Murray, Melissa E.

Abstract Digital pathology (DP) has transformative potential, especially for Alzheimer disease and related disorders. However, infrastructure barriers may limit adoption. To provide benchmarks and insights into implementation barriers, a survey was conducted in 2019 within National Institutes of Health’s Alzheimer’s Disease Centers (ADCs). Questions covered infrastructure, funding sources, and data management related to digital pathology. Of the 35 ADCs to which the survey was sent, 33 responded. Most respondents (81%) stated that their ADC had digital slide scanner access, with the most frequent brand being Aperio/Leica (62.9%). Approximately a third of respondents stated there were fees to utilize the scanner. For DP and machine learning (ML) resources, 41% of respondents stated none was supported by their ADC. For scanner purchasing and operations, 50% of respondents stated they received institutional support. Some were unsure of the file size of scanned digital images (37%) and total amount of storage space files occupied (50%). Most (76%) were aware of other departments at their institution working with ML; a similar (76%) percentage were unaware of multiuniversity or industry partnerships. These results demonstrate many ADCs have access to a digital slide scanner; additional investigations are needed to further understand hurdles to implement DP and ML workflows.

AbstractBackgroundThe nucleus basalis of Meynert (nbM) is a critical hub that supplies cholinergic input throughout the cortex. Prior to even entorhinal cortex involvement, the nbM is observed to be vulnerable to tau pathology. Neuropathologic and neuroimaging studies provide strong evidence suggesting evaluation of nbM volume may be highly informative as an early biomarker of Alzheimer’s disease.MethodThe relevant AD biomarker literature with neuropathologic validation will be highlighted. Data will be provided from the FLorida Autopsied Multi‐Ethnic (FLAME) series of neuropathologically diagnosed AD cases. To enhance translational neuropathologic studies of the nbM, differences in neuronal density will be compared in the context of both typical and atypical (non‐memory) clinical presentations of AD using digital pathology to quantify nbM neurons in the postmortem tissue.ResultIn the FLAME series, we observed greater nbM neuronal loss in individuals with atypical clinical presentations (median=23/mm2) compared to typical AD dementia (median=26; p=0.002). Atypical clinical variants will be compared to provide a didactic learning experience, in addition to discussing the nbM’s influence on cortical tangle accumulation. Moreover, we will emphasize the paradoxical nature of greater nbM neuronal loss in young‐onset AD (median=21) compared to late‐onset AD (median=28; p<0.001).ConclusionEvaluation of cholinergic hub vulnerability may greatly inform our understanding of clinical heterogeneity in AD and provide key insight into early biomarker interpretation.

AbstractBackgroundOther than the typical (memory‐dominant) variant, Alzheimer’s disease (AD) can present as posterior cortical atrophy (PCA) and behavioral/dysexecutive AD. Tangle distribution differs amongst clinical variants. Neuroinflammation is important in AD pathogenesis and may contribute to Aβ and p‐tau distribution. The relationship between pathological hallmarks, neuroinflammation and, APOE genotype in (a)typical AD is still largely unknown.MethodI will discuss our most recent studies on neuroinflammation in (a)typical AD from cohorts derived from the Netherlands Brain Bank and the Mayo Clinic. Atypicality is investigated from both a neuropathological perspective(N=19) and a clinical perspective (N=30, unpublished data). Additionally, the association ofAPOE ε4 with specific Aβ deposits (i.e., the ‘coarse‐grained plaque’ and the classic cored plaque) and their underlying neuroinflammatory response is investigated (N=60, unpublished data).ResultIn neuropathologically‐defined atypical AD, microglia, and complement show an atypical distribution across regions, resembling that of p‐tau. Clinical atypical AD variants show in addition to a distinct distribution for p‐tau and Aβ, a distinct distribution for activated microglia (CD68, MHC‐II), complement (C4b), and astrocytes (GFAP) (p<.05) (Fig. 1). Furthermore, when investigating Aβ in detail, we observed an atypical plaque, defined as the ‘coarse‐grained plaque’. This APOE ε4+ plaque is associated with increased neuroinflammation and p‐tau burden (ρ(58)=0.5 and 0.6;p<.05) in contrast to the classic cored plaque.ConclusionOur data supports that not all types of Aβ deposits are associated to p‐tau damage. Neuroinflammation, a process that is differently activated within AD variants, may be the link between Aβ aggregation and subsequent neurodegeneration and contribute to clinical variability.

