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Clinical tool for disease phenotyping in granulomatous lung disease

BACKGROUND: Exposure to beryllium may lead to granuloma formation and fibrosis in those who develop chronic beryllium disease (CBD). Although disease presentation varies from mild to severe, little is known about CBD phenotypes. This study characterized CBD disease phenotypes using longitudinal meas...

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Autores principales: Silveira, Lori J., Strand, Matthew, Van Dyke, Michael V., Mroz, Margaret M., Faino, Anna V., Dabelea, Dana M., Maier, Lisa A., Fingerlin, Tasha E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690625/
https://www.ncbi.nlm.nih.gov/pubmed/29145499
http://dx.doi.org/10.1371/journal.pone.0188119
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author Silveira, Lori J.
Strand, Matthew
Van Dyke, Michael V.
Mroz, Margaret M.
Faino, Anna V.
Dabelea, Dana M.
Maier, Lisa A.
Fingerlin, Tasha E.
author_facet Silveira, Lori J.
Strand, Matthew
Van Dyke, Michael V.
Mroz, Margaret M.
Faino, Anna V.
Dabelea, Dana M.
Maier, Lisa A.
Fingerlin, Tasha E.
author_sort Silveira, Lori J.
collection PubMed
description BACKGROUND: Exposure to beryllium may lead to granuloma formation and fibrosis in those who develop chronic beryllium disease (CBD). Although disease presentation varies from mild to severe, little is known about CBD phenotypes. This study characterized CBD disease phenotypes using longitudinal measures of lung function. METHODS: Using a case-only study of 207 CBD subjects, subject-specific trajectories over time were estimated from longitudinal pulmonary function and exercise-tolerance tests. To estimate linear combinations of the 30-year values that define underlying patterns of lung function, we conducted factor analysis. Cluster analysis was then performed on all the predicted lung function values at 30 years. These estimates were used to identify underlying features and subgroups of CBD. RESULTS: Two factors, or composite measures, explained nearly 70% of the co-variation among the tests; one factor represented pulmonary function in addition to oxygen consumption and workload during exercise, while the second factor represented exercise tests related to gas exchange. Factors were associated with granulomas on biopsy, exposure, steroid use and lung inflammation. Three clusters of patients (n = 53, n = 59 and, n = 95) were identified based on the collection of test values. Lower levels of each of the factor composite scores and cluster membership were associated with baseline characteristics of patients. CONCLUSIONS: Using factor analysis and cluster analysis, we identified disease phenotypes that were associated with baseline patient characteristics, suggesting that CBD is a heterogeneous disease with varying severity. These clinical tools may be used in future basic and clinical studies to help define the mechanisms and risk factors for disease severity.
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spelling pubmed-56906252017-11-30 Clinical tool for disease phenotyping in granulomatous lung disease Silveira, Lori J. Strand, Matthew Van Dyke, Michael V. Mroz, Margaret M. Faino, Anna V. Dabelea, Dana M. Maier, Lisa A. Fingerlin, Tasha E. PLoS One Research Article BACKGROUND: Exposure to beryllium may lead to granuloma formation and fibrosis in those who develop chronic beryllium disease (CBD). Although disease presentation varies from mild to severe, little is known about CBD phenotypes. This study characterized CBD disease phenotypes using longitudinal measures of lung function. METHODS: Using a case-only study of 207 CBD subjects, subject-specific trajectories over time were estimated from longitudinal pulmonary function and exercise-tolerance tests. To estimate linear combinations of the 30-year values that define underlying patterns of lung function, we conducted factor analysis. Cluster analysis was then performed on all the predicted lung function values at 30 years. These estimates were used to identify underlying features and subgroups of CBD. RESULTS: Two factors, or composite measures, explained nearly 70% of the co-variation among the tests; one factor represented pulmonary function in addition to oxygen consumption and workload during exercise, while the second factor represented exercise tests related to gas exchange. Factors were associated with granulomas on biopsy, exposure, steroid use and lung inflammation. Three clusters of patients (n = 53, n = 59 and, n = 95) were identified based on the collection of test values. Lower levels of each of the factor composite scores and cluster membership were associated with baseline characteristics of patients. CONCLUSIONS: Using factor analysis and cluster analysis, we identified disease phenotypes that were associated with baseline patient characteristics, suggesting that CBD is a heterogeneous disease with varying severity. These clinical tools may be used in future basic and clinical studies to help define the mechanisms and risk factors for disease severity. Public Library of Science 2017-11-16 /pmc/articles/PMC5690625/ /pubmed/29145499 http://dx.doi.org/10.1371/journal.pone.0188119 Text en © 2017 Silveira et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Silveira, Lori J.
Strand, Matthew
Van Dyke, Michael V.
Mroz, Margaret M.
Faino, Anna V.
Dabelea, Dana M.
Maier, Lisa A.
Fingerlin, Tasha E.
Clinical tool for disease phenotyping in granulomatous lung disease
title Clinical tool for disease phenotyping in granulomatous lung disease
title_full Clinical tool for disease phenotyping in granulomatous lung disease
title_fullStr Clinical tool for disease phenotyping in granulomatous lung disease
title_full_unstemmed Clinical tool for disease phenotyping in granulomatous lung disease
title_short Clinical tool for disease phenotyping in granulomatous lung disease
title_sort clinical tool for disease phenotyping in granulomatous lung disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5690625/
https://www.ncbi.nlm.nih.gov/pubmed/29145499
http://dx.doi.org/10.1371/journal.pone.0188119
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