GLCCI1 gene body methylation in peripheral blood is associated with asthma and asthma severity

Jiang, Yuanyuan; Xun, Qiufen; Wan, Rongjun; Deng, Shenghua; Hu, Xinyue; Luo, Lisha; Li, Xiaozhao; Feng, Juntao

doi:10.1016/j.cca.2021.09.006

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…It can reduce collagen deposition and airway hyper-responsiveness in a mouse asthma model through binding with WD repeat domain 45B and represses airway remodeling of the asthmatic mouse via inhibiting IL-13/periostin/ TGF-β1 signaling. In addition, the reduced methylation level of the GLCCI1 gene body in peripheral blood influences PI3k-Akt and MAPK pathways and it may be contributed to detect asthma and asthma severity, 16,28,29 which may further strengthen the understanding of the role and mechanism of GLCCI1 contributed to the pathogenesis of AR.…”

Section: Discussionmentioning

confidence: 99%

Glucocorticoid-Induced Transcript 1(GLCCI1) SNP rs37937 Is Associated With the Risk of Developing Allergic Rhinitis and the Response to Intranasal Corticosteroids in a Chinese Han Population

Peng

Zhan

et al. 2023

Am J Rhinol�Allergy

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Background Evidence has shown that glucocorticoid-induced transcript 1 (GLCCI1) single nucleotide polymorphism (SNP) rs37937 is associated with asthma. Objectives The objective of this study was to investigate whether the GLCCI1 SNP rs37937 is a risk factor for allergic rhinitis (AR) in a Chinese Han population. Methods A total of 220 individuals including 109 AR patients and 111 healthy subjects were included. The genotyping of GLCCI1 rs37973 was performed by the SNaPshot method. The correlations of rs37973 polymorphism, AR risk, and clinical characteristics were further analyzed, as well as the treatment response to intranasal corticosteroids (INCS) in AR patients of different genotypes. Results Three GLCCI1 rs37973 SNP genotypes were identified in both AR patients and healthy subjects. Significant association between rs37973 polymorphism and AR under allele model, dominant model, heterozygote model, and homozygote model were shown. The A allele frequency of SNP rs37973 in AR was significantly higher than that in controls. The serum total immunoglobulin E (IgE) in AR patients of AA genotype was significantly higher than in patients of GA and GG genotype, and the serum total IgE in GA genotype was significantly higher than in GG genotype. Interestingly, after 4 weeks of INCS treatment for AR patients, the improvement of the nasal itching score, sneezing score, runny nose score, total nasal symptom score, and visual analog scale score of the GG genotype were worse than the AA or GA genotype. Conclusion The GLCCI1 rs37937 polymorphism is associated with the risk of developing AR and the response to INCS treatment in the Chinese Han population.

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Section: Discussionmentioning

confidence: 99%

Glucocorticoid-Induced Transcript 1(GLCCI1) SNP rs37937 Is Associated With the Risk of Developing Allergic Rhinitis and the Response to Intranasal Corticosteroids in a Chinese Han Population

Peng

Zhan

et al. 2023

Am J Rhinol�Allergy

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“…Glucocorticoid (GC)-induced transcript 1 (GLCCI1) has been studied for its association with asthma severity as well. According to Jiang et al [36] in 2021, peripheral blood mononuclear cells of asthma patients exhibited low GLCCI1 methylation, with even lower methylation levels present in severe asthma patients. Their analysis brought up five methylation sites independently correlated with the disease, whereas CpG47 is suggested to be a suitable biomarker for asthma severity.…”

Section: Severity Of Asthma/rhinitismentioning

confidence: 98%

The complexity in DNA methylation analysis of allergic diseases

Legaki¹,

Τaka²,

Papadopoulos³

2023

Current Opinion in Allergy &Amp; Clinical Immunology

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Purpose of reviewThis review aims to report all the recent studies that are implicated in DNA methylation analysis in the field of allergy and to underline the complexity of the study methodologies and results. Recent findingsAlthough the growing number of DNA methylation studies have yet to point to a specific mechanism, herein we provide an overview of the majority of pathways considered to be implicated and highlight particular genes, like KNH2, ATPAF2 and ZNF385A, for their potential as biomarkers.

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“…Gaffin et al [8] studied DNA methylation in peripheral blood mononuclear cells nuclear airway epithelial cells of atopic, non-atopic, and healthy asthmatic children and confirmed that multiple CpG sites in the ARDB2 gene promoter region were associated with reduced dyspnea in children. RNA methylation provided new options for asthma treatment [9,10].…”

Section: Introductionmentioning

confidence: 99%

A Methylation Diagnostic Model Based on Random Forests and Neural Networks for Asthma Identification

Chen²,

Ling

et al. 2022

Computational and Mathematical Methods in Medicine

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Background. Asthma significantly impacts human life and health as a chronic disease. Traditional treatments for asthma have several limitations. Artificial intelligence aids in cancer treatment and may also accelerate our understanding of asthma mechanisms. We aimed to develop a new clinical diagnosis model for asthma using artificial neural networks (ANN). Methods. Datasets (GSE85566, GSE40576, and GSE13716) were downloaded from Gene Expression Omnibus (GEO) and identified differentially expressed CpGs (DECs) enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Random forest (RF) and ANN algorithms further identified gene characteristics and built clinical models. In addition, two external validation datasets (GSE40576 and GSE137716) were used to validate the diagnostic ability of the model. Results. The methylation analysis tool (ChAMP) considered DECs that were up-regulated ( n =121) and down-regulated ( n =20). GO results showed enrichment of actin cytoskeleton organization and cell-substrate adhesion, shigellosis, and serotonergic synapses. RF (random forest) analysis identified 10 crucial DECs (cg05075579, cg20434422, cg03907390, cg00712106, cg05696969, cg22862094, cg11733958, cg00328720, and cg13570822). ANN constructed the clinical model according to 10 DECs. In two external validation datasets (GSE40576 and GSE137716), the Area Under Curve (AUC) for GSE137716 was 1.000, and AUC for GSE40576 was 0.950, confirming the reliability of the model. Conclusion. Our findings provide new methylation markers and clinical diagnostic models for asthma diagnosis and treatment.

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GLCCI1 gene body methylation in peripheral blood is associated with asthma and asthma severity

Cited by 4 publications

References 32 publications

Glucocorticoid-Induced Transcript 1(GLCCI1) SNP rs37937 Is Associated With the Risk of Developing Allergic Rhinitis and the Response to Intranasal Corticosteroids in a Chinese Han Population

Glucocorticoid-Induced Transcript 1(GLCCI1) SNP rs37937 Is Associated With the Risk of Developing Allergic Rhinitis and the Response to Intranasal Corticosteroids in a Chinese Han Population

The complexity in DNA methylation analysis of allergic diseases

A Methylation Diagnostic Model Based on Random Forests and Neural Networks for Asthma Identification

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