Experimental gerontology · 2026
In silico analysis of transcriptomic datasets reveals nonlinear gene expression trajectories in aging microglia and Alzheimer's disease.
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Muedano-Sosa Andrés, Trujillo-Pineda Magalli, Ruiz-Pérez Samuel, Cervera Alejandra, González-Barrios Rodrigo, Arias Clorinda, Flores-León Manuel
Аннотация
BACKGROUND: Neuroinflammation, a key factor in aging and neurodegeneration, is characterized by the increased activation of microglia, the brain's resident immune cells. Microglia play a central role in maintaining brain homeostasis, and their dysregulation during aging is increasingly implicated in the onset and progression of Alzheimer's disease (AD). However, the molecular mechanisms underlying microglial state transitions across physiological and pathological aging remain poorly understood.
METHODS: To address this gap, we conducted an in silico comparative transcriptomic study using publicly available datasets from two murine bulk RNA-seq including wild-type (WT) and APP/PS1 transgenic (Tg) mice at multiple ages, one human scRNA-seq dataset with multiple ages, and data obtained from SCAD-Brain.
RESULT: Our analyses revealed that physiological microglial aging is characterized by dynamic, non-linear gene expression trajectories, whereby genes involved in mitochondrial function, lysosomal degradation, and immune response follow a mirror-like pattern across aging. This mirror-like behavior was conserved in human microglial data across ages. In contrast, this adaptive pattern was disrupted at late-stage pathological aging in Tg mice, where sustained alterations in inflammatory, mitochondrial, and lysosomal pathways became more pronounced. Consistent with these findings, genes dysregulated in Tg mice showed similar expression trends in AD patients in the SCAD-Brain database.
CONCLUSION: These results suggest that middle age may represent a critical transition stage preceding neuroinflammation and neurodegeneration, making it an attractive window to identify preventive or therapeutic targets in early AD. Collectively, this study identifies candidate pathways and genes that warrant further experimental validation in the context of AD and age-related neurodegeneration.
METHODS: To address this gap, we conducted an in silico comparative transcriptomic study using publicly available datasets from two murine bulk RNA-seq including wild-type (WT) and APP/PS1 transgenic (Tg) mice at multiple ages, one human scRNA-seq dataset with multiple ages, and data obtained from SCAD-Brain.
RESULT: Our analyses revealed that physiological microglial aging is characterized by dynamic, non-linear gene expression trajectories, whereby genes involved in mitochondrial function, lysosomal degradation, and immune response follow a mirror-like pattern across aging. This mirror-like behavior was conserved in human microglial data across ages. In contrast, this adaptive pattern was disrupted at late-stage pathological aging in Tg mice, where sustained alterations in inflammatory, mitochondrial, and lysosomal pathways became more pronounced. Consistent with these findings, genes dysregulated in Tg mice showed similar expression trends in AD patients in the SCAD-Brain database.
CONCLUSION: These results suggest that middle age may represent a critical transition stage preceding neuroinflammation and neurodegeneration, making it an attractive window to identify preventive or therapeutic targets in early AD. Collectively, this study identifies candidate pathways and genes that warrant further experimental validation in the context of AD and age-related neurodegeneration.