Expression data analysis to identify biomarkers associated with asthma in children.

Wen Xu

doi:10.1155/2014/165175

Abstract

Asthma is characterized by recurrent episodes of wheezing, shortness of breath, chest tightness, and coughing. It is usually caused by a combination of complex and incompletely understood environmental and genetic interactions. We obtained gene expression data with high-throughput screening and identified biomarkers of children's asthma using bioinformatics tools. Next, we explained the pathogenesis of children's asthma from the perspective of gene regulatory networks: DAVID was applied to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enriching analysis for the top 3000 pairs of relationships in differentially regulatory network. Finally, we found that HAND1, PTK1, NFKB1, ZIC3, STAT6, E2F1, PELP1, USF2, and CBFB may play important roles in children's asthma initiation. On account of regulatory impact factor (RIF) score, HAND1, PTK7, and ZIC3 were the potential asthma-related factors. Our study provided some foundations of a strategy for biomarker discovery despite a poor understanding of the mechanisms underlying children's asthma.

Highlights

Asthma is the most common chronic inflammatory disease of the trachea in childhood characterized by variable and recurring symptoms, reversible airflow obstruction, and bronchospasm [1]
Asthma prevalence is rising worldwide and according to the report of International Children’s Asthma and Allergic Organization (ISAAC), the incidence rate of British children’s asthma rose from 10.2% at 2000 to 20.9% at 2011 [2]; the prevalence in American children below 17 years increased from 3.2% at 1999 to 5.7% at 2010 [3]
Some genetic variants may cause asthma only when they are combined with specific environmental exposures [10], for example, a specific single nucleotide polymorphism in the CD14 region and exposure to endotoxin [11]

Summary

Introduction

Asthma is the most common chronic inflammatory disease of the trachea in childhood characterized by variable and recurring symptoms, reversible airflow obstruction, and bronchospasm [1]. Asthma prevalence is rising worldwide and according to the report of International Children’s Asthma and Allergic Organization (ISAAC), the incidence rate of British children’s asthma rose from 10.2% at 2000 to 20.9% at 2011 [2]; the prevalence in American children below 17 years increased from 3.2% at 1999 to 5.7% at 2010 [3]. Asthma is thought to be caused by a combination of genetic and environmental factors [5], which influence both the severity and responsiveness of asthma in treatment [6]. Some genetic variants may cause asthma only when they are combined with specific environmental exposures [10], for example, a specific single nucleotide polymorphism in the CD14 region and exposure to endotoxin [11]. Understanding the genetic basis of asthma susceptibility will allow disease prediction and risk stratification [12]

Methods

Results

Conclusion