Gene Expression in Relation to Exhaled Nitric Oxide Identifies Novel Asthma Phenotypes with Unique Biomolecular Pathways
Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma...
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Published in | American journal of respiratory and critical care medicine Vol. 190; no. 12; pp. 1363 - 1372 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Thoracic Society
15.12.2014
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Subjects | |
Online Access | Get full text |
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Abstract | Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies.
To link gene expression patterns to clinical asthma phenotypes.
We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP).
We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics-termed "subject clusters" (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10(-6). Hierarchical clustering of these 1,384 genes identified nine gene clusters or "biclusters," whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted.
These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes. |
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AbstractList | Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies.
To link gene expression patterns to clinical asthma phenotypes.
We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP).
We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics-termed "subject clusters" (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10(-6). Hierarchical clustering of these 1,384 genes identified nine gene clusters or "biclusters," whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted.
These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes. Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies.RATIONALEAlthough asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly understood. Although genomic studies have successfully broadened our understanding in diseases such as cancer, they have not been widely used in asthma studies.To link gene expression patterns to clinical asthma phenotypes.OBJECTIVESTo link gene expression patterns to clinical asthma phenotypes.We used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP).METHODSWe used a microarray platform to analyze bronchial airway epithelial cell gene expression in relation to the asthma biomarker fractional exhaled nitric oxide (FeNO) in 155 subjects with asthma and healthy control subjects from the Severe Asthma Research Program (SARP).We first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics-termed "subject clusters" (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10(-6). Hierarchical clustering of these 1,384 genes identified nine gene clusters or "biclusters," whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted.MEASUREMENTS AND MAIN RESULTSWe first identified a diverse set of 549 genes whose expression correlated with FeNO. We used k-means to cluster the patient samples according to the expression of these genes, identifying five asthma clusters/phenotypes with distinct clinical, physiological, cellular, and gene transcription characteristics-termed "subject clusters" (SCs). To then investigate differences in gene expression between SCs, a total of 1,384 genes were identified that highly differentiated the SCs at an unadjusted P value < 10(-6). Hierarchical clustering of these 1,384 genes identified nine gene clusters or "biclusters," whose coexpression suggested biological characteristics unique to each SC. Although genes related to type 2 inflammation were present, novel pathways, including those related to neuronal function, WNT pathways, and actin cytoskeleton, were noted.These findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes.CONCLUSIONSThese findings show that bronchial epithelial cell gene expression, as related to the asthma biomarker FeNO, can identify distinct asthma phenotypes, while also suggesting the presence of underlying novel gene pathways relevant to these phenotypes. |
Author | Milosevic, Jadranka Gaston, Benjamin M. Wenzel, Sally E. Modena, Brian D. Meyers, Deborah A. Wu, Wei Bar-Joseph, Ziv Busse, William W. Erzurum, Serpil C. Bleecker, Eugene R. Kaminski, Naftali Jarjour, Nizar N. Tedrow, John R. |
Author_xml | – sequence: 1 givenname: Brian D. surname: Modena fullname: Modena, Brian D. organization: Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Asthma Institute at UPMC, Pittsburgh, Pennsylvania – sequence: 2 givenname: John R. surname: Tedrow fullname: Tedrow, John R. organization: Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Asthma Institute at UPMC, Pittsburgh, Pennsylvania – sequence: 3 givenname: Jadranka surname: Milosevic fullname: Milosevic, Jadranka organization: Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Asthma Institute at UPMC, Pittsburgh, Pennsylvania – sequence: 4 givenname: Eugene R. surname: Bleecker fullname: Bleecker, Eugene R. organization: Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston Salem, North Carolina – sequence: 5 givenname: Deborah A. surname: Meyers fullname: Meyers, Deborah A. organization: Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston Salem, North Carolina – sequence: 6 givenname: Wei surname: Wu fullname: Wu, Wei organization: Lane Center for Computational Biology School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania – sequence: 7 givenname: Ziv surname: Bar-Joseph fullname: Bar-Joseph, Ziv organization: Lane Center for Computational Biology School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania – sequence: 8 givenname: Serpil C. surname: Erzurum fullname: Erzurum, Serpil C. organization: Department of Pathobiology Lerner Research Institute, The Cleveland Clinic Foundation, Cleveland, Ohio – sequence: 9 givenname: Benjamin M. surname: Gaston fullname: Gaston, Benjamin M. organization: Division of Pediatric Pulmonary, Allergy, and Immunology, Case Western Reserve University and Rainbow Babies and Children’s Hospital, Cleveland, Ohio – sequence: 10 givenname: William W. surname: Busse fullname: Busse, William W. organization: Division of Allergy, Pulmonary, and Critical Care Medicine, University of Wisconsin, Madison, Wisconsin; and – sequence: 11 givenname: Nizar N. surname: Jarjour fullname: Jarjour, Nizar N. organization: Division of Allergy, Pulmonary, and Critical Care Medicine, University of Wisconsin, Madison, Wisconsin; and – sequence: 12 givenname: Naftali surname: Kaminski fullname: Kaminski, Naftali organization: Pulmonary, Critical Care, and Sleep Medicine, Yale School of Medicine, New Haven, Connecticut – sequence: 13 givenname: Sally E. surname: Wenzel fullname: Wenzel, Sally E. organization: Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh Asthma Institute at UPMC, Pittsburgh, Pennsylvania |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25338189$$D View this record in MEDLINE/PubMed |
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Snippet | Although asthma is recognized as a heterogeneous disease associated with clinical phenotypes, the molecular basis of these phenotypes remains poorly... |
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SubjectTerms | Adult Asthma - genetics Asthma - metabolism Biomarkers Bronchi - cytology Bronchi - metabolism Case-Control Studies Female Gene Expression - genetics Humans Male Middle Aged Multigene Family - genetics Nitric Oxide - metabolism Oligonucleotide Array Sequence Analysis Original Phenotype Real-Time Polymerase Chain Reaction |
Title | Gene Expression in Relation to Exhaled Nitric Oxide Identifies Novel Asthma Phenotypes with Unique Biomolecular Pathways |
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