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. 2024 Dec 16;10(6):00222-2024.
doi: 10.1183/23120541.00222-2024. eCollection 2024 Nov.

Association of blood inflammatory phenotypes and asthma burden in children with moderate-to-severe asthma

Amir Hossein Alizadeh Bahmani  1   2   3 , Susanne J H Vijverberg  1   2   3 , Simone Hashimoto  1   2   4 , Christine Wolff  5 , Catarina Almqvist  6 , Lizan D Bloemsma  1 , Susanne Brandstetter  7 , Paula Corcuera-Elosegui  8 , Mario Gorenjak  9 , Susanne Harner  5 , Anna M Hedman  6 , Michael Kabesch  5 , Leyre López-Fernández  8 , Aletta D Kraneveld  10 , Anne H Neerincx  1 , Maria Pino-Yanes  11   12   13 , Uroš Potočnik  9 , Olaia Sardón-Prado  8   14 , Barbara S Dierdorp  2   15 , Tamara Dekker  2   15 , Nariman K A Metwally  1 , Jan Willem Duitman  1   2   15 , René Lutter  1   2   15 , Paul Brinkman  1   2   3 , Mahmoud I Abdel-Aziz  1   2   3 , Anke H Maitland-van der Zee  1   2   3
Affiliations

Association of blood inflammatory phenotypes and asthma burden in children with moderate-to-severe asthma

Amir Hossein Alizadeh Bahmani et al. ERJ Open Res. .

Abstract

Background: Underlying immunological mechanisms in children with moderate-to-severe asthma are complex and unclear. We aimed to investigate the association between blood inflammatory parameters and asthma burden in children with moderate-to-severe asthma.

Methods: Blood inflammatory parameters (eosinophil and neutrophil counts and inflammatory mediators using multiplex immunoassay technology) were measured in children (6-17 years) with moderate-to-severe asthma from the SysPharmPediA cohort across four European countries. Based upon low/high blood eosinophil (LBE/HBE) counts of </≥0.3×109·L-1, respectively and low/high blood neutrophil (LBN/HBN) counts of </≥4×109·L-1, respectively, mixed (HBE-HBN), eosinophilic (HBE-LBN), neutrophilic (LBE-HBN) and paucigranulocytic (LBE-LBN) phenotypes were defined. Inflammatory mediator profiles and burden of disease (asthma control status, exacerbations and school days missed in the past year) were compared between phenotypes using adjusted logistic regression models.

Results: Among 126 included children (41% girls and mean (sd) age of 11.94 (2.76)), 22%, 44%, 11% and 23% were classified as mixed, eosinophilic, neutrophilic and paucigranulocytic phenotypes, respectively. Neutrophilic children had the lowest lung function (forced expiratory volume in 1 s % predicted pre-salbutamol) compared with other groups. Children with mixed asthma were most often uncontrolled and had the highest asthma-related school absence in the past year. Interleukin (IL)-6 and matrix metalloproteinase-9 levels were significantly higher in patients with mixed or neutrophilic asthma, whereas tissue inhibitor of metalloproteinase-2 was lower in patients with neutrophilic asthma compared with eosinophilic or paucigranulocytic asthma. IL-5 was increased in eosinophilic group compared with the neutrophilic and paucigranulocytic groups, irrespective of the chosen cut-off for eosinophilia.

Conclusion: Differences in asthma burden-related clinical expression and distinct blood inflammatory mediator profiles were found between phenotypes, highlighting implications for optimising personalised treatment and management strategies in children with moderate-to-severe asthma.

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Conflict of interest statement

Conflict of interest: A.H. Alizadeh Bahrani, S.J.H. Vijverberg, S. Hashimoto, C. Wolff, C. Almqvist, S. Brandstetter, P. Corcuera-Elosegui, S. Harner, A.M. Hedman, L. López-Fernández, A.D. Kraneveld, O. Sardón-Prado, B.S. Dierdop, T. Dekker, N.K.A. Metwally, R. Lutter and P. Brinkman have no conflicts of interest to disclose. L.D. Bloemsma received funding from partners in the Precision Medicine for More Oxygen (P4O2) consortium, which are the Amsterdam UMC, Leiden University Medical Center, Maastricht UMC+, Maastricht University, UMC Groningen, UMC Utrecht, Utrecht University, TNO, Aparito, Boehringer Ingelheim, Breathomix, Clear, Danone Nutricia Research, Fluidda, MonitAir, Ncardia, Ortec Logiqcare, Philips, Proefdiervrij, Quantib-U, RespiQ, Roche, Smartfish, SODAQ, Thirona, TopMD, Lung Alliance Netherlands, the Lung Foundation Netherlands (Longfonds), PPP Allowance made available by Health∼Holland, and Top Sector Life Sciences and Health (LSHM20104 and LSHM20068), to stimulate public–private partnerships and by Novartis. M. Gorenjak received SysPharmPediA grant, cofinanced by the Ministry of Education, Science and Sport Slovenia (MIZS) (contract number C3330-16-500106) and funded by the Slovenian Research Agency (research core funding number P3-0427), and by the Ministry of Education, Science and Sport of the Republic of Slovenia grant PERMEABLE (contract number C3330-19-252012). M. Kabesch received funding from Bundesministerium für Bildung und Forschung (BMFB) grant SysPharmPediA, European Union, BMFB, German Research Foundation, Infectopharm, Bavarian Minsitry of Education and Research, and Bavarian Ministry of Health. He received consulting fees from Bionorica, Sanofi, Novartis and Bencard; he also received honoraria from ERS, EAACI, ATS, Novartis, Glaxo, Chiesi, Sanofi, Nutricia, Hipp and Allergopharma. A.H. Neerincx has received ERANET Systems Medicine and ZonMW grants (project number 9003035001). M. Pino-Yanes received funding from Instituto de Salud Carlos III (AC15/00015) as part of the SysPharmPediA consortium, and grants from MCIN/AEI/10.13039/501100011033, GlaxoSmithKline Spain and CSL Berhing outside of the submitted work. U. Potočnik received SysPharmPediA grant, cofinanced by the Ministry of Higher Education, Science and Innovation Slovenia (MVZI) (contract number C3330-16-500106) and Slovenian Research Agency (research core funding number P3-0427 and research grant number J3-4497). J.W. Duitman received grants from Abbvie and Boehringer Ingelheim in the past 36 months. M.I. Abdel-Aziz was funded by a full PhD scholarship from the Ministry of Higher Education of the Arab Republic of Egypt during the conduct of the study. A.H. Maitland-van der Zee is the principal investigator of a public–private consortium (P4O2) sponsored by Health Holland involving many private partners that contribute in cash and/or in kind (AbbVie, Boehringer Ingelheim, Breathomix, Clear, Fluidda, Ortec Logiqcare, Olive, Philips, Quantib-U, Smartfish, Clear, SODAQ, Thirona, Roche, TopMD, Novartis and RespiQ); she received unrestricted research grants from GSK and Boehringer Ingelheim, and a Vertex Innovation Award grant; and she has received honoraria from Boehringer Ingelheim, GSK and AstraZeneca.

