Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study

Hung-Ling Huang; Ying-Jhen Huang; Yi-Chi Chu; Chia-Wei Chen; Hsin-Chou Yang; Jing-Shiang Hwang; Chun-Houh Chen; Ta-Chien Chan

doi:10.2147/JAA.S397067

Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study

J Asthma Allergy. 2023 Jan 21:16:135-147. doi: 10.2147/JAA.S397067. eCollection 2023.

Authors

Hung-Ling Huang^#^{1

2

3}, Ying-Jhen Huang^#⁴, Yi-Chi Chu⁴, Chia-Wei Chen⁵, Hsin-Chou Yang⁵, Jing-Shiang Hwang⁵, Chun-Houh Chen⁵, Ta-Chien Chan^{4

6}

Affiliations

¹ Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan.
² Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
³ Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
⁴ Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan.
⁵ Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.
⁶ Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.

^# Contributed equally.

Abstract

Background: Uncontrolled asthma in adults leads to poor clinical outcome, while the clinical heterogeneity of phenotypes interferes the applicable genetic determinants. This study aimed to identify phenotypes and genetic impact on poorly-controlled asthma to optimize individualized treatment strategies.

Methods: This propensity score-matched case-control study included 340 and 1020 asthmatics with poorly-controlled asthma and well-controlled asthma, respectively. Data were obtained from the 2008-2015 Taiwan Biobank Database and linked to the National Health Insurance Research Database. All asthmatics were aged ≥30 years, without cancer history, and each completed a questionnaire, physical examination, and genome-wide single nucleotide polymorphisms (SNPs). Multivariate adjusted odds ratios (ORs) for genetic risk scores were calculated using conditional logistic regression, stratified by age and sex. A model integrating obesity- and asthma-associated phenotypes and genotypes was applied for poorly-controlled asthma risk prediction.

Results: General obesity with body mass index (BMI) ≥27 kg/m² (OR:1.49, 95% confidence interval (CI) 1.09-2.03), central obesity with waist-to-height ratio (WHtR) ≥0.5 (OR:1.62, 95% CI 1.22-2.15), and parental history of asthma (OR:1.65, and 1.68; for BMI model and WHtR model, respectively) were significantly associated with poorly-controlled asthma in adults, and the combination effect of both obesity phenotypes was 1.66 (95% CI 1.17-2.35). A total of 16 obesity-associated SNPs and 9 asthma-associated SNPs were converted into genetic scores, and the aforementioned phenotypes were incorporated into the risk prediction model for poorly-controlled asthma, with an area under curve 0.72 in the receiver operating characteristic curve. The potential biological functions of genes are involved in immunity pathways.

Conclusion: The prediction model integrating obesity-asthma phenotypes and genotypes for poorly-controlled asthma can facilitate the prediction of high-risk asthma and provide potential targets for novel treatment.

Keywords: biobank; biomarker; genetic score; obesity; poorly-controlled asthma.

Grants and funding

This research was supported by a grant titled “Obesity and asthma severity: Interactions among health behaviors, genetic polymorphism, and environmental exposure” (grant number: AS-PH 109-01-2) from Academia Sinica and a grant from Kaohsiung Municipal Ta-Tung Hospital (grant number: KMTTH -111-039) for supporting the publication fee. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.