ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Endocrinology of Aging
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1638343
Identifying Aging-Related Biomarkers in Adipose Tissue Using Integrative Bioinformatics and Machine-Learning Approaches: Discovery of ELN, MXD1, and FGF21 as Key Genes
Provisionally accepted- 1Department of Endocrinology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- 2Department of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China
- 3Department of Endocrinology, Bishan Hospital of Chongqing, Bishan Hospital of Chongqing Medical University, Chongqing, China
- 4School of Life Course and Population Sciences, King's College London, London, United Kingdom
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Background: Adipose tissue plays a critical role in aging and age-related diseases. However, the specific molecular and cellular alterations associated with aging in adipose tissue remain incompletely understood.Methods: Aging-related differentially expressed genes (DEARGs) were identified by intersecting differentially expressed genes (DEGs) in adipose tissue, age-related genes (ARGs), and human genes linked to aging. Functional enrichment analysis was conducted to explore the potential roles of these DEARGs. Protein-protein interaction (PPI) networks were analyzed using STRING, and hub DEARGs were identified via least absolute shrinkage and selection operator (LASSO) analysis. OilRed O staining was used to confirm adi-pocyte differentiation, and D-galactose treatment induced cellular senescence. Validation of hub DEARG expression was conducted in an independent dataset and confirmed using quantitative polymerase chain reaction (qPCR) both in vitro and in vivo.Results: Forty-nine DEARGs were identified, with functional enrichment analyses revealing significant roles in glucose homeostasis and key aging pathways, including the FoxO and JAK-STAT signaling pathways, Th17 cell dif-ferentiation, growth hormone signaling, the adiponectin pathway, and AMPK pathway. Five hub genes (PCK1, ELN, MXD1, STAT3, and FGF21) were selected through interaction network anal-ysis and LASSO regression. Expression levels of three DEARGs (ELN, MXD1, and FGF21) were validated by qPCR and an independent dataset. Conclusions: This study identified three DEARGs (ELN, MXD1, and FGF21) as potential biomarkers of adipose tissue aging, suggesting their role in organismal aging and age-related disease pathways.
Keywords: Aging, biomarker, Adipose Tissue, bioinformatics, machine learning
Received: 04 Jun 2025; Accepted: 05 Aug 2025.
Copyright: © 2025 Xie, Wang, Xiao, Jiang, Chen, Huang, Tang, Wang, Rui, Cheng, Deng, Yang and Deng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Wuquan Deng, Department of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China
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