Severity predictors of different phenotypes of T2 asthma endotype

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BACKGROUND

Asthma is a heterogeneous disease pathogenetically based on chronic airway inflammation [1]. Asthma endotypes are classified into two depending on the inflammation type: T2 endotype with eosinophilic inflammation development and non-T2 endotype with neutrophilic or paucigranulocytic inflammation development [2]. Asthma endotype is a disease subtype that has various phenotypes. Further, 50–80% of asthma patients have T2 endotype [3], particularly patients with severe asthma. The current Russian clinical guidelines consider severe asthma as a separate asthma phenotype. Severe asthma remains uncontrolled despite patient adherence to optimized therapy and treatment of concomitant pathologies, and high doses of corticosteroids (CS) are required to control the disease [2].

Epidemiological studies have indicated that severe asthma is observed in 5%–10% of asthma patients. However, severe asthma is the most critical socioeconomic burden for healthcare systems worldwide. Approximately 50% of the funds intended for treating asthma are generally spent on severe asthma treatment [4, 5]. Nagase et al. [6] have shown that medical expenses for the treatment of patients with severe uncontrolled asthma per year in Japan averaged US $8.346, which was significantly higher than in groups of patients with mild and moderate asthma. Furthermore, treatment costs for patients with uncontrolled severe asthma in Mexico were significantly higher compared with the treatment costs for patients with controlled asthma, with each exacerbation increasing costs by US $350 [7]. In Russia, the economic cost of asthma treatment is 13.7 billion rubles/year. This cost is associated with exacerbation treatment, accounting for the largest share of the cost to patients themselves [8].

Factors increasing the risk of asthma exacerbations have been identified: the lack of asthma control; the lack of adherence to prescribed therapy; decrease in forced expiratory volume in the first second (FEV₁ <60% of the project values); smoking; contact with trigger allergens; sputum and peripheral blood eosinophilia; one or more exacerbations over the past year; and concomitant diseases, such as rhinosinusitis, obesity, food allergies, and gastroesophageal reflux disease [2]. However, studies that aimed at identifying predictors of severe asthma are limited. Indicators, such as gender [9], old age [10], increased nitric oxide concentration in exhaled air, and absolute number of eosinophils in peripheral blood, can be predictors of severe asthma [11]. The identification of predictors of severe asthma will help clinical practitioners to timely determine the phenotype of severe asthma in a particular patient and make a personalized approach to the treatment strategy. Thus, research in this area remains relevant.

Therefore, this study aimed to conduct a comparative analysis of the clinical features of allergic and nonallergic phenotypes of T2-endotype asthma and determine predictors of severe asthma.

MATERIALS AND METHODS

Study design

An observational single-center cross-sectional case-control study was conducted.

Eligibility criteria

Inclusion criteria: patient aged 18–65 years; established clinical diagnosis of allergic or nonallergic phenotypes of T2-endotype asthma.

Exclusion criteria: allergen immunotherapy and/or biological therapy at the time of examination; medical records of these treatments received before the study.

Conditions

General clinical and allergological assessment was performed in the Republican Center for Clinical Immunology of the Republican Clinical Hospital of the Ministry of Health of the Republic of Tatarstan, Kazan.

Study duration

The study occurred from November 2019 to August 2022.

Description of medical intervention

We examined 150 patients with asthma aged 18–65 years, including 61 patients with T2-endotype asthma who enrolled in the study.

Asthma was diagnosed based on the diagnostic algorithm presented in the current clinical guidelines.

Examination included general clinical methods (general blood count with white blood cell differential and eosinophil count; spirometry with a bronchodilator test), specific allergy diagnostic methods (patient’s allergy history, skin prick tests with inhalant allergens), and enzyme immunoassay to monitor total and specific IgE levels. Asthma control was assessed using the Asthma Control Test (ACT).

Main study outcomes

The study analyzed clinical symptoms and features of asthma in patients with allergic and nonallergic phenotypes of T2-endotype asthma and identified predictors of severe asthma based on the developed prognostic model.

Additional study outcomes

There were no additional study outcomes.

Subgroup analysis

Following general clinical and allergological examination, the patients were divided into two groups: group 1, 34 patients with allergic asthma phenotype, and group 2, 27 patients with nonallergic phenotype of T2-endotype asthma. Subsequently, clinical and laboratory data were analyzed, and a prognostic model of severe asthma was developed.

Methods for recording outcomes

To record outcomes, we developed an individual patient record, which contained data from the general clinical and specific allergological examinations.

Ethical review

The study was approved by the local ethics committee of the FSBEI HE Kazan State Medical University of the Ministry of Health of Russia (protocol no. 4; dated April 28, 2020).

