Format

Send to

Choose Destination
J Allergy Clin Immunol. 2017 Jun;139(6):1797-1807. doi: 10.1016/j.jaci.2016.08.048. Epub 2016 Oct 20.

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics.

Collaborators (193)

Adriaens N, Ahmed H, Aliprantis A, Alving K, Badorek P, Balgoma D, Barber C, Bautmans A, Behndig AF, Bel E, Beleta J, Berglind A, Berton A, Bigler J, Bisgaard H, Bochenek G, Boedigheimer MJ, Bøonnelykke K, Brandsma J, Braun A, Brinkman P, Burg D, Campagna D, Carayannopoulos L, Carvalho da Purfição Rocha JP, Chaiboonchoe A, Chaleckis R, Coleman C, Compton C, D'Amico A, Dahlén B, De Alba J, de Boer P, De Lepeleire I, Dekker T, Delin I, Dennison P, Dijkhuis A, Draper A, Edwards J, Emma R, Ericsson M, Erpenbeck V, Erzen D, Faulenbach C, Fichtner K, Fitch N, Flood B, Frey U, Gahlemann M, Galffy G, Gallart H, Garret T, Geiser T, Gent J, Gerhardsson de Verdier M, Gibeon D, Gomez C, Gove K, Gozzard N, Guo YK, Hashimoto S, Haughney J, Hedlin G, Hekking PP, Henriksson E, Hewitt L, Higgenbottam T, Hoda U, Hohlfeld J, Holweg C, Howarth P, Hu R, Hu S, Hu X, Hudson V, James AJ, Kamphuis J, Kennington EJ, Kerry D, Klüglich M, Knobel H, Knowles R, Knox A, Kolmert J, Konradsen J, Kots M, Krueger L, Kuo S, Kupczyk M, Lambrecht B, Lantz AS, Larsson L, Lazarinis N, Lone-Satif S, Marouzet L, Martin J, Masefield S, Mathon C, Matthews JG, Mazein A, Meah S, Maiser A, Menzies-Gow A, Metcalf L, Middelveld R, Mikus M, Miralpeix M, Monk P, Mores N, Murray CS, Musial J, Myles D, Naz S, Nething K, Nicholas B, Nihlen U, Nilsson P, Nordlund B, Östling J, Pacino A, Pahus L, Palkonnen S, Pavlidis S, Pennazza G, Petrén A, Pink S, Postle A, Powel P, Rahman-Amin M, Rao N, Ravanetti L, Ray E, Reinke S, Reynolds L, Riemann K, Riley J, Robberechts M, Roberts A, Rossios C, Russell K, Rutgers M, Santini G, Sentoninco M, Schoelch C, Schofield JPR, Seibold W, Sigmund R, Sjödin M, Skipp PJ, Smids B, Smith C, Smith J, Smith KM, Söderman P, Sogbesan A, Staykova D, Strandberg K, Sun K, Supple D, Szentkereszty M, Tamasi L, Tariq K, Thörngren JO, Thornton B, Thorsen J, Valente S, van Aalderenm W, van de Pol M, van Drunen K, van Geest M, Versnel J, Vestbo J, Vink A, Vissing N, von Garnier C, Wagerner A, Wagers S, Wald F, Walker S, Ward J, Weiszhart Z, Wetzel K, Wheelock CE, Wiegman C, Williams S, Wilson SJ, Woosdcock A, Yang X, Yeyashingham E, Yu W, Zetterquist W, Zwinderman K.

Author information

1
European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Lyon, France.
2
Janssen Research and Development LLC, Spring House, Pa.
3
Janssen Research and Development Ltd, High Wycombe, United Kingdom.
4
Acclarogen, St John's Innovation Centre, Cambridge, United Kingdom.
5
Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.
6
Respiratory Therapeutic Unit, GlaxoSmithKline, Stockley Park, United Kingdom.
7
AstraZeneca R&D Molndal, and Areteva R&D, Nottingham, United Kingdom.
8
Data Science Institute, Imperial College London, London, United Kingdom.
9
Department of Clinical Science, University of Bergen, Bergen, Norway.
10
Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy.
11
Département des Maladies Respiratoires, Aix Marseille Université Marseille, Marseille, France.
12
Centre for Allergy Research, Karolinska Institutet, Stockholm, Sweden.
13
National Heart and Lung Institute, Imperial College & Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom.
14
Centre for Respiratory Medicine and Allergy, University of Manchester, Manchester, United Kingdom.
15
Department of Pulmonology, Semmelweis University, Budapest, Hungary.
16
Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany.
17
Faculty of Medicine, Catholic University of the Sacred Heart, Rome, Italy.
18
Department of Medicine, Jagiellonian University Medical School, Krakow, Poland.
19
Department of Public Health and Clinical Medicine, Medicine, Umeå university, Umeå, Sweden.
20
Respiratory Research Unit, University of Nottingham, Nottingham, United Kingdom.
21
University Children's Hospital Bern, Bern, Switzerland.
22
NIHR Respiratory Biomedical Research Unit, Clinical and Experimental Sciences, Southampton, United Kingdom.
23
Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
24
National Heart and Lung Institute, Imperial College & Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom. Electronic address: f.chung@imperial.ac.uk.

Abstract

BACKGROUND:

Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided.

OBJECTIVES:

We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum.

METHODS:

Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data.

RESULTS:

Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels.

CONCLUSION:

Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.

KEYWORDS:

Severe asthma; clustering; partition-around-medoids algorithm; sputum eosinophilia

Comment in

PMID:
27773852
DOI:
10.1016/j.jaci.2016.08.048
[Indexed for MEDLINE]
Free full text

Supplemental Content

Full text links

Icon for Elsevier Science Icon for Spiral, Imperial College Digital Repository
Loading ...
Support Center