ArticleBiomedicines2022
Identification of Hub Genes and Potential Biomarkers for Childhood Asthma by Utilizing an Established Bioinformatic Analysis Approach.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- T-bet: biological functions, molecular mechanisms, and therapeutic applications: a systematic review.Frontiers in immunology · 2026Pooled it
- Identification of Metabolic Pathways and Hub Genes Associated with Ultrasound Subcutaneous Fat and Muscle Depth of the Longissimus Muscle in Cull Beef Cows Using Gene Co-Expression Analysis.Animals : an open access journal from MDPI · 2025Article
- Gene network analysis identifies dysregulated pathways in an autism spectrum disorder caused by mutations in Transcription Factor 4.Scientific reports · 2025Article
- Genome-wide association study comparison analysis based on Hanwoo full-sib family.Animal bioscience · 2024Article
- Differences in the DNA methylome of T cells in adults with asthma of varying severity.Clinical epigenetics · 2024Article
- Asthma-Genomic Advances Toward Risk Prediction.Clinics in chest medicine · 2024Review
- Differences in the DNA Methylome of T cells in Adults With Asthma of Varying Severity.Research square · 2024Article
- Biomarkers Reflecting the Severity of Bronchial Asthma in Children.Journal of asthma and allergy · 2024Article
- Integrated genomic network analysis revealed potential of a druggable target for hemorrhoid treatment.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2023Article
- Bioinformatic Analysis of Key Regulatory Genes in Adult Asthma and Prediction of Potential Drug Candidates.Molecules (Basel, Switzerland) · 2023Article
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein−protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.
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