Clusters based on immune markers in a Lithuanian asthma cohort study. (3rd June 2023)
- Record Type:
- Journal Article
- Title:
- Clusters based on immune markers in a Lithuanian asthma cohort study. (3rd June 2023)
- Main Title:
- Clusters based on immune markers in a Lithuanian asthma cohort study
- Authors:
- Gasiuniene, Edita
Tamasauskiene, Laura
Janulaityte, Ieva
Bjermer, Leif
Sitkauskiene, Brigita - Abstract:
- Abstract: Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristics, physiological findings, and triggers, and phenotyping is usually performed in a hypothesis-driven univariate manner. However, phenotyping can also be performed using computer algorithms to evaluate hypotheses-free relationships among many clinical and biological characteristics. We aimed to identify asthma phenotypes based on multiple demographic, clinical, and immunological characteristics. Methods: Cluster analysis in R v3.5.0 was performed using asthma patient data. A total of 170 adult patients with asthma (diagnosed according to the GINA recommendations) were recruited to the study. All patients completed questionnaires about their smoking history and underwent physical examination, spirometry, skin-prick test, blood sample collection to evaluate peripheral blood cell counts and serum IgE, periostin, and interleukin (IL)-33 levels, as well as body mass index measurements. Data normality was checked with histograms and QQ plots. Hierarchical clustering was performed using Ward's linkage with Ward's clustering criterion. The optimal number of clusters was validated using the Dunn criterion as well as by comparing different clustering algorithms using the clValid package. Results: Three clusters characterizing asthma phenotypes were identified: (1) early-onset, highly atopic, and eosinophilic asthma associated with male sex and high levels of IL-33 andAbstract: Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristics, physiological findings, and triggers, and phenotyping is usually performed in a hypothesis-driven univariate manner. However, phenotyping can also be performed using computer algorithms to evaluate hypotheses-free relationships among many clinical and biological characteristics. We aimed to identify asthma phenotypes based on multiple demographic, clinical, and immunological characteristics. Methods: Cluster analysis in R v3.5.0 was performed using asthma patient data. A total of 170 adult patients with asthma (diagnosed according to the GINA recommendations) were recruited to the study. All patients completed questionnaires about their smoking history and underwent physical examination, spirometry, skin-prick test, blood sample collection to evaluate peripheral blood cell counts and serum IgE, periostin, and interleukin (IL)-33 levels, as well as body mass index measurements. Data normality was checked with histograms and QQ plots. Hierarchical clustering was performed using Ward's linkage with Ward's clustering criterion. The optimal number of clusters was validated using the Dunn criterion as well as by comparing different clustering algorithms using the clValid package. Results: Three clusters characterizing asthma phenotypes were identified: (1) early-onset, highly atopic, and eosinophilic asthma associated with male sex and high levels of IL-33 and periostin; (2) late-onset, eosinophilic asthma associated with female sex and low levels of IL-33 and periostin; and (3) late-onset, obese, neutrophilic asthma associated with female sex, persistent airway obstruction, and very low IL-33 and periostin levels. … (more)
- Is Part Of:
- Journal of asthma. Volume 60:Number 6(2023)
- Journal:
- Journal of asthma
- Issue:
- Volume 60:Number 6(2023)
- Issue Display:
- Volume 60, Issue 6 (2023)
- Year:
- 2023
- Volume:
- 60
- Issue:
- 6
- Issue Sort Value:
- 2023-0060-0006-0000
- Page Start:
- 1123
- Page End:
- 1130
- Publication Date:
- 2023-06-03
- Subjects:
- Asthma -- cluster -- phenotype -- periostin -- interleukin-33
Asthma -- Periodicals
616.238005 - Journal URLs:
- http://www.tandfonline.com/loi/ytsr20#.V6niC1JTF-V ↗
http://informahealthcare.com/journal/jas ↗
http://informahealthcare.com ↗ - DOI:
- 10.1080/02770903.2022.2134792 ↗
- Languages:
- English
- ISSNs:
- 0277-0903
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4947.295000
British Library DSC - BLDSS-3PM
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- 27096.xml