Citations

AbstractBackgroundPreviously, we found that female sex is associated with greater pathology burden in early‐onset Alzheimer’s disease (EOAD) in the Longitudinal EOAD Study (LEADS). Here, we have expanded our analyses by adding APOE‐ε4 carrier status as a further predictor of EOAD pathologic burden.MethodWe included 180 EOAD LEADS participants with available APOE genotype, Flortaucipir PET, Florbetaben PET, and MRI data. Demographic and biomarker differences were analyzed using ANOVA. EOAD participants were split by sex and APOE‐ε4 carrier status. Box plots were created in R and a voxel‐wise multiple linear regression in SPM12 yielded statistical brain maps of gray matter density (GMD), amyloid and tau burden.ResultCompared to males, EOAD females showed significantly greater global amyloid uptake (mean SUVR, p=0.002) and greater tau SUVR in the MetaROI, Braak 3&4 and 5&6 regions (p=0.0007, p=0.001, p=0.01, resp., Table 1). Female APOE‐ε4 carriers showed greater tau SUVR in Braak regions 1&2 than female non‐carriers (p<0.01, Figure 2B). Male APOE‐ε4 carriers showed trend‐level thinner entorhinal cortex than male non‐carriers (p=0.06, Figure 1). Interestingly however, femaleAPOE‐ε4 non‐carriers showed greater global amyloid SUVR than female carriers (p<0.01, Figure 2A). Further, APOE‐ε4 non‐carriers showed significantly thinner medial temporal cortices than carriers in both sexes (M, p<0.05; F, p<0.01). Male APOE‐ε4 non‐carriers also showed significantly lower mean cortical thickness than male carriers (p<0.05, Figure 1). Female APOE‐ε4 non‐carriers showed trend‐level lower mean cortical thickness than female carriers (p=0.06, Figure 1). The FWE corrected SPM12 maps showed significantly greater GM atrophy in the right temporal lobe and greater amyloid burden in a right lateralized occipitoparietal pattern in female APOE‐ε4 non‐carriers compared to female carriers. Further, male APOE‐ε4 non‐carriers showed greater tau uptake in the left frontal lobe than male carriers (Figure 3).ConclusionThese results suggest that APOE‐ε4 non‐carrier status is associated with greater atrophy, amyloid and tau deposition in EOAD. This might be due to the presence of other strong genetic drivers of disease pathology in EOAD.

AbstractBackgroundThe coarse‐grained plaque (CGP) is a divergent plaque‐type recently described in Alzheimer’s disease (AD)1. In the current study, we studied the CGPs distribution over the brain, and its association with APOE, p‐tau, and neuroinflammation.MethodThe cohort (N = 60) was selected from the Mayo Clinic brain bank in Jacksonville, USA. Brain tissue from the frontal ‐, parietal ‐, temporal cortex, and the hippocampus was immunohistochemically stained for Aβ (6F/3D), p‐tau (AT8), CD68, and GFAP. The CGP and classic cored plaque (CCP) were scored as previously described1. Total plaque burden was expressed as the sum of all cortical regions.ResultThe CGP was predominantly located in the neocortex and present in ∼60% of AD cases, who were younger at onset (p<0.05) and had a lower brain weight (p<0.05) than CGP negative cases. When stratified for APOE Ɛ4+ and Ɛ4‐, CGP burden was only in Ɛ4+ positively correlated with p‐tau, Aβ, and GFAP burden in the frontal and parietal cortex (Table 1). CGP burden was not correlated with CD68. The CCP was negatively correlated with p‐tau, and not with GFAP, Aβ or CD68 (Table 1). In APOE Ɛ4+ cases, the burden of CGPs was negatively correlated with the burden of CCPs (Fig.1).ConclusionThe neocortical CGP is correlated with increased p‐tau burden and astrogliosis in APOE Ɛ4+. The CGP is inversely correlated with the common CCP, suggesting an opposite effect of Aβ‐induced tau‐toxicity for the CGP versus the CCP. 1Boon et al., Acta Neuropathologica, 2020

