Integrating longitudinal information on pulmonary function and inflammation using asthma phenotypes
2014; Elsevier BV; Volume: 133; Issue: 5 Linguagem: Inglês
10.1016/j.jaci.2013.12.1084
ISSN1097-6825
AutoresTadao Nagasaki, Hisako Matsumoto, Yoshihiro Kanemitsu, Kenji Izuhara, Yuji Tohda, Hideo Kita, Takahiko Horiguchi, Kazunobu Kuwabara, Keisuke Tomii, Kojiro Otsuka, Masaki Fujimura, Noriyuki Ohkura, Katsuyuki Tomita, Akihito Yokoyama, Hiroshi Ohnishi, Yasutaka Nakano, Tetsuya Oguma, Soichiro Hozawa, Isao Ito, Tsuyoshi Oguma, Hideki Inoue, Tomoko Tajiri, Toshiyuki Iwata, Yumi Izuhara, Junya Ono, Shoichiro Ohta, Akira Yokoyama, Akio Niimi, Michiaki Mishima,
Tópico(s)Chronic Obstructive Pulmonary Disease (COPD) Research
ResumoUnsupervised clustering approaches have recently provided a better understanding of asthma syndrome.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar, 2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar, 3Siroux V. Basagana X. Boudier A. Pin I. Garcia-Aymerich J. Vesin A. et al.Identifying adult asthma phenotypes using a clustering approach.Eur Respir J. 2011; 38: 310-317Crossref PubMed Scopus (205) Google Scholar, 4Amelink M. de Nijs S.B. de Groot J.C. van Tilburg P.M. van Spiegel P.I. Krouwels F.H. et al.Three phenotypes of adult-onset asthma.Allergy. 2013; 68: 674-680Crossref PubMed Scopus (129) Google Scholar, 5Kim T.B. Jang A.S. Kwon H.S. Park J.S. Chang Y.S. Cho S.H. et al.Identification of asthma clusters in two independent Korean adult asthma cohorts.Eur Respir J. 2012; 41: 1308-1314Crossref PubMed Scopus (110) Google Scholar, 6Boudier A. Curjuric I. Basagaña X. Hazgui H. Anto J.M. Bousquet J. et al.Ten-year follow-up of cluster-based asthma phenotypes in adults: a pooled analysis of three cohorts.Am J Respir Crit Care Med. 2013; 188: 550-560Crossref PubMed Scopus (86) Google Scholar Several studies have consistently identified new asthma phenotypes such as benign asthma, early-onset atopic asthma, and obese noneosinophilic asthma.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar, 2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar, 3Siroux V. Basagana X. Boudier A. Pin I. Garcia-Aymerich J. Vesin A. et al.Identifying adult asthma phenotypes using a clustering approach.Eur Respir J. 2011; 38: 310-317Crossref PubMed Scopus (205) Google Scholar, 4Amelink M. de Nijs S.B. de Groot J.C. van Tilburg P.M. van Spiegel P.I. Krouwels F.H. et al.Three phenotypes of adult-onset asthma.Allergy. 2013; 68: 674-680Crossref PubMed Scopus (129) Google Scholar Moore et al2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar and others7Amelink M. de Groot J.C. de Nijs S.B. Lutter R. Zwinderman A.H. Sterk P.J. et al.Severe adult-onset asthma: a distinct phenotype.J Allergy Clin Immunol. 2013; 132: 336-341Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar identified a neutrophilic-predominant phenotype with fixed severe airflow obstruction.2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar Late-onset eosinophilic asthma with few symptoms was identified by 2 research groups as an emerging phenotype.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar, 4Amelink M. de Nijs S.B. de Groot J.C. van Tilburg P.M. van Spiegel P.I. Krouwels F.H. et al.Three phenotypes of adult-onset asthma.Allergy. 2013; 68: 674-680Crossref PubMed Scopus (129) Google Scholar However, analyses on biomarkers and longitudinal information of these phenotypes are limited.6Boudier A. Curjuric I. Basagaña X. Hazgui H. Anto J.M. Bousquet J. et al.Ten-year follow-up of cluster-based asthma phenotypes in adults: a pooled analysis of three cohorts.Am J Respir Crit Care Med. 2013; 188: 550-560Crossref PubMed Scopus (86) Google Scholar We aimed to determine whether longitudinal information on pulmonary function and inflammation was associated with distinct asthma phenotypes. Adult patients with stable asthma were enrolled from 9 institutions participating in the Kinki Hokuriku Airway disease Conference.8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar All patients had received inhaled corticosteroid (ICS) therapy for at least 4 years and had undergone at least 3 pulmonary function tests. Current or ex-smokers smoking more than 10 pack-years were excluded. This study was approved by the ethics committee of each participating institution and was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000002414). Written informed consent was obtained from all participants. At enrollment, patients underwent a workup that included blood tests, as described previously.8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar In addition, because serum IL-6 was a marker of systemic inflammation, which increased in neutrophilic asthma,9Wood L.G. Baines K.J. Fu J. Scott H.A. Gibson P.G. The neutrophilic inflammatory phenotype is associated with systemic inflammation in asthma.Chest. 