CellNeurosciencePeer-reviewed journal article
Spatial and temporal transcriptomics reveal microglia-astroglia crosstalk in the amyloid-β plaque cell niche of Alzheimer’s disease
Wei-Ting CheniD, Ashley Lu, Katleen CraessaertsiD, Benjamin PavieiD, Carlo Sala FrigerioiD, Nikky CorthoutiD, Xiaoyan QianiD, Jana LalákováiD, Malte KühnemundiD, Iryna VoytyukiD, Leen WolfsiD, Renzo MancusoiD, Evgenia SaltaiD, Sriram BalusuiD, An Snellinx, Sebastian MunckiD, Aleksandra Jurek, José Fernández NavarroiD, Takaomi C. SaidoiD, Inge HuitingaiD, Joakim LundebergiD, Mark W. E. J. FiersiD, Bart De StrooperiD
Abstract
The linear cause-consequence relationship linking amyloid-{beta} peptide (A{beta}) accumulation to neuronal dysfunction in Alzheimer disease (AD) is gradually replaced by the concept that A{beta} initiates complex inflammatory-like cellular alterations that progressively become A{beta} independent and lead to brain dyshomeostasis. Little is known about the pathophysiology of this cellular phase of AD. We use here two orthogonal technologies, Spatial Transcriptomics and in situ sequencing, to analyse the transcriptome changes in cells in the amyloid-{beta} plaque niche in a knock-in mouse model for AD. We identify a multicellular co-expressed gene network of 57 Plaque-Induced Genes (PIGs) that define a series of co-ordinated and spatially restricted microglia, astroglia and oligodendrocyte responses to progressing amyloid plaques encompassing complement, oxidative stress and inflammation. A separate oligodendrocyte network suggests abnormal myelination. Spatial Transcriptomics provides an unprecedented approach to untangle the dysregulated cellular network in the vicinity of pathogenic hallmarks of AD and other brain diseases.
- organism: mouse
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 951
- FWCI
- 38.51
- Field percentile
- top 1%
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