AbstractBackgroundWe recently discovered a novel tau binding partner, SERPINA5, to be upregulated in Alzheimer’s disease (AD) and co‐localize with corticolimbic tau distribution. As tau pathology is also observed in primary tauopathies, we hypothesized that SERPINA5 burden would mirror tau burden in these diseases. Thus, we sought to define the relationship between SERPINA5 and tau in primary tauopathies and compare this relationship to AD.MethodImmunohistochemistry was performed on the hippocampus or cingulate in 4 groups (n=6 per disease group): 1) AD, 2) 3R+4R primary age‐related tauopathy, 3) 4R tauopathies (progressive supranuclear palsy, corticobasal degeneration, argyrophilic grains disease), and 4) 3R tauopathy (Pick’s disease). Burden analyses for SERPINA5 and a phospho‐tau marker (AT8) were performed on digitized whole slide images.ResultVisual interpretation of SERPINA5 immunostaining identified both neuronal and glial inclusions that are commonly AT8‐positive in primary tauopathies. There were exceptions to this pattern such as SERPINA5‐positive Pick bodies being rarely observed. However, some pathologic structures, like ballooned neurons, were preferentially stained by SERPINA5. Quantitative analyses confirmed this observation with AT8 and SERPINA5 burden correlating in both the cingulate (R2=0.47, p<0.0001, Figure 1a) and hippocampus (R2=0.74, p<0.0001, Figure 1d). Nonparametric rank sum tests revealed majority of the primary tauopathies had less AT8 and SERPINA5 burden compared to AD in both the cingulate and hippocampus (Figure1b‐c, e‐f; Table 1).ConclusionSERPINA5 immunostaining patterns in primary tauopathies reflect tau immunostaining patterns. Our data suggests the SERPINA5‐tau interaction may not be specific for AD, which may implicate the role of SERPINA5 more broadly across tauopathies.

Abstract Introduction Alzheimer's disease (AD) biomarkers are increasingly more reliable in predicting neuropathology. To facilitate interpretation of phosphorylated tau sites as an early fluid biomarker, we sought to characterize which neurofibrillary tangle maturity levels (pretangle, intermediary 1, mature tangle, intermediary 2, and ghost tangle) are recognized. Methods We queried the Florida Autopsied Multi‐Ethnic (FLAME) cohort for cases ranging from Braak stages I through VI, excluding non‐AD neuropathologies and tauopathies. Thioflavin‐S staining was compared to immunohistochemical measures of phosphorylated threonine (pT) 181, pT205, pT217, and pT231 in two hippocampal subsectors across n = 24 cases. Results Each phosphorylated tau site immunohistochemically labeled early neurofibrillary tangle maturity levels compared to advanced levels recognized by thioflavin‐S. Hippocampal burden generally increased with each Braak stage. Discussion These results provide neurobiologic evidence that these phosphorylated tau fluid biomarker sites are present during early neurofibrillary tangle maturity levels and may explain why these fluid biomarker measures are observed before symptom onset. Highlights Immunohistochemical evaluation of four phosphorylated tau fluid biomarker sites. Earlier neurofibrillary tangle maturity levels recognized by phosphorylated tau in proline‐rich region. Advanced tangle pathology is elevated in the subiculum compared to the cornu ammonis 1 of the hippocampus. Novel semi‐quantitative frequency to calculate tangle maturity frequency.

Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative disease that is the most common cause of dementia. Our previous studies have shown that increased expression of the SERPINA5 gene is associated with hippocampal vulnerability in AD, and that the SERPINA5 protein binds to tau and co-localizes within neurofibrillary tangles. To determine if genetic variants in the SERPINA5 gene may be contributing to this phenotype, we sequenced 103 autopsy-confirmed young-onset AD cases with a positive family history of cognitive decline. We observed one individual with a rare missense variant (rs140138746) in the SERPINA5 gene, resulting in an amino acid change (p.E228Q). We screened a further 1170 neuropathologically diagnosed AD cases and identified an additional 5 carriers of this variant, resulting in an allelic frequency of 0.002141 within our AD validation cohort, which was comparable to online genomic databases. Although not significant, SERPINA5 p.E228Q variant carriers were found to be younger at age of onset and age of death than non-carriers. SERPINA5 p.E228Q variant carriers had a longer disease duration than non-carriers, which approached significance. To further elucidate possible neuropathologic contributions of the SERPINA5 p.E228Q variant, we carried out descriptive neuropathologic burden analysis on a variant carrier that was matched to a non-carrier for age, sex, disease duration, Braak tangle stage, TDP-43 positive status, and who possessed an APOE ε4 risk allele. Interestingly, SERPINA5 burden was lower in the SERPINA5 p.E228Q carrier than the non-carrier in 9 corticolimbic brain regions studied, which exaggerated the tau:SERPINA5 immunohistochemical ratio. The SERPINA5 p.E228Q carrier was observed to have more severe neuronal loss in several brain regions compared to the non-carrier. Together, we cautiously interpret these findings to suggest that the SERPINA5 p.E228Q variant may stall tangle maturity and slow AD disease progression, thus prolonging disease duration in these individuals.

