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J Gen Fam Med. 2017 October; 18(5): 315–316.
Published online 2017 August 31. doi:  10.1002/jgf2.72
PMCID: PMC5689423

Asthma phenotypes: An important step for tailor‐made therapy

Keitaro Nakamoto, MD, 1 Takeshi Saraya, MD, PhD, 1 and Hajime Takizawa, MD, PhD 1

Recently, many bronchial asthma patients have achieved good control with inhaled corticosteroid and long‐acting beta2‐agonists. However, some patients suffer from persistent asthmatic symptoms and have asthma attacks despite treatment with high doses of inhaled corticosteroid. This condition is called severe asthma, refractory asthma, or difficult‐to‐treat asthma. Severe asthma is a serious socio‐medical problem that affects 5%‐10% of patients, and the associated medical costs are high.1

Bronchial asthma was once considered to be a homogeneous disease, but nowadays, based on the accumulated knowledge, it can be recognized as a heterogeneous disease. Recently, in fact, one strategy for the management of severe asthma was established with the discovery of asthma phenotypes. Phenotype describes “observable characteristics” with no direct relationship to a disease process including physiology, triggers, and inflammatory parameters.2

A review article with special reference to asthma phenotypes by Horiguchi3 summarized two previous articles4, 5 referring to asthma phenotypes. For example, one report by Haldar et al.4 analyzed 184 asthma patients and identified five phenotypes using cluster analysis. Each cluster was as follows: (i) early‐onset atopic asthma, (ii) obese, noneosinophilic asthma, (iii) early‐onset symptom‐predominant asthma, (iv) benign asthma, and (v) inflammation‐predominant asthma. Similarly, in another report, Moore et al.5 also analyzed 726 asthma patients and identified five phenotypes. Thus, cluster analysis has emerged as another tool for characterizing asthmatic patients.

Schatz et al.6 examined 4130 patients (children: n=518, adolescents and adults: n=3612) who were enrolled in The Epidemiology and Natural History of Asthma Outcomes and Treatment Regimens (TENOR) study and also divided asthma into five phenotypes. They performed cluster analysis using seven variables: (i) sex, (ii) atopy, (iii) race, (iv) age at asthma onset, (v) smoking status (children: passive smoking, adolescents and adults: smoker or not), (vi) obesity, and (vii) aspirin sensitivity. This article reported that sex, atopic status, and nonwhite race were distinguishing variables in both strata. In particular, in asthmatic pediatric patients, the rate of passive smoke exposure was different among the five phenotypes, and aspirin sensitivity also differed among the five phenotypes in adult patients. Because this study recruited a large number of Caucasian patients (up to 75% of the enrolled subjects), the results might not be applicable to Japanese patients.

Indeed, Kaneko et al.7 examined phenotypes in Japanese patients with adult asthma. They also used cluster analysis and identified six phenotypes (A: older age at onset, no airflow obstruction; B: childhood onset, normal‐to‐mild airflow obstruction; C: childhood onset, the longest disease duration, and moderate‐to‐severe airflow obstruction; D: older age at onset, severe airflow obstruction; E: middle‐age at onset, no airflow obstruction; F: older age at onset, mild‐to‐moderate airflow obstruction). Those six phenotypes were not consistent with those of Schatz et al. possibly due to racial diversity in the latter group.

Interestingly, Lockey simply divided asthma phenotypes into two main categories: major asthma phenotypes and other asthma phenotypes, as shown in Table 1. He described the usefulness of identifying phenotypes, which enable physicians to treat the patients appropriately.8 To date, six articles have been published,3, 4, 5, 6, 7, 8 and all of them recommend phenotype classification in the management of severe asthma.

Table 1
Asthma phenotypes

The article by Horiguchi demonstrated tailor‐made treatment based on each of the phenotype. In Japan, an anti‐IgE monoclonal antibody (omalizumab) has been used for severe asthma; however, Horiguchi stated that omalizumab should be applied cautiously because it actually shows a poor response in low‐biomarker (low fractional exhaled nitric oxide (FeNO), peripheral blood eosinophil count, and serum periostin levels) group with severe asthma. In fact, in 2013, Hanania et al.9 showed greater benefit with omalizumab in a high‐biomarker (high FeNO, peripheral blood eosinophil count, and serum periostin levels) group compared with those in a low‐biomarker group. In this regard, Horiguchi recommended the use of omalizumab for patients with refractory atopic asthma (high FeNO, peripheral eosinophilia, and a high level of serum periostin).

In another report, the use of lebrikizumab (a monoclonal antibody to interleukin‐13) required the presence of a high serum periostin level to obtain a better FEV1 response than that of a placebo group.10 Thus, classification of the appropriate phenotype would contribute to the successful management of asthma.

In addition, in recent years, the new concept of asthma endotype, which is defined as a distinct functional or pathophysiological mechanism, has emerged.2 This new concept might accelerate the proper treatment of asthma. However, the precise clinical significance of asthma endotypes in the management of asthmatic patients is unknown. Of note, as a clinical pitfall, physicians should never forget to check the education status of their patients with severe asthma whenever they examine them (eg, Do the patients know how to use the devices properly or how to control their disease?).

In conclusion, presently, recognition of asthma phenotypes is a critical issue in the management of asthmatic patients, especially in those with severe asthma.


The authors have stated explicitly that there are no conflicts of interest in connection with this article.


1. Moore WC, Bleecker ER, Curran‐Everett D, et al. Characterization of the severe asthma phenotype by the National Heart, Lung, and Blood Institute's Severe Asthma Research Program. J Allergy Clin Immunol. 2007;119:405–13. [PubMed]
2. Lotvall J, Akdis CA, Bacharier LB, et al. Asthma endotypes: a new approach to classification of disease entities within the asthma syndrome. J Allergy Clin Immunol. 2011;127:355–60. [PubMed]
3. Horiguchi T. Bronchial asthma: progress in diagnosis and treatments. Topics: IV. Subtype/particular type/comorbidities; 1. Asthma phenotypes. Nihon Naika Gakkai Zasshi. 2013;102:1404–11. [PubMed]
4. Haldar P, Pavord ID, Shaw DE, et al. Cluster analysis and clinical asthma phenotypes. Am J Respir Crit Care Med. 2008;178:218–24. [PubMed]
5. Moore WC, Meyers DA, Wenzel SE, et al. Identification of asthma phenotypes using cluster analysis in the Severe Asthma Research Program. Am J Respir Crit Care Med. 2010;181:315–23. [PubMed]
6. Schatz M, Hsu JW, Zeiger RS, et al. Phenotypes determined by cluster analysis in severe or difficult‐to‐treat asthma. J Allergy Clin Immunol. 2014;133:1549–56. [PubMed]
7. Kaneko Y, Masuko H, Sakamoto T, et al. Asthma phenotypes in Japanese adults ‐ their associations with the CCL5 and ADRB2 genotypes. Allergol Int. 2013;62:113–21. [PubMed]
8. Lockey RF. Asthma phenotypes: an approach to the diagnosis and treatment of asthma. J Allergy Clin Immunol Pract. 2014;2:682–5. [PubMed]
9. Hanania NA, Wenzel S, Rosen K, et al. Exploring the effects of omalizumab in allergic asthma: an analysis of biomarkers in the EXTRA study. Am J Respir Crit Care Med. 2013;187:804–11. [PubMed]
10. Corren J, Lemanske RF, Hanania NA, et al. Lebrikizumab treatment in adults with asthma. N Engl J Med. 2011;365:1088–98. [PubMed]

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