Integrative genetics-metabolomics analysis of infant bronchiolitis-childhood asthma link: A multicenter prospective study.

asthma bronchiolitis childhood asthma genetics integrated-omics metabolomics phosphatidylglycerol sphingolipids

Journal

Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960

Informations de publication

Date de publication:
2022
Historique:
received: 30 11 2022
accepted: 28 12 2022
entrez: 23 2 2023
pubmed: 24 2 2023
medline: 3 3 2023
Statut: epublish

Résumé

Infants with bronchiolitis are at high risk for developing childhood asthma. While genome-wide association studies suggest common genetic susceptibilities between these conditions, the mechanisms underlying the link remain unclear. Through integrated genetics-metabolomics analysis in this high-risk population, we sought to identify genetically driven metabolites associated with asthma development and genetic loci associated with both these metabolites and asthma susceptibility. In a multicenter prospective cohort study of infants hospitalized for bronchiolitis, we profiled the nasopharyngeal metabolome and genotyped the whole genome at hospitalization. We identified asthma-related metabolites from 283 measured compounds and conducted metabolite quantitative trait loci (mtQTL) analyses. We further examined the mtQTL associations by testing shared genetic loci for metabolites and asthma using colocalization analysis and the concordance between the loci and known asthma-susceptibility genes. In 744 infants hospitalized with bronchiolitis, 28 metabolites (e.g., docosapentaenoate [DPA], 1,2-dioleoyl-sn-glycero-3-phosphoglycerol, sphingomyelin) were associated with asthma risk. A total of 349 loci were associated with these metabolites-161 for non-Hispanic white, 120 for non-Hispanic black, and 68 for Hispanics. Of these, there was evidence for 30 shared loci between 16 metabolites and asthma risk (colocalization posterior probability ≥0.5). The significant SNPs within loci were aligned with known asthma-susceptibility genes (e.g., The integrated genetics-metabolomics analysis identified genetically driven metabolites during infancy that are associated with asthma development and genetic loci associated with both these metabolites and asthma susceptibility. Identifying these metabolites and genetic loci should advance research into the functional mechanisms of the infant bronchiolitis-childhood asthma link.

Sections du résumé

Background
Infants with bronchiolitis are at high risk for developing childhood asthma. While genome-wide association studies suggest common genetic susceptibilities between these conditions, the mechanisms underlying the link remain unclear.
Objective
Through integrated genetics-metabolomics analysis in this high-risk population, we sought to identify genetically driven metabolites associated with asthma development and genetic loci associated with both these metabolites and asthma susceptibility.
Methods
In a multicenter prospective cohort study of infants hospitalized for bronchiolitis, we profiled the nasopharyngeal metabolome and genotyped the whole genome at hospitalization. We identified asthma-related metabolites from 283 measured compounds and conducted metabolite quantitative trait loci (mtQTL) analyses. We further examined the mtQTL associations by testing shared genetic loci for metabolites and asthma using colocalization analysis and the concordance between the loci and known asthma-susceptibility genes.
Results
In 744 infants hospitalized with bronchiolitis, 28 metabolites (e.g., docosapentaenoate [DPA], 1,2-dioleoyl-sn-glycero-3-phosphoglycerol, sphingomyelin) were associated with asthma risk. A total of 349 loci were associated with these metabolites-161 for non-Hispanic white, 120 for non-Hispanic black, and 68 for Hispanics. Of these, there was evidence for 30 shared loci between 16 metabolites and asthma risk (colocalization posterior probability ≥0.5). The significant SNPs within loci were aligned with known asthma-susceptibility genes (e.g.,
Conclusion
The integrated genetics-metabolomics analysis identified genetically driven metabolites during infancy that are associated with asthma development and genetic loci associated with both these metabolites and asthma susceptibility. Identifying these metabolites and genetic loci should advance research into the functional mechanisms of the infant bronchiolitis-childhood asthma link.

Identifiants

pubmed: 36818476
doi: 10.3389/fimmu.2022.1111723
pmc: PMC9936313
doi:

Types de publication

Multicenter Study Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1111723

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI127507
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI148338
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI134940
Pays : United States
Organisme : NIH HHS
ID : UH3 OD023253
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI137091
Pays : United States
Organisme : NIAID NIH HHS
ID : K01 AI153558
Pays : United States
Organisme : NIH HHS
ID : UG3 OD023253
Pays : United States

Informations de copyright

Copyright © 2023 Ooka, Zhu, Liang, Celedon, Harmon, Hahn, Rhee, Freishtat, Camargo and Hasegawa.

Déclaration de conflit d'intérêts

JC received research materials from Merck Rahway, NJ in order to provide medications free of cost to participants in an NIH-funded study, unrelated to the current work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.

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Auteurs

Tadao Ooka (T)

Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Department of Health Science, University of Yamanashi, Chuo, Yamanashi, Japan.

Zhaozhong Zhu (Z)

Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Liming Liang (L)

Program in Genetic Epidemiology and Statistical Genetics, Harvard T. H. Chan School of Public Health, Boston, MA, United States.
Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, United States.

Juan C Celedon (JC)

Division of Pediatric Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, United States.

Brennan Harmon (B)

Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, United States.

Andrea Hahn (A)

Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, United States.
Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, United States.
Division of Infectious Diseases, Children's National Hospital, Washington, DC, United States.

Eugene P Rhee (EP)

Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Robert J Freishtat (RJ)

Center for Genetic Medicine Research, Children's National Hospital, Washington, DC, United States.
Department of Pediatrics, George Washington University School of Medicine and Health Sciences, Washington, DC, United States.
Division of Emergency Medicine, Children's National Hospital, Washington, DC, United States.

Carlos A Camargo (CA)

Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

Kohei Hasegawa (K)

Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.

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