Exploration of m6A methylation regulators as epigenetic targets for immunotherapy in advanced sepsis

• Published in: BMC bioinformatics Vol. 24; no. 1; pp. 1 - 9
• Main Authors: Qian, Weiwei, Zhou, Jian, Shou, Songtao
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 17.06.2023; BioMed Central; BMC
• Subjects: Advanced sepsis; Algorithms; B cells; Bacterial infections; Care and treatment; Cells; Cluster analysis; Correlation; Datasets; Disease; Epigenetic inheritance; Epigenetics; Gene expression; Gene set enrichment analysis; Genes; Genetic aspects; Health aspects; Helper cells; Immune system; Immunological research; Immunoregulation; Immunotherapy; Infection; Infections; Insulin-like growth factor-binding protein 1; Insulin-like growth factor-binding protein 2; Insulin-like growth factors; Lymphocytes; Lymphocytes T; m6A methylation modification; Medical research; Medicine, Experimental; Methods; Methylation; Methyltransferases; Multiple organ dysfunction syndrome; N6-methyladenosine; Physiology; Proteins; Sepsis; Statistical analysis; T cells; Therapeutic applications; Therapeutic targets; Variance analysis; Viral infections; China
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-023-05379-w

This study aims to deeply explore the relationship between m.sup.6A methylation modification and peripheral immune cells in patients with advanced sepsis and mine potential epigenetic therapeutic targets by analyzing the differential expression patterns of m.sup.6A-related genes in healthy subjects and advanced sepsis patients. A single cell expression dataset of peripheral immune cells containing blood samples from 4 patients with advanced sepsis and 5 healthy subjects was obtained from the gene expression comprehensive database (GSE175453). Differential expression analysis and cluster analysis were performed on 21 m.sup.6A-related genes. The characteristic gene was identified based on random forest algorithm, and the correlation between the characteristic gene METTL16 and 23 immune cells in patients with advanced sepsis was evaluated using single-sample gene set enrichment analysis. IGFBP1, IGFBP2, IGF2BP1, and WTAP were highly expressed in patients with advanced sepsis and m.sup.6A cluster B. IGFBP1, IGFBP2, and IGF2BP1 were positively correlated with Th17 helper T cells. The characteristic gene METTL16 exhibited a significant positive correlation with the proportion of various immune cells. IGFBP1, IGFBP2, IGF2BP1, WTAP, and METTL16 may accelerate the development of advanced sepsis by regulating m.sup.6A methylation modification and promoting immune cell infiltration. The discovery of these characteristic genes related to advanced sepsis provides potential therapeutic targets for the diagnosis and treatment of sepsis.