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AbstractBackgroundParkinson’s disease and dementia with Lewy bodies are characterized by abnormal iron deposition in the substantia nigra, which can be measured with quantitative susceptibility mapping (QSM) on MRI. However, neuropathologic validation of the increased QSM in the substantia nigra associated with Lewy body disease (LBD) is lacking. We compared substantia nigra QSM on antemortem MRI between patients with and without Lewy‐related pathology which was confirmed by autopsy in all cases.MethodWe studied cases with antemortem QSM who underwent autopsy from the Mayo Clinic Alzheimer’s Disease Research Center and Mayo Clinic Study of Aging (n=54). Immunohistochemistry was performed with rabbit NACP antibody against the amino acids 98‐115 of the α‐synuclein protein to detect Lewy‐related pathology. After neuropathologic evaluation, cases were classified as LBD‐present (n=13) if they had Lewy‐related pathology and LBD‐absent (n=42) if they did not have Lewy‐related pathology. Alzheimer’s disease co‐pathology was present in 9 of the LBD‐present cohort (70%). QSM was calculated for the whole substantia nigra and the two sub‐regions: pars compacta and pars reticulata. Non‐parametric Wilcoxon rank‐sum test was used to compare substantia nigra QSM values between LBD‐present and LBD‐absent cases. Area under the curve (AUC) analyses tested the accuracy of QSM to distinguish the two groups.ResultsLBD‐present group had higher QSM values in the substantia nigra than LBD‐absent group. Furthermore, sub‐regional analyses showed that the LBD‐present group had higher QSM in the substantia nigra pars compacta (p=0.008) but not in the pars reticulata than the LBD‐absent group (Figure 1). QSM of the substantia nigra pars compacta distinguished LBD‐present and LBD‐absent cases with good accuracy (AUC=0.74; p=0.006; Figure 2).ConclusionThis study provides neuropathologic insight into the relevance of QSM of substantia nigra pars compacta as an in‐vivo biomarker of autopsy‐confirmed LBD. These findings indicate that imaging evidence of abnormal iron deposition in the substantia nigra may serve as a biomarker of Lewy‐related pathology in patients with primary LBD (i.e., Parkinson disease, dementia with Lewy bodies) and patients with potential LBD co‐pathology (e.g., patients with Alzheimer disease).

AbstractBackgroundUnderstanding the relationship between AβPET and AβCSF biomarkers will define their potential utility in Aβ treatment. Few longitudinal or neuropathological comparisons have been reported. We assessed the relationship of AβPET and AβCSF biomarkers in a large community cohort.MethodParticipants 50+ years with coincident AβPET and AβCSF biomarkers (pTau181/Aβ42, n=505, and Aβ42/40, n=54) were included. Of these participants, a subgroup was identified that had neuropathology data (n=47) of which many had longitudinal AβPET and CSF testing. The relationships of AβPET and CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in those with autopsy data. Analyses were performed using AβPET Meta‐ROI and AβPET early‐Aβ‐deposition ROIs (ROIs with early Aβ deposition: fusiform, angular, inferior temporal, middle temporal, middle occipital, and calcarine).ResultIn biomarker tests performed at the same time, more participants were AβPET+ and CSF‐ than AβPET‐ and CSF+ using Meta‐ROI AβPET. This discordance occurred more frequently when using early‐Aβ‐deposition regions (Figure 1). Of 47 participants with autopsy data, 35 had Thal stage ≥1. The sensitivity for earliest detection of cortical Aβ neuropathology by AβPET was 89% (31/35) and by CSF was 66%, (23/35). Eight of these 35 had positive AβPET findings and negative coincident CSF tests at the first time tested. Of these, 5/8 were Meta‐ROI and early AβPET ROI positive. The other 3/8 were only positive on early‐Aβ AβPET ROIs. Four of the 8 with negative CSF and positive AβPET had subsequent testing and 2/4 became positive on CSF tests after 1.5 years while 2/4 continued to be negative on subsequent testing.ConclusionAβPET is more sensitive for detection of early cortical Aβ deposition than CSF biomarkers in cross‐sectional or autopsy data. While the assessment of AβPET by standard Meta‐ROI AβPET methods showed cortical Aβ deposition occurring when not indicated by CSF biomarkers, AβPET ROIs for early Aβ deposition detected additional participants that were AβPET positive and AβCSF negative. These findings have implications for detecting early Aβ neuropathology among CU participants in Aβ prevention trials when robust detection is needed. Further work is needed to compare Aβ plasma biomarkers and AβPET using these methods.

