Validation of machine learning models to detect amyloid pathologies across institutions.

Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) are the most commonly used method in Alzheimer's disease (AD) neuropathology practice. Computational approaches based on machine learning have recently generated quantitative scores for whole slide images (WSIs) that are highly correlated with human derived semi-quantitative scores, such as those of CERAD, for Alzheimer's disease pathology. However, the robustness of such models have yet to be tested in different cohorts. To validate previously published machine learning algorithms using convolutional neural networks (CNNs) and determine if pathological heterogeneity may alter algorithm derived measures, 40 cases from the Goizueta Emory Alzheimer's Disease Center brain bank displaying an array of pathological diagnoses (including AD with and without Lewy body disease (LBD), and / or TDP-43-positive inclusions) and levels of Aβ pathologies were evaluated. Furthermore, to provide deeper phenotyping, amyloid burden in gray matter vs whole tissue were compared, and quantitative CNN scores for both correlated significantly to CERAD-like scores. Quantitative scores also show clear stratification based on AD pathologies with or without additional diagnoses (including LBD and TDP-43 inclusions) vs cases with no significant neurodegeneration (control cases) as well as NIA Reagan scoring criteria. Specifically, the concomitant diagnosis group of AD + TDP-43 showed significantly greater CNN-score for cored plaques than the AD group. Finally, we report that whole tissue computational scores correlate better with CERAD-like categories than focusing on computational scores from a field of view with densest pathology, which is the standard of practice in neuropathological assessment per CERAD guidelines. Together these findings validate and expand CNN models to be robust to cohort variations and provide additional proof-of-concept for future studies to incorporate machine learning algorithms into neuropathological practice

Interpretable classification of Alzheimer's disease pathologies with a convolutional neural network pipeline.

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies-amyloid plaques and cerebral amyloid angiopathy-in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate > 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist's ability suggests a route to neuropathologic deep phenotyping

Tau immunoreactivity in peripheral tissues of human aging and select tauopathies

Many studies have been directed at understanding mechanisms of tau aggregation and therapeutics, nearly all focusing on the brain. It is critical to understand the presence of tau in peripheral tissues since this may provide new insights into disease progression and selective vulnerability. The current study sought to determine the presence of select tau species in peripheral tissues in elderly individuals and across an array of tauopathies. Using formalin fixed paraffin embedded sections, we examined abdominal skin, submandibular gland, and sigmoid colon among 69 clinicopathologically defined cases: 19 lacking a clinical neuropathological diagnosis (normal controls), 26 progressive supranuclear palsy (PSP), 21 Alzheimer's disease (AD), and 3 with corticobasal degeneration (CBD). Immunohistochemistry was performed using antibodies for "total" tau (HT7) and two phosphorylated tau species (AT8 and pT231). HT7 staining of abdominal skin revealed immunoreactivity of potential nerve elements in 5% of cases (1 AD, 1 AD/PSP, and 1 CBD out of 55 cases examined); skin sections lacked AT8 and pT231 immunoreactive nerve elements. Submandibular glands from all cases had HT7 immunoreactive nerve elements; while pT231 was present in 92% of cases, and AT8 in only 3 cases (2 AD and one AD/PSP case). In sigmoid colon, HT7 immunoreactivity was present in all but 2 cases (97%), pT231 in 54%, and AT8 was present in only 5/62 cases (8%). These data suggest select tau species in CNS tauopathies do not have a high propensity to spread to the periphery and this may hold clues for the understanding of CNS tau pathogenicity and vulnerability

Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases.

Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveraging a machine learning (ML) pipeline to perform a granular quantification of Aβ deposits and assess their distribution in the temporal lobe. Utilizing 131 whole-slide-images from consecutive autopsied cases at the University of California Davis Alzheimer Disease Research Center, our objectives were threefold: (1) Validate an automatic workflow for Aβ deposit quantification in white matter (WM) and gray matter (GM); (2) define the distributions of different Aβ deposit types in GM and WM, and (3) investigate correlates of Aβ deposits with dementia status and the presence of mixed pathology. Our methodology highlights the robustness and efficacy of the ML pipeline, demonstrating proficiency akin to experts' evaluations. We provide comprehensive insights into the quantification and distribution of Aβ deposits in the temporal GM and WM revealing a progressive increase in tandem with the severity of established diagnostic criteria (NIA-AA). We also present correlations of Aβ load with clinical diagnosis as well as presence/absence of mixed pathology. This study introduces a reproducible workflow, showcasing the practical use of ML approaches in the field of neuropathology, and use of the output data for correlative analyses. Acknowledging limitations, such as potential biases in the ML model and current ML classifications, we propose avenues for future research to refine and expand the methodology. We hope to contribute to the broader landscape of neuropathology advancements, ML applications, and precision medicine, paving the way for deep phenotyping of AD brain cases and establishing a foundation for further advancements in neuropathological research