Statistical analysis

Sample size was not previously calculated. Statistical analysis and visualization of the obtained data were performed using the statistical computing environment R 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria) and Statistica 12.0 (StatSoft, TIBCO, USA). The normality test was conducted with the Shapiro–Wilk W-test. Descriptive analysis included calculation of median and quartiles (Me [Q₁; Q₃]) for non-normally distributed parameters. Comparative analysis was performed using the Mann–Whitney U test. p=0.05 indicated statistical significance.

Proportional odds models were used to analyze the association of asthma severity with possible predictors. Proportional odds ratio with corresponding 95% confidence intervals (95% CI) was used as an estimate of the effect size. Proportional odds models, including interactions between covariates, were utilized to establish differences in the effects of predictors on asthma severity according to asthma phenotype. The following indicators were considered as predictors of severe asthma: asthma phenotype; gender; age, including elderly age [12]; total number of daytime/nighttime symptoms per week; the number of exacerbations requiring systemic corticosteroids (CS) and hospitalizations; FEV₁ (% of the project values); body mass index (kg/m²); concomitant pathology (allergic rhinitis, allergic conjunctivitis, rhinosinusitis with nasal polyps); hypersensitivity to nonsteroidal anti-inflammatory drugs; smoking; sensitization to the main groups of inhalant allergens; and peripheral blood eosinophil count. The association was considered statistically significant with p <0.05.

Stepwise selection (exclusion method) of variables into the multivariate prognostic model was performed using Akaike information criterion. Selected predictors were included in a proportional odds model without interactions. Multicollinearity was assessed using variance inflation factor (VIF) values. Nagelkerke’s pseudo-R2, C-index, and Somers’ Dxy were evaluated as model characteristics.

RESULTS

Objects (participants) of the study

The study included 61 patients aged 18–65 years with allergic and nonallergic phenotypes of T2-endotype asthma. Group 1 included 34 patients with allergic asthma, of whom 15 (44.1%) were male and 19 (55.9%) were female. The median age of group 1 was 27 [20, 43] years. Group 2 included 27 patients with nonallergic phenotype of T2-endotype asthma, of which 6 (22.2%) were male and 21 (77.8%) were female. The median age of group 2 was 53 years [39, 58]. The clinical characteristics of patients from both groups are presented in Table. 1.

Table 1. Clinical characteristics of patients with allergic and non-allergic phenotypes of T2 endotype of asthma

Note: Statistical significance of difference between groups 1 and 2 was calculated using the Mann–Whitney U test. NSAIDs: nonsteroidal anti-inflammatory drugs; FEV1: forced expiratory volume in 1 second; sCS: systemic corticosteroids.

Main results of the study

Our results revealed clinical and anamnestic differences between patients in two studied groups. Patients with allergic phenotype of asthma were significantly younger than those with nonallergic phenotype. The disease onset in the group with allergic phenotype was registered at an earlier age. Additionally, patients with allergic asthma were more likely to have a family history of allergic diseases and asthma (p=0.001) (Table 1).

Moreover, the groups differed in the range of comorbidities. Concomitant allergic rhinitis was diagnosed in 32 (94.1%) patients with allergic phenotype of asthma, of whom 12 patients also had allergic conjunctivitis. In turn, 11 (40.7%) patients with nonallergic asthma were diagnosed with rhinosinusitis with nasal polyps, whereas 6 patients had hypersensitivity to nonsteroidal anti-inflammatory drugs.

Allergy testing revealed sensitization to inhalant allergens in all patients with allergic asthma (Fig. 1). Monosensitization was confirmed in 11 (32.4%) patients and polysensitization in 23 (67.7%) patients (p=0.002) (Fig. 1). No allergic sensitization was found in group 2, in contrast to group 1.

Fig. 1. Sensitization profile in patients with allergic asthma, n (%).

In both groups, patients had high peripheral blood eosinophil count (291.8 [140.6; 516.5] and 286.0 cells/μl [170.0; 451.0], respectively), indicating eosinophilic inflammation, a characteristic of patients with T2-endotype asthma. Furthermore, high IgE in the blood serum were detected only in patients with allergic asthma phenotype (251.5 [165.2; 496.1] and 61.0 IU/ml [24.0; 84.1], respectively; p=0.0001).

