Department of Dermatology, First Medical Center of PLA General Hospital, Beijing, China.
Department of Dermatology, Third Medical Center of PLA General Hospital, Beijing, China.
J Cosmet Dermatol. 2024 Jun;23(6):2270-2278. doi: 10.1111/jocd.16266. Epub 2024 Apr 17.
Ultraviolet radiation causes skin photoaging by producing a variety of enzymes, which impact both skin health and hinder beauty. Currently, the early diagnosis and treatment of photoaging remain a challenge. Bioinformatics analysis has strong advantages in exploring core genes and the biological pathways of photoaging.
To screen and validate key risk genes associated with plasminogen in photoaging and to identify potential target genes for photoaging.
Two human transcriptome datasets were obtained by searching the Gene Expression Omnibus (GEO) database, and the mRNAs in the GSE131789 dataset were differentially analyzed, and then the weighted gene co-expression network analysis (WGCNA) was performed to find out the strongest correlations. Template genes, interaction analysis of differentially expressed genes (DEGs), modular genes with the most WGCNA correlations, and genecard database genes related to plasminogen were performed, and further Kyoto genes and Genome Encyclopedia (KEGG) pathway analysis. Two different algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machines-recursive feature elimination (SVM-RFE), were used to find key genes. Then the data set (GSE206495) was validated and analyzed. Real-time PCR was performed to validate the expression of key genes through in vitro cellular experiments.
IFI6, IFI44L, HRSP12, and BMP4 were screened from datasets as key genes for photoaging and further analysis showed that these genes have significant diagnostic value for photoaging.
IFI6, IFI44L, HRSP12, and BMP4 play a key role in the pathogenesis of photoaging, and serve as promising potential predictive biomarkers for photoaging.
紫外线辐射通过产生多种酶导致皮肤光老化，影响皮肤健康和美容。目前，光老化的早期诊断和治疗仍是一个挑战。生物信息学分析在探索光老化的核心基因和生物途径方面具有强大的优势。
筛选和验证与光老化相关的纤溶酶原的关键风险基因，并确定光老化的潜在靶基因。
通过搜索基因表达综合数据库（GEO）数据库获得了两个人类转录组数据集，对 GSE131789 数据集进行差异分析，然后进行加权基因共表达网络分析（WGCNA）以找出最强的相关性。对模板基因、差异表达基因（DEGs）的相互作用分析、与 WGCNA 相关性最强的模块基因以及与纤溶酶原相关的 genecard 数据库基因进行了研究，并进一步进行京都基因和基因组百科全书（KEGG）通路分析。使用两种不同的算法，最小绝对收缩和选择算子（LASSO）和支持向量机递归特征消除（SVM-RFE）来寻找关键基因。然后验证和分析数据集（GSE206495）。通过体外细胞实验，实时 PCR 验证了关键基因的表达。
从数据集中筛选出 IFI6、IFI44L、HRSP12 和 BMP4 作为光老化的关键基因，进一步分析表明这些基因对光老化具有显著的诊断价值。
IFI6、IFI44L、HRSP12 和 BMP4 在光老化的发病机制中起关键作用，可作为有前途的光老化潜在预测生物标志物。
