Scientific Reports (Oct 2023)

Deconvolution reveals cell-type-specific transcriptomic changes in the aging mouse brain

  • Yingxue Ren,
  • Xue Wang,
  • Shuwen Zhang,
  • Hongru Hu,
  • Zachary Quicksall,
  • Sangderk Lee,
  • Josh M. Morganti,
  • Lance A. Johnson,
  • Yan W. Asmann,
  • Na Zhao

DOI
https://doi.org/10.1038/s41598-023-44183-7
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Abstract Mounting evidence highlights the crucial role of aging in the pathogenesis of Alzheimer's disease (AD). We have previously explored human apoE-targeted replacement mice across different ages and identified distinct molecular pathways driven by aging. However, the specific contribution of different brain cell types to the gene modules underlying these pathways remained elusive. To bridge this knowledge gap, we employed a computational deconvolution approach to examine cell-type-specific gene expression profiles in major brain cell types, including astrocytes (AS), microglia (MG), oligodendroglia (OG), neurons (NEU), and vascular cells (VC). Our findings revealed that immune module genes were predominantly expressed in MG, OG, and VC. The lipid metabolism module genes were primarily expressed in AS, MG, and OG. The mitochondria module genes showed prominent expression in VC, and the synapse module genes were primarily expressed in NEU and VC. Furthermore, we identified intra- and inter-cell-type interactions among these module genes and validated their aging-associated expression changes using published single cell studies. Our study dissected bulk brain transcriptomics data at the cellular level, providing a closer examination of the cell-type contributions to the molecular pathways driven by aging.