Moreover, the patients in both groups had different frequencies of daytime and nighttime asthma symptoms. Patients with nonallergic phenotype had higher frequency of both daytime and nighttime asthma attacks (Table 1). However, the number of patients with exacerbations requiring the administration of systemic CS and subsequent hospitalization in the year preceding observation did not differ significantly (p=0.520). Pulmonary function tests showed significantly lower FEV₁ value (% of the project values) in patients with nonallergic phenotype of asthma than in patients with allergic phenotype of asthma. The FEV₁ median was 79.0% [62.5; 90.0] and 93.0 % [63.3; 111.0], respectively (p=0.02).

The number of patients with severe asthma was significantly higher in the group with nonallergic phenotype of T2-endotype asthma (n=13, 48.2%; p=0.039). Conversely, the number of patients with moderate asthma was higher in the group with allergic phenotype of asthma (Fig. 2).

Fig. 2. Asthma severity in the studied groups.

According to clinical guidelines, anti-inflammatory therapy is crucial for asthma patients. Analysis of the controller therapy prescribed to the observed patients revealed that a larger number of patients with nonallergic phenotype of asthma (57.9%) received the maximum amount of drug therapy corresponding to the 4th and 5th stages of Global Initiative for Asthma owing to severe asthma. The number of patients receiving inhaled corticosteroids (iCS) in medium or high doses along with long-acting β2-agonists (LABAs) and systemic corticosteroids (sCS) or iCS along with LABAs and long-acting anticholinergics (LABAs) and sGCS was significantly higher in group 2 (n=5, 18.5%, versus n=2, 5.9%, respectively; p=0.001). Moreover, patients with allergic phenotype of asthma predominantly received treatment with low doses of inhaled corticosteroids/LABAs (Fig. 3).

Fig. 3. Controller medication characteristics; iCS: inhaled corticosteroids; LABA: long-acting β2 agonists; sCS: systemic corticosteroids; LAMA: long-acting muscarinic antagonists.

However, in 10 (52.6%) patients in group 1 and 14 (73.7%) patients in group 2, asthma remained uncontrolled, as confirmed by ACT. Concurrently, the median in group 2 was lower than that in group 1 (7 [6; 14.5] and 18 [9.5; 23] points, respectively, p=0.047).

At the time of examination, 15 (44.1%) patients with allergic phenotype of asthma and 8 (29.6%) patients with nonallergic phenotype of T2-endotype asthma did not receive controller therapy (p=0.021), which in a significant number of cases was associated with low adherence to prescribed treatment or the fact that the diagnosis of asthma was first established during the study.

The next stage of our study was to identify predictors of severe asthma. The following parameters were considered as predictors: asthma phenotype, gender, age (including the elderly), total number of daytime symptoms per week, total number of nighttime symptoms per week, the number of exacerbations requiring the use of CS and hospitalizations, FEV₁ (% of the project values), body mass index (kg/m²), concomitant pathology (allergic rhinitis, allergic conjunctivitis, rhinosinusitis with nasal polyps, hypersensitivity to nonsteroidal anti-inflammatory drugs), smoking, identified sensitization to the main groups of inhalant allergens, and absolute number of peripheral blood eosinophils.

A univariate analysis showed that asthma phenotype is a predictor of disease severity. For example, in patients with nonallergic phenotype of T2-endotype asthma, the chance of a more severe course was on average 3.14 [95% CI, 1.09–9.58] times higher compared to patients with allergic phenotype of asthma. Further, the identified sensitization was associated with a milder course of asthma (0.3 [95% CI, 0.1–0.85], p=0.026), as were concomitant diseases, such as allergic rhinitis and allergic conjunctivitis (OR, 0.29 [95% CI 0.09–0.84], p=0.026, and 0.16 [95% CI, 0.03–0.61], p=0.013, respectively). We found that an increase in patient age by each year was associated with an increase in the odds of a more severe course of asthma by an average of 1.06 times (95% CI, 1.02–1.11; p=0.002). Nonetheless, the older age of the patient was associated with an increase in the odds of a more severe course by 5.31 times (95% CI, 1.31–27.2; p=0.026). Regardless of asthma phenotype, increases in the total number of daytime symptoms per week, total number of nighttime symptoms per week, number of exacerbations requiring the use of CS, and number of hospitalizations because of exacerbations were associated with more severe asthma by an average of 1.05 (95% CI, 1.01–1.11), 1.21 (95% CI, 1.05–1.45), 3.46 (95% CI, 1.68–10.19), and 4 [95% CI, 1.75–12.32] times, respectively. In addition, a decrease in FEV₁ was a predictor of a more severe disease (OR, 0.96 [95% CI, 0.93–0.99]).

Subsequently, we compiled a multifactorial model of predictors of severe asthma. This model showed that variables such as the patient’s age at the time of examination, an increase in the number of nighttime symptoms, and a low FEV₁ value are associated with severe asthma (Table 2).

