Skip to main content

Main menu

  • Home
  • Current issue
  • ERJ Early View
  • Past issues
  • ERS Guidelines
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • Open access
    • Peer reviewer login
  • Alerts
  • Subscriptions
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

User menu

  • Log in
  • Subscribe
  • Contact Us
  • My Cart

Search

  • Advanced search
  • ERS Publications
    • European Respiratory Journal
    • ERJ Open Research
    • European Respiratory Review
    • Breathe
    • ERS Books
    • ERS publications home

Login

European Respiratory Society

Advanced Search

  • Home
  • Current issue
  • ERJ Early View
  • Past issues
  • ERS Guidelines
  • Authors/reviewers
    • Instructions for authors
    • Submit a manuscript
    • Open access
    • Peer reviewer login
  • Alerts
  • Subscriptions

Distinct epithelial gene expression phenotypes in childhood respiratory allergy

Lisa Giovannini-Chami, Brice Marcet, Chimène Moreilhon, Benoît Chevalier, Marius I. Illie, Kévin Lebrigand, Karine Robbe-Sermesant, Thierry Bourrier, Jean-François Michiels, Bernard Mari, Dominique Crénesse, Paul Hofman, Jacques de Blic, Laurent Castillo, Marc Albertini, Pascal Barbry
European Respiratory Journal 2012 39: 1197-1205; DOI: 10.1183/09031936.00070511
Lisa Giovannini-Chami
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Brice Marcet
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chimène Moreilhon
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Benoît Chevalier
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marius I. Illie
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kévin Lebrigand
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karine Robbe-Sermesant
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Thierry Bourrier
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jean-François Michiels
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bernard Mari
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dominique Crénesse
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Paul Hofman
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jacques de Blic
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Laurent Castillo
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marc Albertini
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pascal Barbry
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: barbry@ipmc.cnrs.fr
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Figures

  • Tables
  • Additional Files
  • Figure 1–
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1–

    Discrimination by Random Forest (RF) of children with dust mite allergic rhinitis from healthy children and heat-map representation of the 61 most discriminant genes. a) Histogram showing, for each patient, the percentage of classification as a dust mite-allergic rhinitis (red) or healthy (blue) child. b) Nonsupervised, hierarchical clustering of the same patients using the set of 61 genes common to all Random Forest classifiers (see details in the Materials and methods section). Each square represents the expression level of a given gene in a given sample relative to the average expression level in controls. A red to green colour scale indicates gene expression levels above (red) or below (green) the average level of expression in healthy subjects for the same transcript. Clustering was performed using an average linkage method, using a Manhattan distance. The red colour on gene names (right) indicates genes induced in vitro by interleukin (IL)-4 and IL-13.

  • Figure 2–
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2–

    Discrimination by Random Forest (RF) of children with uncontrolled versus controlled asthma and heat-map representation of the 41 most discriminant genes. a) Histogram showing, for each patient, the percentage of classification as uncontrolled asthma (red) and controlled asthma (orange). b) Nonsupervised, hierarchical clustering of the same patients using the 41 probes common to all Random Forest classifiers (see Materials and methods section for details). Each square represents the expression level of a given gene in a given sample. A red to green colour scale indicates gene expression levels above (red) or below (green) the average level of the healthy controls for the same transcript. Clustering was performed using an average linkage method, using a Manhattan distance. Red-coloured gene names indicate transcripts induced by interleukin (IL)-4 and IL-13 (left) or by interferons (IFNs) (right) (corresponding to a log2(ratio) >1 in human nasal epithelial cells (HNECs)). Gene names coloured in green indicate transcripts down-regulated by IL-4 and IL-13 (left) (log2(ratio) >-1 in HNECs).

  • Figure 3–
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3–

    Immunohistochemical staining of sinus and bronchial biopsies. Representative immunostaining of a–c) GSDML and d–f) DUOX2 in surface epithelium and submucosal glands for healthy adults are shown. Positive immunostaining was observed for the two proteins in sinus and bronchial sections. Strong signals were also detected in submucosal glands for the different markers. Scale bars=100 μm.

  • Figure 4–
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4–

    Characterisation of the interferon (IFN) response. a) Measurement by real-time quantitative PCR (qPCR) of the induction of GSDML, ST8SIA4 and MX1 by IFN-α in human nasal epithelial cells (HNECs). Levels of GSDML, ST8SIA4 and MX1 were assessed in differentiated HNECs 3, 6, 12 and 24 h after stimulation with IFN-α. Measurements were performed using SYBR Green. Results are expressed as fold-change relative to the unstimulated HNECs. b) Measurement of IFNs by qPCR in patients. Levels of IFN-α1, IFN-α2, IFN-β, IFN-λ1 and IFN-λ2/3 transcripts in patients with uncontrolled asthma, patients with controlled asthma and healthy controls. Data are expressed relative to an average of 11 healthy controls. Measurements were performed using Taqman probes. Results are expressed as fold-change relative to the healthy control group. Data are presented as mean±sem. #: p<0.005 by unpaired t-test; *: p<0.05 by unpaired t-test; **: p<0.01 by unpaired t-test.

