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

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 strateg...

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Autores principales: Huang, Hung-Ling, Huang, Ying-Jhen, Chu, Yi-Chi, Chen, Chia-Wei, Yang, Hsin-Chou, Hwang, Jing-Shiang, Chen, Chun-Houh, Chan, Ta-Chien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875574/
https://www.ncbi.nlm.nih.gov/pubmed/36714050
http://dx.doi.org/10.2147/JAA.S397067
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author Huang, Hung-Ling
Huang, Ying-Jhen
Chu, Yi-Chi
Chen, Chia-Wei
Yang, Hsin-Chou
Hwang, Jing-Shiang
Chen, Chun-Houh
Chan, Ta-Chien
author_facet Huang, Hung-Ling
Huang, Ying-Jhen
Chu, Yi-Chi
Chen, Chia-Wei
Yang, Hsin-Chou
Hwang, Jing-Shiang
Chen, Chun-Houh
Chan, Ta-Chien
author_sort Huang, Hung-Ling
collection PubMed
description 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/m(2) (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.
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spelling pubmed-98755742023-01-26 Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study Huang, Hung-Ling Huang, Ying-Jhen Chu, Yi-Chi Chen, Chia-Wei Yang, Hsin-Chou Hwang, Jing-Shiang Chen, Chun-Houh Chan, Ta-Chien J Asthma Allergy Original Research 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/m(2) (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. Dove 2023-01-21 /pmc/articles/PMC9875574/ /pubmed/36714050 http://dx.doi.org/10.2147/JAA.S397067 Text en © 2023 Huang et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Huang, Hung-Ling
Huang, Ying-Jhen
Chu, Yi-Chi
Chen, Chia-Wei
Yang, Hsin-Chou
Hwang, Jing-Shiang
Chen, Chun-Houh
Chan, Ta-Chien
Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title_full Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title_fullStr Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title_full_unstemmed Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title_short Exploring Factors Underlying Poorly-Controlled Asthma in Adults by Integrating Phenotypes and Genotypes Associated with Obesity and Asthma: A Case-Control Study
title_sort exploring factors underlying poorly-controlled asthma in adults by integrating phenotypes and genotypes associated with obesity and asthma: a case-control study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9875574/
https://www.ncbi.nlm.nih.gov/pubmed/36714050
http://dx.doi.org/10.2147/JAA.S397067
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