Moloney, Christina M.

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.

We previously demonstrated that increased expression of the SERPINA5 gene is associated with hippocampal vulnerability in Alzheimer’s disease (AD) brains. SERPINA5 was further demonstrated to be a novel tau-binding partner that colocalizes within neurofibrillary tangles. Our goal was to determine whether genetic variants in the SERPINA5 gene contributed to clinicopathologic phenotypes in AD. To screen for SERPINA5 variants, we sequenced 103 autopsy-confirmed young-onset AD cases with a positive family history of cognitive decline. To further assess the frequency of a rare missense variant, SERPINA5 p.E228Q, we screened an additional 1114 neuropathologically diagnosed AD cases. To provide neuropathologic context in AD, we immunohistochemically evaluated SERPINA5 and tau in a SERPINA5 p.E228Q variant carrier and a matched noncarrier. In the initial SERPINA5 screen, we observed 1 individual with a rare missense variant (rs140138746) that resulted in an amino acid change (p.E228Q). In our AD validation cohort, we identified an additional 5 carriers of this variant, resulting in an allelic frequency of 0.0021. There was no significant difference between SERPINA5 p.E228Q carriers and noncarriers in terms of demographic or clinicopathologic characteristics. Although not significant, on average SERPINA5 p.E228Q carriers were 5 years younger at age of disease onset than noncarriers (median: 66 [60–73] vs 71 [63–77] years, P = .351). In addition, SERPINA5 p.E228Q carriers exhibited a longer disease duration than noncarriers that approached significance (median: 12 [10–15]) vs 9 [6–12] years, P = .079). More severe neuronal loss was observed in the locus coeruleus, hippocampus, and amygdala of the SERPINA5 p.E228Q carrier compared to noncarrier, although no significant difference in SERPINA5-immunopositive lesions was observed. Throughout the AD brain in either carrier or noncarrier, areas with early pretangle pathology or burnt-out ghost tangle accumulation did not reveal SERPINA5-immunopositive neurons. Mature tangles and newly formed ghost tangles appeared to correspond well with SERPINA5-immunopositive tangle-bearing neurons. SERPINA5 gene expression was previously associated with disease phenotype; however, our findings suggest that SERPINA5 genetic variants may not be a contributing factor to clinicopathologic differences in AD. SERPINA5-immunopositive neurons appear to undergo a pathologic process that corresponded with specific levels of tangle maturity.

AbstractBackgroundBlood‐based biomarkers of amyloid and neurodegeneration are increasingly used in clinical trials and entering clinical use. Differentially mapping the plasma markers to post‐mortem neuropathology in a community‐based sample is critical for interpretation.MethodWe identified 64 Mayo Clinic Study of Aging (MCSA) participants with antemortem plasma markers (Aβ42, Aβ40, NfL, T‐tau, Aβ42/40 ratio) measured on the Quanterix Simoa HD‐1 analyzer and with postmortem neuropathologic assessments of Alzheimer’s pathology (Braak tangle stage, Thal phase, neuritic plaque burden) and cerebrovascular pathology (Strozyk scale focused on macrovascular brain changes and Kalaria scale focused on detailed micro‐ and macro‐ vascular brain changes). Weighted linear regression models with adjustment for time between plasma markers and death were conducted with exact permutation tests to evaluate the relationships between antemortem plasma and postmortem neuropathology markers.ResultHigher plasma NfL levels and Aβ42/40 ratio were associated with both cerebrovascular neuropathologic scales (p<0.05) but were not associated with Braak neurofibrillary tangle stage, neuritic plaque score, or Thal stage (p>0.5). Plasma T‐tau was not associated with any pathological assessment. Plasma Aβ42/40 and NfL explained up to 18% of the variability in cerebrovascular neuropathologic scales.ConclusionIn this community sample of participants predominantly without dementia, plasma markers for amyloid (Aβ42/40) and neurodegeneration (NfL) were associated with cerebrovascular neuropathology at autopsy. NfL is a non‐specific marker of brain injury, therefore, its association with cerebrovascular neuropathology was in the expected direction. The association between greater cerebrovascular neuropathology and elevated Aβ42/40 requires further investigation. These findings provide evidence that cerebrovascular disease may significantly influence levels of plasma biomarkers proposed for Alzheimer’s disease. This information will be important to consider for accurate clinical interpretation of the proposed biomarkers.

AbstractBackgroundNeurofibrillary tangles are dynamic entities with a lifespan encompassing three maturity levels: intracellular pretangles, intracellular mature tangles, and extracellular ghost tangles. Proteins are suggested to be differentially expressed throughout the tangle lifespan; however, past studies may be limited by spatial expression or number of proteins investigated. We sought to assess differences in protein expression across the tangle lifespan using GeoMxTM Digital Spatial Profiler (DSP) by NanoString, a new technology allowing for spatially derived multiplex investigation.MethodWe used DSP to measure protein expression in hippocampi from Alzheimer’s disease (n=6) and nondemented controls (n=2) using the “Human Neural Cell Profiling Core” and “Alzheimer’s Pathology” module. Regions of interest (ROIs) were classified by the major tangle maturity level recognized by a primary fluorescent conjugated tau antibody. Protein expression was normalized to the geomean of the three housekeeping genes. The tau‐positive segment was specifically analyzed for comparisons. ANOVA was used for group‐wise comparisons and t‐test using the Benjamini‐Yekutieli adjustment for multiple tests was used for pair‐wise comparisons.ResultAs expected, cytoskeletal (e.g., MAP2, Tau) and neuronal (e.g., NeuN) markers generally decreased through the neurofibrillary tangle lifespan (Figure). Markers profiled as neurodegenerative (e.g., amyloid‐β1‐42, APOE, APP) generally increased through tangle maturity levels, except for TDP‐43 which decreased. Interestingly, there was no significant difference in ubiquitin expression. Astrocytic GFAP and S100B expression was significantly increased through each maturity level. Expression of microglial‐specific markers P2RY12 and TMEM119 was significantly elevated in ghost tangles compared to mature tangles. Additional microglial/macrophage markers including Iba‐1 and CD68 were generally increased as neurofibrillary tangles matured. Interestingly, APOE expression remained low in pretangles and mature tangles before dramatically increasing in ghost tangles (Figure).ConclusionOur findings suggest that proteins are differentially expressed throughout the tangle lifespan and the majority followed a monotonically directed pattern. Non‐monotonically directed protein patterns may reflect the death of the neuron during the ghost tangle maturity level. Future studies will test the hypothesis that the microenvironment of the hippocampus is altered with increasing vulnerability to tangle pathology.

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.

AbstractNeurofibrillary tangles, one of the neuropathologic hallmarks of Alzheimer's disease, have a dynamic lifespan of maturity that associates with progressive neuronal dysfunction and cognitive deficits. As neurofibrillary tangles mature, the biology of the neuron undergoes extensive changes that may impact biomarker recognition and therapeutic targeting. Neurofibrillary tangle maturity encompasses three levels: pretangles, mature tangles, and ghost tangles. In this review, we detail distinct and overlapping characteristics observed in the human brain regarding morphologic changes the neuron undergoes, conversion from intracellular to extracellular space, tau immunostaining patterns, and tau isoform expression changes across the lifespan of the neurofibrillary tangle. Post‐translational modifications of tau such as phosphorylation, ubiquitination, conformational events, and truncations are discussed to contextualize tau immunostaining patterns. We summarize accumulated and emerging knowledge of neurofibrillary tangle maturity, discuss the current tools used to interpret the dynamic nature in the postmortem brain, and consider implications for cognitive dysfunction and tau biomarkers.

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.