AbstractBackgroundSelective corticolimbic vulnerability to tau pathology in Alzheimer’s disease (AD) underlies clinicopathologic heterogeneity. The goal of this presentation will be to examine spatial heterogeneity of tangle distribution on a continuum through the utility of the corticolimbic index (CLix).MethodWe will discuss the development of CLix in the Florida Autopsied Multi‐Ethnic (FLAME) cohort, which sought to collapse the spatial distribution of thioflavin‐S tangle counts in AD (n=1361) to assign a continuum: hippocampal sparing with cortical predominance (<10), representative/typical (≥10 to <30), and limbic predominant with cortical sparing (≥30). The relationship with atypical, non‐amnestic clinical presentations will be described. Relevant clinical measures, including age at symptomatic onset and longitudinal decline on mini‐mental state examination (MMSE) will be examined. Digital pathology measures of AD (tau [AT8, GT‐38], amyloid‐β [6F/3D]) and glial activation (astrogliosis: GFAP, activated microglia/macrophage: CD68) will be shown in hippocampus and association cortices (n=60). To further extend these findings to the antemortem space, CLix score will be examined in an independent, autopsied neuroimaging group (n=93).ResultsLower CLix score correlated with younger age at symptomatic onset (R=0.39, p<0.001), faster MMSE decline (R=0.27, p<0.001), and associated with non‐amnestic clinical presentations (median=13 vs. 21, p<0.001). Lower CLix score correlated with greater hippocampal volume on MRI (R=‐0.45, p<0.001) and higher flortaucipir‐PET uptake (e.g., posterior cingulate‐precuneus cortex: R=‐0.74, p<0.001). Advanced tangle maturity burden (GT‐38) differed across all regions (p<0.001). Hippocampal sparing AD exhibited higher cortical tau pathology and reduced cortical activated microglia/macrophage.ConclusionsCorticolimbic tangle distribution links with AD clinical features and neuroimaging changes. Reduced activated microglia/macrophage in association cortices of relative hippocampal sparing AD may contribute to higher tau burden. Corticolimbic vulnerability should be considered for personalized therapies targeting immune dysregulation.

AbstractBackgroundImaging and plasma markers are used as key indicators of disease for Alzheimer’s disease (AD) but their usefulness in predicting regional tau pathology is relatively understudied. Our objective was to construct predictive models for regional tau pathology measured on postmortem brain tissue using multiple ante‐mortem AD biomarkers. We focused on hippocampal and parietal regions that were immunostained with AT8 and 2E9 that reflect early and advanced aspects of tangle maturity, respectively.MethodsUsing autopsy data from 63 participants enrolled in the Mayo Clinic Study of Aging (MCSA) where the last clinical visit is within three years of death, we analyzed three ante‐mortem plasma markers ‐ phosphorylated tau protein at the threonine 181 residue, glial fibrillary acidic protein, total ß‐amyloid Aß42 relative to Aß40 ratio (Quanterix Simoa HD‐X Analyzer), and three regional MRI markers computed using SPM12 ‐ parietal thickness, parietal volume relative to total intracranial volume ratio, and hippocampal volume adjusted for total intracranial volume. Based on eight separate cross‐sectional linear regression models weighted by the inverse of time from last visit to death, we estimated the multiple and partial R2 predicting post‐mortem pathology measures, including AT8 and 2E9 in both the hippocampal and parietal regions. All models were adjusted for age, sex, and cardiovascular and metabolic conditions score.ResultsThe MRI models (R2 of 0.26‐0.53) had greater predictive power compared to the plasma models (R2 of 0.17‐0.26). The best multiple R2 was 0.53 for prediction of hippocampal AT8 using antemortem hippocampal volume adjusted for total intracranial volume followed by R2 of 0.43 for prediction of hippocampal 2E9 using hippocampal volume adjusted for total intracranial volume. Though the model prediction of parietal AT8 and 2E9 measurements was low (R2 of 0.21‐0.26), parietal thickness exhibited better predictive performance than parietal volume relative to total intracranial volume ratio.ConclusionsThe data we presented here may be utilized to validate biomarkers using regional pathology. Our results support that regional MRI is sensitive to tau pathology. Newer MRI methods should be tested to examine the specificity of newer quantitative measurements to tau pathology.

