Evidence map›Paper›PMID 40958908›Full record

ArticleFrontiers in endocrinology2025

Identifying aging-related biomarkers in adipose tissue using integrative bioinformatics and machine-learning approaches: discovery of ELN, MXD1, and FGF21 as key genes.

Xin Xie, Hongyan Wang, Fugang Xiao, Xiaoyan Jiang, Yan Chen, Chenghu Huang, Dongfeng Tang, Yanzhong Wang, Shunli Rui, Xi Cheng and 3 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Xin Xie *Department of Endocrinology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hongyan Wang *Department of Endocrinology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Fugang XiaoDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Xiaoyan JiangDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Yan ChenDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Chenghu HuangDepartment of Endocrinology, Bishan Hospital of Chongqing, Bishan Hospital of Chongqing Medical University, Bishan, Chongqing, China.
Dongfeng TangSchool of Life Course and Population Sciences, King's College London, London, United Kingdom.
Yanzhong WangSchool of Life Course and Population Sciences, King's College London, London, United Kingdom.
Shunli RuiDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Xi ChengDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Bo DengDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.
Gangyi YangDepartment of Endocrinology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Wuquan DengDepartment of Endocrinology and Metabolism, Chongqing Emergency Medical Center, Chongqing University Central Hospital, School of Medicine, Chongqing University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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. Oil Red 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 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.

Indexed as

Adipose TissueAgingBiomarkersComputational BiologyFibroblast Growth FactorsMachine LearningAnimalsHumansMaleMiceProtein Interaction MapsBiomarkersFGF21 protein, humanFibroblast Growth Factorsadipose tissueagingbioinformaticsbiomarkermachine learning

Identifiers

PMID40958908
PMCPMC12433875

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.