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.

AbstractBackgroundDiffusion MRI (dMRI) based quantification of microstructural changes in white matter (WM) are increasingly proposed to measure cerebrovascular disease (CVD) related changes. Our objective was to compare the proposed dMRI markers using postmortem neuropathologic CVD data and then evaluate the predictors of longitudinal dMRI markers using serial scans.MethodWe identified n=51 participants (mean age: 83.8 years, 63% males) with ante‐mortem dMRI and postmortem CVD evaluation and n=718 participants (mean age: 71.1 years, 56% males) with at least two dMRI scans from the population‐based sample of Mayo Clinic Study of Aging. We computed dMRI measures proposed for measuring CVD: Free Water (FW), Fractional Anisotropy (FA) adjusted for FW (FAadj), Peak width Skeletonized Mean Diffusivity (PSMD), and FA of the genu of corpus callosum (Genu‐FA). We used the FW and PSMD (PSMD release 1.8.1) kits from the MarkVCID consortium.Using weighted linear regression models with adjustments for MRI scan time to death, we evaluated associations between the baseline dMRI and two pathology CVD scores: Strozyk (represents the presence and number of macroscopic lesions) and Kalaria (represents the summary score of vessel wall modifications) scales. We ran linear mixed effect models with all available serial dMRI measures as outcomes and vascular risk (measured by the number of cardiovascular and metabolic conditions‐CMC), baseline imaging measures (amyloid and white matter hyperintensities (WMH)) and their interaction with time as key predictors.ResultMost dMRI markers were predictors of postmortem CVD pathology (Table 1). In longitudinal dMRI models, terms associated with amyloid explained little variability in dMRI (<1%) (Table 2). WMH was a significant predictor of baseline and decline in dMRI measures with WMH explaining a considerable percentage of variability in FW (34%) and PSMD (28%). Vascular risk measures were significant predictors of three out of the four dMRI measures.ConclusionThe diffusion measures proposed as surrogate markers of CVD map reasonably well to CVD pathological scales and do not change substantially as a function of baseline amyloidosis. Our findings shed light on variability in the proposed diffusion markers using postmortem data and longitudinal imaging data. Further work is needed to evaluate their clinical utility.

AbstractBackgroundMulti‐compartment modelling of white matter (WM) microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) can provide information on WM health through the neurite (axons and dendrites) density index and free water measures. We hypothesized that cerebrovascular disease (CVD), Alzheimer’s disease (AD), and an FDG pattern suggestive of TDP‐43 proteinopathy would be associated with distinct NODDI readouts of WM damage which would be informative for identifying the substrate for cognitive impairment.MethodWe identified two independent cohorts with multi‐shell diffusion MRI, amyloid and tau PET, and cognitive assessments. One, were participants from the Mayo Clinic Study of Aging, a population‐based cohort of 347 elderly randomly sampled from the Olmsted county, Minnesota. The second were 61 amyloid positive AD participants from the Mayo AD Research Center.ResultWe observed an increase in free water and decrease in neurite density in the genu of the corpus callosum associated with vascular risk factors, which we refer to as vascular WM component (Figure 1). Tau PET signal reflective of 3R/4R tau deposition was associated with worsening neurite density index in the temporal WM where we measured parahippocampal cingulum and inferior temporal WM bundles. Worsening temporal neurite density was associated with (antemortem confirmed) FDG TDP‐43 signature. Post‐mortem neuropathologic data on a small subset (n=9) of this sample lend support to our findings. In the population‐based cohort where vascular disease was more prevalent, the vascular WM component explained variability in global cognition (partial R2 of free water and neurite density = 8.3%) and MMSE performance (8.2%) which was comparable to amyloid PET (7.4% for global cognition and 6.6% for memory) (Table 1). In the AD dementia clinic‐based cohort, tau deposition was the greatest contributor to cognitive performance (9.6%), but there was also a non‐trivial contribution of the temporal WM component (8.5%) to cognitive performance. The differences observed between the two cohorts were reflective of their distinct clinical composition.ConclusionWhite matter microstructural damage assessed using advanced diffusion models may add significant value for distinguishing the underlying substrate (whether CVD versus neurodegenerative disease caused by tau deposition or TDP‐43 pathology) for cognitive impairment in older individuals.

