Subphenotypes of Mild-to-Moderate COPD by Factor and Cluster Analysis of Pulmonary Function, CT Imaging and Breathomics in a Population-Based Survey

被引:32
作者
Fens, Niki [1 ]
van Rossum, Annelot G. J. [1 ]
Zanen, Pieter [2 ]
van Ginneken, Bram [3 ,4 ]
van Klaveren, Rob J. [5 ]
Zwinderman, Aeilko H. [6 ]
Sterk, Peter J. [1 ]
机构
[1] Univ Amsterdam, Acad Med Ctr, Dept Resp Med, NL-1100 DE Amsterdam, Netherlands
[2] Univ Utrecht, Univ Med Ctr, Dept Pulmonol, Utrecht, Netherlands
[3] Univ Utrecht, Univ Med Ctr, Dept Radiol, Utrecht, Netherlands
[4] Radboud Univ Nijmegen, Med Ctr, NL-6525 ED Nijmegen, Netherlands
[5] Univ Rotterdam, Erasmus Med Ctr, Dept Pulmonol, Rotterdam, Netherlands
[6] Univ Amsterdam, Acad Med Ctr, Dept Clin Epidemiol & Biostatist, NL-1105 AZ Amsterdam, Netherlands
关键词
exhaled breath analysis; metabolomics; volatile organic compounds; phenotyping; electronic nose; ELECTRONIC NOSE; PHENOTYPES; DISEASE; LUNG; EMPHYSEMA; ASTHMA; STANDARDIZATION; IDENTIFICATION; DEFINE; FUTURE;
D O I
10.3109/15412555.2012.744388
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
100201 [内科学];
摘要
Introduction: Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers. Methods: Adults between 50-75 years with a smoking history of at least 15 pack-years derived from a random population-based survey as part of the NELSON study underwent detailed assessment of pulmonary function, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor and cluster analyses were performed on the subgroup of subjects fulfilling the GOLD criteria for COPD (post-BD FEV1 /FVC < 0.70). Results: Three hundred subjects were recruited, of which 157 fulfilled the criteria for COPD and were included in the factor and cluster analysis. Four clusters were identified: cluster 1 (n = 35; 22%): mild COPD, limited symptoms and good quality of life. Cluster 2 (n = 48; 31%): low lung function, combined emphysema and chronic bronchitis and a distinct breath molecular profile. Cluster 3 (n = 60; 38%): emphysema predominant COPD with preserved lung function. Cluster 4 (n = 14; 9%): highly symptomatic COPD with mildly impaired lung function. In a leave-one-out validation analysis an accuracy of 97.4% was reached. Conclusions: This unbiased taxonomy for mild to moderate COPD reinforces clusters found in previous studies and thereby allows better phenotyping of COPD in the general (ex-) smoking population.
引用
收藏
页码:277 / 285
页数:9
相关论文
共 38 条
[1]
Avoiding confusion in COPD: from risk factors to phenotypes to measures of disease characterisation [J].
Agusti, A. ;
Celli, B. .
EUROPEAN RESPIRATORY JOURNAL, 2011, 38 (04) :749-751
[2]
[Anonymous], 2002, The Analysis and Interpretation of Multivariate Data for Social Scientists
[3]
Acute Exacerbations of Chronic Obstructive Pulmonary Disease Identification of Biologic Clusters and Their Biomarkers [J].
Bafadhel, Mona ;
McKenna, Susan ;
Terry, Sarah ;
Mistry, Vijay ;
Reid, Carlene ;
Haldar, Pranabashis ;
McCormick, Margaret ;
Haldar, Koirobi ;
Kebadze, Tatiana ;
Duvoix, Annelyse ;
Lindblad, Kerstin ;
Patel, Hemu ;
Rugman, Paul ;
Dodson, Paul ;
Jenkins, Martin ;
Saunders, Michael ;
Newbold, Paul ;
Green, Ruth H. ;
Venge, Per ;
Lomas, David A. ;
Barer, Michael R. ;
Johnston, Sebastian L. ;
Pavord, Ian D. ;
Brightling, Christopher E. .
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2011, 184 (06) :662-671
[4]
The Role of CT Scanning in Multidimensional Phenotyping of COPD [J].
Bafadhel, Mona ;
Umar, Imran ;
Gupta, Sumit ;
Raj, J. Vimal ;
Vara, Dhiraj D. ;
Entwisle, James J. ;
Pavord, Ian D. ;
Brightling, Christopher E. ;
Siddiqui, Salman .
CHEST, 2011, 140 (03) :634-642
[5]
Time to define the disorders of the syndrome of COPD [J].
Beasley, Richard ;
Weatherall, Mark ;
Travers, Justin ;
Shirtcliffe, Philippa .
LANCET, 2009, 374 (9691) :670-672
[6]
Machaon CVE:: cluster validation for gene expression data [J].
Bolshakova, N ;
Azuaje, F .
BIOINFORMATICS, 2003, 19 (18) :2494-2495
[7]
The STARD statement for reporting studies of diagnostic accuracy: Explanation and elaboration [J].
Bossuyt, PM ;
Reitsma, JB ;
Bruns, DE ;
Gatsonis, CA ;
Glasziou, PP ;
Irwig, LM ;
Moher, D ;
Rennie, D ;
de Vet, HCW ;
Lijmer, JG .
CLINICAL CHEMISTRY, 2003, 49 (01) :7-18
[8]
Clustering binary data in the presence of masking variables [J].
Brusco, MJ .
PSYCHOLOGICAL METHODS, 2004, 9 (04) :510-523
[9]
Clinical COPD phenotypes: a novel approach using principal component and cluster analyses [J].
Burgel, P-R. ;
Paillasseur, J-L. ;
Caillaud, D. ;
Tillie-Leblond, I. ;
Chanez, P. ;
Escamilla, R. ;
Court-Fortune, I. ;
Perez, T. ;
Carre, P. ;
Roche, N. .
EUROPEAN RESPIRATORY JOURNAL, 2010, 36 (03) :531-539
[10]
THE EUROPEAN-COMMUNITY-RESPIRATORY-HEALTH-SURVEY [J].
BURNEY, PGJ ;
LUCZYNSKA, C ;
CHINN, S ;
JARVIS, D ;
VERMEIRE, P ;
DAHL, R ;
NIELSEN, N ;
MAGNUSSEN, H ;
WICHMANN, H ;
PAPAGEORGIOU, N ;
ANTO, J ;
CAPELASTEGUI, A ;
CASTILLO, J ;
MALDONADO, J ;
MORATALLA, J ;
QUIROS, R ;
BOUSQUET, J ;
NEUKIRCH, F ;
PIN, I ;
TAYTARD, A ;
TECULESCU, D ;
PRICHARD, J ;
BUGIANI, M ;
DEMARCO, R ;
CASCIO, VL ;
RIJCKEN, B ;
AVILA, R ;
LOUREIRO, C ;
MARQUES, A ;
BURR, M ;
HALL, R ;
HARRISON, B ;
STARK, J ;
FLOREY, C ;
POPP, W ;
GISLASON, T ;
GULSVIK, A ;
ACKERMANNLIEBRICH, U ;
LINDHOLM, N ;
BOMAN, G ;
ROSENHALL, L ;
AITKHALED, N ;
ABRAMSON, M ;
MANFREDA, J ;
CHOWGULE, R ;
CRANE, J ;
STEPANOV, I ;
BUIST, S .
EUROPEAN RESPIRATORY JOURNAL, 1994, 7 (05) :954-960