Abstract INTRODUCTION The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. METHODS The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as “rarely appropriate,” “uncertain,” or “appropriate.” Ratings were performed separately for amyloid and tau PET as stand‐alone modalities. RESULTS For amyloid PET, seven scenarios were rated as appropriate, two as uncertain, and eight as rarely appropriate. For tau PET, five scenarios were rated as appropriate, six as uncertain, and six as rarely appropriate. DISCUSSION AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease. Highlights A multidisciplinary workgroup convened by the Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging updated the appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. The goal of these updated AUC is to assist clinicians in identifying clinical scenarios in which amyloid or tau PET may be useful for guiding the diagnosis and management of patients who have, or are at risk for, cognitive decline These updated AUC are intended for dementia specialists who spend a significant proportion of their clinical effort caring for patients with cognitive complaints, as well as serve as a general reference for a broader audience interested in implementation of amyloid and tau PET in clinical practice.

AbstractBackgroundAlzheimer’s disease (AD) missing heritability remains extensive despite numerous genetic risk loci identified by genome‐wide association or sequencing studies. This has been attributed, at least partially, to mechanisms not currently investigated by traditional single‐marker/gene approaches. Polygenic Risk Scores (PRS) aggregate sparse genetic information across the genome to identify individual genetic risk profiles for disease prediction and patient risk stratification. Recent advancements have pivoted on innovative approaches utilizing OMICS data to construct such risk scores.MethodWe employed a random forest algorithm to identify a list of gene candidates from bulk RNA sequencing data in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks. Subsequently, we calculated their effect size on Braak staging using regression models to construct a polytranscriptomic risk score (PTRS). We employed two distinct models: “Ethnicity‐Agnostic” Model (randomly assigning samples to training and testing samples) and “Ethnicity‐Aware” Model (assigning NHW samples to training and Hispanics to testing sample). Analysis of variance and the receiver operating characteristics area under the curve (ROC AUC) was used to evaluate PTRS’s classification performances. We validated findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095).ResultWe found a significant difference in PTRS between samples with low vs. high Braak stages (≤4 vs. ≥5, p = 1*E‐04; Figure 1 upper panel). AUC was found to be 79‐81%, consistently in both Ethnicity‐Agnostic and Ethnicity‐Aware models (Figure 1 lower panel). Finally, the PTRS in ROS/MAP yielded a similar classification performance (p = 2*E‐04, AUC = 77%).Conclusioncontrary to prior studies, we developed a PTRS with optimal transferability across ethnicities. This underscores the importance of developing novel tools to stratify and harmonize large brain repositories for AD.

