Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

SysPharmPediA Consortium

doi:10.1111/pai.13919

Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

SysPharmPediA Consortium

Faculty of Science

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

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.

Original language	English
Article number	e13919
Pages (from-to)	e13919
Journal	Pediatric Allergy and Immunology
Volume	34
Issue number	2
DOIs	https://doi.org/10.1111/pai.13919
Publication status	Published - Feb 2023

Bibliographical note

Funding

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.

Funders	Funder number
Ministry of Education, Science, and Sport of the Republic of Slovenia	C330‐16‐500106
State Research Agency
European Commission	RYC‐2015‐17205, AC15/00015, AC15/00058
European Commission
ZonMw	9003035001
ZonMw
Bundesministerium für Bildung und Forschung	FKZ 031 L0088
Bundesministerium für Bildung und Forschung
Javna Agencija za Raziskovalno Dejavnost RS	P3‐0067
Javna Agencija za Raziskovalno Dejavnost RS
Instituto de Salud Carlos III
Ministerio de Ciencia e Innovación
European Regional Development Fund	SAF2017‐83417R
European Regional Development Fund
Agencia Estatal de Investigación

Keywords

Humans
Child
Quality of Life
Asthma/drug therapy
Microbiota
Bacteria
Feces/microbiology

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10.1111/pai.13919

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Cite this

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title = "Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma",

abstract = "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.",

keywords = "Humans, Child, Quality of Life, Asthma/drug therapy, Microbiota, Bacteria, Feces/microbiology",

author = "Blankestijn, \{Jelle M\} and Alejandro Lopez-Rincon and Neerincx, \{Anne H\} and Vijverberg, \{Susanne J H\} and Simone Hashimoto and Mario Gorenjak and \{Sard{\'o}n Prado\}, Olaia and Paula Corcuera-Elosegui and Javier Korta-Murua and Maria Pino-Yanes and Uro{\v s} Poto{\v c}nik and Corinna Bang and Andre Franke and Christine Wolff and Susanne Brandstetter and Toncheva, \{Antoaneta A\} and Parastoo Kheiroddin and Susanne Harner and Michael Kabesch and Kraneveld, \{Aletta D\} and Abdel-Aziz, \{Mahmoud I\} and \{Maitland-van der Zee\}, \{Anke H\} and \{SysPharmPediA Consortium\}",

note = "{\textcopyright} 2023 The Authors. Pediatric Allergy and Immunology published by European Academy of Allergy and Clinical Immunology and John Wiley \& Sons Ltd.",

year = "2023",

month = feb,

doi = "10.1111/pai.13919",

language = "English",

volume = "34",

pages = "e13919",

journal = "Pediatric Allergy and Immunology",

issn = "0905-6157",

publisher = "Blackwell Munksgaard",

number = "2",

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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 - Abdel-Aziz, Mahmoud I

AU - Maitland-van der Zee, Anke H

AU - SysPharmPediA Consortium

PY - 2023/2

Y1 - 2023/2

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 - Humans

KW - Child

KW - Quality of Life

KW - Asthma/drug therapy

KW - Microbiota

KW - Bacteria

KW - Feces/microbiology

U2 - 10.1111/pai.13919

DO - 10.1111/pai.13919

M3 - Article

C2 - 36825736

SN - 0905-6157

VL - 34

SP - e13919

JO - Pediatric Allergy and Immunology

JF - Pediatric Allergy and Immunology

IS - 2

M1 - e13919

ER -

Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

Abstract

Bibliographical note

Funding

Keywords

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