Serrano, Geidy E.

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.

Abstract INTRODUCTION Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within non‐Hispanic White (NHW) populations. Here we provide an extensive survey of the proteomic landscape of AD across diverse racial/ethnic groups. METHODS Two cortical regions, from multiple centers, were harmonized by uniform neuropathological diagnosis. Among 998 unique donors, 273 donors self‐identified as African American, 229 as Latino American, and 434 as NHW. RESULTS While amyloid precursor protein and the microtubule‐associated protein tau demonstrated higher abundance in AD brains, no significant race‐related differences were observed. Further proteome‐wide and focused analyses (specific amyloid beta [Aβ] species and the tau domains) supported the absence of racial differences in these AD pathologies within the brain proteome. DISCUSSION Our findings indicate that the racial differences in AD risk and clinical presentation are not underpinned by dramatically divergent patterns in the brain proteome, suggesting that other determinants account for these clinical disparities. Highlights We present a large‐scale proteome (∼10,000 proteins) of DLPFC (998) and STG (244) across AD cases. About 50% of samples were from racially and ethnically diverse brain donors. Key AD proteins (amyloid and tau) correlated with CERAD and Braak stages. No significant race‐related differences in amyloid and tau protein levels were observed in AD brains. AD‐associated protein changes showed a strong correlation between the brain proteomes of African American and White individuals. This dataset advances understanding of ethnoracial‐specific AD pathways and potential therapies.

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.

Abstract INTRODUCTION Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.

AbstractBackgroundThe G2019S leucine‐rich repeat kinase 2 (LRRK2) gene mutation is an important and commonly found genetic determinant of Parkinson's disease (PD). The neuropathological findings associated with this mutation have thus far been varied but are most often associated with Lewy body (LB) pathology.ObjectiveDescribe a case of clinical Parkinson's disease with levodopa responsiveness found to have LRRK2 mutations and the absence of Lewy bodies.MethodWe present an 89‐year‐old man with a 10‐year history of slowly progressive parkinsonism suspected to be secondary to Parkinson's disease.ResultsNeuropathological evaluation revealed nigral degeneration without Lewy bodies or Lewy neurites, but there were frequent tau‐immunopositive neurites and astrocytes in the putamen and substantia nigra, neocortical glial tau positive astrocytes associated with aging‐related tau astrogliopathy (ARTAG), as well as neurofibrillary tangles, beta amyloid plaques, and amyloid angiopathy typical of advanced Alzheimer's disease. G2019S LRRK2 homozygous mutations were found.ConclusionThis case illustrates that levodopa‐responsive clinical PD caused by G2019S LRRK2 mutations can occur without Lewy bodies.

AbstractBackgroundWhile preclinical studies have shown that alpha‐synuclein can spread through cell‐to‐cell transmission whether it can be transmitted between humans is unknown.ObjectivesThe aim was to assess the presence of a synucleinopathy in autopsied conjugal couples.MethodsNeuropathological findings in conjugal couples were categorized as Parkinson's disease (PD), dementia with Lewy bodies (DLB), Alzheimer's disease with Lewy bodies (ADLB), incidental Lewy body disease (ILBD), or no Lewy bodies.ResultsNinety conjugal couples were included; the mean age of death was 88.3 years; 32 couples had no Lewy bodies; 42 couples had 1 spouse with a synucleinopathy: 10 PD, 3 DLB, 13 ADLB, and 16 ILBD; 16 couples had both spouses with a synucleinopathy: in 4 couples both spouses had PD, 1 couple had PD and DLB, 4 couples had PD and ADLB, 2 couples had PD and ILBD, 1 couple had DLB and ADLB, in 3 couples both had ADLB, and 1 couple had ADLB and ILBD. No couples had both spouses with ILBD.ConclusionsThis large series of 90 autopsied conjugal couples found 16 conjugal couples with synucleinopathies, suggesting transmission of synucleinopathy between spouses is unlikely. © 2024 International Parkinson and Movement Disorder Society.

AbstractBackgroundNeuropsychiatric symptoms (NPS) are frequent in Alzheimer’s Disease dementia (ADD) 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). Previous studies have shown that both ADLB and DLB cases have faster cognitive and/or functional decline compared to AD. However, the differences in NPS severity over disease course and survival in these pathologic subgroups is not well understood.MethodCases from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with a final neuropathologic diagnosis of DLB (±AD co‐pathology; n = 65), ADLB (n = 89), AD (without LB) (n = 140), and controls (no neuropathological diagnosis) (n = 82) were included. Total NPI‐Q (scores ranging from 0‐36) at time of enrollment and within 2.5 years of death were calculated for all groups. Statistical analysis utilizing ANCOVA (adjusting for age, sex, baseline MMSE and cognitive symptom duration) with pairwise comparisons, and Kaplan‐Meier curves were completed.ResultAge at onset of cognitive symptoms was not different between pathology groups. NPI‐Q scores at enrollment were highest in ADLB (7.33 ± 4.85), and higher (p<0.001) than DLB (5.10 ± 3.37), AD (4.54 ± 3.63) and controls (1.78 ± 1.70). At final evaluation, NPI‐Q scores were highest in DLB (10.04 ± 6.28), followed by ADLB (8.0 ± 4.), and ADD (7.61 ± 5.05) when compared to controls (2.78 ± 3.97) (all p<0.001). DLB and AD demonstrated significant increases in NPI‐Q severity during follow up (p < 0.001). AD had longer survival time (5.8 years) compared to ADLB (4.0 years) and DLB (3.9 years). Subjects with NPS had a shorter median survival time (3.4 years) compared to subjects without NPS (6.5 years; p = 0.002).ConclusionA higher NPS burden and shorter survival is seen in both DLB and ADLB, as compared with AD. This suggests that diffuse neocortical LB pathology is not the major driver of either NPS or survival.