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Gomes LGDS, Cruz ÁASD, de Santana MBR, Pinheiro GP, Santana CVN, Santos CBS, Boorgula MP, Campbell M, Machado ADS, Veiga RV, Barnes KC, Costa RDS, Figueiredo CA. Predictive genetic panel for adult asthma using machine learning methods. THE JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. GLOBAL 2024; 3:100282. [PMID: 38952894 PMCID: PMC11215340 DOI: 10.1016/j.jacig.2024.100282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/20/2024] [Accepted: 04/05/2024] [Indexed: 07/03/2024]
Abstract
Background Asthma is a chronic inflammatory disease of the airways that is heterogeneous and multifactorial, making its accurate characterization a complex process. Therefore, identifying the genetic variations associated with asthma and discovering the molecular interactions between the omics that confer risk of developing this disease will help us to unravel the biological pathways involved in its pathogenesis. Objective We sought to develop a predictive genetic panel for asthma using machine learning methods. Methods We tested 3 variable selection methods: Boruta's algorithm, the top 200 genome-wide association study markers according to their respective P values, and an elastic net regression. Ten different algorithms were chosen for the classification tests. A predictive panel was built on the basis of joint scores between the classification algorithms. Results Two variable selection methods, Boruta and genome-wide association studies, were statistically similar in terms of the average accuracies generated, whereas elastic net had the worst overall performance. The predictive genetic panel was completed with 155 single-nucleotide variants, with 91.18% accuracy, 92.75% sensitivity, and 89.55% specificity using the support vector machine algorithm. The markers used range from known single-nucleotide variants to those not previously described in the literature. Our study shows potential in creating genetic prediction panels with tailored penalties per marker, aiding in the identification of optimal machine learning methods for intricate results. Conclusions This method is able to classify asthma and nonasthma effectively, proving its potential utility in clinical prediction and diagnosis.
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Affiliation(s)
| | | | | | | | - Cinthia Vila Nova Santana
- Programa de Controle da Asma na Bahia (ProAR), Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | | | | | - Monica Campbell
- Department of Medicine, University of Colorado Denver, Aurora, Colo
| | - Adelmir de Souza Machado
- Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Bahia, Brazil
- Programa de Controle da Asma na Bahia (ProAR), Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Rafael Valente Veiga
- Laboratory of Lymphocyte Signalling and Development, The Babraham Institute, Cambridge, United Kingdom
| | | | - Ryan dos Santos Costa
- Instituto de Ciências da Saúde, Universidade Federal da Bahia, Salvador, Bahia, Brazil
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Challenges in the Management of Asthma in Older Adults. CURRENT TREATMENT OPTIONS IN ALLERGY 2023. [DOI: 10.1007/s40521-023-00331-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
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Huang HL, Huang YJ, Chu YC, Chen CW, Yang HC, Hwang JS, Chen CH, Chan TC. 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; 16:135-147. [PMID: 36714050 PMCID: PMC9875574 DOI: 10.2147/jaa.s397067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/10/2023] [Indexed: 01/21/2023] Open
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.
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Affiliation(s)
- Hung-Ling Huang
- Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan,Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan,Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ying-Jhen Huang
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan
| | - Yi-Chi Chu
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan
| | - Chia-Wei Chen
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Hsin-Chou Yang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | | | - Chun-Houh Chen
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Ta-Chien Chan
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan,Institute of Public Health, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan,Correspondence: Ta-Chien Chan, Research Center for Humanities and Social Sciences, Academia Sinica, 128 Academia Road, Section 2, Nankang, Taipei, 115, Taiwan, Tel +886-2-2789-8160, Email
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Figueiredo RG, Pinheiro GP, Arata V, Leal MFM, Santana CVN, Tiraboschi TL, Bessa Junior J, Cruz ÁA. Impact of frailty in elderly patients with moderate to severe asthma. PLoS One 2022; 17:e0270921. [PMID: 35834436 PMCID: PMC9282437 DOI: 10.1371/journal.pone.0270921] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/17/2022] [Indexed: 11/18/2022] Open
Abstract
Frailty assessment has been identified as critical approach in chronic respiratory diseases with substantial impact in the health status and functionality in later life. Aging modifies the immune response leading to a chronic pro-inflammatory state and increased susceptibility to airway infections. Since epigenetic changes, airway epithelium dysfunction and inflammatory cytokine activity seem to be more pronounced in the immunosenescence, elderly asthmatics are at higher risk of poor clinical outcomes. Therefore, we hypothesize that frailty would be associated with the degree of asthma control in elderly patients with moderate to severe asthma. The aims of this study are to investigate association between frailty and asthma control in patients over 60 years old to estimate the prevalence of frailty in this study population. We plan to conduct a cross-sectional study with at least 120 patients above 60 years old with diagnostic of moderate to severe asthma according to Global Initiative for Asthma (GINA) guidelines, treated at a referral outpatient clinic. We defined asthma control by the six-domain Asthma Control Questionnaire (ACQ-6) and frailty phenotype in accordance with Fried scale and visual scale of frailty (VS-Frailty). We hope to analyze the multidimensional relationships between frailty and asthma and contribute to innovative therapeutic plans in geriatric asthma.
