糖皮质激素在脓毒症治疗中免疫调节机制的生物信息学探索

目的探索糖皮质激素用于脓毒症患者引起的差异表达基因。方法从GEO数据库下载基因芯片数据集,按照糖皮质激素治疗前后分为两组,通过数据处理后筛选出差异基因,再经过功能通路富集(GO、KEGG、GSEA)及蛋白相互作用网络(PPI)筛选出关键基因。结果两组数据共筛选出685个差异基因,GO、KEGG、GSEA与PPI主要富集到粒细胞活化及免疫应答通路等,基因FPR2、RETN、HMA1、UBB、TFRC、RUMX1参与广泛的基因间调节作用。结论生物信息学技术有助于对脓毒症免疫药物治疗机制的认识。

Bioinformatics exploration of immunoregulatory mechanism of glucocorticoids in the treatment of sepsis

Objective To explore the differential expressed genes（DEGs） in sepsis patients treated by glucocorticoids. Methods The gene chip datasets were obtained from the Gene Expression Omnibus （GEO） database. Then the common differential genes were carried out for later analyses according to the glucocorticoid treatment. The genes were analyzed by Gene ontology （GO）， pathway enrichment analysis （KEGG， GSEA） and Protein?protein interaction （PPI） network forscreening out key genes. Results A total of 685 genes in the two groups were identified as DEGs （P<0.05）， and GO， KEGG， GSEA and PPI were mainly enriched into granulocyte activation and immune response pathways. The genes of FPR2， RETN， HMA1， UBB， TFRC and RUMX1 were involved in a wide range of intergenic regulation.Conclusion Bioinformatics technology contributes to the understanding of the mechanisms of immunotherapy for sepsis.