Dickson, Dennis W.

AbstractBackgroundPerturbations in immune pathways are strongly associated with Alzheimer’s disease. A positive association between autoimmune diseases and frontotemporal dementia has been reported. We explored whether early onset Alzheimer’s disease (EOAD) would associate with autoimmune diseases.MethodWe compared 313 patients with EOAD from the Mayo Clinic Florida, Alzheimer’s Disease Research Center (ADRC) Registry with matched cognitively normal controls (NC) based on age (+/‐ 2 years) and gender at 1:2 ratio. NC were derived from Mayo Clinic Biobank Project, Rochester (N = 313) and the Mayo Clinic Study of Aging (N = 313). Data abstraction was performed by trained statisticians using ICD 9&10 codes corresponding to 40 specified autoimmune diseases and/or documentation of specified immunomodulatory treatment. Data was also abstracted via retrospective record review. We further reviewed clinical records from EOAD patients with neuropathologically confirmed Alzheimer’s disease patients enrolled in the ADRC (n = 10). Each autoimmune disease type was compared between cases and controls using Fisher’s exact test. All tests were two‐sided with alpha level set at 0.05 for statistical significance. Continuous variables were summarized as median (range) while categorical variables were reported as frequency (percentage). The prevalence of autoimmune disease in the general population was based off Hayter & Cook, 2012 and Roberts & Erdei, 2020. All data abstraction was done blinded to the clinical diagnosis and baseline demographics.ResultAutoimmune disease history was abstracted from 949 patient records (313 EOAD, 10 pathologically‐confirmed EOAD, 626 NCI). The median age was 57 years‐old. (EOAD range 28,65 yrs.; NC 30,66 yrs.). Autoimmune thyroiditis (p = 0.0008), ulcerative colitis (p = 0.011, psoriasis (<0.0001), rheumatoid arthritis (p = 0.0005), and Raynaud’s syndrome (p = 0.0021) were less prevalent in patients with EOAD compared to NC. Furthermore, patients with EOAD had a lower prevalence of immune mediated hematologic disorders.ConclusionPatients with EOAD have a lower prevalence of autoimmune diseases than NC. Immune activation identified in early onset AD patients may be unrelated to autoimmunity. Findings should be explored in late onset AD patients.

AbstractBackgroundThere is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behavior/personality. This is due to a lack of knowledge about the macro‐scale anatomy underlying these symptomatologies, a partial overlap in clinical features, and the fact that a single underlying pathology can give rise to both phenotypes and vice‐versa.MethodWe included data from patients with genetic, biomarker, and/or autopsy evidence for fronto‐temporal lobar degeneration (FTLD) diagnosed with behavioral variant fronto‐temporal dementia (bvFTD, n = 30) and patients with biomarker and/or autopsy evidence for Alzheimer’s disease (AD) pathology diagnosed with either an initial and predominant dysexecutive (dAD, n = 52), behavioral (bvAD, n = 7), or amnestic (aAD, n = 28) syndrome. We assessed group‐wise differences in clinical/cognitive features and 18Fluorodeoxyglucose‐positron emission tomography (FDG‐PET) patterns. This was followed by a spectral covariance decomposition between FDG‐PET images to yield latent patterns of relative metabolism (“eigenbrains”). These eigenbrains were subsequently linked to clinical/cognitive data and meta‐analytic topics reflecting a wide range of mental abilities. We used a linear discriminant analysis (LDA) to perform eigenbrain‐based diagnostic predictions.ResultdAD and bvFTD patients were the youngest at symptom onset, followed by bvAD, then aAD. dAD patients had worse cognitive performance on nearly all cognitive domains compared to other groups. Hypometabolism was observed across associative cortices in dAD, temporo‐parietal areas in aAD, and fronto‐temporal areas in bvFTD and bvAD (Fig. 1). The spectral covariance decomposition yielded nine eigenbrains which explained 61% of the variance in patterns of FDG‐PET, and only the first three are presented (Fig. 2). These eigenbrains revealed that relative hypometabolism in association cortices, notably lateral parietal areas, associated with dysexecutive symptomatology and a lower likelihood of behavior/personality problems, whereas relative hypometabolism restricted to frontal and temporopolar areas showed opposite associations. The LDA yielded an accuracy of 82.1% in predicting diagnostic category (Fig. 3).ConclusionThis study suggests distinct macro‐scale underpinnings underlying predominant dysexecutive versus behavioral symptomatology in degenerative dementia phenotypes. This has implication for the implementation of clinical and research criteria for these dementia syndromes and highlights the importance of data‐driven techniques to inform the classification of degenerative diseases.

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.

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.

