4.6 Article

Integration of segmented regression analysis with weighted gene correlation network analysis identifies genes whose expression is remodeled throughout physiological aging in mouse tissues

Journal

AGING-US
Volume 13, Issue 14, Pages 18150-18190

Publisher

IMPACT JOURNALS LLC

Keywords

aging; transcriptome; mus musculus; trendy; WGCNA

Funding

  1. Portuguese Foundation for Science and Technology (FCT)
  2. FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE 2020
  3. Operational Programme for Competitiveness and Internationalization (POCI) [POCI-01-0145-FEDER-022184, POCI-01-0145-FEDER-016428-PAC, POCI-01-0145-FEDER-029843]
  4. European Regional Development Fund [Centro-01-0145-FEDER-000003, CENTRO-01-0246-FEDER-000018, POCI-01-0145-FEDER-016385]
  5. FCT [SFRH/BD/131736/2017, SFRH/BD/148323/2019, UID/BIM/04501/2020]
  6. Fundação para a Ciência e a Tecnologia [SFRH/BD/131736/2017, SFRH/BD/148323/2019] Funding Source: FCT

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The study identified tissue-specific effects of aging in the brain, heart, liver, skeletal muscle, and pancreas of C57BL/6 mice, showing alterations in immune, inflammation responses, amino acid and fatty acid metabolism, and tissue regeneration. Additionally, it revealed significant gender differences in gene expression, particularly in proteostasis-related pathways, across the lifespan, highlighting the common biological processes triggered by aging in distinct tissues.
Gene expression alterations occurring with aging have been described for a multitude of species, organs, and cell types. However, most of the underlying studies rely on static comparisons of mean gene expression levels between age groups and do not account for the dynamics of gene expression throughout the lifespan. These studies also tend to disregard the pairwise relationships between gene expression profiles, which may underlie commonly altered pathways and regulatory mechanisms with age. To overcome these limitations, we have combined segmented regression analysis with weighted gene correlation network analysis (WGCNA) to identify high-confidence signatures of aging in the brain, heart, liver, skeletal muscle, and pancreas of C57BL/6 mice in a publicly available RNA-Seq dataset (GSE132040). Functional enrichment analysis of the overlap of genes identified in both approaches showed that immune-and inflammation-related responses are prominently altered in the brain and the liver, while in the heart and the muscle, aging affects amino and fatty acid metabolism, and tissue regeneration, respectively, which reflects an age-related global loss of tissue function. We also explored sexual dimorphism in the aging mouse transcriptome and found the liver and the muscle to have the most pronounced gender differences in gene expression throughout the lifespan, particularly in proteostasis-related pathways. While the data showed little overlap among the age-dysregulated genes between tissues, aging triggered common biological processes in distinct tissues, which we highlight as important features of murine tissue physiological aging.

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