AI Maps the Hidden Diversity of Amyloid Plaques Across the Alzheimer’s Brain

For more than a century, the amyloid-beta plaque has been the most recognizable villain in the story of Alzheimer’s disease. These extracellular protein deposits, together with tangles of hyperphosphorylated tau, define the disease under the microscope and have anchored decades of therapeutic research. Yet plaques have never been a single, uniform entity. They appear in the brain as fuzzy diffuse clouds, dense compact knots, classic cored structures with a dark center and pale halo, tiny punctate deposits, and accumulations within blood vessel walls known as cerebral amyloid angiopathy. What has been missing is a comprehensive, quantitative map of this morphological diversity across the entire human brain, and an answer to the question of whether different plaque types track with the clinical and genetic features of the patients who carry them.

A new study published in Acta Neuropathologica by Antonia Neubauer, Paul Feyen, Jochen Herms and colleagues at Ludwig-Maximilians-Universität München and the German Center for Neurodegenerative Diseases tackles that gap at unprecedented scale. The team systematically documented the abundance and morphological variety of amyloid-beta deposits in up to 23 brain regions of 84 cases of advanced Alzheimer’s disease, drawn from the Neurobiobank Munich. The cohort included both familial and sporadic cases, with an average age at clinical onset of 61.6 years and an average age at death of 73.9 years. All cases had died with dementia, and most showed the highest neuropathological stages of both tau and amyloid pathology. In total, the researchers extracted 57,233 individual amyloid-beta deposits from 1,179 annotated brain regions.

The technical achievement at the heart of the study is a machine-learning pipeline built for digital pathology. Formalin-fixed, paraffin-embedded tissue was cut into five-micrometer sections and stained with the monoclonal antibody 4G8 to visualize amyloid-beta, with diaminobenzidine producing the brown signal. Digitized slides were preprocessed by color deconvolution, and a random forest pixel classifier trained in ilastik detected candidate deposits. Each deposit was then classified by a convolutional neural network, an extension of an earlier architecture, into six classes: cored plaques, diffuse light plaques, diffuse dense plaques, compact plaques, small dense plaques, and cerebral amyloid angiopathy. The network was trained on 2,135 manually classified deposit images, validated on 533, and tested on a held-out set of 471, achieving a recall of 81.5 percent and a precision of 82.4 percent. Because cored plaques and vascular amyloid were rare and harder to call, every prediction in those two categories was manually verified and reclassified where necessary, a step that proved essential given the low precision the model initially achieved for cored plaques.

The regional map that emerged confirms and refines the classical staging of amyloid spread. Cortical regions carried by far the heaviest plaque loads, with median counts between roughly 81 and 104 deposits per square millimeter in areas such as the insula and frontal sulcus, while the occipital, parahippocampal and entorhinal cortex showed significantly lower densities. Subcortical regions, the hippocampus and the cerebellum were less affected still, with the dentate nucleus of the cerebellum essentially spared. Plaque counts correlated strongly within the cortical group, within the hippocampal group, and between cortex and hippocampus, hinting at shared mechanisms or connected pathways driving accumulation. Intriguingly, regions that are typically devastated by tau, alpha-synuclein and TDP-43 pathology, such as the amygdala and entorhinal cortex, were comparatively lightly affected by amyloid, a dissociation the authors suggest may reflect amyloid released from tau-bearing projection neurons accumulating at distant cortical targets rather than locally.

Across the brain, the plaque landscape was dominated by poorly differentiated deposits. Diffuse light plaques were the most abundant class in nearly every region, followed by small dense plaques and then diffuse dense plaques, with compact plaques in fourth place. Cored plaques and cerebral amyloid angiopathy played a statistically minor role, with median proportions near zero. Yet the correlation analyses revealed that these numerically rare classes behave differently from everything else. Densities of diffuse dense, small dense and compact plaques correlated positively with one another and with the total plaque load, suggesting shared origins or transitions. Cored plaques and vascular amyloid, by contrast, did not correlate with the overall amyloid burden at all, pointing to distinct mechanisms of formation that do not simply scale with the amount of amyloid in a region.