Table 2. Main predictors of asthma severity

Note: FEV₁: forced expiratory volume in 1 s; CS: corticosteroids; OR: odds ratio; CI: confidence interval; VIF: variance inflation factor.

Adverse events

No adverse events were observed.

DISCUSSION

Summary of the main outcome of the study

We performed a comparative analysis of the clinical features of allergic and nonallergic phenotypes of T2-endotype asthma. Significant predictors of severe asthma were identified using the proportional odds model.

Discussion of the main outcome of the study

Clinical and anamnestic differences were found between the allergic and nonallergic phenotypes of T2-endotype asthma. Patients with an allergic phenotype of asthma were younger at the time of disease onset compared to those with nonallergic phenotype of asthma. Similar results were reported by Pakkasela et al. [13], who in a cross-sectional study showed that patients with nonallergic phenotype of asthma were older than patients with allergic phenotype of asthma at the time of diagnosis. Additionally, only patients with allergic phenotype of asthma had a family history of atopic diseases in our study, which is consistent with literature data [14, 15].

A family history of asthma and other allergic diseases is directly linked to the development of asthma in patients [1, 16]. While the probability of asthma in a child is 25%, if one of the parents has an allergic disease, it increases to 40% in children whose parents both have allergic diseases [15]. Moreover, in patients with allergic phenotype of asthma polysensitization to inhalant allergens prevails (67.7%; p=0.002). Similar data were revealed by Burte et al. [17], who have reported polysensitization in 65% of patients with asthma and allergic rhinitis. Considering the pathogenesis of chronic inflammation in the bronchial mucosa in allergic phenotype of asthma, increased IgE was noted only in group 1 patients. This finding was consistent with that of other studies [18, 19].

Furthermore, patients in groups 1 and 2 differed by the range of concomitant pathologies. In patients with allergic phenotype of asthma, allergic rhinitis and its combination with allergic conjunctivitis prevailed, which is fully consistent with the results of epidemiological studies, showing that 40–90% of patients with asthma have symptoms of allergic rhinitis [20]. Conversely, in the group of patients with nonallergic phenotype of T2-endotype asthma, a significant number of patients (40.7%) had chronic sinusitis with nasal polyps, often combined with hypersensitivity to nonsteroidal anti-inflammatory drugs. This observation is consistent with that of previous studies, according to which 45–76% of patients with chronic sinusitis with nasal polyps have symptoms of asthma, and in 14% of cases, chronic sinusitis with nasal polyps is linked to hypersensitivity to nonsteroidal anti-inflammatory drugs [21–23]. However, Hakansson et al. [24], upon comparing individual parameters characterizing various asthma phenotypes in patients with chronic sinusitis with nasal polyps, have shown no relationship between atopy and chronic sinusitis with nasal polyps. Some studies have revealed that nonallergic phenotype of T2-endotype asthma was most often associated with central obesity [13, 25]. Our analysis also revealed a high body mass index in patients with nonallergic phenotype of asthma.

A subsequent univariate analysis showed that patients with nonallergic phenotype of T2-endotype asthma have a higher chance of developing severe asthma. This group included a higher number of patients with severe asthma and lower FEV₁ numbers compared to patients with allergic phenotype of asthma. An increase in the frequency of daytime and nighttime asthma symptoms was higher in patients with nonallergic phenotype of asthma, whereas the number of exacerbations requiring systemic CSs and hospitalizations were comparable in both groups. We found that an increase in FEV₁ was associated with a decrease in the chances of a more severe course of asthma (p=0.004), regardless of asthma phenotype. In general, similar data were obtained by other researchers who noted a more severe course of nonallergic phenotype of T2-endotype asthma and a more significant decrease in pulmonary function indicators in this category of patients [13, 26, 27]. Suruki et al. [28] have shown that patients with severe asthma have a higher risk of developing exacerbations. In addition, some studies have determined a relationship between the severity of nonallergic phenotype of T2-endotype asthma and chronic sinusitis with nasal polyps and hypersensitivity to nonsteroidal anti-inflammatory drugs [23, 29]. However, we were unable to identify such a relationship.

As we previously noted, in the group of patients with allergic phenotype of asthma, the proportion of patients with severe asthma was smaller compared to patients in group 2, where the proportion of patients with asthma of moderate severity was greater. Further, concomitant diseases (allergic rhinitis and allergic conjunctivitis) were not associated with an increased chance of developing a severe course of asthma, which is generally consistent with the data of Toppila Salmi et al. [9]. Moreover, this concomitant pathology in our study increased the chances of developing a mild course of asthma.