AbstractBackgroundUFMylation is an understudied ubiquitin‐like post‐translational modification (PTM). Like ubiquitin, UFM1 is conjugated to substrates via a catalytic cascade involving a UFM1‐specific E1 (UBA5), E2 (UFC1), and an E3 ligase complex (UFL1, DDRGK1 and CDK5RAP3). UFMylation is reversible, and this is mediated by UFSP2. UFMylation plays essential roles in several biological processes including the DNA damage response, endoplasmic reticulum homeostasis, unfolded protein response, autophagic functions, and immune response. Importantly, UFMylation is also crucial for healthy brain development. Alzheimer’s disease (AD), a complex neurodegenerative disorder, is characterized by the accumulation of pathologic tau and beta‐amyloid proteins and has been associated with abnormalities in the aforementioned processes. Intriguingly, the potential link between AD and UFMylation has not been investigated yet. Considering that pathological tau plays a critical role in AD, and tau also plays an important role for the DNA damage response in neurons under physiological conditions, we speculated that tau itself could be modified with UFM1.MethodWe performed Western blot and Meso Scale Discovery based ELISA to measure the protein level of UFM1, UFSP2 and other UFMylation pathway components in RIPA‐soluble and insoluble fraction in human post‐mortem frontal cortex. To test whether tau can be modified by UFM1, we performed co‐immunoprecipitation (Co‐IP), Proximity Ligation Assays (PLA) and liquid chromatography‐tandem mass spectrometry (LC‐MS/MS).ResultWe found a significant reduction of soluble UFSP2, but an increase of soluble total UFM1 in AD compared to controls. We found that tau interacts with UFL1 and DDRGK1. In addition, using immunoprecipitation of denaturing lysates we found that tau can indeed be covalently modified by UFM1 when overexpressed. We detected strong signal of HA‐UFM1‐tau in neurons but not in negative controls using PLA. Furthermore, we immunoprecipitated denatured UFM1 from human autopsy brain, and detected two specific UFM1‐tau bands with tau antibodies. Together, this data strongly indicates that tau is UFMylated under endogenous conditions. Using LC‐MS/MS, we identified 17 UFMylation sites in tau proteins.ConclusionUFMylation is dysregulated in AD; tau protein can be modified by UFM1 both in vitro and in vivo, which enables a more comprehensive understanding of tau PTMs.

AbstractBackgroundIndividuals meeting neuropathological criteria for Alzheimer’s disease (AD) may manifest with atypical clinical syndromes. Past work showed that the neurobiological basis for these differences is related to specific neuronal vulnerabilities for tau pathology. For instance, amnestic cases have a higher burden of neurofibrillary changes in CA1. In contrast, logopenic variant primary progressive aphasia (lvPPA) cases have a higher tau burden in the superior temporal gyrus (STG). Single‐cell technology enables investigations on the molecular basis of differential neuronal vulnerability in AD. Consequently, we delved into the factors that underlie this selective vulnerability by analyzing brain samples from individuals exclusively afflicted with AD but exhibiting diverse clinical manifestations.MethodsnRNA Sequencing using the Chromium Single Cell 3′ (10X Genomics, USA) on nuclei cells extracted from the CA1 sector and posterior STG of postmortem brain tissue of 48 individuals either meeting pathological criteria for AD (A3B3C3; 24 amnestic and eleven lvPPA) and healthy controls (A≤1B≤1C≤1; n = 13) (Table 1, Fig. 1A/B). Bioinformatics analyses were conducted using Cell Ranger and R software. Comparisons between cell subpopulations were conducted with the Wald statistical test, and p‐values < .05 were considered significant.ResultAfter quality control, we recovered more than 250k nuclei with a mean of 2,130 genes per nuclei. Upon cross‐sample alignment and t‐stochastic neighborhood embedding clustering (Fig. 1C), we found 21 excitatory neuronal subpopulations (Exc‐sub) in CA1 and 26 in STG, and 22 and 25 inhibitory neuronal subpopulations (Inh‐sub) in CA1 and STG, respectively; 16 astrocytes subpopulations in both areas and 20 microglia subpopulations in CA1 and 17 in STG (Fig. 2). One STG Exc‐sub, expressing CUX2 and LAMP5 genes showed vulnerability in lvPPA patients. Also, one STG Inh‐sub, expressing the ADARB2 gene, showed vulnerability for all AD patients.ConclusionOur preliminary study identified a vulnerable population of excitatory neurons related to lvPPA. We are conducting validation studies using quantitative pathology to confirm these results. Furthermore, analysis of a higher number of cases is ongoing and will continue to inform on factors associated with neuronal vulnerability.

