Dataset Information

Body Composition-Specific Asthma Phenotypes: Clinical Implications.

ABSTRACT:

Background

Previous studies have indicated the limitations of body mass index for defining disease phenotypes. The description of asthma phenotypes based on body composition (BC) has not been largely reported.

Objective

To identify and characterize phenotypes based on BC parameters in patients with asthma.

Methods

A study with two prospective observational cohorts analyzing adult patients with stable asthma (n = 541 for training and n = 179 for validation) was conducted. A body composition analysis was performed for the included patients. A cluster analysis was conducted by applying a 2-step process with stepwise discriminant analysis. Logistic regression models were used to evaluate the association between identified phenotypes and asthma exacerbations (AEs). The same algorithm for cluster analysis in the independent validation set was used to perform an external validation.

Results

Three clusters had significantly different characteristics associated with asthma outcomes. An external validation identified the similarity of the participants in training and the validation set. In the training set, cluster Training (T) 1 (29.4%) was "patients with undernutrition", cluster T2 (18.9%) was "intermediate level of nutrition with psychological dysfunction", and cluster T3 (51.8%) was "patients with good nutrition". Cluster T3 had a decreased risk of moderate-to-severe and severe AEs in the following year compared with the other two clusters. The most important BC-specific factors contributing to being accurately assigned to one of these three clusters were skeletal muscle mass and visceral fat area.

Conclusion

We defined three distinct clusters of asthma patients, which had distinct clinical features and asthma outcomes. Our data reinforced the importance of evaluating BC to determining nutritional status in clinical practice.

SUBMITTER: Zhang X

PROVIDER: S-EPMC9229860 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Body Composition-Specific Asthma Phenotypes: Clinical Implications.

Zhang Xin X Deng Ke K Yuan Yulai Y Liu Lei L Zhang Shuwen S Wang Changyong C Wang Gang G Zhang Hongping H Wang Lei L Cheng Gaiping G Wood Lisa G LG Wang Gang G

Nutrients 20220617 12

<h4>Background</h4>Previous studies have indicated the limitations of body mass index for defining disease phenotypes. The description of asthma phenotypes based on body composition (BC) has not been largely reported.<h4>Objective</h4>To identify and characterize phenotypes based on BC parameters in patients with asthma.<h4>Methods</h4>A study with two prospective observational cohorts analyzing adult patients with stable asthma (<i>n</i> = 541 for training and <i>n</i> = 179 for validation) was ...[more]

PMID: 35745259

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Project description:BackgroundThe impact of body composition (BC) abnormalities on COVID-19 outcomes remains to be determined.ObjectivesWe summarized the evidence on BC abnormalities and their relationship with adverse clinical outcomes in patients with COVID-19.MethodsA systematic search was conducted up until 26 September, 2022 for observational studies using BC techniques to quantify skeletal muscle mass (or related compartments), muscle radiodensity or echo intensity, adipose tissue (AT; or related compartments), and phase angle (PhA) in adults with COVID-19. Methodological quality of studies was assessed using the Newcastle-Ottawa Scale. A synthesis without meta-analysis was conducted to summarize the prevalence of BC abnormalities and their significant associations with clinical outcomes.ResultsWe included 62 studies (69.4% low risk of bias) with 12-1138 participants, except 3 studies with ≤490,301 participants. Using CT and different cutoff values, prevalence ranged approximately from 22% to 90% for low muscle mass, 12% to 85% for low muscle radiodensity, and 16% to 70% for high visceral AT. Using BIA, prevalence of high FM was 51%, and low PhA was 22% to 88%. Mortality was inversely related to PhA (3/4 studies) and positively related to intra- and intermuscular AT (4/5 studies), muscle echo intensity (2/2 studies), and BIA-estimated FM (2/2 studies). Intensive care unit (ICU) admission was positively related to visceral AT (6/7 studies) and total AT (2/3 studies). Disease severity and hospitalization outcomes were positively related to intra- and intermuscular AT (2/2 studies). Inconsistent associations were found for the rest of the BC measures and hospitalization outcomes.ConclusionsAbnormalities in BC were prevalent in patients with COVID-19. Although conflicting associations were observed among certain BC abnormalities and clinical outcomes, higher muscle echo intensity (reflective of myosteatosis) and lower PhA were more consistently associated with greater mortality risk. Likewise, high intra- and intermuscular AT and visceral AT were associated with mortality and ICU admission, respectively. This trial was registered at PROSPERO as CRD42021283031.

Project description:BACKGROUND: Evaluation of the airway transcriptome may reveal patterns of gene expression that are associated with clinical phenotypes of asthma. To define transcriptomic endotypes of asthma (TEA) we analyzed gene expression in induced sputum that correlate with phenotypes of disease. METHODS: Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation. RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower pre-bronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04), compared to the other TEA clusters. TEA cluster 2, the smallest cluster had the most subjects that were hospitalized for asthma (P = 0.04). Subjects in TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 x 10-06) and hospitalization (P = 0.01), respectively. CONCLUSIONS: Patterns of gene expression in the sputum and blood reveal TEA clusters that are associated with severe asthma phenotypes in children and adults. Gene expression was measured in sputum of subjects with asthma using Affymetrix HuGene ST 1.0 microarrays. Unsupervised clustering analysis of genes in pathways selected from the Kyoto Encyclopedia of Genes and Genomes (KEGG) identified TEA clusters. Clinical characteristics were compared and logistic regression analysis of matched blood samples defined an expression profile to determine the TEA cluster assignment in a cohort of children with asthma for validation.

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Dataset Information

Body Composition-Specific Asthma Phenotypes: Clinical Implications.

Background

Objective

Methods

Results

Conclusion

Publications

Body Composition-Specific Asthma Phenotypes: Clinical Implications.

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