Evidence map›Paper›PMID 39871218›Full record

ArticleBMC pediatrics2025

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

Liuzhao Zhang, Quanwang Chu, Shuyue Jiang, Bo Shao

Abstract read
In one paragraph

Article in BMC pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liuzhao ZhangDepartment of Critical Care Medicine, Anhui Jing'an Medicine Hospital, Hefei, 230032, China.
Quanwang ChuDepartment of Critical Care Medicine, Anhui Jing'an Medicine Hospital, Hefei, 230032, China.
Shuyue JiangDepartment of Critical Care Medicine, Anhui Jing'an Medicine Hospital, Hefei, 230032, China.
Bo ShaoDepartment of Pathology, Anhui Provincial Children's Hospital, 39 Wangjiang East Road, Hefei, Anhui, 230051, China. shaobo5988@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis 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.

methodsDifferential 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.

resultsDifferential 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.

conclusionRGL4,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.

Indexed as

DEAD-box RNA HelicasesGTPase-Activating ProteinsMendelian Randomization AnalysisMitochondrial Proton-Translocating ATPasesSepsisChildChild, PreschoolFemaleGenetic Predisposition to DiseaseHumansMalePolymorphism, Single NucleotideDEAD-box RNA HelicasesGTPase-Activating ProteinsMitochondrial Proton-Translocating ATPasesATP9ADDX11L2Differential expression analysisImmune cell infiltrationMAP3K7CLMendelian RandomizationPediatric sepsisRGL4

Identifiers

PMID39871218
PMCPMC11770931

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.