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Affiliation(s)
- Ricardo G. Figueiredo
- Departamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
- Fundação ProAR, Salvador, Bahia, Brazil
- Programa de Pós-Graduação em Saúde Coletiva, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
- * E-mail:
| | | | - Vanessa Arata
- Departamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
| | | | | | - Taciana L. Tiraboschi
- Departamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
- Programa de Pós-Graduação em Saúde Coletiva, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
| | - José Bessa Junior
- Departamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
- Programa de Pós-Graduação em Saúde Coletiva, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil
| | - Álvaro A. Cruz
- Fundação ProAR, Salvador, Bahia, Brazil
- Faculdade de Medicina, Universidade Federal da Bahia, Salvador, Bahia, Brazil
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5
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Kachroo P, Stewart ID, Kelly RS, Stav M, Mendez K, Dahlin A, Soeteman DI, Chu SH, Huang M, Cote M, Knihtilä HM, Lee-Sarwar K, McGeachie M, Wang A, Wu AC, Virkud Y, Zhang P, Wareham NJ, Karlson EW, Wheelock CE, Clish C, Weiss ST, Langenberg C, Lasky-Su JA. Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma. Nat Med 2022; 28:814-822. [PMID: 35314841 PMCID: PMC9350737 DOI: 10.1038/s41591-022-01714-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 01/24/2022] [Indexed: 02/02/2023]
Abstract
The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.
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Affiliation(s)
- Priyadarshini Kachroo
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Rachel S Kelly
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Meryl Stav
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin Mendez
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Amber Dahlin
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Djøra I Soeteman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Su H Chu
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Mengna Huang
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Margaret Cote
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Hanna M Knihtilä
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Kathleen Lee-Sarwar
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael McGeachie
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alberta Wang
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ann Chen Wu
- Harvard Pilgrim Health Care Institute and Department of Population Medicine, Harvard Medical School, Boston, MA, USA
| | - Yamini Virkud
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Pei Zhang
- Gunma University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Japan
- Department of Medical Biochemistry and Biophysics, Division of Physiological Chemistry 2, Karolinska Institute, Stockholm, Sweden
| | | | - Elizabeth W Karlson
- Department of Medicine, Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Craig E Wheelock
- Gunma University Initiative for Advanced Research (GIAR), Gunma University, Maebashi, Japan
- Department of Medical Biochemistry and Biophysics, Division of Physiological Chemistry 2, Karolinska Institute, Stockholm, Sweden
- Department of Respiratory Medicine and Allergy, Karolinska University Hospital, Stockholm, Sweden
| | | | - Scott T Weiss
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jessica A Lasky-Su
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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Pharmacogenetics of Bronchodilator Response: Future Directions. Curr Allergy Asthma Rep 2021; 21:47. [PMID: 34958416 DOI: 10.1007/s11882-021-01023-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/02/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE OF REVIEW Several genome-wide association studies (GWASs) of bronchodilator response (BDR) to albuterol have been published over the past decade. This review describes current knowledge gaps, including pharmacogenetic studies of albuterol response in minority populations, effect modification of pharmacogenetic associations by age, and relevance of BDR phenotype characterization to pharmacogenetic findings. New approaches, such as leveraging additional "omics" data to focus pharmacogenetic interrogation, as well as developing polygenic risk scores in asthma treatment responses, are also discussed. RECENT FINDINGS Recent pharmacogenetic studies of albuterol response in minority populations have identified genetic polymorphisms in loci (DNAH5, NFKB1, PLCB1, ADAMTS3, COX18, and PRKG1), that are associated with BDR. Additional studies are needed to replicate these findings. Modification of the pharmacogenetic associations for SPATS2L and ASB3 polymorphisms by age has also been published. Evidence from metabolomic and epigenomic studies of BDR may point to new pharmacogenetic targets. Lastly, a polygenic risk score for response to albuterol has been developed but requires validation in additional cohorts. In order to expand our knowledge of pharmacogenetics of BDR, additional studies in minority populations are needed. Consideration of effect modification by age and leverage of other "omics" data beyond genomics may also help uncover novel pharmacogenetic loci for use in precision medicine for asthma treatment.
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