No abstract available.
Asthma* ; Genetics*

No Abstracts Available.
Asthma* ; Genetics*

Using an integrated bioinformatics approach to find novel biomarkers that can predict asthma severity. From June 2022 to December 2022, this clinical medical study was conducted and completed in the Department of Allergy, Zhongnan Hospital of Wuhan University. The gene chip dataset GSE43696 was screened and downloaded from the high-throughput Gene Expression Omnibus (GEO) database, and the gene chip data preprocessing was completed using package "affy" in R and "rma" algorithm in turn. Use the the "edgeR" and "limma" packages to screen out the differentially expressed genes (DEGs) between normal controls, mild to moderate asthma patients and severe asthma patients, and then use the "clusterProfiler" package to perform GO enrichment analysis and KEGG pathway enrichment analysis of DEGs, finally use the STRING website to construct a protein-protein interaction (PPI) network of DEGs to further screen key genes. Using the R language "WGCNA" package, the weighted gene co-expression network analysis (WGCNA) was performed on the dataset GSE43696, and the modules significantly related to the severity of asthma were screened out, then the hub genes were obtained by intersecting the WGCNA analysis results with the DEGs screened by PPI. Datasets GSE43696 and GSE63142 were used to verify the expression of hub genes, and the diagnostic value was evaluated according to the ROC curve, then the potential function of hub genes in dataset GSE43696 was further clarified by gene set enrichment analysis (GSEA). The results showed that a total of 251 DEGs were screened, including 39 in the normal group and mild to moderate asthma group, 178 in the normal group and severe asthma group, and 34 in the mild to moderate asthma group and severe asthma group, mainly involved in biological processes such as response to toxic substance, response to oxidative stress, extracellular structure organization, extracellular matrix organization. Two modules significantly correlated with asthma severity were screened out (red module, P=7e-6, r=0.43; pink module, P=5e-8, r=-0.51), and finally six hub genes were obtained, including B3GNT6, CEACAM5, CCK, ERBB2, CSH1 and DPPA5. The comparison of gene expression levels and ROC curve analysis of datasets GSE43696 and GSE63142 further verified the six hub genes, which may associated with o-glycan biosynthesis, alpha linolenic acid metabolism, linoleic acid metabolism, pentose and glucoronate interconversions. In conclusion, through a variety of bioinformatics analysis methods, this study identified six hub genes significantly related to the severity of asthma, which potentially provided a new direction for the prediction and targeted therapy of asthma.
Humans ; Asthma/genetics* ; Computational Biology ; Hospitals

Using an integrated bioinformatics approach to find novel biomarkers that can predict asthma severity. From June 2022 to December 2022, this clinical medical study was conducted and completed in the Department of Allergy, Zhongnan Hospital of Wuhan University. The gene chip dataset GSE43696 was screened and downloaded from the high-throughput Gene Expression Omnibus (GEO) database, and the gene chip data preprocessing was completed using package "affy" in R and "rma" algorithm in turn. Use the the "edgeR" and "limma" packages to screen out the differentially expressed genes (DEGs) between normal controls, mild to moderate asthma patients and severe asthma patients, and then use the "clusterProfiler" package to perform GO enrichment analysis and KEGG pathway enrichment analysis of DEGs, finally use the STRING website to construct a protein-protein interaction (PPI) network of DEGs to further screen key genes. Using the R language "WGCNA" package, the weighted gene co-expression network analysis (WGCNA) was performed on the dataset GSE43696, and the modules significantly related to the severity of asthma were screened out, then the hub genes were obtained by intersecting the WGCNA analysis results with the DEGs screened by PPI. Datasets GSE43696 and GSE63142 were used to verify the expression of hub genes, and the diagnostic value was evaluated according to the ROC curve, then the potential function of hub genes in dataset GSE43696 was further clarified by gene set enrichment analysis (GSEA). The results showed that a total of 251 DEGs were screened, including 39 in the normal group and mild to moderate asthma group, 178 in the normal group and severe asthma group, and 34 in the mild to moderate asthma group and severe asthma group, mainly involved in biological processes such as response to toxic substance, response to oxidative stress, extracellular structure organization, extracellular matrix organization. Two modules significantly correlated with asthma severity were screened out (red module, P=7e-6, r=0.43; pink module, P=5e-8, r=-0.51), and finally six hub genes were obtained, including B3GNT6, CEACAM5, CCK, ERBB2, CSH1 and DPPA5. The comparison of gene expression levels and ROC curve analysis of datasets GSE43696 and GSE63142 further verified the six hub genes, which may associated with o-glycan biosynthesis, alpha linolenic acid metabolism, linoleic acid metabolism, pentose and glucoronate interconversions. In conclusion, through a variety of bioinformatics analysis methods, this study identified six hub genes significantly related to the severity of asthma, which potentially provided a new direction for the prediction and targeted therapy of asthma.
Humans ; Asthma/genetics* ; Computational Biology ; Hospitals

OBJECTIVETo elucidate the development of mapping and localization of susceptible genes on chromosomes to asthma related phenotypes.

DATA SOURCESPublished articles about susceptibility genes for asthma related phenotypes were selected using PubMed.

STUDY SELECTIONUsing methods of candidate gene positional clone and genome-wide scan with linkage and association analysis to determine the location in the genome of susceptibility genes to asthma and asthma related phenotypes.