AbstractBackgroundUsing an objective mathematical algorithm to assess corticolimbic involvement of neurofibrillary tangle pathology, we identified three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Typical AD brains were representative of the expected patterns of hippocampal and cortical involvement as outlined by Braak tangle stage. In contrast, we discovered an extreme phenotype that exists outside of the Braakian‐concept of neurofibrillary tangle patterns. Hippocampal sparing AD cases demonstrate unexpected sparing of the hippocampus relative to severely involved association cortices and limbic predominant AD cases demonstrate inundation of the hippocampus relative to mildly involved association cortices. Using these AD subtypes, our objective was to leverage our understanding of disease spectrum to uncover transcriptomic changes that underlie selective vulnerability of the hippocampus in AD.MethodWe performed RNA‐sequencing in 40 neuropathologically diagnosed AD cases (10 HpSp, 20 Typical and 10 Limbic) and 15 controls to uncover gene expression changes associated with phenotype differences allowing us to prioritize 44 genes for further exploration. Validation with NanoString and quantification with digital pathology were performed in an expanded cohort of 158 AD cases (36 HpSp, 79 Typical and 35 Limbic) and 32 controls. We quantified digital pathology measures of early tangle pathology (CP13), mature tangle pathology (Ab39), amyloid‐β (33.1.1). In addition, we measured cellular markers for microglia (CD68), endothelia (CD34), and astroglia (GFAP). Deep learning based prediction models were employed, which nominated the SLC38A2 gene as a predictor of AD.ResultThe SLC38A2 gene was originally prioritized in our RNA‐sequencing data based upon differential expression between controls and typical AD. We observed upregulation of SLC38A2 in all AD subtypes. RNA‐seq gene expression measures validated well with NanoString for SLC38A2 (R=0.97, p<0.001). Regression analysis identified early tangle (p=0.011) and late tangle measures (p=0.026) as significant predictors of gene expression, but not amyloid measures (p=0.74). Microgliosis approached significance (p=0.052), but with no contribution from endothelial cell burden (p=0.17) or astrogliosis (p=0.58). Age approached significance (p=0.06), but not sex (p=0.88) or APOE‐ε4 status (p=0.10).ConclusionOur data supports consideration of intra‐disease divergence with regard to case stratification and may reveal genes previously masked by heterogeneity of cohorts.

Background: Plasma NfL (pNfL) levels are elevated in many neurological disorders. However, the utility of pNfL in a clinical setting has not been established. Objective: In a cohort of diverse older participants, we examined: 1) the association of pNfL to age, sex, Hispanic ethnicity, diagnosis, and structural and amyloid imaging biomarkers; and 2) its association to baseline and longitudinal cognitive and functional performance. Methods: 309 subjects were classified at baseline as cognitively normal (CN) or with cognitive impairment. Most subjects had structural MRI and amyloid PET scans. The most frequent etiological diagnosis was Alzheimer’s disease (AD), but other neurological and neuropsychiatric disorders were also represented. We assessed the relationship of pNfL to cognitive and functional status, primary etiology, imaging biomarkers, and to cognitive and functional decline. Results: pNfL increased with age, degree of hippocampal atrophy, and amyloid load, and was higher in females among CN subjects, but was not associated with Hispanic ethnicity. Compared to CN subjects, pNfL was elevated among those with AD or FTLD, but not those with neuropsychiatric or other disorders. Hippocampal atrophy, amyloid positivity and higher pNfL levels each added unique variance in predicting greater functional impairment on the CDR-SB at baseline. Higher baseline pNfL levels also predicted greater cognitive and functional decline after accounting for hippocampal atrophy and memory scores at baseline. Conclusion: pNfL may have a complementary and supportive role to brain imaging and cognitive testing in a memory disorder evaluation, although its diagnostic sensitivity and specificity as a stand-alone measure is modest. In the absence of expensive neuroimaging tests, pNfL could be used for differentiating neurodegenerative disease from neuropsychiatric disorders.