: 73.7%) than those without (177/494: 35.8%) (P < 0.001). LTS was more frequent in cases with PRBD and a low UPSIT score (90.8%) compared to cases with PRBD only (73.7%) (P < 0.001) or cases with a low UPSIT score only (69.4%) (P < 0.001). Sensitivity of PRBD diagnosis for predicting LTS was 38.8% and specificity 88.8%, whereas sensitivity of a low UPSIT score was 74.4% and specificity 73.4% (Youden's index = 0.276 for PRBD, 0.478 for UPSIT). When combining both measures, sensitivity was 34.3% and specificity increased to 97.2%.ConclusionPRBD, diagnosed without sleep study confirmation, combined with a reduced olfactory performance is highly specific for predicting post‐mortem presence of LTS. The combination of both measures may provide a cost‐effective means of predicting LTS in a broader community.