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

AbstractBackgroundTDP‐43 is a nuclear RNA‐binding protein involved in various neurodegenerative diseases, including Alzheimer’s Disease (AD), and normal aging. It strongly affects cognition and memory loss in AD. Concomitant TDP‐43 pathology increases the likelihood of being cognitively impaired at death.MethodMayo Clinic has amassed a large database with 1072 study participants with known TDP‐43 pathology status, who were prospectively recruited and followed in the Mayo Clinic Alzheimer’s Disease Research Center, Mayo Clinic Study of Aging, and Neurodegenerative Research Group. All underwent neurologic, genetic, and neuropathologic evaluations. Amygdala sections immunostained with antibodies against TDP‐43 were screened for TDP‐43‐immunoreactive inclusions and successively staged using the Josephs staging scheme. The frequency of TDP‐43 pathology by age at death was estimated using logistic regression with age modelled using a restricted cubic spline. Models were fit for all cases including the subset of 581 cases with dementia.ResultOur cohort was predominantly White (99%) with median age at death of 87 years (IQR: 80‐92) and relatively even sex distribution (52% female). About 55% had Braak stage V‐VI and 61% had Thal amyloid phase ≥3. Fifty‐two percent met criteria for intermediate‐high probability AD. TDP‐43‐immunoreactivity (TDP‐43+) was detected in 44% with median TDP‐43 stage of 3 (IQR: 1‐5), and in 54% with a median stage of 3 (IQR: 2‐5) in those with dementia. TDP‐43+ frequency increased approximately linearly with age at death. At 70 years at death, an estimated 30% (95% CI: 25–35) of the cohort was TDP‐43+ versus 33% (CI: 27–40) of those with dementia. By 90 years at death, 49% (CI: 45–52) of the overall cohort and 68% (CI:62‐73) of those with dementia were TDP‐43+.ConclusionThe results from our large cohort confirm that TDP‐43 pathology frequency increases in elderly White study participants with age of death, independent of cognitive status. Furthermore, TDP‐43 pathology frequency increases to a greater degree with age in those with dementia. Given the clear links between TDP‐43 and impaired cognition, the contribution of TDP‐43 to an individual’s cognitive impairment is likely to increase with age; a dynamic with significant public health consequences given our aging population.

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.

AbstractBackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder neuropathologically characterized by amyloid‐β (Aβ) plaques and tau neurofibrillary tangles often measured by Thal phase and Braak stage, respectively. Frequently, Aβ also deposits in the brain vasculature with severity categorized by a cerebral amyloid angiopathy (CAA) score. Assessment of these and related endophenotypes can reveal biological insights into the phenotypic variability in AD. We hypothesize that, amongst AD patients, severity of neuropathology and brain levels of AD‐related proteins are influenced by variation in DNA methylation (DNAm), the identification of which may uncover biological pathways for AD pathogenesis. To test this, we performed epigenome‐wide association studies (EWAS) using DNAm from the temporal cortex (TCX) and cerebellum (CER) with AD‐related neuropathology measures (Braak, Thal, and CAA) and brain levels of five proteins (apoE, Aβ40, Aβ42, tau, and p‐tau).MethodsDNAm from autopsy‐confirmed AD cases available through the Mayo Clinic Brain Bank was measured by reduced representation bisulfite sequencing (RRBS) from 471 brain samples, 200 of which had both TCX and CER measures. Bisulfite converted reads were sequenced on the Illumina High Seq4000 and quality filtered. Neuropathology scoring was performed by an experienced neuropathologist. TCX levels of five AD‐related proteins from three fractions (buffer‐soluble, detergent‐soluble, and insoluble) were measured by ELISA (Liu et al. 2020). Individual CpG methylation ratios were tested for association with each neuropathological and biochemical measure using the R package CpGassoc.ResultsWe identified multiple epigenome‐wide significant CpGs unique to each AD‐related measure. Comparisons between the TCX and CER revealed region specific CpG associations. The effects of sex, age at death, APOE genotype, and presence of genetic variants for each significant CpG association were also identified.ConclusionsAlthough all neuropathological and biochemical measures tested reflect core AD pathologies, our results demonstrate unique associations of epigenetic factors with these individual phenotypes, suggesting that their variability may be governed by distinct epigenetic processes. Discovery of DNAm changes that underlie specific neuropathological or biochemical outcomes can enhance our understanding of AD pathophysiology and may lead to the identification of novel gene or pathway targets for the different facets of this complex condition.