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A multivariate analysis of risk factors for the air-trapping asthmatic phenotype as measured by quantitative CT analysis.

ABSTRACT: BACKGROUND:Patients with severe asthma have increased physiologically measured air trapping; however, a study using CT measures of air trapping has not been performed. This study was designed to address two hypotheses: (1) air trapping measured by multidetector CT (MDCT) quantitative methodology would be a predictor of a more severe asthma phenotype; and (2) historical, clinical, allergic, or inflammatory risk factors could be identified via multivariate analysis. METHODS:MDCT scanning of a subset of Severe Asthma Research Program subjects was performed at functional residual capacity. Air trapping was defined as >or= 9.66% of the lung tissue < - 850 Hounsfield units (HU). Subjects classified as having air trapping were then compared to subjects without air trapping on clinical and demographic factors using both univariate and multivariate statistical analyses. RESULTS:Subjects with air trapping were significantly more likely to have a history of asthma-related hospitalizations, ICU visits, and/or mechanical ventilation. Duration of asthma (odds ratio [OR], 1.42; 95% confidence interval [CI], 1.08 to 1.87), history of pneumonia (OR, 8.55; 95% CI, 2.07 to 35.26), high levels of airway neutrophils (OR, 8.67; 95% CI, 2.05 to 36.57), airflow obstruction (FEV(1)/FVC) [OR, 1.61; 95% CI, 1.21 to 2.14], and atopy (OR, 11.54; 95% CI, 1.97 to 67.70) were identified as independent risk factors associated with the air-trapping phenotype. CONCLUSIONS:Quantitative CT-determined air trapping in asthmatic subjects identifies a group of individuals at high risk for severe disease. Several independent risk factors for the presence of this phenotype were identified: perhaps most interestingly, history of pneumonia, neutrophilic inflammation, and atopy.

SUBMITTER: Busacker A

PROVIDER: S-EPMC2849984 | biostudies-literature | 2009 Jan

REPOSITORIES: biostudies-literature

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A multivariate analysis of risk factors for the air-trapping asthmatic phenotype as measured by quantitative CT analysis.

Busacker Ashley A Newell John D JD Keefe Thomas T Hoffman Eric A EA Granroth Janice Cook JC Castro Mario M Fain Sean S Wenzel Sally S

Chest 20080808 1

<h4>Background</h4>Patients with severe asthma have increased physiologically measured air trapping; however, a study using CT measures of air trapping has not been performed. This study was designed to address two hypotheses: (1) air trapping measured by multidetector CT (MDCT) quantitative methodology would be a predictor of a more severe asthma phenotype; and (2) historical, clinical, allergic, or inflammatory risk factors could be identified via multivariate analysis.<h4>Methods</h4>MDCT sca ...[more]

PMID: 18689585

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Project description:With the advent of modern imaging and measurement technology, complex phenotypes are increasingly represented by large numbers of measurements, which may not bear biological meaning one by one. For such multivariate phenotypes, studying the pairwise associations between all measurements and all alleles is highly inefficient and prevents insight into the genetic pattern underlying the observed phenotypes. We present a new method for identifying patterns of allelic variation (genetic latent variables) that are maximally associated-in terms of effect size-with patterns of phenotypic variation (phenotypic latent variables). This multivariate genotype-phenotype mapping (MGP) separates phenotypic features under strong genetic control from less genetically determined features and thus permits an analysis of the multivariate structure of genotype-phenotype association, including its dimensionality and the clustering of genetic and phenotypic variables within this association. Different variants of MGP maximize different measures of genotype-phenotype association: genetic effect, genetic variance, or heritability. In an application to a mouse sample, scored for 353 SNPs and 11 phenotypic traits, the first dimension of genetic and phenotypic latent variables accounted for >70% of genetic variation present in all 11 measurements; 43% of variation in this phenotypic pattern was explained by the corresponding genetic latent variable. The first three dimensions together sufficed to account for almost 90% of genetic variation in the measurements and for all the interpretable genotype-phenotype association. Each dimension can be tested as a whole against the hypothesis of no association, thereby reducing the number of statistical tests from 7766 to 3-the maximal number of meaningful independent tests. Important alleles can be selected based on their effect size (additive or nonadditive effect on the phenotypic latent variable). This low dimensionality of the genotype-phenotype map has important consequences for gene identification and may shed light on the evolvability of organisms.

Dataset Information

A multivariate analysis of risk factors for the air-trapping asthmatic phenotype as measured by quantitative CT analysis.

Publications

A multivariate analysis of risk factors for the air-trapping asthmatic phenotype as measured by quantitative CT analysis.

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