Gender and age of patients are found to be predictors of severe asthma [9, 30]. We have shown that elderly patients have an increased risk of developing severe asthma. However, our univariate analysis did not show a significant effect of the patient’s gender on the risk of developing severe asthma, although in the literature there is evidence of a more severe course of asthma in women, which is associated with the influence of ovarian hormones (estrogen and progesterone) on T2 inflammation [31].

Finally, high levels of peripheral blood eosinophils are also a predictor of severe asthma [32, 33]. Studies by Casciano [34] and Oppenheimer [35] have shown that the severity of asthma can be associated with a high level of peripheral blood eosinophils. In our study, patients in both groups had increased levels of peripheral blood eosinophils. However, univariate analysis revealed that an absolute number of eosinophils do not increase the risk of developing severe asthma.

At the final stage of the study, we conducted a multivariate analysis of predictors of severe asthma. The following parameters were studied as independent variables by selection with exclusion based on the Akaike information criterion: age of patients at the time of examination, absolute number of eosinophils, number of hospitalizations for exacerbations, number of exacerbations requiring the use of systemic CS, total number of night symptoms per week, and FEV₁ (percent of project values). Analysis showed that the absolute number of peripheral blood eosinophils, the number of hospitalizations for exacerbations, and exacerbations requiring the use of systemic CS did not increase the risk of severe asthma. In turn, the patient’s age at the time of examination, an increase in the number of nighttime symptoms, and a low FEV₁ are reliable criteria for the increased risk of severe asthma.

Study limitations

The study was limited by the small sample size.

CONCLUSION

Allergic and nonallergic phenotypes of T2-endotype asthma have clinical differences, which can be determined during analysis of clinical and anamnestic data. Patients with nonallergic phenotype of T2-endotype asthma are characterized by the late onset of the disease, absence of clinically significant sensitization, and concomitant pathology in the form of rhinosinusitis with nasal polyps, combined with hypersensitivity to nonsteroidal anti-inflammatory drugs. In addition, patients with this asthma phenotype are more likely to experience a severe course of the disease. In contrast, patients with allergic asthma are characterized by an early onset and milder course of the disease, concomitant allergic rhinitis, and other allergic diseases in a significant number of cases and clinically significant sensitization.

Our data showed that parameters, such as the number of nighttime symptoms per week, low FEV₁, and patient age, should be considered as significant predictors of severe asthma. Awareness of primary care physicians and specialists (allergists, pulmonologists, otorhinolaryngologists) regarding risk factors of severe asthma will help with earlier identification of patients with severe asthma and the prescription or timely correction of controller anti-inflammatory therapy to prevent severe exacerbations.

ADDITIONAL INFORMATION

Funding source. This work was supported by Russian Foundation for Basic Research, project N 19-05-50094.

Competing interests. The authors declare that they have no competing interests.

Authors’ contribution. All authors made a substantial contribution to the conception of the work, acquisition, analysis, interpretation of data for the work, drafting and revising the work, final approval of the version to be published and agree to be accountable for all aspects of the work. M.R. Khakimova ― formed a group of asthma patients and performed clinical examination of asthma patients, analyzed data, reviewed the literature, wrote the manuscript; A.R. Valeeva, N.Sh. Kurmaeva ― selected patients with asthma; O.V. Skorokhodkina ― shaped the conceptual framework, directed the project, analyzed data, wrote the manuscript.

About the authors

Milyausha R. Khakimova

Author for correspondence.
Email: mileushe7@gmail.com
ORCID iD: 0000-0002-3533-2596
SPIN-code: 1875-3934
Россия, Kazan

Alina R. Valeeva

Email: aliv05@mail.ru
ORCID iD: 0009-0007-6528-6774
SPIN-code: 1485-5669
Россия, Kazan

Naira S. Kurmaeva

Email: nkurmaeva@inbox.ru
ORCID iD: 0000-0002-5505-4984
SPIN-code: 6678-2044
Россия, Kazan

Olesya V. Skorokhodkina

Email: olesya-27@rambler.ru
ORCID iD: 0000-0001-5793-5753
SPIN-code: 8649-6138

MD, Dr. Sci. (Med.), Professor

References

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2. Fig. 1. Sensitization profile in patients with allergic asthma, n (%).

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3. Fig. 2. Asthma severity in the studied groups.

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4. Fig. 3. Controller medication characteristics; iCS: inhaled corticosteroids; LABA: long-acting β2 agonists; sCS: systemic corticosteroids; LAMA: long-acting muscarinic antagonists.

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