Integrated multi‐omic analyses uncover the effects of aging on cell‐type regulation in glucose‐responsive tissues

Author:

Xu Peng1234ORCID,Kong Yimeng1,Palmer Nicholette D.5,Ng Maggie C. Y.6,Zhang Bin234,Das Swapan K.7

Affiliation:

1. Center of Clinical Laboratory Medicine, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health Southeast University Nanjing China

2. Department of Genetics & Genomic Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute Icahn School of Medicine at Mount Sinai New York New York USA

3. Department of Pharmacological Sciences, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute Icahn School of Medicine at Mount Sinai New York New York USA

4. Department of Artificial Intelligence and Human Health, Mount Sinai Center for Transformative Disease Modeling, Icahn Genomics Institute Icahn School of Medicine at Mount Sinai New York New York USA

5. Department of Biochemistry Wake Forest University School of Medicine Winston–Salem North Carolina USA

6. Division of Genetic Medicine, Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville Tennessee USA

7. Department of Internal Medicine, Section on Endocrinology and Metabolism Wake Forest University School of Medicine Winston‐Salem North Carolina USA

Abstract

AbstractAging significantly influences cellular activity and metabolism in glucose‐responsive tissues, yet a comprehensive evaluation of the impacts of aging and associated cell‐type responses has been lacking. This study integrates transcriptomic, methylomic, single‐cell RNA sequencing, and metabolomic data to investigate aging‐related regulations in adipose and muscle tissues. Through coexpression network analysis of the adipose tissue, we identified aging‐associated network modules specific to certain cell types, including adipocytes and immune cells. Aging upregulates the metabolic functions of lysosomes and downregulates the branched‐chain amino acids (BCAAs) degradation pathway. Additionally, aging‐associated changes in cell proportions, methylation profiles, and single‐cell expressions were observed in the adipose. In the muscle tissue, aging was found to repress the metabolic processes of glycolysis and oxidative phosphorylation, along with reduced gene activity of fast‐twitch type II muscle fibers. Metabolomic profiling linked aging‐related alterations in plasma metabolites to gene expression in glucose‐responsive tissues, particularly in tRNA modifications, BCAA metabolism, and sex hormone signaling. Together, our multi‐omic analyses provide a comprehensive understanding of the impacts of aging on glucose‐responsive tissues and identify potential plasma biomarkers for these effects.

Funder

National Institutes of Health

Publisher

Wiley

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