Perhaps the most striking finding concerns tau. When the researchers correlated each plaque class with the tau-covered area in the entorhinal cortex, only cored plaques showed a significant positive relationship. Every other class except vascular amyloid was negatively correlated with tau load. This is a provocative result, because cored plaques are known to overlap heavily with neuritic plaques, the variety surrounded by dystrophic neurites, activated microglia and reactive astrocytes, and the variety most consistently linked to synaptic loss and cognitive decline. The data suggest that while diffuse amyloid accumulates broadly and largely silently, the emergence of cored plaques may mark a closer pathological partnership with the tau process that ultimately drives neurodegeneration.

The study also tied plaque composition to patient characteristics in ways that varied by class. Women carried significantly higher densities of diffuse light, diffuse dense, compact and small dense plaques than men, but not of cored plaques or vascular amyloid, meaning that the well-documented sex difference in amyloid burden does not extend uniformly across plaque types. Carriers of at least one ApoE4 allele, the strongest genetic risk factor for late-onset Alzheimer’s disease, showed higher densities of diffuse dense and small dense plaques, consistent with experimental evidence that ApoE4 promotes denser, more condensed plaque morphologies. Among familial cases, PSEN1 mutation carriers had more cored plaques than sporadic cases. Younger age at clinical onset and younger age at death were both associated with higher densities of diffuse light plaques, and younger age at death specifically with more cored plaques, findings partly attributable to the inclusion of familial cases in the cohort.

Disease duration added another layer of nuance. Longer illness was associated with accumulating diffuse light and diffuse dense plaques, while cases with short disease durations showed proportionally more cored plaques and vascular amyloid. The authors interpret this cautiously but suggest that diffuse deposits can accumulate over many years without immediately limiting life, whereas cored plaques and vessel-wall amyloid may be more tightly linked to the pace of clinical progression. An integrative linear mixed-effects model combining sex, ApoE status, age at onset and disease duration confirmed the association between female sex and diffuse light plaques and between younger onset and cored plaques, but also revealed how much remains unexplained: these factors accounted for only a modest share of the variance in plaque densities, leaving room for lifestyle, comorbidities and vascular factors not captured in the analysis.

The authors are candid about the limitations. The cohort reflects voluntary brain donation in a Western country, with limited ethnic diversity and an overrepresentation of familial disease. Sampling was uneven across subjects, though control analyses in a fully sampled subset suggested this did not distort the main conclusions. The two-dimensional nature of histological sections likely underestimates cored plaques, whose dense cores may simply fall outside the cutting plane, and deposits smaller than 100 square micrometers, along with soluble oligomeric amyloid, were excluded entirely. Causality, moreover, cannot be established from post-mortem correlations. Even so, the study delivers something the field has lacked: a cross-regional, class-resolved atlas of amyloid pathology in the human Alzheimer’s brain, with code and models publicly available for the community. Its central message is that amyloid is not one target but many, and that cored plaques and cerebral amyloid angiopathy, despite their rarity, stand apart statistically from the diffuse background in ways that may prove crucial for understanding, and one day treating, the disease.

Subject of Research: Machine-learning-based classification of amyloid-beta plaque diversity across brain regions in Alzheimer's disease and its clinicopathological associations

Article Title: Amyloid-β plaque diversity across brain regions in Alzheimer’s disease and its relation to major clinicopathological traits

Article References: Neubauer, A., Feyen, P., Pekrun, S., Roeber, S., Ruf, V., Strübing, F. L., & Herms, J. (2026). Amyloid-β plaque diversity across brain regions in Alzheimer’s disease and its relation to major clinicopathological traits. Acta Neuropathologica, 152(1), Article 46. https://doi.org/10.1007/s00401-026-03096-1

Image Credits: AI Generated

DOI: 10.1007/s00401-026-03096-1

Keywords: Alzheimer's disease, amyloid-beta, plaques, tau, cerebral amyloid angiopathy, ApoE4, convolutional neural network, neuropathology, digital pathology, machine learning, brain regions, plaque morphology