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Updated: Jun 6, 2025
High-Dimensionality Flow Cytometry for Immune Function Analysis of Dissected Implant Tissues
Published on: September 15, 2021
Cross-tissue, age-specific flow cytometry reference for immune cells in airway and blood of children
Shivanthan Shanthikumar1, Liam Gubbels2, Karen Davies3
1Infection, Immunity and Global Health, Murdoch Children's Research Institute, Parkville, Australia; Department of Paediatrics, University of Melbourne, Parkville, Australia; Respiratory and Sleep Medicine, Royal Children's Hospital, Parkville, Australia.
Insights
This study establishes a pediatric airway immune cell dataset, revealing age-specific immune system maturation. Findings highlight correlations between local and systemic immune responses, crucial for understanding childhood respiratory diseases.
Area of Science:
- Pediatric immunology
- Respiratory medicine
- Flow cytometry
Background:
- Respiratory diseases are a major cause of childhood illness and hospitalization.
- Current treatments for pediatric respiratory diseases are limited and often ineffective.
- Understanding early airway immunity is crucial for developing better treatments.
Purpose of the Study:
- To create a comprehensive flow cytometry dataset of immune cells in the pediatric airway.
- To analyze immune cells across five upper and lower airway tissues and whole blood.
- To investigate local and systemic immune responses in children aged 1-15 years.
Main Methods:
- Analyzed 180 samples from 68 children using 17-plex and 31-plex antibody panels.
- Characterized immune and epithelial cell lineages in nasal, bronchial, and alveolar samples.
- Phenotyped mononuclear immune cells in tonsil, adenoid, and blood samples.
Main Results:
- Provided age-specific data for 37 cell populations across infancy to adolescence.
- Demonstrated tissue-specific maturation of the airway immune system.
- Found significant correlations in immune cell proportions between paired nasal-bronchial, tonsil-adenoid, and adenoid-blood samples.
Conclusions:
- Advanced understanding of airway immunity from infancy through adolescence.
- Provided an openly available control dataset for interpreting pediatric respiratory disease findings.
- Highlighted the importance of age-specific reference data for the pediatric airway.
Background:
Respiratory diseases are a common cause of morbidity and hospitalization for children. Despite this, treatment options are limited and are often ineffective. The development of curative or disease-modifying treatments for children relies on a better understanding of underlying immunity in the early airway.
Objective:
To establish a flow cytometry dataset for immune cells in the pediatric airway, we analyzed 180 samples from 68 children aged between 1 and 15 years. This included 5 tissues of the upper (nasal brushings, palatine tonsils, adenotonsil) and lower (bronchial brushings, bronchoalveolar lavage) airway, as well as whole blood for paired analysis of local and systemic immune response.
Methods:
Nasal, bronchial, and alveolar samples were analyzed using a 17-plex antibody panel that captures cells of immune and epithelial lineage, while tonsil, adenoid, and blood samples were analyzed using a 31-plex antibody panel that extensively phenotypes mononuclear immune cells. All protocols, panels, and data are openly available to facilitate implementation in pediatric clinical laboratories.
Results:
We provide age-specific airway cell data for infancy (0-2 years), preschool (3-5 years), childhood (6-10 years) and adolescence (11-15 years) for 37 cell populations. We show tissue-specific maturation of the airway immune system across childhood, further highlighting the importance of developing age-specific references of the pediatric airway. Intraindividual, cross-tissue analysis of paired samples revealed marked correlation in immune cell proportions between paired nasal-bronchial samples, paired tonsil-adenoid samples, and paired adenoid-blood samples, which may have implications for clinical testing.
Conclusion:
Our study advances knowledge of airway immunity from infancy through to adolescence and provides an openly available control dataset to aid in interpretation of clinical findings in samples obtained from children with respiratory diseases.