RESULTSThere are multiple regions in the genome harboring susceptibility genes to asthma and asthma related phenotypes, including chromosomes 5, 11, 12, 6, 2, 3, 13, 7, 14, 9, 19 and 17. Many of these regions contain candidate genes involved in asthma development and progression. Some susceptible genes may affect the phenotype expression or response to therapy. In addition, the interaction of multiple genes with the environment may contribute to the susceptibility to asthma.

CONCLUSIONSAs an essential step toward cloning the susceptible genes to asthma, fine mapping and localization on chromosomes are definitely needed. Novel powerful tools for gene discovery and the integration of genetics, biology and bioinformatics should be pursued.

Bronchial asthma (i.e. asthma) is a chronic inflammatory disease characterized by airway inflammatory response, hyperresponsiveness and airway remodeling, in which T cells play a vital role, especially T helper cells (Th cells). Non-coding RNAs (ncRNAs) are the RNAs that do not encode proteins, mainly including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which are widely found in eukaryotic genomes and participate in the regulation of various biological processes. Previous studies have shown that ncRNAs play an important role in the activation and transformation of T cells and other biological processes in asthma. The specific molecular mechanism and clinical application are worth in-depth discussion. This article reviewed the research progress in regulation of miRNAs, lncRNAs and circRNAs on T cells in asthma in recent years.
Asthma/genetics* ; Humans ; MicroRNAs/genetics* ; RNA, Long Noncoding/genetics* ; RNA, Untranslated/genetics* ; T-Lymphocytes

Since Cookson et al. first reported the association of atopy with chromosome 11q13 in 1989, there have been numerous studies of genetics for allergic diseases. Their aim is to identify genetic factors modifying susceptibility to allergic diseases, determining the severity of disease in affected individuals and affecting the response to treatment. With these efforts, allergic diseases can be termed complex genetic disorders, defined as disorders that have numerous contributing genes, each having variable degrees of involvement in any given individual. This review aims to provide information on the current state of genetic research in Korean pediatric allergic diseases.
Asthma ; Child* ; Genetic Research* ; Genetics ; Humans ; Hypersensitivity ; Korea ; Pediatrics

Proteomic tools were used to identify the key proteins that might be associated with bronchial asthma(BA). Firstly, the serum samples from healthy adults and asthmatic patients were collected. Tandem Mass Tag~(TM)(TMT), which removes high-abundance structures and nonspecific proteins, was employed to identify the differentially expressed proteins between asthmatic patients and healthy adults. Gene Ontology(GO) annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were carried out for the differentially expressed proteins. The core proteins in the asthma group were screened out by protein-protein interaction(PPI) analysis. Then the core proteins were verified by Western blot for 3 patients with bronchial asthma and 3 healthy adults. A total of 778 differentially expressed proteins were screened out, among which 32 proteins contained quantitative information, including 18 up-regulated proteins and 14 down-regulated proteins. The differentially expressed proteins were enriched in 28 KEGG signaling pathways. The PPI analysis showed that 10 proteins(GDN, 1433 Z, VWF, HEMO, CERU, A1 AT, TSP1, G3 P, IBP7, and KPYM) might be involved in the pathogenesis of bronchial asthma. Compared with those in healthy adults, the expression levels of SLC25 A4, SVEP1, and KRT25 in the sera of asthmatic patients were up-regulated(P<0.05). Therefore, it is hypothesized that a variety of immune signaling pathways and differentially expressed proteins play a role in the pathogenesis of BA, which provides potential target information for the treatment of BA.
Adult ; Humans ; Proteomics ; Gene Ontology ; Proteins ; Disease Susceptibility ; Asthma/genetics*

The relationship between 3 polymorphisms sites [interleulin-4 (IL-4), IL-4 receptor (IL-4R) alpha chain and activation-induced cytidine deaminase (AICDA)] and adult allergic asthma in China was studied. By using case-control method, DNA and clinical data were obtained from allergic asthmatic patients and compared with those in the control subjects. The subjects were genotyped for the IL-4 C-589T promoter polymorphism, the IL-4R alpha chain Q576R and the AICDA C8408T by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The results showed that the IL-4 C-589T was not associated with adult allergic asthma in China. However, the IL-4R alpha chain 576R/R and AICDA 8408T/T frequency was significantly increased in allergic asthma group as compared with that in the control group [odd ratio (OR) = 3.797 and 9.127, respectively; P < 0.01)] and was correlated with the increased plasma total IgE. These data suggested that the IL-4R alpha chain 576R/R and AICDA 8408T/T genotypes confer genetic susceptibility to adult allergic asthma in China.
Alleles ; Asthma/etiology ; Asthma/*genetics ; Cytidine Deaminase/*genetics ; Immunoglobulin E/blood ; Interleukin-4/*genetics ; Phenotype ; *Polymorphism, Restriction Fragment Length ; RNA Processing, Post-Transcriptional ; Receptors, Interleukin-4/*genetics

Allergic diseases mentioned in this review is regarding to I type allergic inflammation induced by an IgE-mediated reaction, including asthma, allergic rhinitis, atopic dermatitis and food allergy. It is convinced that allergic diseases belong to multiple genes diseases and are controlled by both genetic and environmental factors. Meanwhile there exists gene-gene as well as gene-environment interactions during the development of the disease. The aim of this review is to summarize the toolkit, advance, inherent difficulties and future clinical application prospect in genetic studies of allergic disease.
Asthma ; genetics ; Gene-Environment Interaction ; Humans ; Hypersensitivity ; genetics ; Immunoglobulin E ; Rhinitis, Allergic, Perennial ; genetics ; Rhinitis, Allergic, Seasonal ; genetics ; Risk Factors