Biochemical analyses of tau and other neuronal markers in the submandibular gland and frontal cortex across stages of Alzheimer disease

Hyperphosphorylation of the microtubule-associated protein tau is hypothesized to lead to the development of neurofibrillary tangles in select brain regions during normal aging and in Alzheimer disease (AD). The distribution of neurofibrillary tangles is staged by its involvement starting in the transentorhinal regions of the brain and in final stages progress to neocortices. However, it has also been determined neurofibrillary tangles can extend into the spinal cord and select tau species are found in peripheral tissues and this may be depended on AD disease stage. To further understand the relationships of peripheral tissues to AD, we utilized biochemical methods to evaluate protein levels of total tau and phosphorylated tau (p-tau) as well as other neuronal proteins (i.e., tyrosine hydroxylase (TH), neurofilament heavy chain (NF-H), and microtubule-associated protein 2 (MAP2)) in the submandibular gland and frontal cortex of human cases across different clinicopathological stages of AD (n = 3 criteria not met or low, n = 6 intermediate, and n = 9 high likelihood that dementia is due to AD based on National Institute on Aging-Reagan criteria). We report differential protein levels based on the stage of AD, anatomic specific tau species, as well as differences in TH and NF-H. In addition, exploratory findings were made of the high molecular weight tau species big tau that is unique to peripheral tissues. Although sample sizes were small, these findings are, to our knowledge, the first comparison of these specific protein changes in these tissues

The Impact of Aging on Brain Pituitary Adenylate Cyclase Activating Polypeptide Pathology and Cognition in Mice and Rhesus Macaques

Pituitary adenylate cyclase activating polypeptide (PACAP) is associated with Alzheimer\u27s disease (AD), but its age-related effects are unknown. We chose the rhesus macaque due to its closeness to human anatomy and physiology. We examined four variables: aging, cognitive performance, amyloid plaques and PACAP. Delayed nonmatching-to-sample recognition memory scores declined with age and correlated with PACAP levels in the striatum, parietal and temporal lobes. Because amyloid plaques were the only AD pathology in the old rhesus macaque, we further studied human amyloid precursor protein (hAPP) transgenic mice. Aging was associated with decreased performance in the Morris Water Maze (MWM). In wild type (WT) C57BL/6 mice, the performance was decreased at age 24-26 month whereas in hAPP transgenic mice, it was decreased as early as 9-12 month. Neuritic plaques in adult hAPP mice clustered in hippocampus and adjacent cortical regions, but did not propagate further into the frontal cortex. Cerebral PACAP protein levels were reduced in hAPP mice compared to age-matched WT mice, but the genetic predisposition dominated cognitive decline. Taken together, these data suggest an association among PACAP levels, aging, cognitive function and amyloid load in nonhuman primates, with both similarities and differences from human AD brains. Our results suggest caution in choosing animal models and in extrapolating data to human AD studies

Epigenetic and genetic risk of Alzheimer disease from autopsied brains in two ethnic groups.

Genetic variants and epigenetic features both contribute to the risk of Alzheimer's disease (AD). We studied the AD association of CpG-related single nucleotide polymorphisms (CGS), which act as a hub of both the genetic and epigenetic effects, in Caribbean Hispanics (CH) and generalized the findings to Non-Hispanic Whites (NHW). First, we conducted a genome-wide, sliding-window-based association with AD, in 7,155 CH and 1,283 NHW participants. Next, using data from the dorsolateral prefrontal cortex in 179 CH brains, we tested the cis- and trans-effects of AD-associated CGS on brain DNA methylation to mRNA expression. For the genes with significant cis- and trans-effects, we investigated their enriched pathways. We identified six genetic loci in CH with CGS dosage associated with AD at genome-wide significance levels: ADAM20 (Score = 55.19, P = 4.06 × 10-8), the intergenic region between VRTN and SYNDIG1L (Score = - 37.67, P = 2.25 × 10-9), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10-8), PVRL2 (Score = 125.86, P = 1.64 × 10-9), TOMM40 (Score = - 18.58, P = 4.61 × 10-8), and APOE (Score = 75.12, P = 7.26 × 10-26). CGSes in PVRL2 and APOE were also significant in NHW. Except for ADAM20, CGSes in the other five loci were associated with CH brain methylation levels (mQTLs) and CGSes in SPG7, PVRL2, and APOE were also mQTLs in NHW. Except for SYNDIG1L (P = 0.08), brain methylation levels in the other five loci affected downstream mRNA expression in CH (P < 0.05), and methylation at VRTN and TOMM40 were also associated with mRNA expression in NHW. Gene expression in these six loci were also regulated by CpG sites in genes that were enriched in the neuron projection and glutamatergic synapse pathways (FDR < 0.05). DNA methylation at all six loci and mRNA expression of SYNDIG1 and TOMM40 were significantly associated with Braak Stage in CH. In summary, we identified six CpG-related genetic loci associated with AD in CH, harboring both genetic and epigenetic risks. However, their downstream effects on mRNA expression maybe ethnic specific and different from NHW

