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Castaldi PJ, Benet M, Petersen H, Rafaels N, Finigan J, Paoletti M, Marike Boezen H, Vonk JM, Bowler R, Pistolesi M, Puhan MA, Anto J, Wauters E, Lambrechts D, Janssens W, Bigazzi F, Camiciottoli G, Cho MH, Hersh CP, Barnes K, Rennard S, Boorgula MP, Dy J, Hansel NN, Crapo JD, Tesfaigzi Y, Agusti A, Silverman EK, Garcia-Aymerich J. Do COPD subtypes really exist? COPD heterogeneity and clustering in 10 independent cohorts. Thorax 2017. [PMID: 28637835 DOI: 10.1136/thoraxjnl-2016-209846] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND COPD is a heterogeneous disease, but there is little consensus on specific definitions for COPD subtypes. Unsupervised clustering offers the promise of 'unbiased' data-driven assessment of COPD heterogeneity. Multiple groups have identified COPD subtypes using cluster analysis, but there has been no systematic assessment of the reproducibility of these subtypes. OBJECTIVE We performed clustering analyses across 10 cohorts in North America and Europe in order to assess the reproducibility of (1) correlation patterns of key COPD-related clinical characteristics and (2) clustering results. METHODS We studied 17 146 individuals with COPD using identical methods and common COPD-related characteristics across cohorts (FEV1, FEV1/FVC, FVC, body mass index, Modified Medical Research Council score, asthma and cardiovascular comorbid disease). Correlation patterns between these clinical characteristics were assessed by principal components analysis (PCA). Cluster analysis was performed using k-medoids and hierarchical clustering, and concordance of clustering solutions was quantified with normalised mutual information (NMI), a metric that ranges from 0 to 1 with higher values indicating greater concordance. RESULTS The reproducibility of COPD clustering subtypes across studies was modest (median NMI range 0.17-0.43). For methods that excluded individuals that did not clearly belong to any cluster, agreement was better but still suboptimal (median NMI range 0.32-0.60). Continuous representations of COPD clinical characteristics derived from PCA were much more consistent across studies. CONCLUSIONS Identical clustering analyses across multiple COPD cohorts showed modest reproducibility. COPD heterogeneity is better characterised by continuous disease traits coexisting in varying degrees within the same individual, rather than by mutually exclusive COPD subtypes.
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Affiliation(s)
- Peter J Castaldi
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of General Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, USA
| | - Marta Benet
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Hans Petersen
- COPD Program, Lovelace Respiratory Research Institute, Albuquerque, New Mexico, USA
| | - Nicholas Rafaels
- Center for Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA
| | - James Finigan
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Matteo Paoletti
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - H Marike Boezen
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Judith M Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Russell Bowler
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Massimo Pistolesi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Milo A Puhan
- Epidemiology, Biostatistics & Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Josep Anto
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Els Wauters
- Vesalius Research Center (VRC), VIB, Leuven, Belgium.,Laboratory for Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium.,Respiratory Division, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Diether Lambrechts
- Vesalius Research Center (VRC), VIB, Leuven, Belgium.,Laboratory for Translational Genetics, Department of Oncology, KU Leuven, Leuven, Belgium
| | - Wim Janssens
- Respiratory Division, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Francesca Bigazzi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Gianna Camiciottoli
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Michael H Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Pulmonary and Critical Care Division, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Craig P Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Pulmonary and Critical Care Division, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Kathleen Barnes
- Center for Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA
| | - Stephen Rennard
- Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.,Clinical Discovery Unit, AstraZeneca, Cambridge, UK
| | - Meher Preethi Boorgula
- Center for Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Center, Aurora, Colorado, USA
| | - Jennifer Dy
- Department of Computer Science, Northeastern University, Boston, Massachusetts, USA
| | - Nadia N Hansel
- Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.,Department of Environmental Health Sciences, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - James D Crapo
- Department of Medicine, National Jewish Health, Denver, Colorado, USA
| | - Yohannes Tesfaigzi
- COPD Program, Lovelace Respiratory Research Institute, Albuquerque, New Mexico, USA
| | - Alvar Agusti
- Respiratory Institute, Hospital Clinic, University of Barcelona, IDIBAPS and CIBERES, Barcelona, Spain