Tables

  • Figures
  • Additional Files
  • Table 1– Subject characteristics
    Group
    aARC
    Subjects761411
    Dust mite-allergic rhinitisYesYesYesNo
    AsthmaControlledUncontrolledNoNo
    Age yrs11.5±3.29.1±0.611.3±2.811.5±3.1
    Males/females2/54/27/77/4
    Epithelial cells %85.8±10.486.5±6.586.9±8.786.9±8.5
    PMNs %6.9±6.15±3.27.2±7.86.8±6.1
    Lymphocytes %7.3±10.78.4±65.5±7.36.3±5.6
    FEV197.6±13.278.2±7.7#99±9.4NA
    FEV1/FVC89.3±5.776.5±3.2#90.4±5.2NA
    FEF25–75%103.6±17.956.2±9.6#107.3±18.2NA
    • Data are presented as n or mean±sd, unless otherwise stated. Statistical comparisons were performed in allergic (groups a, A and R) versus healthy control subjects (group C) and in uncontrolled (group A) versus controlled (group a) asthmatics using unpaired t-tests and the Chi-squared test. PMN: polymorphonuclear cell; FEV1: forced expiratory volume in 1 s; FVC: forced vital capacity; FEF25–75%: forced expiratory flow at 25–75% of FVC; NA: not available. #: p<0.005 for group A versus group a by unpaired t-test.

  • Table 2– Genes differentially expressed in nasal epithelial brushings from dust mite-allergic rhinitis patients versus healthy subjects (microarray analysis)
    Probe set identifiermRNA accession numberUniGene identifierGeneGene productCytobandlog2(signal)log2(allergic/healthy)p-value
    8065412NM_001898Hs.123114CST1Cystatin SN20p11.219.657.154.95×10−12
    7971077NM_006475Hs.136348/Hs.664318POSTNPeriostin, osteoblast-specific factor13q13.37.123.562.66×10−3
    8083260NM_001870Hs.646CPA3Carboxypeptidase A3 (mast cell)3q21–q256.172.515.20×10−5
    7921690NM_017625Hs.50813ITLN1Intelectin 1 (galactofuranose binding)1q22–q23.55.832.453.87×10−2
    8065416NM_001322Hs.669305CST2Cystatin SA20p11.217.971.871.06×10−3
    8084657NM_014375Hs.81073FETUBFetuin B3q275.781.773.63×10−3
    8021635NM_002575Hs.594481SERPINB2Serpin peptidase inhibitor, clade B (ovalbumin), member 218q21.39.201.646.97×10−3
    8056222NM_001935Hs.368912DPP4Dipeptidyl-peptidase 4 (CD26)2q24.36.441.566.18×10−3
    7921900NM_053282Hs.350581SH2D1BSH2 domain-containing 1B1q215.911.553.05×10−7
    8036755NM_001828Hs.889CLCCharcot−Leyden crystal protein19q13.14.571.502.73×10−2
    7984001NM_004751Hs.194710GCNT3Glucosaminyl (N-acetyl) transferase 3, mucin type15q21.38.731.398.15×10−5
    8063761NM_177980Hs.54973CDH26Cadherin-like 2620q13.2–q13.338.671.386.84×10−3
    8089568NM_138806Hs.309158CD200R1CD200 receptor 13q13.28.901.353.90×10−5
    8112668NM_016591Hs.272404GCNT4Glucosaminyl (N-acetyl) transferase 4, core 2 (β-1,6-N-acetylglucosaminyltransferase)5q125.851.294.05×10−2
    8070567NM_003226Hs.82961TFF3Trefoil factor 3 (intestinal)21q22.39.861.262.11×10−2
    7942135NM_018043Hs.503074TMEM16ATransmembrane protein 16A11q13.37.411.236.48×10−3
    8154233NM_014143Hs.521989CD274CD274 molecule9p246.751.233.84×10−5
    7957458NM_006183Hs.80962NTSNeurotensin12q219.141.164.79×10−2
    8023688NM_002974Hs.123035SERPINB4Serpin peptidase inhibitor, clade B (ovalbumin), member 418q21.38.671.153.40×10−3
    8147132NM_000067Hs.155097CA2Carbonic anhydrase II8q226.441.143.87×10−2
    7909946GENSCAN00000026059NANANANA6.011.141.05×10−2
    8156134NM_006180Hs.494312//Hs.653428NTRK2Neurotrophic tyrosine kinase receptor, type 29q22.15.631.105.93×10−3
    8102050NM_178833Hs.546482NHEDC2Na+/H+ exchanger domain-containing 24q246.021.026.84×10−3
    8089851NM_000187Hs.368254HGDHomogentisate 1,2-dioxygenase (homogentisate oxidase)3q13.335.71-1.222.50×10−2
    • Genes were ranked according to decreasing log2(allergic/healthy). Only genes with a log2(ratio) >1 and a significant p-value (p<0.05) after a Benjamini–Hochberg correction for multiple tests were selected. Bold indicates genes induced in vitro with a value of log2(ratio) >1 by both interleukin (IL)-4 and IL-13 in human nasal epithelial cells. A more detailed table is provided as online supplementary table E3. NA: not available.