Figures

None
Graphical abstract
FIGURE 1
FIGURE 1
Categorising participants into four different groups using a set of cut-offs for blood eosinophil (BE) (0.3×109·L−1) and blood neutrophil (BN) (4×109·L−1) counts. WBC: white blood cell.
FIGURE 2
FIGURE 2
Adjusted association of blood inflammatory phenotypes defined by high and low blood eosinophil and neutrophil levels with asthma burden. Phenotypes were defined based upon low/high blood eosinophil (LBE/HBE) counts of 9·L−1, respectively, and low/high blood neutrophil (LBN/HBN) counts of </≥4×109·L−1, respectively; mixed (HBE-HBN), eosinophilic (HBE-LBN), neutrophilic (LBE-HBN) and paucigranulocytic (LBE-LBN). The models were adjusted for confounding factors such as age, sex, smoking exposure, BMI z-score, centre of inclusion, antibiotic intake in the past 2 months, inhaled corticosteroid daily dose levels (low, moderate and high based on GINA guidelines), medication adherence, biological intake and ethnicity (White and non-White). The x axis shows the OR values. The red dashed line indicates the significance level threshold. The paucigranulocytic group was considered as the reference group. OR: odds ratio; CI: confidence interval.
FIGURE 3
FIGURE 3
Cytokine and mediator levels for each inflammatory phenotype. Phenotypes were defined based upon low/high blood eosinophil (LBE/HBE) counts of 9·L−1, respectively and low/high blood neutrophil (LBN/HBN) counts of </≥4×109·L−1, respectively), mixed (HBE-HBN), eosinophilic (HBE-LBN), neutrophilic (LBE-HBN) and paucigranulocytic (LBE-LBN). The adjusted p-values shown in the figures are the corrected p-values by multiple testing by Benjamini–Hochberg false discovery rate. IL: interleukin; MMP: matrix metalloproteinase; PARC: pulmonary and activation-regulated chemokine; TIMP: tissue inhibitor of metalloproteinase; OSF2: periostin; MDC: macrophage-derived chemokine; CRP: C-reactive protein; NS: p>0.05; *: p<0.05; **: p<0.01; ***: p<0.001; ****: p<0.0001.
FIGURE 4
FIGURE 4
Heatmap and cluster analysis of the inflammatory mediator profiles per patient between each phenotype. Phenotypes were defined based upon low/high blood eosinophil (LBE/HBE) counts of 9·L−1, respectively and low/high blood neutrophil counts (LBN/HBN) of </≥4×109·L−1, respectively, mixed (HBE-HBN), eosinophilic (HBE-LBN), neutrophilic (LBE-HBN) and paucigranulocytic (LBE-LBN). a) Heatmap of blood inflammatory mediators. Each column represents an individual participant and each row shows the abundance of the mentioned mediator (z-score). b) Sparse partial least squares discriminant analysis (sPLS-DA) scores plot for each phenotype. c) Strongest contributing variables (mediators) to sPLS-DA components. d,e) Boxplots of sPLS-DA components 1 (d) and 2 (e) for each phenotype, including Kruskal–Wallis and pairwise Wilcoxon test results (false discovery rate adjusted). IL: interleukin; MMP: matrix metalloproteinase; PARC: pulmonary and activation-regulated chemokine; TIMP: tissue inhibitor of metalloproteinase; OSF2: periostin; MDC: macrophage-derived chemokine; CRP: C-reactive protein; NS: p>0.05; *: p<0.05; **: p<0.01; ***: p<0.001; ****: p<0.0001.
FIGURE 5
FIGURE 5
Summary of findings regarding asthma burden and inflammatory mediators. The paucigranulocytic group was considered as the reference group. a) Main analysis. b) Sensitivity analysis. Phenotypes were defined based upon low/high blood eosinophil (LBE/HBE) counts of 9·L−1 (main analysis) or 0.5×109·L−1 (sensitivity analysis), respectively and low/high blood neutrophil (LBN/HBN) counts of </≥4×109·L−1, respectively, mixed (HBE-HBN), eosinophilic (HBE-LBN), neutrophilic (LBE-HBN) and paucigranulocytic (LBE-LBN). IL: interleukin; MMP: matrix metalloproteinase; TARC: thymus and activation-regulated chemokine; PARC: pulmonary and activation-regulated chemokine; TIMP: tissue inhibitor of metalloproteinase; CRP: C-reactive protein.
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