Integration of Mendelian Randomization to explore the genetic influences of pediatric sepsis: a focus on RGL4, ATP9A, MAP3K7CL, and DDX11L2

• Published in: BMC pediatrics Vol. 25; no. 1; pp. 66 - 11
• Main Authors: Zhang, Liuzhao, Chu, Quanwang, Jiang, Shuyue, Shao, Bo
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 27.01.2025; BioMed Central; BMC
• Subjects: Analysis; ATP9A; Biomarkers; Child; Child, Preschool; Datasets; DEAD-box RNA Helicases - genetics; Demographic aspects; Differential expression analysis; Female; Gene expression; Genetic aspects; Genetic markers; Genetic Predisposition to Disease; Genomes; Genomics; GTPase-Activating Proteins - genetics; Humans; Immune response; Immune system; Infections; Inflammation; Influence; Male; MAP3K7CL; Mendelian Randomization; Mendelian Randomization Analysis; Mitochondrial Proton-Translocating ATPases - genetics; Pathogens; Pathophysiology; Pediatric sepsis; Pediatrics; Polymorphism, Single Nucleotide; RGL4; Risk factors; Sepsis; Sepsis - genetics; Sepsis - immunology; China; Immune cell infiltration; Differential expression analysis; MAP3K7CL; Mendelian Randomization; Pediatric sepsis; RGL4; ATP9A; DDX11L2
• DOI: 10.1186/s12887-025-05424-y
• ISSN: 1471-2431

This study aims to explore the genetic characteristics of pediatric sepsis through a combined analysis of multiple methods, including Mendelian Randomization (MR), differential gene expression analysis, and immune cell infiltration assessment. It explores their potential as biomarkers for sepsis risk and their involvement in immune-related pathways. Differential expression analysis was performed using public datasets to identify genes with significant expression changes between pediatric sepsis patients and healthy controls. MR analysis utilized genome-wide significant SNPs as instrumental variables to assess causal relationships between gene expression and sepsis risk. Bi-directional MR was conducted to assess both forward and reverse causality. FDR correction was applied to adjust for multiple comparisons in MR results. Immune cell infiltration analysis was performed to investigate the genes' roles in immune responses, and findings were validated with independent datasets. ROC curves were constructed to assess predictive performance. Differential expression analysis identified significant changes in RGL4,ATP9A,MAP3K7CL, and DDX11L2. MR analysis revealed causal associations between these genes and sepsis risk, with RGL4 and ATP9A upregulated (inflammatory roles), and MAP3K7CL and DDX11L2 downregulated (protective roles). Bi-directional MR found no significant reverse causality. Immune cell analysis showed associations with key immune cell types, and ROC analysis demonstrated strong predictive potential. RGL4,ATP9A,MAP3K7CL, and DDX11L2 play important roles in pediatric sepsis risk and immune response regulation, offering insights into genetic and immune mechanisms that may inform future sepsis research and treatment.