Murray, Melissa E.

AbstractBackgroundApproximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer’s Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns.MethodCognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume.ResultScree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration.

AbstractBackgroundThere is a gap in knowledge concerning which tangle maturity levels (Moloney, Alzheimers Dement, 2021) are associated with antemortem measures (tau‐PET, MRI, cognitive testing). We hypothesized antemortem measures would be more strongly correlated with markers recognizing middling to advanced tangle maturity. We additionally sought to assess the strength of the relationship with tangle and neuritic pathology recognized by tangle maturity markers.MethodPosterior hippocampi from n = 30 cases with antemortem measures ≤3 years prior to death were cut (5µm) and immunostained with tau antibodies to evaluate early (AT8), middling (PHF‐1), or advanced (2E9) tangle maturity. GENIE (pattern recognition software) separated tangle from neuritic burden (Figure). Hippocampus, parahippocampus, and fusiform were analyzed to correlate digital pathology with flortaucipir tau‐PET standard uptake value ratio (SUVr, cerebellar crus normalization), MRI volume/thickness, and cognitive measures which included Auditory Verbal Learning Test (AVLT) delayed recall, Mini‐Mental State Exam (MMSE), and Clinical Dementia Rating (CDR).ResultThe strongest relationships observed with flortaucipir were with PHF‐1 and 2E9 burden (Table). AT8 tangle and neuritic burden correlations with flortaucipir were relatively similar in the hippocampus but were stronger with neuritic pathology in parahippocampus and fusiform. PHF‐1 tangle and neuritic burden correlations were relatively similar with flortaucipir. 2E9 correlations were stronger with neuritic pathology in hippocampus. MRI measures were more strongly correlated with PHF‐1 and 2E9 burden. AT8 tangle and neuritic burden were correlated with fusiform thickness. The correlations between MRI measures and 2E9 tangle and neuritic burden were similar. Correlations between cognitive measures were similar between tangle maturity markers. AVLT delayed recall correlated with all tangle maturity markers, but neuritic burden was stronger for AT8 and 2E9 in hippocampus compared to tangle burden. MMSE correlated with neuritic burden for all tangle maturity markers. CDR remained statistically non‐significant.ConclusionInterpretation of the strength of the relationship between tau burden and antemortem measures differed across tangle maturity markers. Neuroimaging measures may be more sensitive to middle/advanced maturity markers with limited differences between tangle and neuritic pathology. These findings may be biologically relevant and imply either a limited recognition of tangles depending on antibody epitope, and/or may represent the clinicoradiologic impact of increasing neuritic burden.

AbstractBackgroundPlasma biomarkers for Alzheimer’s disease (AD) such as phosphorylated tau protein 181 (p‐tau 181), neurofilament light chain (NfL), amyloid‐β 42/40 ratio (Aβ42/40), and glial fibrillary acidic protein (GFAP) have shown high performance in the discrimination of those with clinical mild cognitive impairment (MCI) or dementia from cognitively unimpaired individuals, but few population‐based autopsy studies have evaluated the neuropathological correlates of plasma biomarkers.MethodWe utilized a population‐based prospective study of 350 participants with autopsy and antemortem plasma biomarker data. Plasma biomarkers Aβ42/40 ratio, p‐tau181, GFAP, and NfL were measured using Quanterix Simoa assays. We predicted AD neuropathological change (ADNC), Braak staging, and neuritic plaque score using these plasma biomarkers and investigated the added utility of cognitive and demographic information. We utilized a variable selection procedure in cross‐validated (CV) logistic regression models by minimizing the Bayesian Information Criterion to identify the best set of predictors for a given outcome among plasma biomarkers, demographic variables, and neuropsychological tests included in the Mayo Clinic Preclinical Alzheimer Cognitive Composite (Mayo‐PACC).ResultADNC was best predicted with plasma GFAP, NfL, p‐tau181 biomarkers along with APOE ε4 carrier status and Mayo‐PACC cognitive score (CV AUC = 0.821). Braak staging was best predicted using plasma GFAP, p‐tau181, and cognitive scores (CV AUC = 0.788). Neuritic plaque score was best predicted using plasma Aβ42/40 ratio, p‐tau181, GFAP, and NfL biomarkers (CV AUC = 0.778). Inclusion of plasma biomarkers demonstrated significantly better prediction of Braak staging (p<0.01) and neuritic plaque score (p<0.01), but not ADNC (p = 0.13), when compared to models that included only cognitive and demographic information. Univariate models consistently underperformed in comparison to multivariate models.ConclusionPlasma biomarkers can provide valuable predictive information about the presence of AD pathology, which can facilitate earlier recognition and diagnosis of AD. Incorporation of demographic and cognitive variables along with plasma variables in multivariable models will improve prediction accuracy of AD pathology, specifically Braak staging and ADNC.

