Integrative bioinformatics analysis of pyroptosis-related genes and immune infiltration patterns in childhood asthma.

IF 2.8 3区 生物学 Q2 GENETICS & HEREDITY
Frontiers in Genetics Pub Date : 2025-06-20 eCollection Date: 2025-01-01 DOI:10.3389/fgene.2025.1557709
Di Lian, Chenye Lin, Meiling Xie, JianXing Wei, Xueling Huang, Ke Lian, Qiuyu Tang
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引用次数: 0

Abstract

Introduction: Childhood asthma (CA) is a common chronic respiratory condition that significantly impacts the respiratory function and quality of life of affected children. With a rising global incidence, CA poses substantial physical, psychological, and economic burdens. This study aimed to elucidate the role of pyroptosis-related differentially expressed genes (PRDEGs) in CA by conducting a comprehensive bioinformatics analysis using an integrated dataset from the Gene Expression Omnibus.

Methods: Differential expression analysis was performed using the R package limma, identifying 2,069 differentially expressed genes (DEGs), with 1,158 upregulated and 911 downregulated genes in CA compared with the control group. Among these DEGs, 45 PRDEGs were identified, suggesting the potential involvement of pyroptosis in the pathological processes of CA. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that PRDEGs were primarily enriched in biological processes related to the immune response, cell disassembly, and inflammatory pathways.

Results: Immune cell infiltration analysis using the CIBERSORT algorithm revealed significant differences between the CA and control groups, with increased macrophages M0, activated mast cells, and γδ T cells and decreased resting natural killer cells in the CA group. Among the six hub genes identified, BAX, BECN1, MAVS, and BCL2 exhibited statistically significant expression differences between the groups (p < 0.05 in GEO data; p < 0.0001 or p < 0.001 in quantitative real-time polymerase chain reaction validation), while NOD2 and NFKBIA showed no significant differences. Receiver operating characteristic analysis of BAX, BECN1, MAVS, and BCL2 supported their potential as diagnostic biomarkers for CA, with area under the curve values ranging from 0.602 to 0.621 (95% confidence interval: 0.510-0.712).

Discussion: Our findings provide novel insights into the molecular mechanisms underlying CA and highlight the diagnostic potential of BAX, BECN1, MAVS, and BCL2 as biomarkers. Targeting PRDEGs may offer new therapeutic avenues, and further research is warranted to validate these findings and explore the clinical applicability of suggested biomarkers in precision medicine for managing CA.

儿童哮喘热释热相关基因和免疫浸润模式的综合生物信息学分析。
儿童哮喘(CA)是一种常见的慢性呼吸系统疾病,严重影响儿童的呼吸功能和生活质量。随着全球发病率的上升,CA造成了巨大的身体、心理和经济负担。本研究旨在通过使用来自基因表达综合数据库的综合生物信息学分析,阐明热腐相关差异表达基因(PRDEGs)在CA中的作用。方法:采用R包limma进行差异表达分析,鉴定出2069个差异表达基因(deg),与对照组相比,CA中有1158个基因表达上调,911个基因表达下调。在这些DEGs中,鉴定出45个PRDEGs,表明CA的病理过程中可能参与了焦亡。基因本体和京都基因与基因组百科全书富集分析表明,PRDEGs主要富集于与免疫反应、细胞解体和炎症途径相关的生物过程中。结果:免疫细胞浸润分析CIBERSORT算法显示CA组与对照组之间存在显著差异,CA组巨噬细胞M0升高,肥大细胞和γδ T细胞活化,静息自然杀伤细胞减少。在所鉴定的6个枢纽基因中,BAX、BECN1、MAVS和BCL2组间表达差异有统计学意义(GEO数据p < 0.05);(p < 0.0001或p < 0.001),而NOD2和NFKBIA无显著差异。BAX、BECN1、MAVS和BCL2的受试者工作特征分析支持它们作为CA诊断生物标志物的潜力,曲线下面积范围为0.602至0.621(95%置信区间:0.510-0.712)。讨论:我们的研究结果为CA的分子机制提供了新的见解,并强调了BAX、BECN1、MAVS和BCL2作为生物标志物的诊断潜力。靶向PRDEGs可能提供新的治疗途径,需要进一步的研究来验证这些发现,并探索所建议的生物标志物在精准医学中治疗CA的临床适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Genetics
Frontiers in Genetics Biochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
5.50
自引率
8.10%
发文量
3491
审稿时长
14 weeks
期刊介绍: Frontiers in Genetics publishes rigorously peer-reviewed research on genes and genomes relating to all the domains of life, from humans to plants to livestock and other model organisms. Led by an outstanding Editorial Board of the world’s leading experts, this multidisciplinary, open-access journal is at the forefront of communicating cutting-edge research to researchers, academics, clinicians, policy makers and the public. The study of inheritance and the impact of the genome on various biological processes is well documented. However, the majority of discoveries are still to come. A new era is seeing major developments in the function and variability of the genome, the use of genetic and genomic tools and the analysis of the genetic basis of various biological phenomena.
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