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A longitudinal 1H NMR-based urinary metabolomics dataset in a birth cohort for childhood atopic diseases
Yi-Hsin Kuo1, Chih-Yung Chiu1,2,3, Meng-Han Chiang2
1Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, and Chang Gung University College of Medicine, Taoyuan, Taiwan.
Insights
This study tracked urinary metabolites in children from infancy to age five. It explores links between early growth, metabolic changes, and the development of allergies and atopic diseases.
Area of Science:
- Pediatric Allergy and Immunology
- Metabolomics
- Developmental Biology
Background:
- Early childhood is a critical window for immune system development and the onset of allergic diseases.
- Understanding the interplay between metabolic profiles and allergic sensitization is crucial for early intervention.
- Longitudinal data on urinary metabolomics in relation to atopic disease development is limited.
Purpose of the Study:
- To analyze longitudinal urinary metabolomic profiles in children from 1 month to 5 years of age.
- To investigate the relationship between early life factors, metabolomic changes, and the development of allergic sensitization and atopic diseases.
- To provide a comprehensive dataset for metabolic modeling and understanding early childhood health trajectories.
Main Methods:
- Longitudinal collection of urinary samples from 198 children at multiple time points (1 month, 6 months, 1 year, 3 years, 5 years).
- Collection of demographic data, birth history, feeding practices, parental atopy, and household income.
- Measurement of total and allergen-specific IgE (mite, egg, cow's milk) and atopic disease status.
- Generation of urinary metabolomic data using proton nuclear magnetic resonance (1H-NMR) spectroscopy, followed by data processing and normalization.
Main Results:
- The dataset captures detailed longitudinal urinary metabolomic profiles across early childhood.
- It includes concurrent data on allergic sensitization markers (IgE) and clinical atopic disease status.
- Demographic and environmental factors relevant to child development and allergy are also provided.
Conclusions:
- This dataset offers a valuable resource for exploring the metabolic underpinnings of allergic sensitization and atopic disease development in children.
- It enables research into the impact of early growth and environmental factors on metabolic trajectories and immune outcomes.
- Further analysis can reveal predictive biomarkers for atopic diseases based on early-life metabolomic profiles.
Abstract:
This dataset provides a longitudinal analysis of urinary metabolomic profiles from 198 children aged 1 month, 6 months, 1 year, 3 years, and 5 years. Demographic information, including birth history, feeding practices, parental atopic history, household income, and atopic disease status at different ages, was collected. Total and allergen-specific IgE levels (mite, egg, cow's milk) were measured to evaluate allergic sensitization over time. Atopic disease status was also monitored at multiple time points to assess its development. The urinary metabolomic data, generated using advanced 1H-nuclear magnetic resonance (NMR) spectroscopy, were processed and normalized to support robust metabolic modeling. This dataset aims to provide insights into the relationships among early growth, metabolomic changes, and the development of allergic sensitization and atopic diseases in early childhood.
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