Abstract
Skin aging is the most intuitive manifestation of aging. Skin aging inevitably leads to cosmetic and psychological problems, and even diseases. The present study aims to research the pathological and molecular mechanisms underlying skin aging and identify the therapeutic agents for reversing skin aging. Two available gene expression datasets (GSE55118 and GSE72264) for skin aging were downloaded from Gene Expression Omnibus, followed by bioinformatic analyses performed on the datasets. Firstly, 169 crucial mRNAs, 27 crucial miRNAs and 50 crucial lncRNAs closely related to skin aging were identified by weighted gene co-expression network analysis. Then, function Enrichment Analysis performed by Metascape database showed that skin aging involves a variety of biological functions, such as detection of stimulus, response to steroid hormone and water channel activity, regulation of muscle contraction. Next, ten hub genes including AQP4, TRPM8, TBR1, NTSR2, MPPED1, BARHL2, PAX9, CPN1, CES3, and CHGB were screened out by the protein–protein interaction analysis. Next, the “lncRNA-miRNA-mRNA” network and the “lncRNA-miRNA-hub mRNA” network were constructed to explore the competing endogenous RNAs mechanism of skin aging. Finally, ten significant potential small molecules mitigating skin aging were screened using CMAP platform, including tretinoin, pifithrin, selamectin, entinostat, bretazenil, syringic-acid, BRD-K96475865, emedastine, abacavir, and rotenone, and their reliability was verified by molecular docking experiments. The present study provided basis for revealing the molecular mechanism of skin aging and identified the potential candidate drugs for mitigating skin aging.
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Data Availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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XX and HF carried out the studies, participated in collecting data, and drafted the manuscript. HT, YL and LL performed the statistical analysis and participated in its design. KL and FH participated in acquisition, analysis, or interpretation of data and draft the manuscript. All authors read and approved the final manuscript.
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Xiao, X., Feng, H., Liao, Y. et al. Identification of lncRNA-miRNA-mRNA Regulatory Network and Therapeutic Agents for Skin Aging by Bioinformatics Analysis. Biochem Genet 61, 1606–1624 (2023). https://doi.org/10.1007/s10528-023-10334-8
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DOI: https://doi.org/10.1007/s10528-023-10334-8