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

Details

Serval ID
serval:BIB_A38FD2552764
Type
Article: article from journal or magazin.
Collection
Publications
Title
U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics.
Journal
The Journal of allergy and clinical immunology
Author(s)
Lefaudeux D., De Meulder B., Loza M.J., Peffer N., Rowe A., Baribaud F., Bansal A.T., Lutter R., Sousa A.R., Corfield J., Pandis I., Bakke P.S., Caruso M., Chanez P., Dahlén S.E., Fleming L.J., Fowler S.J., Horvath I., Krug N., Montuschi P., Sanak M., Sandstrom T., Shaw D.E., Singer F., Sterk P.J., Roberts G., Adcock I.M., Djukanovic R., Auffray C., Chung K.F.
Working group(s)
U-BIOPRED Study Group
Contributor(s)
Adriaens N., Ahmed H., Aliprantis A., Alving K., Badorek P., Balgoma D., Barber C., Bautmans A., Behndig A.F., Bel E., Beleta J., Berglind A., Berton A., Bigler J., Bisgaard H., Bochenek G., Boedigheimer M.J., Bøonnelykke K., Brandsma J., Braun A., Brinkman P., Burg D., Campagna D., Carayannopoulos L., Carvalho da Purfição Rocha J.P., 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 Y.K., Hashimoto S., Haughney J., Hedlin G., Hekking P.P., Henriksson E., Hewitt L., Higgenbottam T., Hoda U., Hohlfeld J., Holweg C., Howarth P., Hu R., Hu S., Hu X., Hudson V., James A.J., Kamphuis J., Kennington E.J., 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 A.S., Larsson L., Lazarinis N., Lone-Satif S., Marouzet L., Martin J., Masefield S., Mathon C., Matthews J.G., Mazein A., Meah S., Maiser A., Menzies-Gow A., Metcalf L., Middelveld R., Mikus M., Miralpeix M., Monk P., Mores N., Murray C.S., 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 P.J., Smids B., Smith C., Smith J., Smith K.M., Söderman P., Sogbesan A., Staykova D., Strandberg K., Sun K., Supple D., Szentkereszty M., Tamasi L., Tariq K., Thörngren J.O., 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 C.E., Wiegman C., Williams S., Wilson S.J., Woosdcock A., Yang X., Yeyashingham E., Yu W., Zetterquist W., Zwinderman K.
ISSN
1097-6825 (Electronic)
ISSN-L
0091-6749
Publication state
Published
Issued date
06/2017
Peer-reviewed
Oui
Volume
139
Number
6
Pages
1797-1807
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
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.
We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum.
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.
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.
Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways.
Keywords
Adult, Aged, Algorithms, Asthma/classification, Asthma/genetics, Asthma/metabolism, Biomarkers/metabolism, Female, Gene Expression Profiling, Humans, Leukocyte Count, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, Phenotype, Proteomics, Severity of Illness Index, Sputum/cytology, Sputum/metabolism, Severe asthma, clustering, partition-around-medoids algorithm, sputum eosinophilia
Pubmed
Web of science
Open Access
Yes
Create date
13/04/2017 16:57
Last modification date
15/10/2019 16:36
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