Abstract
OBJECTIVE: Genome-length association studies have shown that Gasdermin B (GSDMB) and Orosomucoid-like 3 (ORMDL3) genes located on the long arm of chromosome 17 are associated with asthma. In this study, it was aimed to determine the possible relationship between asthma control test (ACT), exercise provocation test (ECT), and fractional nitric oxide (FENO) levels and GSDMB and ORMDL3 gene expressions. METHODS: 59 asthmatic and 38 non-asthmatic children were included in the study. We divided the patient group into two subgroups as mild persistent asthma (29 patients) and moderate persistent asthma (30 patients). ORMDL3, GSDMB gene expression levels, ECT, total IgE levels, and eosinophil counts were measured in all cases. In addition, ACT and FeNO levels were measured in children with asthma. Afterward, the relationship of ORMDL3 and GSDMB gene expression coefficient changes with ECT, ACT, and FeNO was examined. RESULTS: When patients with ACT ≤15 were compared with patients with ACT ≥20, ORMDL3 and GSDMB gene expressions were increased 6.74 and 11.74 times, respectively. Comparing patients with ACT ≥20 and ACT ≤15 in terms of coefficient changes (ΔCq), higher change values were observed for ΔCq ORMDL3 in patients with ACT ≤15 (p=0.015). Similarly, when patients with FENO ≤25 ppb were compared with patients with FENO >25 ppb, ORMDL3 and GSDMB gene expressions were increased by 2.93 and 3.56 times, respectively. When the coefficient changes were compared, no significant difference was found between FENO≤25 and FENO >25 patients. There was a slight negative correlation between ΔCq values and ACT score (p=0.003, r=-0.418 for ORMDL3, and p=0.016, r=-0.345 for GSDMB). In addition, we observed a statistically significant positive correlation between ORMDL3 and GSDMB gene expressions (r=0.80, p<0.001). CONCLUSION: We showed that increased ORMDL3 and GSDMB gene expression levels may be associated with ACT scores, FeNO and ECT in asthma. These findings may encourage future studies with larger numbers of subjects that can use gene expression levels in various asthma phenotypes for prognostic prediction.