AbstractBackgroundAlzheimer’s Disease (AD) presents complex molecular heterogeneity, influenced by a variety of factors including heterogeneous phenotypic, genetic, and neuropathologic presentations. Regulation of gene expression mechanisms is a primary interest of investigations aiming to uncover the underlying disease mechanisms and progression.MethodWe generated bulk RNA‐sequencing in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks, and conducted differential gene expression and enrichment analyses. We sought to identify cross‐ancestry and ancestry‐specific differentially expressed genes (DEG) and pathways across Braak stages, adjusting for sex, age at death, and RNA quality metrics. We validated our findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095). Lastly, we validated top DEG using publically‐available human single‐nucleus RNA sequencing (snRNAseq) data.ResultAD‐known genes VGF (LFC = ‐0.661, padj = 3.78) and ADAMTS2 (padj = 1.21) were consistently differentially expressed across statistical models, ethnic groups, and replicated in ROS/MAP (Figure 1). Genes from the heat shock protein (HSP) family, e.g. HSPB7 (padj = 3.78), were the top DEG, also replicated in ROS/MAP. Ethnic‐stratified analyses prioritized TNFSF14 and SPOCD1 as top DEG in Hispanic samples. Gene set enrichment analysis highlighted several significantly pathways, including “TYROBP causal network in microglia” (WP3945; padj = 1.68) and “Alzheimer Disease” (WP5124; padj = 4.24). snRNAseq validated several DEG, including VGF downregulated in neurons (padj = 1.1).ConclusionTo our knowledge, this is the largest diverse transcriptome study for AD in post‐mortem tissue. We identified perturbated genes and pathways resulting in cross‐ethnic and ethnic‐specific findings, ultimately highlighting the importance of diversity in AD investigations.

AbstractBackgroundWe recently developed a novel tau‐PET summary measure THETA, capturing regional heterogeneity and identifying tau status, using ground truth visual assessments from a large single‐center cross‐sectional dataset and validated on independent cohorts [1, 2]. In this study, we aimed to evaluate the performance of THETA on longitudinal and histopathology data.MethodWe included longitudinal tau‐PET ([18F]flortaucipir) data from 696 Mayo Clinic Study of Aging (MCSA) and ADRC participants, with histopathology in n = 90. Fig. 1 shows the model that uses regional standard uptake value ratios (SUVR) and a target of binary class of tau positivity for prediction of THETA. This model was applied to predict tau status on each followup scan. Slopes of the meta‐ROIs’ tau SUVRs and THETA were evaluated by diagnostic group and as a function of baseline amyloid SUVR in discordant CU participants (where meta‐ROI and visual assessments did not match at baseline) and in incident‐THETA+ CU participants (whose THETA moved from below to above 1 over serial tau‐PET scans). We evaluated tau measurements as a function of Braak stages for neurofibrillary tangles.ResultLongitudinal plots of meta‐ROIs for diagnostic groups were very similar, but the expanded range of THETA based on visual positivity prediction clearly identified tau positive or tau‐negative scans. In discordant‐CU (n = 97) and incident‐THETA+ CU participants (n = 14 all amyloid positive at follow‐up but only 65% at baseline), the relationship between baseline amyloid and rate of tau increase was stronger for THETA than temporal meta‐ROI (Fig. 2). Separation between baseline and follow‐up was greater for THETA (t‐statistics = 90) compared to temporal meta‐ROI (t‐statistics = 20) (p<0.01) in the incident‐THETA+ CU participants. THETA showed a slightly stronger association with Braak stage than meta‐ROIs (rho = 0.87 vs. ≤0.83, p<0.05), with better separation of clinical diagnoses (Fig. 3).ConclusionTHETA remained clearly negative or positive in MCI and AD, providing consistent information on underlying etiology of impairment at both baseline and follow‐up. Although binary in its construction, THETA both provided separation of values based on tau status and its change correlated with baseline amyloid burden especially in discordant‐CU where tau deposition is not in typical meta‐ROIs. Further work is needed to confirm if THETA captures early tau changes.