Sputum transcriptomic analysis of air pollutant signatures: link to asthma severity and phenotype

A. TIOTIU (Nancy, France), Y. Badi (London, United Kingdom), H. Abubakr-Waziri (London, United Kingdom), A. Versi (London, United Kingdom), C. Wiegman (London, United Kingdom), P. Hansbro (Newcastle, Australia), S. Mumby (London, United Kingdom), S. Dahlen (Stockholm, Sweden), P. Sterk (Amsterdam, Netherlands), R. Djukanovic (Southampton, United Kingdom), I. Adkock (London, United Kingdom), K. Chung (London, United Kingdom)

Source: Virtual Congress 2021 – Environment and air pollution
Session: Environment and air pollution
Session type: E-poster
Number: 1783

Congress or journal article abstract

Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
A. TIOTIU (Nancy, France), Y. Badi (London, United Kingdom), H. Abubakr-Waziri (London, United Kingdom), A. Versi (London, United Kingdom), C. Wiegman (London, United Kingdom), P. Hansbro (Newcastle, Australia), S. Mumby (London, United Kingdom), S. Dahlen (Stockholm, Sweden), P. Sterk (Amsterdam, Netherlands), R. Djukanovic (Southampton, United Kingdom), I. Adkock (London, United Kingdom), K. Chung (London, United Kingdom). Sputum transcriptomic analysis of air pollutant signatures: link to asthma severity and phenotype. 1783

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.


Related content which might interest you:
Identification of COPD phenotypes using cluster analysis including exhaled air molecular profiling
Source: Annual Congress 2010 - COPD: diagnosis
Year: 2010

Are epigenetic and transcriptomic signatures of air pollution exposure valid biomarkers?
Source: ERS Research Seminar 2017 – The impact of air pollution on respiratory health
Year: 2018


Assessment of induced sputum cellularity in COPD patients belonging to two different classes of air pollution exposure.
Source: International Congress 2019 – Research and innovation in airway diseases
Year: 2019

Exhaled air molecular profiling in relation to inflammatory subtype and activity in COPD
Source: Eur Respir J 2011; 38: 1301-1309
Year: 2011



Establishing the relationship between air pollution and asthma hospitalizations using neural network
Source: Eur Respir J 2003; 22: Suppl. 45, 556s
Year: 2003

The six-gene expression signature in whole sampled sputum provides clinically feasible inflammatory phenotyping of asthma
Source: ERJ Open Res, 6 (1) 00280-2019; 10.1183/23120541.00280-2019
Year: 2020



Histological changes in smoking and COPD mice with short-term exposure of PM2.5
Source: International Congress 2016 – How the understanding og molecular and genomic crosstalk is helping to diagnose lung disease
Year: 2016


Interaction with air pollution exposure for genetic loci associated with lung function
Source: International Congress 2019 – Genes and environment
Year: 2019


COPD phenotypes revealed by the integrated sputum microbiome and proteome analysis in COPDMAP cohort
Source: International Congress 2019 – Host-microbe interactions in lung disease and exacerbations
Year: 2019

Sputum proteomics and airway cell transcripts of current and ex-smokers with severe asthma in U-BIOPRED: an exploratory analysis
Source: Eur Respir J, 51 (5) 1702173; 10.1183/13993003.02173-2017
Year: 2018



Discriminating phenotypes of severe eosinophilic asthma using gene profiling in sputum
Source: International Congress 2018 – Does asthma phenotyping improve treatment?
Year: 2018



A proteomic approach to the progression of COPD: protein expression profile in induced sputum samples
Source: Eur Respir J 2006; 28: Suppl. 50, 824s
Year: 2006

The use of microarray analysis of gene signalling to determine heterogeneity of COPD exacerbation phenotypes
Source: ERS Lung Science Conference 2016
Year: 2016




Identifying adult asthma phenotypes using a clustering approach
Source: Eur Respir J 2011; 38: 310-317
Year: 2011



Unbiased clustering of severe asthma patients based on exhaled breath profiles
Source: International Congress 2015 – Exhaled biomarkers in monitoring airways disease
Year: 2015

Using omics data to detect gene-environment interactions - results from studies on air pollution and asthma
Source: International Congress 2018 – Gene-environment interactions in the omics era
Year: 2018


Molecular, metabolic and histological profiling reveal smoke worsens inflammation in a mouse model of viral COPD exacerbation
Source: Eur Respir J 2005; 26: Suppl. 49, 251s
Year: 2005

Concordance in temporally distinct blood and sputum inflammatory phenotypic measures in severe asthma
Source: International Congress 2019 – Clinical implications of asthma management
Year: 2019


Effects of traffic-related air pollution on airway epithelial transcriptome in older adults with and without COPD: a controlled human exposure study
Source: Virtual Congress 2021 – Environment and air pollution
Year: 2021


Gene expression signatures in airway and nasal epithelium of COPD: linking endotypes to clinical outcomes
Source: International Congress 2017 – Heterogeneity in COPD inflammation: implications for therapy and clinical outcomes
Year: 2017