Additional Files

  • Figures
  • Tables
  • Supplementary material

    Files in this Data Supplement:

    • Supplementary tables - Tables E1-E8
    • Supplementary materials and methods - Subjects and samples
      Viral respiratory tract infection detection by Real-time quantitative PCR (qPCR)
      Isolation and culture of primary human nasal epithelial cells (HNECs)
      Microarray analysis
      Real-time quantitative PCR (qPCR)
      Immunohistochemistry
    • Figure E1
    • Figure E2
    • Figure E3
    • Figure E4
    • Figure E5
PreviousNext
Back to top
View this article with LENS
Vol 39 Issue 5 Table of Contents
European Respiratory Journal: 39 (5)
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
Email

Thank you for your interest in spreading the word on European Respiratory Society .

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Distinct epithelial gene expression phenotypes in childhood respiratory allergy
(Your Name) has sent you a message from European Respiratory Society
(Your Name) thought you would like to see the European Respiratory Society web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Print
Citation Tools
Distinct epithelial gene expression phenotypes in childhood respiratory allergy
Lisa Giovannini-Chami, Brice Marcet, Chimène Moreilhon, Benoît Chevalier, Marius I. Illie, Kévin Lebrigand, Karine Robbe-Sermesant, Thierry Bourrier, Jean-François Michiels, Bernard Mari, Dominique Crénesse, Paul Hofman, Jacques de Blic, Laurent Castillo, Marc Albertini, Pascal Barbry
European Respiratory Journal May 2012, 39 (5) 1197-1205; DOI: 10.1183/09031936.00070511

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero

Share
Distinct epithelial gene expression phenotypes in childhood respiratory allergy
Lisa Giovannini-Chami, Brice Marcet, Chimène Moreilhon, Benoît Chevalier, Marius I. Illie, Kévin Lebrigand, Karine Robbe-Sermesant, Thierry Bourrier, Jean-François Michiels, Bernard Mari, Dominique Crénesse, Paul Hofman, Jacques de Blic, Laurent Castillo, Marc Albertini, Pascal Barbry
European Respiratory Journal May 2012, 39 (5) 1197-1205; DOI: 10.1183/09031936.00070511
del.icio.us logo Digg logo Reddit logo Technorati logo Twitter logo CiteULike logo Connotea logo Facebook logo Google logo Mendeley logo
Full Text (PDF)

Jump To

  • Article
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • Acknowledgments
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

Subjects

  • Lung biology and experimental studies
  • Paediatric pulmonology
  • Tweet Widget
  • Facebook Like
  • Google Plus One

More in this TOC Section

Original Article

  • Lung volumes and survival in chronic lung allograft dysfunction
  • Social consequences of sleep disordered breathing
  • Diagnosing airflow obstruction in COPD
Show more Original Article

Paediatric Lung Disease

  • Airway microbiome changes related to ventilator-associated pneumonia
  • Does early onset asthma increase childhood obesity risk?
  • Air pollution exposure and lung function until age 16
Show more Paediatric Lung Disease

Related Articles

Navigate

  • Home
  • Current issue
  • Archive

About the ERJ

  • Journal information
  • Editorial board
  • Press
  • Permissions and reprints
  • Advertising

The European Respiratory Society

  • Society home
  • myERS
  • Privacy policy
  • Accessibility

ERS publications

  • European Respiratory Journal
  • ERJ Open Research
  • European Respiratory Review
  • Breathe
  • ERS books online
  • ERS Bookshop

Help

  • Feedback

For authors

  • Instructions for authors
  • Publication ethics and malpractice
  • Submit a manuscript

For readers

  • Alerts
  • Subjects
  • Podcasts
  • RSS

Subscriptions

  • Accessing the ERS publications

Contact us

European Respiratory Society
442 Glossop Road
Sheffield S10 2PX
United Kingdom
Tel: +44 114 2672860
Email: journals@ersnet.org

ISSN

Print ISSN:  0903-1936
Online ISSN: 1399-3003

Copyright © 2023 by the European Respiratory Society