Literature DB >> 25763605

Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma.

Xiting Yan1, Jen-Hwa Chu, Jose Gomez, Maria Koenigs, Carole Holm, Xiaoxuan He, Mario F Perez, Hongyu Zhao, Shrikant Mane, Fernando D Martinez, Carole Ober, Dan L Nicolae, Kathleen C Barnes, Stephanie J London, Frank Gilliland, Scott T Weiss, Benjamin A Raby, Lauren Cohn, Geoffrey L Chupp.   

Abstract

RATIONALE: The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma.
OBJECTIVES: We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease.
METHODS: Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes.
MEASUREMENTS AND MAIN RESULTS: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). 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 × 10(-6)) and hospitalization (P = 0.01), respectively.
CONCLUSIONS: There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma.

Entities:  

Keywords:  RNA; genomic; molecular endotyping; pathway analysis; severe asthma

Mesh:

Substances:

Year:  2015        PMID: 25763605      PMCID: PMC4451618          DOI: 10.1164/rccm.201408-1440OC

Source DB:  PubMed          Journal:  Am J Respir Crit Care Med        ISSN: 1073-449X            Impact factor:   21.405


  32 in total

1.  Transcriptional phenotypes of asthma defined by gene expression profiling of induced sputum samples.

Authors:  Katherine J Baines; Jodie L Simpson; Lisa G Wood; Rodney J Scott; Peter G Gibson
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Authors:  Prescott G Woodruff; Barmak Modrek; David F Choy; Guiquan Jia; Alexander R Abbas; Almut Ellwanger; Laura L Koth; Joseph R Arron; John V Fahy
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Authors:  Sally E Wenzel
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4.  Current asthma prevalence - United States, 2006-2008.

Authors:  Jeanne E Moorman; Hatice Zahran; Benedict I Truman; Michael T Molla
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5.  Bronchoscopic evaluation of severe asthma. Persistent inflammation associated with high dose glucocorticoids.

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6.  The CHI3L1 rs4950928 polymorphism is associated with asthma-related hospital admissions in children and young adults.

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7.  Association of defensin beta-1 gene polymorphisms with asthma.

Authors:  Hara Levy; Benjamin A Raby; Stephen Lake; Kelan G Tantisira; David Kwiatkowski; Ross Lazarus; Edwin K Silverman; Brent Richter; Walter T Klimecki; Donata Vercelli; Fernando D Martinez; Scott T Weiss
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8.  Expression profiling of genes related to asthma exacerbations.

Authors:  T Aoki; Y Matsumoto; K Hirata; K Ochiai; M Okada; K Ichikawa; M Shibasaki; T Arinami; R Sumazaki; E Noguchi
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9.  Cluster analysis and clinical asthma phenotypes.

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Authors:  Hyo Jung Kang; Yuka Imamura Kawasawa; Feng Cheng; Ying Zhu; Xuming Xu; Mingfeng Li; André M M Sousa; Mihovil Pletikos; Kyle A Meyer; Goran Sedmak; Tobias Guennel; Yurae Shin; Matthew B Johnson; Zeljka Krsnik; Simone Mayer; Sofia Fertuzinhos; Sheila Umlauf; Steven N Lisgo; Alexander Vortmeyer; Daniel R Weinberger; Shrikant Mane; Thomas M Hyde; Anita Huttner; Mark Reimers; Joel E Kleinman; Nenad Sestan
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  32 in total

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2.  Toward Precision Medicine of Symptom Control in Asthma.

Authors:  Jose L Gomez; Naftali Kaminski
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3.  Gene Expression Profiling in Blood Provides Reproducible Molecular Insights into Asthma Control.

Authors:  Damien C Croteau-Chonka; Weiliang Qiu; Fernando D Martinez; Robert C Strunk; Robert F Lemanske; Andrew H Liu; Frank D Gilliland; Joshua Millstein; W James Gauderman; Carole Ober; Jerry A Krishnan; Steven R White; Edward T Naureckas; Dan L Nicolae; Kathleen C Barnes; Stephanie J London; Albino Barraza-Villarreal; Vincent J Carey; Scott T Weiss; Benjamin A Raby
Journal:  Am J Respir Crit Care Med       Date:  2017-01-15       Impact factor: 21.405

Review 4.  The Reemergence of the Asthma-COPD Overlap Syndrome: Characterizing a Syndrome in the Precision Medicine Era.

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6.  A Network of Sputum MicroRNAs Is Associated with Neutrophilic Airway Inflammation in Asthma.

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Review 7.  Are We Meeting the Promise of Endotypes and Precision Medicine in Asthma?

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8.  Systemic Corticosteroid Responses in Children with Severe Asthma: Phenotypic and Endotypic Features.

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9.  Profiling cellular heterogeneity in asthma with single cell multiparameter CyTOF.

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Review 10.  Biomarkers of Airway Type-2 Inflammation and Integrating Complex Phenotypes to Endotypes in Asthma.

Authors:  Michael C Peters; Michelle-Linh T Nguyen; Eleanor M Dunican
Journal:  Curr Allergy Asthma Rep       Date:  2016-10       Impact factor: 4.806

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