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已发表论文

与皮肤衰老相关的潜在靶点:基于表达定量性状位点(eQTL)和全基因组关联研究(GWAS)数据集

 

Authors Shi H, Cao X

Received 27 November 2024

Accepted for publication 5 March 2025

Published 21 March 2025 Volume 2025:18 Pages 677—686

DOI http://doi.org/10.2147/CCID.S508946

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Prof. Dr. Rungsima Wanitphakdeedecha

Hanping Shi,1,2 Xianwei Cao1– 3 

1School of Public Health, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, People’s Republic of China; 2Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, Nanchang, Jiangxi, 330006, People’s Republic of China; 3Department of Dermatology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, People’s Republic of China

Correspondence: Xianwei Cao, Department of Dermatology, The First Affiliated Hospital of Nanchang University, No. 17 Yongwai Street, Donghu District, Nanchang, Jiangxi, 330006, People’s Republic of China, Tel +86-0791-88692748, Email ndyfyygk@163.com

Background: The aging of skin has important impact on various systems, and certain skin aging (SG) markers can not only help with early diagnosis, but also provide new ideas for pathophysiological research and treatment strategies.
Objective: To identify target genes related to SG through bioinformatics technology and provide ideas for skin anti-aging.
Methods: Differential expression genes (DEGs) related to SG were screened through transcriptome information from GEO datasets (GSE85358 and GSE670988). Based on eQTL and GWAS datasets, Mendelian Randomization (MR) analysis was applied to identify associations between gene expression and SG. Then, aging skin related important genes (AS-IGs) were obtained based on above two steps, and functional and pathway analyses were performed to explore the potential mechanisms AS-IGs in SG. Finally, the CIBERSORT evaluation was used to assess the infiltration of immune cells related to SG.
Results: Seven AS-IGs were selected through intersection from 612 DEGs and 399 eQTL genes. Then, enrichment analysis results showed there were 60 GO terms may involved in the process of SG, like fatty-acyl-CoA metabolic process, while KEGG enrichment pathways identified mainly involved in mechanisms related to fatty acid metabolism, energy generation, and inflammation regulation. The CIBERSORT evaluation showed that NK cells resting were the main infiltrating cells.
Conclusion: AS-IGs may play important roles in the process of SG in the body. These molecules involve multiple systems and mechanisms in the body, such as immune function, metabolic function, and neuroendocrine function.

Keywords: skin aging, biomarkers, eQTL, GWAS, Mendelian analysis

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