Deep spatial phenotyping of microglial populations and pathological features in Alzheimer's disease brains using CODEX Multiplexed Imaging. (20th December 2022)

• Record Type: Journal Article
• Authors: Sanchez‐Molina, Paula; Pratapa, Aditya; Singh, Jasmine; Chiot, Aude; Bogachuk, Alina; Nikulina, Nadezhda; Woltjer, Randy; Braubach, Oliver; Ajami, Bahareh
• Is Part Of: Alzheimer's & dementia. Volume 18(2022)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-20
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.066433
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Recent high‐throughput transcriptomics and proteomics analysis have shown a remarkable heterogeneity of microglia phenotypes across various disease conditions. Differently from neurons, microglia appearance can be characterized as a continuum between ramified and amoeboid morphologies. The transcriptional and proteomic profiles associated to each degree of morphology are potentially multiple and dependent on the healthy/pathological conditions in consideration with sex, anatomical area of the brain and disease stage. While single‐cell RNA sequencing (scRNA‐seq) has been instrumental in revealing microglia sub‐populations, it is lacking in spatial information and phenotypic characterization. The scarcity of fresh human brain tissue imposes a bottleneck for RNA‐seq studies, while paraffin‐embedded tissues are widely available in most brain banks. CODEX multiplexed imaging technology permits a deep characterization of microglial cells preserving their morphology and avoiding cell activation by aggressive sample preparation methods as occurs in tissue homogenates. Moreover, we can discriminate the immune cells in brain blood vessel from those in the parenchyma. Method: Using this technology, we characterize microglia sub‐population localization in relationship to the distance from neurodegenerative disease pathogenic features in post‐mortem AD brain samples and matching controls. Bioinformatics analysis were performed to achieve microglial segmentation to a single‐cell level and cell clustering by protein expression. Result: Our results show the existence of different microglial cells populations, which vary between AD and control brains. Expression of blood‐derived macrophages markers was observed in parenchymal ramified cells close to blood vessels and/or Aβ plaques. We were able to deeply characterize this population and measure their distance to the nearest blood vessel and Aβ plaque. Microglial/macrophages activation markers were increased correlating with the distance to the plaques. Conclusion: This study allowed us to characterize the changes of microglia phenotype in the immediate neighborhood of pathogenic features. Such observation will be instrumental to understanding the role of several Late Onset Alzheimer's Diseases associated genes and potentially identify novel drug targets.