An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma
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An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma. / Kelly, Rachel S; Chawes, Bo L; Blighe, Kevin; Virkud, Yamini V; Croteau-Chonka, Damien C; McGeachie, Michael J; Clish, Clary B; Bullock, Kevin; Celedón, Juan C; Weiss, Scott T; Lasky-Su, Jessica A.
In: Chest, Vol. 154, No. 2, 08.2018, p. 335-348.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - An Integrative Transcriptomic and Metabolomic Study of Lung Function in Children With Asthma
AU - Kelly, Rachel S
AU - Chawes, Bo L
AU - Blighe, Kevin
AU - Virkud, Yamini V
AU - Croteau-Chonka, Damien C
AU - McGeachie, Michael J
AU - Clish, Clary B
AU - Bullock, Kevin
AU - Celedón, Juan C
AU - Weiss, Scott T
AU - Lasky-Su, Jessica A
N1 - Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
PY - 2018/8
Y1 - 2018/8
N2 - BACKGROUND: Single omic analyses have provided some insight into the basis of lung function in children with asthma, but the underlying biologic pathways are still poorly understood.METHODS: Weighted gene coexpression network analysis (WGCNA) was used to identify modules of coregulated gene transcripts and metabolites in blood among 325 children with asthma from the Genetic Epidemiology of Asthma in Costa Rica study. The biology of modules associated with lung function as measured by FEV1, the FEV1/FVC ratio, bronchodilator response, and airway responsiveness to methacholine was explored. Significantly correlated gene-metabolite module pairs were then identified, and their constituent features were analyzed for biologic pathway enrichments.RESULTS: WGCNA clustered 25,060 gene probes and 8,185 metabolite features into eight gene modules and eight metabolite modules, where four and six, respectively, were associated with lung function (P ≤ .05). The gene modules were enriched for immune, mitotic, and metabolic processes and asthma-associated microRNA targets. The metabolite modules were enriched for lipid and amino acid metabolism. Integration of correlated gene-metabolite modules expanded the single omic findings, linking the FEV1/FVC ratio with ORMDL3 and dysregulated lipid metabolism. This finding was replicated in an independent population.CONCLUSIONS: The results of this hypothesis-generating study suggest a mechanistic basis for multiple asthma genes, including ORMDL3, and a role for lipid metabolism. They demonstrate that integrating multiple omic technologies may provide a more informative picture of asthmatic lung function biology than single omic analyses.
AB - BACKGROUND: Single omic analyses have provided some insight into the basis of lung function in children with asthma, but the underlying biologic pathways are still poorly understood.METHODS: Weighted gene coexpression network analysis (WGCNA) was used to identify modules of coregulated gene transcripts and metabolites in blood among 325 children with asthma from the Genetic Epidemiology of Asthma in Costa Rica study. The biology of modules associated with lung function as measured by FEV1, the FEV1/FVC ratio, bronchodilator response, and airway responsiveness to methacholine was explored. Significantly correlated gene-metabolite module pairs were then identified, and their constituent features were analyzed for biologic pathway enrichments.RESULTS: WGCNA clustered 25,060 gene probes and 8,185 metabolite features into eight gene modules and eight metabolite modules, where four and six, respectively, were associated with lung function (P ≤ .05). The gene modules were enriched for immune, mitotic, and metabolic processes and asthma-associated microRNA targets. The metabolite modules were enriched for lipid and amino acid metabolism. Integration of correlated gene-metabolite modules expanded the single omic findings, linking the FEV1/FVC ratio with ORMDL3 and dysregulated lipid metabolism. This finding was replicated in an independent population.CONCLUSIONS: The results of this hypothesis-generating study suggest a mechanistic basis for multiple asthma genes, including ORMDL3, and a role for lipid metabolism. They demonstrate that integrating multiple omic technologies may provide a more informative picture of asthmatic lung function biology than single omic analyses.
U2 - 10.1016/j.chest.2018.05.038
DO - 10.1016/j.chest.2018.05.038
M3 - Journal article
C2 - 29908154
VL - 154
SP - 335
EP - 348
JO - Chest
JF - Chest
SN - 0012-3692
IS - 2
ER -
ID: 218399411