Advanced quantitative mapping of Alzheimer’s disease neuropathology and microglial activation in post-mortem hippocampal tissue

We developed a high-throughput imaging workflow to spatially map Alzheimer’s disease (AD) pathology in postmortem hippocampal and medial temporal lobe sections from 65 University of Southern California Alzheimer's Disease Research Center (USC ADRC) cases classified by low, intermediate and high levels of AD neuropathologic change (ADNC). Sections were stained for microglia (Iba1), amyloid-β (4G8), and neurofibrillary tangles (NFTs; Gallyas), and analyzed using pixel-based machine learning (Ilastik). Amyloid pathology was classified as dense, diffuse, or intracellular amyloid precursor protein (APP)-positive; microglia were categorized into ramified, rod-like, and amoeboid morphologies.

Diffuse amyloid plaques increased most significantly across disease, particularly in the subiculum and dentate gyrus molecular layer, while dense plaques and intracellular APP were concentrated in entorhinal and perirhinal cortices. NFT burden was elevated in males, especially in parahippocampal cortical areas. Microglial morphology shifted with AD progression, showing reduced ramified and increased amoeboid profiles in high ADNC cases.

Rod microglia in CA regions were correlated with amyloid in high ADNC and tau in low ADNC cases. Memory impairment correlated more strongly with amyloid pathology in apolipoprotein E (ApoE) ε4 non-carriers, with females showing greater amyloid burden and males more NFT-related decline. These findings reveal region- and sex-specific patterns of pathology and neuroinflammation, offering new insights into mechanisms driving cognitive decline and informing future diagnostic and therapeutic strategies.

We would like to acknowledge the USC ADRC clinicians, researchers, patients, and administrators whose efforts have made this study possible. Cognitive and clinical data were collected by the USC ADRC using the National Alzheimer's Coordinating Center (NACC) Uniform Data Set; the NACC database is funded by NIA/NIH Grant U24 AG072122. This work was supported by NIH grants: K01AG066847 (Author MSB), R01AG092662 (MSB), P30AG066530 (USC ADRC) and a P30AG066530 Pilot Grant (MSB), as well as NSF Grant 2121164 (MSB), the Epstein Family Foundation Alzheimer’s Research Collaboration Gene Therapy Program, and USC Center for Neuronal Longevity.

Slides for this study were obtained from the Alzheimer’s Disease Research Center Neuropathology Core, funded by NIA AG066530. Author RPC’s contributions were supported by grant number 2020-225670 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation. Author MP’s contributions were supported by NIA Supplement 3P30AG066530-02S1 and NIA R36AG087310.

Research data reported in this publication was supported by the Office of the Director, National Institutes of Health under award number S10OD032285. Terri-Leigh Stephen and Laura Korobkova contributed equally to this work. Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA, 90033, USA Terri-Leigh Stephen, Laura Korobkova, Kenneth Nguyen, Maricarmen Pachicano, Bayla Breningstall, Ryan P.