2012; 142: 86-93Crossref PubMed Scopus (210) Google Scholar and because IL-17 was closely related to IL-6, we measured serum IL-6, soluble IL-6 receptor, and IL-17 levels by using ELISA kits (R&D Systems, Inc, Minneapolis, Minn). Furthermore, in a subset of patients (n = 131), blood granulocyte counts before the initiation of ICS therapy were obtained from medical records on their first visits. Statistical analyses were performed by using JMP software, version 9.0 (SAS Institute, Inc, Tokyo, Japan). Hierarchical Ward's cluster analysis was also conducted. Because the number of clinical variables available in this study was limited, we used the variables that were determined by Haldar et al.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar In their study, 14 variables were categorized into the following 4 factors: symptom score, atopy/allergy, eosinophilic inflammation, and airflow variability. Accordingly, in our study, we used 4 variables, including the Asthma Control Test (ACT) scores, serum IgE levels, and blood eosinophil counts (because exhaled nitric oxide was not determined for all patients), corresponding to the above-mentioned factors. Furthermore, instead of airflow variability, we used prebronchodilator percent predicted FEV1 (% predicted FEV1). Therefore, a cluster analysis was performed by using these 4 variables and 3 demographic variables, including sex, age at asthma onset, and body mass index.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar Choosing these variables that were essential and measurable in our daily practice with asthma and avoiding excess weighting in a specific direction1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar would allow us to use these variables in an ethnically and genetically different population. As appropriate, 2 or more groups were compared by using the Wilcoxon rank-sum test, the Kruskal-Wallis test, or the χ2 test. Results are presented as means ± SDs. P < .05 was considered significant. The detailed demographic characteristics of 224 patients were previously reported.8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar On average, these patients had undergone 16.2 ± 13.9 FEV1 measurements, and the mean follow-up period was 8.0 ± 4.5 years. Four clusters were identified by using cluster analysis (Table I; see Fig E1 in this article's Online Repository at www.jacionline.org), of which clusters 1 and 2 were considered benign or mild: Cluster 1 was characterized by patients with late-onset nonatopic asthma and paucigranulocytic inflammation (defined as <250 eosinophils/μL and <5000 neutrophils/μL10Nadif R. Siroux V. Oryszczyn M.P. Ravault C. Pison C. Pin I. et al.Heterogeneity of asthma according to blood inflammatory patterns.Thorax. 2009; 64: 374-380Crossref PubMed Scopus (97) Google Scholar), with the highest %FEV1 among the 4 clusters, and cluster 2 was characterized by patients with early-onset atopic asthma and mild eosinophilic inflammation.Table IPatients' characteristics and biomarkers of each clusterCluster 1: late-onset, nonatopic, paucigranulocytic (n = 25)Cluster 2: early-onset, highly atopic (n = 105)Cluster 3: late-onset, highly eosinophilic (n = 73)Cluster 4: poorly controlled, mixed granulocytic, low FEV1 (n = 21)P value∗By Kruskal-Wallis test or χ2 test, except for ΔFEV1.Sex, males/females, n0/2532/7319/542/19.005Age at enrollment (y)68.9 ± 9.855.3 ± 13.669.4 ± 9.064.9 ± 14.3<.0001Age at asthma onset (y)55.7 ± 13.129.0 ± 14.856.2 ± 9.841.4 ± 21.9<.0001Body mass index (kg/m2)24.0 ± 2.323.2 ± 3.721.7 ± 2.325.7 ± 5.3.0002Smoking history, ex (%)8231819.39Pediatric asthma, none/recurrent/persistent, n24/1/069/15/2171/1/118/0/3<.0001Disease duration (y)13 ± 1026 ± 1613 ± 724 ± 16<.0001ICS daily maintenance dose (μg)†Equivalent to fluticasone propionate.432 ± 229505 ± 309536 ± 352694 ± 305.049Treatment step, 2-4/5‡According to the Global Initiative for Asthma 2010 guidelines.25/0100/567/613/8<.0001ACT (points)23.6 ± 1.823.4 ± 2.223.7 ± 1.713.9 ± 3.5<.0001Exacerbation within 6 mo0.2 ± 0.50.1 ± 0.50.1 ± 0.40.9 ± 0.9<.0001Adherence to medications§0, never; 1, seldom; 2, sometimes; 3, often; 4, always, to the question, "How often do you forget to take inhaled corticosteroids or other medications?"0.4 ± 0.50.8 ± 0.70.6 ± 0.70.7 ± 0.9.22Ischemic heart disease (%)021114.021Gastroesophageal reflux disease (%)2481638.002FEV1 at enrollment (% predicted)124.3 ± 16.696.7 ± 15.994.0 ± 24.780.9 ± 20.9<.0001FEV1/FVC at enrollment (%)77.1 ± 7.473.7 ± 9.968.8 ± 9.971.3 ± 11.2.0008ΔFEV1 (mL/y)‖Annual change in FEV1.