Citations

Abstract Importance Decline in olfactory function may be used as a predictor of cognitive decline, to enhance early detection models, improve risk stratification, and enable early intervention. Objective To assess the longitudinal association between olfactory decline, cognitive decline, and postmortem neuropathology. Design, setting and participants Retrospective longitudinal analysis with clinicopathological correlations of a prospective population-based cohort study using data from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) and its Brain and Body Donation Program. Participants included cognitively unimpaired individuals without parkinsonism that converted to mild cognitive impairment (MCI) and/or dementia or remained cognitively stable. Main Outcomes and Measures longitudinal change in olfaction, neuropsychiatric symptoms, motor function and memory, conversion to MCI/dementia, postmortem neuropathology Results Over a mean follow-up period of 7.7 ± 5.4 years, out of 922 participants who were cognitively unimpaired at the first cognitive conference, 643 remained cognitively unimpaired, 279 converted to MCI, and 82 developed dementia. Of these, 633 individuals had at least 2 olfactory tests. Converters showed reduced olfactory function (t=-12.6, p <0.0001), faster progression in neuropsychiatric symptom burden (t=3.42, p < 0.001), and faster decline in memory (t= -7.33, p <0.0001) prior to conversion while no significant differences were observed in motor scores between converters and non-converters. Using ROC analysis, olfactory decline, increased neuropsychiatric symptom burden, as well as motor and memory decline predicted conversion to MCI with a consistent accuracy of ∼ 70% up to 5 years before conversion, while UPSIT alone had an accuracy of ∼ 60%. Longitudinal decline in olfaction was associated with a higher burden of a-synuclein (t= -8.21, p <0.0005), tau tangle (t= -2.66, p < 0.01) and amyloid plaque burden (t= -2.85, p < 0.005) and a faster decline over time was associated with a higher burden of tau (t=5.66, p<0.0001). Conclusions and Relevance A reduction in olfactory identification ability is observed up to a decade prior to conversion to MCI and is associated with underlying burden of neuropathology markers, underscoring the value of incorporating olfactory testing in cognitively unimpaired individuals to identify those at-risk of future cognitive decline.

Abstract Skin biopsies analyzed with α-synuclein seed amplification assays (SAAs) are a simple way to clinically interrogate the presence of α-synuclein aggregates. We determined the accuracy of skin biopsy SAA in predicting the clinical diagnoses of Parkinson disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB). Blinded SAAs were performed in 3 independent laboratories. Subjects diagnosed with PD, PDD and DLB were analyzed together as group 1, clinically unaffected subjects as group 2 and those with risk factors for LBD as group 3. Punch biopsies were taken from the posterior neck and analyzed by the 3 labs in 6 separate SAAs. Pairwise agreement between labs and assays ranged from excellent (kappa 0.82) to moderate (kappa 0.40-0.68). Sensitivity across assays ranged between 50.0% and 61.3%; specificity ranged between 68.6% and 100%. Comparisons of group 1 vs group 2 produced the greatest specificities, between 77.3% and 100%. In 17 cases that subsequently came to autopsy, 93% of SAAs were positive in those at the neocortical LBD stage but in only &lt;10% of those at lower stages. Skin biopsy α-synuclein SAA may be useful as a diagnostic and progression biomarker in Lewy body dementia clinical trials.

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.

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.

AbstractBackgroundMild Cognitive Impairment (MCI) is a pre‐dementia state where impaired cognitive domains (memory, executive, visuospatial processing, language) may predict underlying pathology, e.g. Alzheimer’s disease(AD), Lewy body (LB), and other. Delineating neuropathological heterogeneity in MCI and their associations with neuropsychological profiles are important in identifying individuals at risk of further deterioration. We aimed to characterize the neuropathological heterogeneity in cases with a diagnosis of MCI.MethodCases with a final consensus cognitive diagnosis of MCI (n = 128) prior to death were selected from the Arizona Study of Aging and Neurodegenerative disorders (AZSAND). Groups were divided into amnestic (aMCI) and non‐amnestic MCI (naMCI), single and multi‐domain impairment, and specific domain impairment (executive, language, visuospatial) was explored. Presence and severity of neuropathology including AD, LB, cerebral white matter rarefaction (CWMR), cerebral amyloid angiopathy (CAA), cerebral infarcts and microinfarcts (cortical and subcortical), TAR DNA‐binding protein 43 (TDP‐43), and apolipoprotein E (ApoE) status were compared between MCI subtypes.ResultThe number of cases meeting neuropathological criteria for AD was not different between aMCI (36.4%) and naMCI (22.6%) while co‐existent PD was less frequent in aMCI (19.5% vs 38.7%). When compared to naMCI (n = 31), the aMCI (n = 85) group had an older age of death (p = 0.001), less educational years (p = 0.04), a higher number of subcortical infarcts (p = 0.012), a higher regional density of neurofibrillary tangles (p = 0.027) and a lower density of LB (p = 0.015) in the temporal lobe, and CWMR in tended to be more severe in the frontal lobe (p = 0.052). Those with single domain aMCI had less CWMR (p = 0.001) compared to the multidomain. Within the naMCI group, those with single domain MCI had higher proportions of CAA (p = 0.042), and lower LB density (p = 0.019) compared to multidomain. CWMR was more severe (p = 0.026) inConclusionA high heterogeneity was observed between MCI subtypes. While AD pathology was similar between groups, regional anatomical differences were observed. Vascular pathology including subcortical infarcts, CWMR and CAA appear to be commonly associated with both aMCI and naMCI respectively while CWMR was associated with executive dysfunctions. CWMR, CAA and LBs appear to be more frequent in multidomain aMCI and naMCI respectively.

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.