AbstractBackgroundThe Alzheimer’s Association and Society for Nuclear Medicine and Molecular Imaging convened a Workgroup to update previous Appropriate Use Criteria (AUC) for amyloid PET (Johnson 2013) and develop the first AUC for tau PET. The AUC represent general guidelines and should not be considered a substitute for clinical judgment exercised in the care of individual patients.MethodThe Workgroup included 14 researchers with multidisciplinary expertise. Meetings were held between June 2020 and August 2021. Key research questions were identified using the PICOTS framework, triggering an independent systematic literature review. Using established methods (Fitch 2001), the Workgroup identified 17 clinical scenarios in which amyloid/tau PET may be considered. Appropriateness of amyloid and tau PET as independent, stand‐alone modalities were ranked for each scenario using a 9‐point scale (Table 1). Consensus was achieved using a modified Delphi process. Online surveys were completed iteratively by Workgroup members, followed by discussion, until all votes for each scenario fell within one of the following categories: Appropriate/Uncertain/Rarely Appropriate.ResultAs an over‐arching principle, amyloid/tau PET should be considered in patients who: (1) have undergone a comprehensive assessment by a dementia expert; (2) Alzheimer’s disease (AD) is a diagnostic possibility but uncertainty remains; and (3) knowledge of amyloid/tau PET results is expected to help establish diagnosis and guide patient management. Consensus ratings for clinical scenarios are shown in Table 2. More evidence was available to inform recommendations for amyloid than tau PET. Amyloid PET was considered “Appropriate” to inform diagnosis of MCI or dementia due to suspected AD; clarify diagnosis when CSF biomarkers are equivocal; to inform prognosis in MCI; and to determine eligibility for amyloid‐targeting therapies. Tau PET was considered “Appropriate” to clarify diagnosis in patients with MCI/dementia under age 65 or those with atypical presentations; and to inform prognosis in MCI or dementia due to suspected AD.ConclusionThe updated AUC highlight a growing role for amyloid PET and an emerging role for tau PET in the clinical evaluation of cognitively impaired patients. AUC are expected to further evolve based on data from ongoing studies of clinical utility and a rapidly developing therapeutic landscape.

AbstractBackgroundIndividuals with 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. Therefore, we investigated factors underlying selective vulnerability using brain samples from individuals with pure AD with different 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 24 individuals either meeting pathological criteria for AD (A3B3C3; 12 amnestic and eight lvPPA) and healthy controls (A≤1B≤1C≤1; n = 4) (Table 1, Fig. 1A/B). Bioinformatics analyses were conducted using Cell Ranger and R software. Comparisons between cell subpopulations were conducted with Wald statistical test, and p‐values < .05 were considered significant.ResultAfter quality control, we recovered 98,180 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 27 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. Furthermore, two astrocytes subpopulations (one in both areas and one in STG) and three STG microglia subpopulations showed proportional composition changes comparing AD patients and HC.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.

AbstractBackgroundPSEN1 mutations are the most common genetic cause for autosomal dominant forms of Alzheimer’s disease patients with an age at onset below 65 years (ADAD). Even though all PSEN1 mutations lead to an increased Aβ processing and production, there is a large variability in phenotypic presentation even in individuals with the same mutation. Splicing isoforms in AD genes are reported to be associated with the disease, however little is known about correlation between splicing pattern and phenotypic presentation (e.g. variable age onset). We hypothesized that cellular and transcriptomic alterations differ amongst patients with different phenotypic presentation. In a group of 8 ADAD with the same PSEN1 p.G206A mutation, we investigate the association between brain cell type proportion, gene expression, and splicing isoforms with age at onset, Aβ plaque type and severity of AD neuropathologic change.MethodsEight Hispanic ADAD cases with PSEN1 p.G206A mutation were identified in the Mayo Clinic brain bank housed in Jacksonville, FL. Standard (immuno)histochemical stains, including H&E and thioflavin S, were performed to evaluate AD neuropathologic change. We focused on distinct Aβ plaque types in an association cortex (inferior parietal gyrus) and primary cortex (motor). We carried‐out single‐nuclei short and long read RNA sequencing on both brain regions. We will stratify our transcriptomic analyses based on neuropathology and phenotypic presentation.ResultsWe observed large variability in age at onset (median = 53 years; range: 42‐59 years). Furthermore, disease duration was reportedly variable (median = 10 years; range: 8‐17). All cases had a Braak tangle stage VI and Thal amyloid phase 5. Only 3 patients carried at least one APOE*ε4 risk allele, suggesting that its effect was minimal on ages at onset and death. Different plaque types were observed for short versus long survivors. In short survivors, plaques were predominantly fibrillar with an eosinophilic radial component, whereas in longer survivors predominantly cored plaques were observed.ConclusionLarge phenotypic variability within patients with the same mutation is observed suggesting the involvement of yet to be discovered genetic modifiers. Understanding cellular transcriptomic events in ADAD is essential to future development of therapeutic approaches and development of biomarkers.