−2.1 ± 28.9−1.7 ± 33.0−12.7 ± 36.1−28.2 ± 35.5.028¶Adjusted by sex, height, age at enrollment, and FEV1 at the first measurement.8Serum IgE (IU/mL)26 ± 17834 ± 2699576 ± 636410 ± 587<.0001Atopic predisposition (%)#Considered atopic when 1 or more specific IgE antibodies against cat or dog dander, weed, grass, Japanese cedar pollens, moulds, or house dust mite were positive.44796476.003Serum periostin (ng/mL)74.7 ± 24.590.3 ± 42.7101.6 ± 35.995.8 ± 30.0.001Serum ECP (μg/L)4.7 ± 4.215.7 ± 39.218.0 ± 18.013.6 ± 12.9<.0001Serum IL-6 (pg/mL)1.2 ± 1.01.1 ± 1.61.4 ± 1.92.1 ± 1.8.0001Serum soluble IL-6R (ng/mL)45.4 ± 14.542.6 ± 19.439.4 ± 20.545.7 ± 17.8.63Serum IL-17 (pg/mL)5.9 ± 8.75.8 ± 11.34.9 ± 10.06.7 ± 15.0.80Serum hsCRP (mg/L)665 ± 10561287 ± 30211184 ± 20592908 ± 6537.11Blood eosinophils (cells/μL)109 ± 85311 ± 363415 ± 408279 ± 241<.0001Blood neutrophils (cells/μL)3204 ± 8883749 ± 13123504 ± 11445771 ± 2330<.0001Data at enrollment are presented unless otherwise stated. Data are expressed as means ± SDs.ECP, Eosinophil cationic protein; FVC, forced vital capacity; hsCRP, high sensitivity C-reactive protein; IL-6R, IL-6 receptor.∗ By Kruskal-Wallis test or χ2 test, except for ΔFEV1.† Equivalent to fluticasone propionate.‡ According to the Global Initiative for Asthma 2010 guidelines.§ 0, never; 1, seldom; 2, sometimes; 3, often; 4, always, to the question, "How often do you forget to take inhaled corticosteroids or other medications?"‖ Annual change in FEV1.¶ Adjusted by sex, height, age at enrollment, and FEV1 at the first measurement.8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar# Considered atopic when 1 or more specific IgE antibodies against cat or dog dander, weed, grass, Japanese cedar pollens, moulds, or house dust mite were positive. Open table in a new tab Data at enrollment are presented unless otherwise stated. Data are expressed as means ± SDs. ECP, Eosinophil cationic protein; FVC, forced vital capacity; hsCRP, high sensitivity C-reactive protein; IL-6R, IL-6 receptor. Cluster 3 was characterized by patients with late-onset asthma and severe eosinophilic inflammation. The blood eosinophil counts (P = .008) and serum periostin levels (P = .003) were higher in cluster 3 than in cluster 2. The average ACT score in cluster 3 was more than 20, which was similar to that in clusters 1 and 2. Cluster 4 was characterized by patients showing the lowest ACT scores, frequent exacerbations within 6 months despite receiving high ICS doses, and mixed granulocytic patterns with the highest blood neutrophil counts. In cluster 4, serum IL-6 levels were the highest and serum periostin levels were the second highest among the 4 clusters. The frequencies of ischemic heart disease and gastro-oesophageal reflux were also the highest in this cluster. The longitudinal information revealed that the adjusted annual decline in FEV18Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar was significantly associated with these clusters (F value = 3.1; P = .028); cluster 4 exhibited the greatest decline in FEV1. Patients with an annual decline of 30 mL or more8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar in FEV1 were most frequently noted in cluster 4 (43%), followed by cluster 3 (32%). For post hoc analysis, patients in each cluster were stratified into 2 groups on the basis of their serum periostin levels because there was an association between serum periostin levels and pulmonary function decline in patients with asthma.8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar Patients in cluster 3 with high serum periostin levels (≥95 ng/mL)8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar showed a greater decline in FEV1 than did those with low serum periostin levels (<95 ng/mL [Fig 1]). In cluster 4, patients with both low and high serum periostin levels showed a similar degree of decline in FEV1. Before the