Abstract
BACKGROUND: Severe asthma is a chronic disease contributing to disproportionate disease morbidity and mortality. From the year of 2007, many genome-wide association studies (GWAS) have documented a large number of asthma-associated genetic variants and related genes. Nevertheless, the molecular mechanism of these identified variants involved in asthma or severe asthma risk remains largely unknown. METHODS: In the current study, we systematically integrated 3 independent expression quantitative trait loci (eQTL) data (N = 1977) and a large-scale GWAS summary data of moderate-to-severe asthma (N = 30,810) by using the Sherlock Bayesian analysis to identify whether expression-related variants contribute risk to severe asthma. Furthermore, we performed various bioinformatics analyses, including pathway enrichment analysis, PPI network enrichment analysis, in silico permutation analysis, DEG analysis and co-expression analysis, to prioritize important genes associated with severe asthma. RESULTS: In the discovery stage, we identified 1129 significant genes associated with moderate-to-severe asthma by using the Sherlock Bayesian analysis. Two hundred twenty-eight genes were prominently replicated by using MAGMA gene-based analysis. These 228 replicated genes were enriched in 17 biological pathways including antigen processing and presentation (Corrected P = 4.30 × 10(- 6)), type I diabetes mellitus (Corrected P = 7.09 × 10(- 5)), and asthma (Corrected P = 1.72 × 10(- 3)). With the use of a series of bioinformatics analyses, we highlighted 11 important genes such as GNGT2, TLR6, and TTC19 as authentic risk genes associated with moderate-to-severe/severe asthma. With respect to GNGT2, there were 3 eSNPs of rs17637472 (P(eQTL) = 2.98 × 10(- 8) and P(GWAS) = 3.40 × 10(- 8)), rs11265180 (P(eQTL) = 6.0 × 10(- 6) and P(GWAS) = 1.99 × 10(- 3)), and rs1867087 (P(eQTL) = 1.0 × 10(- 4) and P(GWAS) = 1.84 × 10(- 5)) identified. In addition, GNGT2 is significantly expressed in severe asthma compared with mild-moderate asthma (P = 0.045), and Gngt2 shows significantly distinct expression patterns between vehicle and various glucocorticoids (Anova P = 1.55 × 10(- 6)). CONCLUSIONS: Our current study provides multiple lines of evidence to support that these 11 identified genes as important candidates implicated in the pathogenesis of severe asthma.