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

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
• obesity
• genetic score
• poorly-controlled asthma

Data Sharing Statement

The data that support the findings of this study are available from the Taiwan Biobank and Ministry of Health and Welfare, Taiwan, but restrictions apply to the availability of these data, which were under approval for the current study and so are not publicly available. The linked data set used in this study had to be analyzed in person in the Health and Welfare Data Science Center, Ministry of Health and Welfare, Taiwan. The researchers who meet the criteria can apply the data from the Taiwan Biobank and Ministry of Health and Welfare, Taiwan to access to confidential data.

Acknowledgments

We are grateful to the Health and Welfare Data Science Center, Ministry of Health and Welfare (HWDC MOHW), for providing administrative and technical support.

Author Contributions

TCC, HLH, and JSH designed this study. YJH and YCC reviewed the literature, refined the data, performed statistical analyses, and drafted the manuscript. CWC helped in the preparation of the genetic data and quality control. HCY, JSH, and CHC provided statistical consultation and helped interpret the results. HLH provided clinical suggestions and helped to interpret the results. YJH and HLH drafted the manuscript. TCC revised the manuscript accordingly. All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests in this work.

Additional information

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.