initiation of ICS therapy, patients in cluster 3 showed the highest blood eosinophil counts and those in cluster 4 showed the highest blood neutrophil counts among the 4 clusters, although not all patient data were available (see Table E1 in this article's Online Repository at www.jacionline.org). Using clinically available and important variables, 2 mild and 2 moderate-to-severe clusters were identified among Japanese patients with asthma, which overlapped to a great extent with previously identified phenotypes for other ethnic groups.1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar, 2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar, 3Siroux V. Basagana X. Boudier A. Pin I. Garcia-Aymerich J. Vesin A. et al.Identifying adult asthma phenotypes using a clustering approach.Eur Respir J. 2011; 38: 310-317Crossref PubMed Scopus (205) Google Scholar, 4Amelink M. de Nijs S.B. de Groot J.C. van Tilburg P.M. van Spiegel P.I. Krouwels F.H. et al.Three phenotypes of adult-onset asthma.Allergy. 2013; 68: 674-680Crossref PubMed Scopus (129) Google Scholar Regarding differences from Euro-American studies,1Haldar P. Pavord I.D. Shaw D.E. Berry M.A. Thomas M. Brightling C.E. et al.Cluster analysis and clinical asthma phenotypes.Am J Respir Crit Care Med. 2008; 178: 218-224Crossref PubMed Scopus (1557) Google Scholar, 2Moore W.C. Meyers D.A. Wenzel S.E. Teague W.G. Li H. Li X. et al.Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program.Am J Respir Crit Care Med. 2010; 181: 315-323Crossref PubMed Scopus (1621) Google Scholar we did not identify a cluster of obese females with adult-onset asthma and minimal inflammation, possibly because of the few obese people in the Japanese population. The age of "late-onset asthma" was older. This may have been biased because of recall memory at enrollment, although we made every effort to ensure accuracy, including reviewing patients' medical records on their first visit when the age of asthma onset was also carefully recorded by experts. Here, we newly demonstrated that a decline in FEV1 and pretreatment inflammatory patterns were associated with these phenotypes, although the latter information was noted in only a subset of patients. Furthermore, the combination of unsupervised cluster analysis and a supervised subanalysis based on serum periostin levels successfully translated and expanded lung function–centered information8Kanemitsu Y. Matsumoto H. Izuhara K. Tohda Y. Kita H. Horiguchi T. et al.Increased periostin associates with greater airflow limitation in patients receiving inhaled corticosteroids.J Allergy Clin Immunol. 2013; 132: 305-312Abstract Full Text Full Text PDF PubMed Scopus (187) Google Scholar into patient-centered information. Indeed, in cluster 3, serum periostin levels were particularly informative for identifying patients who were apparently well controlled but at risk of functional undertreatment when symptom-based strategies are implemented. Cluster 4 showed the greatest decline in FEV1 and systemic inflammation. Biomarkers other than periostin that underlie the decline in FEV1 in this cluster should be further clarified. Although this study population was not limited to patients with severe asthma, we provided longitudinal information on asthma phenotypes, which could be generalized to other ethnic groups. Optimal management and targeting therapies for distinct asthma phenotypes are warranted. We thank Dr Kazuko Uno of the Louis Pasteur Center for Medical Research in Kyoto, Japan, and Ms Aya Inazumi and Ms Yuko Maeda of Kyoto University for their technical assistance. Table E1Blood granulocyte counts before treatment and at enrollmentBlood eosinophil countsBefore treatment (cells/μL)At enrollment (cells/μL)P value∗By Wilcoxon signed-rank test.Cluster 1 (n = 15)351 ± 600106 ± 70.0067Cluster 2 (n = 57)982 ± 1380369 ± 458<.0001Cluster 3 (n = 49)1646 ± 1897403 ± 346<.0001Cluster 4 (n = 10)623 ± 1171211 ± 267.49P value†By Kruskal-Wallis test.<.0001<.0001Blood neutrophil countsBefore treatment (cells/μL)At enrollment (cells/μL)P value∗By Wilcoxon signed-rank test.Cluster 1 (n = 15)3297 ± 14453472 ± 666.64Cluster 2 (n = 57)3521 ± 18573524 ± 1136.71Cluster 3 (n = 49)2501 ± 17783536 ± 1208.0003Cluster 4 (n = 10)4574 ± 16166611 ± 2748.084P value†By Kruskal-Wallis test..002.001∗ By Wilcoxon signed-rank test.† By Kruskal-Wallis test. Open table in a new tab
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