AbstractBackgroundTau aggregation is the underlying cause of several neurodegenerative tauopathies. Formation of tau aggregates with seeding activity involves interactions with other proteins, but with unknown effects on tau‐seed properties. Our previous study found that Bassoon (BSN), a presynaptic protein, interacts with tau‐seed, exacerbating its toxicity in vivo. Bsn downregulation reduced tau spreading and overall pathology. A previous study also linked missense mutations in BSN to the aggregation of 3‐ and 4‐repeat tau in patients. However, it is unknown how genetic mutations in BSN influence tau pathology in vivo.MethodWe developed a knock‐in mouse model harboring a mutation in endogenous BSN (p.Pro3882Ala), equivalent to p.Pro3866Ala BSN mutation identified in patients. We evaluated the cognitive and motor abilities of aged heterozygous and homozygous BSNKI mice and also we analyzed BSN and tau patterns in the brains of these mice. Additionally, we examined BSN and tau patterns in the BSN mutation carrier.ResultAt 10 months, BSNKI mice did not exhibit anxiety‐related behavior and had similar activity as WT littermates. They also displayed similar cognitive abilities as the WT mice. Interestingly, the BSNKI mice displayed lower latency to fall off the rotarod and reduced grip strength compared to the WT mice. We also observed an increase in the accumulation of pathological tau and BSN deposits in the brains of the BSNKI mice. The BSN mutation carrier displayed inclusions of BSN and tau pathology.ConclusionWe developed a mouse model with a knock‐in mutation in the Bassoon gene, allowing us to evaluate the effects of this disease‐associated mutation in vivo. Our results have shown that the mice with Bsn mutation have impairments in motor coordination, and postural instability, similar to BSN mutation carriers and show pathological tau and BSN deposits in the brain. We found inclusions of BSN and tau pathology in BSN mutation the carrier that resembled certain pathological features of AD and PSP. These findings suggest that BSN plays a role in tau pathology and targeting it may represent a promising therapeutic strategy for tauopathies. Further research is needed to fully understand our findings' underlying mechanisms and potential therapeutic implications.

AbstractBackgroundInter‐cellular communication within the gliovascular unit (GVU) is critical for cerebral blood flow regulation, and maintenance of the blood‐brain‐barrier (BBB) properties. The breakdown of BBB in Alzheimer’s disease (AD) is well‐established, but precise underlying molecular changes remain unclear. Additionally, whether GVU molecular alterations observed in AD brains are also detected in blood from living patients is unknown. Further, these GVU molecular perturbations require further investigation in different model systems to identify both human brain‐specific and cross‐species conserved alterations. In this study, we investigated prioritized GVU molecules altered in AD brains for their conservation in blood and cross‐species model systems.MethodsWe performed single nucleus RNA sequencing (snRNAseq) of temporal cortex tissue in AD and control brains. We analyzed this data to detect cell‐specific GVU molecular perturbations and their interactions. We investigated molecular interactions between vascular and astrocyte clusters, the major cell types of the GVU of the BBB. To determine whether GVU transcriptional alterations detected in the brain are preserved in the blood, existing blood expression, genetic, and neuroimaging data from two longitudinal antemortem cohorts were analyzed. Using model systems, including mouse, drosophila, and zebrafish, we evaluated the cross‐species conservation of the top GVU alterations detected in AD brains.ResultsBrain snRNAseq revealed transcriptional profiles of 6,541 astrocytes and 2,210 vascular cells. The latter formed three distinct vascular clusters characterized as pericytes, endothelia and perivascular fibroblasts. We identified differentially expressed genes and their enriched pathways within these clusters and observed the highest levels of transcriptional changes within pericytes. Vascular targets that interact with astrocytic ligands have biological functions in cell signaling, angiogenesis, amyloid ß metabolism, and cytoskeletal architecture. We discovered that genetic variants influencing blood expression levels of some of the prioritized GVU genes were associated with neuroimaging burden of cerebrovascular disease in living human cohorts. Our ongoing studies in model systems revealed conservation of some of the top prioritized molecular perturbations across species.ConclusionOur findings prioritized by multiscale, cross‐tissue human data revealed GVU perturbations within interacting pericyte and astrocyte molecules, which are conserved across multiple cross‐species models. These results nominate new molecular targets and mechanistic insights for BBB disruptions in AD.