| | - Edwin K Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Judith Garcia-Aymerich
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
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Brune K, Frank J, Schwingshackl A, Finigan J, Sidhaye VK. Pulmonary epithelial barrier function: some new players and mechanisms. Am J Physiol Lung Cell Mol Physiol 2015; 308:L731-45. [PMID: 25637609 DOI: 10.1152/ajplung.00309.2014] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Accepted: 01/27/2015] [Indexed: 12/20/2022] Open
Abstract
The pulmonary epithelium serves as a barrier to prevent access of the inspired luminal contents to the subepithelium. In addition, the epithelium dictates the initial responses of the lung to both infectious and noninfectious stimuli. One mechanism by which the epithelium does this is by coordinating transport of diffusible molecules across the epithelial barrier, both through the cell and between cells. In this review, we will discuss a few emerging paradigms of permeability changes through altered ion transport and paracellular regulation by which the epithelium gates its response to potentially detrimental luminal stimuli. This review is a summary of talks presented during a symposium in Experimental Biology geared toward novel and less recognized methods of epithelial barrier regulation. First, we will discuss mechanisms of dynamic regulation of cell-cell contacts in the context of repetitive exposure to inhaled infectious and noninfectious insults. In the second section, we will briefly discuss mechanisms of transcellular ion homeostasis specifically focused on the role of claudins and paracellular ion-channel regulation in chronic barrier dysfunction. In the next section, we will address transcellular ion transport and highlight the role of Trek-1 in epithelial responses to lung injury. In the final section, we will outline the role of epithelial growth receptor in barrier regulation in baseline, acute lung injury, and airway disease. We will then end with a summary of mechanisms of epithelial control as well as discuss emerging paradigms of the epithelium role in shifting between a structural element that maintains tight cell-cell adhesion to a cell that initiates and participates in immune responses.
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Affiliation(s)
- Kieran Brune
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland
| | - James Frank
- The Division of Pulmonary and Critical Care Medicine, University of California, San Francisco, San Francisco VA Medical Center, and NCIRE/Veterans Health Research Institute, San Francisco, California
| | - Andreas Schwingshackl
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee
| | - James Finigan
- Division of Oncology, Cancer Center, National Jewish Health, Denver, Colorado
| | - Venkataramana K Sidhaye
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland;
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Finigan J, Gossiel F, Glüer CC, Felsenberg D, Reid DM, Roux C, Eastell R. Endogenous estradiol and the risk of incident fracture in postmenopausal women: the OPUS study. Calcif Tissue Int 2012; 91:59-68. [PMID: 22644322 DOI: 10.1007/s00223-012-9611-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2012] [Accepted: 05/02/2012] [Indexed: 11/30/2022]
Abstract
Some, but not all, studies have found that low endogenous estradiol levels in postmenopausal women are predictive of fractures. The aim of this study was to examine the roles of endogenous estradiol (E(2)), sex hormone binding globulin (SHBG), and dehydroepiandrosterone sulfate (DHEAS) in the prediction of incident vertebral and nonvertebral fractures. The study subjects were 797 postmenopausal women from the population-based OPUS (Osteoporosis and Ultrasound Study) study. Spine radiographs and dual-energy X-ray absorptiometry scans were obtained for all subjects at baseline and 6-year follow-up. Nonfasting blood samples were taken at baseline for E(2), SHBG, DHEAS, and bone turnover markers. Incident nonvertebral fractures were self-reported and verified; vertebral fractures were diagnosed at a single center from spinal radiographs. Medical and lifestyle data were obtained by questionnaire at each visit. Thirty-nine subjects had an incident vertebral fracture and 119 a nonvertebral fracture. Estradiol in the lowest quartile predicted vertebral fracture independent of confounders including age, body mass index, bone mineral density, bone turnover, fracture history, and use of antiresorptive therapy, with an OR of 2.97 (95 % confidence interval [CI] 1.52-5.82) by logistic regression. A calculated free estradiol index was not a stronger predictor than total E(2). Higher SHBG predicted vertebral fracture independently of age and body mass index, but not independently of E(2), bone mineral density, or prevalent fracture. Low DHEAS did not predict vertebral fracture. Nonvertebral fractures were not predicted by any of E(2), SHBG, or DHEAS, either in univariate or multivariate analyses. These findings suggest that there may be mechanistic differences in the protective effect of E(2) at vertebral compared with nonvertebral sites.
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Affiliation(s)
- J Finigan
- Academic Unit of Bone Metabolism, University of Sheffield, Sheffield, UK.
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