{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T17:29:37Z","timestamp":1788283777089,"version":"build-2803163510"},"reference-count":38,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2017,8,1]],"date-time":"2017-08-01T00:00:00Z","timestamp":1501545600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["Grant\u2010in\u2010Aid for Young Scientists (B) (16K18949)"],"award-info":[{"award-number":["Grant\u2010in\u2010Aid for Young Scientists (B) (16K18949)"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Clin Experimental Allergy"],"published-print":{"date-parts":[[2017,11]]},"abstract":"<jats:title>Summary<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Asthma and chronic obstructive pulmonary disease (<jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content>) are heterogeneous diseases. The phenotypes that have clinical features of both asthma and <jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> are still incompletely understood.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>To clarify the best discriminators of the asthma\u2010<jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> overlap phenotype from asthma and <jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> subgroups using a clustering approach.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study assessed pathophysiological parameters, including <jats:styled-content style=\"fixed-case\">mRNA<\/jats:styled-content> expression levels of T helper cell\u2010related transcription factors, namely <jats:italic><jats:styled-content style=\"fixed-case\">TBX<\/jats:styled-content>21<\/jats:italic> (Th1), <jats:italic><jats:styled-content style=\"fixed-case\">GATA<\/jats:styled-content>3<\/jats:italic> (Th2), <jats:italic><jats:styled-content style=\"fixed-case\">RORC<\/jats:styled-content><\/jats:italic> (Th17) and <jats:italic><jats:styled-content style=\"fixed-case\">FOXP<\/jats:styled-content>3<\/jats:italic> (Treg), in peripheral blood mononuclear cells in asthma patients (n=152) and in <jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> patients (n=50). Clusters were determined using k\u2010means clustering. Exacerbations of asthma and <jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> were recorded during the 1\u2010year follow\u2010up period.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The cluster analysis revealed four biological clusters: cluster 1, predominantly patients with <jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content>; cluster 2, patients with an asthma\u2010<jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> overlap phenotype; cluster 3, patients with non\u2010atopic and late\u2010onset asthma; and cluster 4, patients with early\u2010onset atopic asthma. Hazard ratios for exacerbation were 2.5 (95% confidence interval [<jats:styled-content style=\"fixed-case\">CI<\/jats:styled-content>], 1.1\u20105.6) in cluster 1 and 2.3 (95% <jats:styled-content style=\"fixed-case\">CI<\/jats:styled-content>, 1.0\u20105.0) in cluster 2 compared with patients in other clusters. Cluster 2 was discriminated from other clusters by total serum IgE level \u2265310 <jats:styled-content style=\"fixed-case\">IU<\/jats:styled-content>\/<jats:styled-content style=\"fixed-case\">mL<\/jats:styled-content>, blood eosinophil counts \u2265280\u00a0cells\/\u03bcL, a higher ratio of <jats:italic><jats:styled-content style=\"fixed-case\">TBX<\/jats:styled-content>21<\/jats:italic>\/<jats:italic><jats:styled-content style=\"fixed-case\">GATA<\/jats:styled-content>3<\/jats:italic>,<jats:styled-content style=\"fixed-case\"> FEV<\/jats:styled-content><jats:sub>1<\/jats:sub>\/<jats:styled-content style=\"fixed-case\">FVC<\/jats:styled-content> ratio &lt;0.67 and smoking \u226510\u00a0pack\u2010years with an area under the curve of 0.94 (95% <jats:styled-content style=\"fixed-case\">CI<\/jats:styled-content>, 0.90\u20100.98) in the receiver operating characteristic analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions and Clinical Relevance<\/jats:title><jats:p>The asthma\u2010<jats:styled-content style=\"fixed-case\">COPD<\/jats:styled-content> overlap phenotype was characterized by peripheral blood eosinophilia and higher levels of IgE despite the Th2\u2010low endotype.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cea.12970","type":"journal-article","created":{"date-parts":[[2017,6,28]],"date-time":"2017-06-28T16:56:43Z","timestamp":1498669003000},"page":"1374-1382","source":"Crossref","is-referenced-by-count":35,"title":["A clustering approach to identify and characterize the asthma and chronic obstructive pulmonary disease overlap phenotype"],"prefix":"10.1111","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8027-3508","authenticated-orcid":false,"given":"K.","family":"Hirai","sequence":"first","affiliation":[{"name":"Department of Clinical Pharmacology &amp; 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