AbstractBackgroundGlial activation plays a critical role in Alzheimer’s disease (AD) pathogenesis and is associated with amyloid‐β plaques and neurofibrillary tangles composed of phosphorylated tau (phospho‐tau). With approximately 40%‐60% of AD cases having limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), TDP‐43 pathology has become more the rule than the exception in AD brains. However, the effect of LATE‐NC in AD‐related glial activation is unknown.MethodWe analyzed the effect of TDP‐43 pathology on glial activation in three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Twenty cases of each subtype (n = 60 total) were selected from the FLorida Autopsied Multi‐Ethnic (FLAME) cohort. Cases were immunohistochemically evaluated on serial sections of the hippocampus in the CA1 and subiculum subsectors, and superior temporal, inferior parietal, and mid‐frontal cortices with antibodies to CD68 (phagocytosis), GFAP (astrogliosis), GT‐38 (conformation‐specific AD‐type tau), 6F/3D (amyloid‐β), and phospho‐Serine 409/410 of TDP‐43 (pTDP‐43). Digital pathology was employed to quantify immunohistochemical staining. Multivariable regression modeling was utilized to understand the relationship between glial activation and AD pathologies.ResultThe level of glial activation, defined as % of immunoreactive surface area for CD68 and GFAP, was lowest in HpSp AD (0.54%, 13%), whereas typical AD (1.3%, 33%) and limbic predominant AD (1.3%, 30%) had similar levels suggesting a ceiling effect, or plateau, of gliosis levels (both p<0.001). HpSp AD was more often male (p<0.001) and younger at disease onset (p<0.001) compared to both typical AD and limbic predominant AD. Multivariable regression modeling of CD68 (subiculum R2 = 0.60) identified advanced tau to be a significant predictor of CD68 in all brain regions. LATE‐NC stage predicted increased CD68 levels in limbic brain regions. Multivariable regression modeling of GFAP (CA1 R2 = 0.60) showed that Aβ was the strongest predictor of astrogliosis in CA1 and subiculum (p<0.001). Advanced tau in CA1 and parietal cortex, LATE‐NC in subiculum and temporal cortex, and APOE4 genotype in CA1 predicted a significant increase in GFAP.ConclusionThese findings highlight the significant role TDP‐43 pathology plays in affecting the microenvironment and interplay between neuroinflammation and neurodegeneration and have important implications for therapeutic strategies in AD with co‐morbid LATE‐NC.

AbstractBackgroundTau proteins aggregate into spatially and morphologically distinct lesions in primary and secondary tauopathies. These signature lesions result from deposition of tau proteins that are distinctly modified via missense mutation and/or post‐translational modification for each disease strain. Identifying the unique tau protein abnormalities that lead to specific neurodegenerative diseases is beneficial in their early diagnosis and treatment. This is especially true for Progressive Supranuclear Palsy a primary tauopathy with clinical symptoms mirroring Parkinsonian syndromes and frontotemporal dementias.MethodBiochemical analysis of tau aggregates from patients with a pathological diagnosis of Progressive Supranuclear Palsy (n = 60) demonstrate that the tau protein modifications observed in this disease result from tau that is specifically modified and thereby forms the basis of the distinct disease strains observed. Here data collected using the sarkosyl‐insoluble tau fractions from tissue samples of pathologically diagnosed patients with Progressive Supranuclear Palsy without comorbidities allows for the direct observation of the modifications. Most interesting is the variability of the tau proteins that actually accumulate for this disease opening up the possibility that tau strains may exist within any given tauopathy even as the clinical manifestations appear similar. This indicates that early and specific identification and detection of these strains is critical for the development of therapies for these diseases.ResultExtraction and examination of sarkosyl‐insoluble tau proteins from deceased patients pathologically diagnosed with Progressive Supranuclear Palsy indicate that multiple tau strains exist within this primary tauopathy. Western blotting of these extracts from patient tissues demonstrates a unique banding pattern of insoluble tau in a subset of the cases that exhibit extreme hyperphosphorylation as indicated by additional high molecular weight tau banding. These patients also had an earlier age of onset and age of death indicating a more aggressive disease strain. Additional data is presented comparing the structure and seeding capability of this insoluble tau and the distribution and burden of insoluble tau in these Progressive Supranuclear Palsy patients compared to those with typical onset and insoluble tau signature.ConclusionMultiple pathological tau strains exist in Progressive Supranuclear Palsy.