Robust differences in cortical cell type proportions across healthy human aging inferred through cross-dataset transcriptome analyses.
Aging
Cell type proportions
Deconvolution
Gene expression
Microarray
Mixed effect models
RNAseq
Journal
Neurobiology of aging
ISSN: 1558-1497
Titre abrégé: Neurobiol Aging
Pays: United States
ID NLM: 8100437
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
received:
20
05
2022
revised:
22
01
2023
accepted:
24
01
2023
pubmed:
26
2
2023
medline:
25
3
2023
entrez:
25
2
2023
Statut:
ppublish
Résumé
Age-related declines in cognitive function are driven by cell type-specific changes in the brain. However, it remains challenging to study cellular differences associated with healthy aging as traditional approaches scale poorly to the sample sizes needed to capture aging and cellular heterogeneity. Here, we employed cellular deconvolution to estimate relative cell type proportions using frontal cortex bulk gene expression from individuals without psychiatric conditions or brain pathologies. Our analyses comprised 8 datasets and 6 cohorts (1142 subjects and 1429 samples) with ages of death spanning 15-90 years. We found aging associated with profound differences in cellular proportions, with the largest changes reflecting fewer somatostatin- and vasoactive intestinal peptide-expressing interneurons, more astrocytes and other non-neuronal cells, and a suggestive "U-shaped" quadratic relationship for microglia. Cell type associations with age were markedly robust across bulk-and single nucleus datasets. Altogether, we present a comprehensive account of proportional differences in cortical cell types associated with healthy aging.
Identifiants
pubmed: 36841202
pii: S0197-4580(23)00021-0
doi: 10.1016/j.neurobiolaging.2023.01.013
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
49-61Subventions
Organisme : CIHR
ID : NGN-171423
Pays : Canada
Organisme : CIHR
ID : PJT-175254
Pays : Canada
Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.