Metabolomics : population epidemiology and concordance in Australian children aged 11-12 years and their parents

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http://hdl.handle.net/10138/306213

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Ellul , S , Wake , M , Clifford , S A , Lange , K , Würtz , P , Juonala , M , Dwyer , T , Carlin , J B , Burgner , D P & Saffery , R 2019 , ' Metabolomics : population epidemiology and concordance in Australian children aged 11-12 years and their parents ' , BMJ Open , vol. 9 , pp. 106-117 . https://doi.org/10.1136/bmjopen-2017-020900

Title: Metabolomics : population epidemiology and concordance in Australian children aged 11-12 years and their parents
Author: Ellul, Susan; Wake, Melissa; Clifford, Susan A.; Lange, Katherine; Würtz, Peter; Juonala, Markus; Dwyer, Terence; Carlin, John B.; Burgner, David P.; Saffery, Richard
Contributor: University of Helsinki, University Management
Date: 2019-07-04
Language: eng
Number of pages: 12
Belongs to series: BMJ Open
ISSN: 2044-6055
URI: http://hdl.handle.net/10138/306213
Abstract: Objectives Nuclear magnetic resonance (NMR) metabolomics is high throughput and cost-effective, with the potential to improve the understanding of disease and risk. We examine the circulating metabolic profile by quantitative NMR metabolomics of a sample of Australian 11-12 year olds children and their parents, describe differences by age and sex, and explore the correlation of metabolites in parent-child dyads. Design The population-based cross-sectional Child Health CheckPoint study nested within the Longitudinal Study of Australian Children. Setting Blood samples collected from CheckPoint participants at assessment centres in seven Australian cities and eight regional towns; February 2015-March 2016. Participants 1180 children and 1325 parents provided a blood sample and had metabolomics data available. This included 1133 parent-child dyads (518 mother-daughter, 469 mother-son, 68 father-daughter and 78 father-son). Outcome measures 228 metabolic measures were obtained for each participant. We focused on 74 biomarkers including amino acid species, lipoprotein subclass measures, lipids, fatty acids, measures related to fatty acid saturation, and composite markers of inflammation and energy homeostasis. Results We identified differences in the concentration of specific metabolites between childhood and adulthood and in metabolic profiles in children and adults by sex. In general, metabolite concentrations were higher in adults than children and sex differences were larger in adults than in children. Positive correlations were observed for the majority of metabolites including isoleucine (CC 0.33, 95% CI 0.27 to 0.38), total cholesterol (CC 0.30, 95% CI 0.24 to 0.35) and omega 6 fatty acids (CC 0.28, 95% CI 0.23 to 0.34) in parent-child comparisons. Conclusions We describe the serum metabolite profiles from mid-childhood and adulthood in a population-based sample, together with a parent-child concordance. Differences in profiles by age and sex were observed. These data will be informative for investigation of the childhood origins of adult non-communicable diseases and for comparative studies in other populations.
Subject: metabolomics
lipids
inflammation
reference values
parents
children
inheritance patterns
correlation studies
epidemiologic studies
cross-sectional studies
GENOME-WIDE ASSOCIATION
GENDER
LIPOPROTEINS
CHOLESTEROL
PROFILES
PATHWAYS
DISEASE
SYSTEMS
YOUNG
RATIO
3121 General medicine, internal medicine and other clinical medicine
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