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the accumulation of neurofibrillary tangles (NFTs), comprised primarily of microtubule‐associated protein tau. NFTs are defining hallmarks of AD and its accumulation into pathological oligomers and fibrils has been associated with cognitive decline in AD and other tauopathies. Despite its pivotal role in the disease process, we still have a poor understanding of how their formation, toxicity, and spread across brain regions is regulated via tau‐associated proteins that regulate the oligomerization, pathological accumulation, and seeding of tau in affected cell types and vulnerable brain regions.MethodWe have established two proximity‐dependent biotin‐identification (BioID) models as novel approaches to identify the composition and proximal molecular environment of tau aggregates. Using an in vitro and ex vivo model approach coupled with mass spectrometry, we have identified proteins that were primarily associated with mutant tau aggregates vs. soluble wildtype tau and stratified them based on significance, molecular pathway and druggability. Immunoblotting and immunofluorescence were performed to assess the interaction of endogenous and overexpressed top candidates with tau, along with visualization with NFTs in the context of human AD pathology to assess their impact on tau‐aggregate formation and toxicity.ResultTo determine the physiological and aggregate specific interacting partners of tau, we are comparing wild type tau (TauWT) with mutant tau (Tau3xMUT) carrying three tauopathy‐associated mutations (A152T/P301L/S320F). The proteomic analysis from our combined proteomic datasets revealed that significantly changed proteins included candidates involved in RNA processing, as well as protein ubiquitination and proteasome degradation. We have begun validating proteins that are enriched in mutant tau in human tissue of AD, as well as primary tauopathies, that may be druggable targets for tauopathies.ConclusionThis study provides novel insights into cellular pathways and molecular mechanisms of neurodegeneration, by identifying in the context of living neurons and brain tissue different functional classes of tau‐associated proteins with relevance for AD pathophysiology. These are expected to include proteins that may mediate the toxic effect of NFTs, facilitate the formation or degradation of pathological tau aggregates, and catalyze posttranslational modifications of tau oligomers and associated proteins.

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.

AbstractBackgroundAlthough we have greatly increased our ability to identify the presence of neurodegenerative pathology during life, additional techniques and targets are still needed to increase diagnostic specificity. Recently, it has become evident that the neuroinflammatory response might be tailored towards distinct diseases resulting in disease specific “neuroinflammatory signatures”. Therefore, a detailed comparison of neuroinflammatory molecules present among distinct neurodegenerative diseases could provide novel information of disease specific therapeutic targets or differential biomarkers.MethodTo better examine potential neuroinflammatory signatures, a 71 immune‐related protein multiplex ELISA panel was utilized to analyze anterior cingulate grey matter from 127 individuals neuropathologically diagnosed with Alzheimer’s disease (AD), but chronic traumatic encephalopathy (CTE), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and argyrophilic grain disease (AGD). A partial least square regression analysis was used for unbiased clustering and identifying proteins that were distinctly correlated with each disease correcting for age and gender. Receiver operator characteristic and binary logistic regression analyses were then used to examine the ability of each candidate protein to distinguish diseases. Validation in postmortem cerebrospinal fluid (CSF) from 15 AD and 14 CTE cases was performed to determine if candidate proteins could act as possible biomarkers. Finally, histology was performed using candidate proteins to visualize cell type expression for better understanding of potential mechanistic pathways.ResultFive clusters of neuroimmune proteins were identified and compared to determine if clusters were specific to distinct disease. Each cluster was found to correlate with either CTE, AD, PSP, CBD, or AGD. When examining which proteins were the strongest driver of each cluster, it was observed the most distinctive protein for CTE was CCL21, AD was FLT3L, and PSP was IL13. Individual proteins that were specific to CBD and AGD were not observed. CCL21 was observed to be elevated in CTE CSF compared to AD, further validating the use as possible biomarkers.ConclusionOverall, these results highlight that different neuroinflammatory responses might underlie unique mechanisms in related neurodegenerative pathologies. Additionally, the use of distinct neuroinflammatory signatures could help differentiate between neuropathologies and act as novel biomarker candidate to increase specificity for in‐life diagnoses.

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.

AbstractBackgroundLewy body dementia (LBD) is one of the most common causes of dementia and is characterized by the deposition of extracellular amyloid plaques and intracellular accumulation of alpha‐synuclein in the form of Lewy bodies and neurites. Many of these individuals also have concomitant neuropathological changes such as vascular disease, tangles, and TDP‐43. Like in Alzheimer’s disease, APOE4 is the most significant genetic risk factor for the development of LBD. We sought to survey the landscape of transcriptional changes in the cingulate cortex from a large cohort of LBD cases (>400) compared to normal controls of both sexes.MethodWe performed bulk tissue RNAseq and aligned reads to a human reference genome that is informed on the sex chromosome complement of the sample. Differentially expressed genes were determined after genome‐wide correction.ResultWe found a core set of transcriptional changes that were shared between both sexes in pathways related to neuronal functions and inflammation. However, we also identified numerous changes in genetic female samples that were not significantly altered in genetic males, or that were significantly altered but in the opposite direction. Similar male‐specific changes were also found. These alterations were present for genes on both sex chromosomes as well as autosomes. Though cohort sizes were smaller, we also compared this dataset to Alzheimer’s disease and found shared but unique transcriptional alterations.ConclusionOverall, genetic males and females exhibit sex‐shared and sex‐specific gene expression patterns in dementia with Lewy bodies. We are currently assessing splice alterations, running causal gene network analysis, and performing histological validation.