TY - JOUR
T1 - Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma
AU - Blankestijn, Jelle M.
AU - Lopez-Rincon, Alejandro
AU - Neerincx, Anne H.
AU - Vijverberg, Susanne J. H.
AU - Hashimoto, Simone
AU - Gorenjak, Mario
AU - Sardón Prado, Olaia
AU - Corcuera-Elosegui, Paula
AU - Korta-Murua, Javier
AU - Pino-Yanes, Maria
AU - Potočnik, Uroš
AU - Bang, Corinna
AU - Franke, Andre
AU - Wolff, Christine
AU - Brandstetter, Susanne
AU - Toncheva, Antoaneta A.
AU - Kheiroddin, Parastoo
AU - Harner, Susanne
AU - Kabesch, Michael
AU - Kraneveld, Aletta D.
AU - the SysPharmPediA Consortium
AU - Abdel-Aziz, Mahmoud I.
AU - Maitland-van der Zee, Anke H.
N1 - Funding Information: The SysPharmPediA consortium is supported by ZonMW [project number: 9003035001], the Ministry of Education, Science, and Sport of the Republic of Slovenia [contract number C330‐16‐500106]; the German Ministry of Education and Research (BMBF) [project number FKZ 031 L0088]; Instituto de Salud Carlos III (ISCIII) through Strategic Action for Health Research (AES) and European Community (EC) within the Active and Assisted Living (AAL) Program framework [award numbers AC15/00015 and AC15/00058] under the frame of the ERACoSysMed JTC‐1 Call. M.P.‐Y. was funded by the Ramón y Cajal Program (RYC‐2015‐17205) by the Spanish Ministry of Science and Innovation (MICINN), the State Research Agency, and the European Regional Development Fund from the European Union (MICINN/AEI/FEDER, UE, grant SAF2017‐83417R). U.P. and M.G. were funded by Slovenian Research Agency (research core funding No. P3‐0067). M.I.A.‐A. was funded by the Egyptian Government Ph.D. Scholarships. Publisher Copyright: © 2023 The Authors. Pediatric Allergy and Immunology published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Ltd.
PY - 2023/2/1
Y1 - 2023/2/1
N2 - Background: Uncontrolled asthma can lead to severe exacerbations and reduced quality of life. Research has shown that the microbiome may be linked with asthma characteristics; however, its association with asthma control has not been explored. We aimed to investigate whether the gastrointestinal microbiome can be used to discriminate between uncontrolled and controlled asthma in children. Methods: 143 and 103 feces samples were obtained from 143 children with moderate-to-severe asthma aged 6 to 17 years from the SysPharmPediA study. Patients were classified as controlled or uncontrolled asthmatics, and their microbiome at species level was compared using global (alpha/beta) diversity, conventional differential abundance analysis (DAA, analysis of compositions of microbiomes with bias correction), and machine learning [Recursive Ensemble Feature Selection (REFS)]. Results: Global diversity and DAA did not find significant differences between controlled and uncontrolled pediatric asthmatics. REFS detected a set of taxa, including Haemophilus and Veillonella, differentiating uncontrolled and controlled asthma with an average classification accuracy of 81% (saliva) and 86% (feces). These taxa showed enrichment in taxa previously associated with inflammatory diseases for both sampling compartments, and with COPD for the saliva samples. Conclusion: Controlled and uncontrolled children with asthma can be differentiated based on their gastrointestinal microbiome using machine learning, specifically REFS. Our results show an association between asthma control and the gastrointestinal microbiome. This suggests that the gastrointestinal microbiome may be a potential biomarker for treatment responsiveness and thereby help to improve asthma control in children.
AB - Background: Uncontrolled asthma can lead to severe exacerbations and reduced quality of life. Research has shown that the microbiome may be linked with asthma characteristics; however, its association with asthma control has not been explored. We aimed to investigate whether the gastrointestinal microbiome can be used to discriminate between uncontrolled and controlled asthma in children. Methods: 143 and 103 feces samples were obtained from 143 children with moderate-to-severe asthma aged 6 to 17 years from the SysPharmPediA study. Patients were classified as controlled or uncontrolled asthmatics, and their microbiome at species level was compared using global (alpha/beta) diversity, conventional differential abundance analysis (DAA, analysis of compositions of microbiomes with bias correction), and machine learning [Recursive Ensemble Feature Selection (REFS)]. Results: Global diversity and DAA did not find significant differences between controlled and uncontrolled pediatric asthmatics. REFS detected a set of taxa, including Haemophilus and Veillonella, differentiating uncontrolled and controlled asthma with an average classification accuracy of 81% (saliva) and 86% (feces). These taxa showed enrichment in taxa previously associated with inflammatory diseases for both sampling compartments, and with COPD for the saliva samples. Conclusion: Controlled and uncontrolled children with asthma can be differentiated based on their gastrointestinal microbiome using machine learning, specifically REFS. Our results show an association between asthma control and the gastrointestinal microbiome. This suggests that the gastrointestinal microbiome may be a potential biomarker for treatment responsiveness and thereby help to improve asthma control in children.
KW - asthma: disease management
KW - asthma: treatment
UR - http://www.scopus.com/inward/record.url?scp=85148763102&partnerID=8YFLogxK
U2 - https://doi.org/10.1111/pai.13919
DO - https://doi.org/10.1111/pai.13919
M3 - Article
C2 - 36825736
SN - 0905-6157
VL - 34
JO - Pediatric allergy and immunology
JF - Pediatric allergy and immunology
IS - 2
M1 - e13919
ER -