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Identifying Potential Biomarkers Associated with Sebum Production, Pore Enlargement, and Comedones Using Transcriptomic Approaches

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE308390
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The molecular mechanisms underlying skin pore issues—excessive sebum secretion, pore enlargement, and comedone formation—remain poorly defined. We collected skin samples from four groups—dry skin without enlarged pores (DNEP), oily skin without pores (ONEP), oily skin with enlarged pores (OEP), oily skin with pores and comedones (OEPC)—measured physiological parameters, identified differentially expressed genes (DEGs) via RNA sequencing, conducted KEGG/GO enrichment analysis for DEGs, and used canonical correlation analysis to explore gene expression-physiological parameter relationships. Group comparisons revealed key genes and pathways: sebum production (DNEP vs. ONEP) involved lipid synthesis and inflammation, with ADM and PLAUR correlating with sebum content. Pore enlargement (ONEP vs. OEP) implicated ECM remodeling and immune processes, with IL27RA, MTOR, and PTAFR linked to skin roughness and elasticity. Comedogenesis (OEP vs. OEPC) involved lipid metabolism and differentiation, with ACADVL and CHST11 correlating with sebum and roughness. This study highlights seven core genes (ADM, PLAUR, IL27RA, MTOR, PTAFR, ACADVL, CHST11) and immune-inflammatory/ECM-receptor pathways as critical drivers of pore phenotypes, suggesting promising therapeutic targets. Microbiopsy collection Facial skin biopsies on the cheekbone were extracted using microbiopsy tools (Trajan Scientific and Medical, Melbourne, Australia, described by Lin et al14.) by trained staff for gene expression assessments. Next, the microbiopsy device lancet was sterily removed and stored at –80°C. RNA extraction and sequencing Total RNA was isolated from samples using Trizol reagent. RNA concentration and quality were assessed with a NanoDrop spectrophotometer. Starting from three micrograms of total RNA, sequencing libraries were prepared. mRNA was enriched using poly-T oligo-attached magnetic beads and fragmented. Double-stranded cDNA was synthesized, end-repaired, adenylated, and ligated with Illumina adapters. Library fragments were size-selected (400-500 bp) using AMPure XP system. Enrichment PCR (15 cycles) was performed, followed by purification and quality assessment on a Bioanalyzer 2100 system. Raw data were sequenced and generated in FASTQ format on the Illumina NovaSeq 6000 platform of Shanghai Personal Biotechnology Co., LTD. Fastp (0.22.0) software was used to get high quality sequence (Clean Data) for further analysis. The filtered reads were mapping to the reference genome using HISAT2 (v2.1.0). Pathway Enrichment Analysis Pathway enrichment analysis shows the gene expression information and classifies DEGs for gene annotation. ClusterProfiler (v4.6.0) software was used to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis16-18 and Gene ontology (GO) analysis of differential genes19,20. GO analysis can be divided into three parts: biological progress (BP), cellular component (CC) and molecular function (MF). KEGG is a database that integrates genomic information and biological pathways, signaling pathways, diseases, and drugs. The p-value was calculated by hypergeometric distribution method. Bonferroni-corrected p-value<0.05 was considered to be statistically significant.
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2025-09-18
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