Potential Targets Related to Skin Aging: Based on eQTL and GWAS Datasets

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. To identify target genes related to SG through bioinformatics technology and provide ideas for skin anti-aging. 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. 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. 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.