Frequency of LATE neuropathologic change across the spectrum of Alzheimer’s disease neuropathology: combined data from 13 community-based or population-based autopsy cohorts

Limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) and Alzheimer’s disease neuropathologic change (ADNC) are each associated with substantial cognitive impairment in aging populations. However, the prevalence of LATE-NC across the full range of ADNC remains uncertain. To address this knowledge gap, neuropathologic, genetic, and clinical data were compiled from 13 high-quality community- and population-based longitudinal studies. Participants were recruited from United States (8 cohorts, including one focusing on Japanese–American men), United Kingdom (2 cohorts), Brazil, Austria, and Finland. The total number of participants included was 6196, and the average age of death was 88.1 years. Not all data were available on each individual and there were differences between the cohorts in study designs and the amount of missing data. Among those with known cognitive status before death (n = 5665), 43.0% were cognitively normal, 14.9% had MCI, and 42.4% had dementia—broadly consistent with epidemiologic data in this age group. Approximately 99% of participants (n = 6125) had available CERAD neuritic amyloid plaque score data. In this subsample, 39.4% had autopsy-confirmed LATE-NC of any stage. Among brains with “frequent” neuritic amyloid plaques, 54.9% had comorbid LATE-NC, whereas in brains with no detected neuritic amyloid plaques, 27.0% had LATE-NC. Data on LATE-NC stages were available for 3803 participants, of which 25% had LATE-NC stage > 1 (associated with cognitive impairment). In the subset of individuals with Thal Aβ phase = 0 (lacking detectable Aβ plaques), the brains with LATE-NC had relatively more severe primary age-related tauopathy (PART). A total of 3267 participants had available clinical data relevant to frontotemporal dementia (FTD), and none were given the clinical diagnosis of definite FTD nor the pathological diagnosis of frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP). In the 10 cohorts with detailed neurocognitive assessments proximal to death, cognition tended to be worse with LATE-NC across the full spectrum of ADNC severity. This study provided a credible estimate of the current prevalence of LATE-NC in advanced age. LATE-NC was seen in almost 40% of participants and often, but not always, coexisted with Alzheimer’s disease neuropathology

LATE-NC staging in routine neuropathologic diagnosis : an update

An international consensus report in 2019 recommended a classification system for limbic-predominant age-related TDP-43 encephalopathy neuropathologic changes (LATE-NC). The suggested neuropathologic staging system and nomenclature have proven useful for autopsy practice and dementia research. However, some issues remain unresolved, such as cases with unusual features that do not fit with current diagnostic categories. The goal of this report is to update the neuropathologic criteria for the diagnosis and staging of LATE-NC, based primarily on published data. We provide practical suggestions about how to integrate available genetic information and comorbid pathologies [e.g., Alzheimer's disease neuropathologic changes (ADNC) and Lewy body disease]. We also describe recent research findings that have enabled more precise guidance on how to differentiate LATE-NC from other subtypes of TDP-43 pathology [e.g., frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS)], and how to render diagnoses in unusual situations in which TDP-43 pathology does not follow the staging scheme proposed in 2019. Specific recommendations are also made on when not to apply this diagnostic term based on current knowledge. Neuroanatomical regions of interest in LATE-NC are described in detail and the implications for TDP-43 immunohistochemical results are specified more precisely. We also highlight questions that remain unresolved and areas needing additional study. In summary, the current work lays out a number of recommendations to improve the precision of LATE-NC staging based on published reports and diagnostic experience.Peer reviewe