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Sex and puberty-related differences in metabolomic profiles associated with adiposity measures in youth with obesity

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Abstract

Background

Specific patterns of metabolomic profiles relating to cardiometabolic disease are associated with increased weight in adults. In youth with obesity, metabolomic data are sparse and associations with adiposity measures unknown.

Objectives

Primary, to determine associations between adiposity measures and metabolomic profiles with increased cardiometabolic risks in youth with obesity. Secondary, to stratify associations by sex and puberty.

Methods

Participants were from COBRA (Childhood Overweight BioRepository of Australia; a paediatric cohort with obesity). Adiposity measures (BMI, BMI z-score, %truncal and %whole body fat, waist circumference and waist/height ratio), puberty staging and NMR metabolomic profiles from serum were assessed. Statistics included multivariate analysis (principal component analysis, PCA) and multiple linear regression models with false discovery rate adjustment.

Results

214 participants had metabolomic profiles analyzed, mean age 11.9 years (SD ± 3.1), mean BMI z-score 2.49 (SD ± 0.24), 53% females. Unsupervised PCA identified no separable clusters of individuals. Positive associations included BMI z-score and phenylalanine, total body fat % and lipids in medium HDL, and waist circumference and tyrosine; negative associations included total body fat % and the ratio of docosahexaenoic acid/total fatty acids and histidine. Stratifying by sex and puberty, patterns of associations with BMI z-score in post-pubertal males included positive associations with lipid-, cholesterol- and triglyceride-content in VLDL lipoproteins; total fatty acids; total triglycerides; isoleucine, leucine and glycoprotein acetyls.

Conclusion

In a paediatric cohort with obesity, increased adiposity measures, especially in post-pubertal males, were associated with distinct patterns in metabolomic profiles.

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Acknowledgements

The authors would like to thank the COBRA participants and their families.

Funding

Authors from the Murdoch Children’s Research Institute are supported in part by the Victorian Government Operational Infrastructure Support Program. CS was supported for a 1 year clinical research fellowship position at the Endocrinology Department at the Royal Children’s Hospital by “Batzebaer Foundation”, Inselspital Bern; “Fondazione Ettore e Valeria Rossi”; “Freie akademische Gesellschaft Basel” and “NovoNordisk”, all Switzerland. CS declares that he has no conflict of interest to declare. BEH is an NHMRC Peter Doherty ECF Fellow (APP: 1072086). BEH declares that he has no conflict of interest to declare. DPB is supported by NHMRC Senior Research Fellowship (1064629) and an Honorary Future Leader Fellowship of the National Heart Foundation of Australia (100369). DPB declares that he has no conflict of interest to declare. MJ was supported by Juho Vainio Foundation and federal research grants to Turku University Hospital. MJ declares that he has no conflict of interest to declare. The funding bodies did not play any role in this study or the decision to publish.

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Authors and Affiliations

  1. Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC, Australia

    Christoph Saner, Brooke E. Harcourt, Susan Ellul, Zoe McCallum, Kung-Ting Kao, Celia Twindyakirana, Anke Pons, Erin J. Alexander, Richard Saffery, David P. Burgner, Markus Juonala & Matthew A. Sabin

  2. Department of Endocrinology and Diabetes, The Royal Children’s Hospital, Parkville, VIC, Australia

    Christoph Saner, Brooke E. Harcourt, Zoe McCallum, Kung-Ting Kao, Erin J. Alexander, Richard Saffery & Matthew A. Sabin

  3. Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia

    Brooke E. Harcourt, Kung-Ting Kao, Celia Twindyakirana, Richard Saffery, David P. Burgner & Matthew A. Sabin

  4. Peter MacCallum Cancer Centre, Melbourne, VIC, Australia

    Ahwan Pandey

  5. Department of Paediatrics, Monash University, Clayton, VIC, Australia

    David P. Burgner

  6. Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, Turku, Finland

    Christoph Saner & Markus Juonala

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  1. Christoph Saner
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  2. Brooke E. Harcourt
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  3. Ahwan Pandey
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  4. Susan Ellul
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Contributions

CS conceptualized the study, undertook statistical analysis and interpreted results and wrote/revised manuscript; BEH conceptualized the study, collected data and analyzed samples and revised manuscript; AP provided statistical support; SE provided statistical support; ZM collected data; KTK initial study design and data collection; CT collected data; AP collected data; EJA collected data; RS assisted with result interpretation and revised manuscript; DPB assisted with result interpretation and revised manuscript; MJ assisted with result interpretation and revised manuscript; MAS set up the cohort, conceptualized the study, interpreted results and revised manuscript.

Corresponding author

Correspondence to Christoph Saner.

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All authors have no conflicts of interest to declare.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Supplementary material 1 (DOCX 56 kb)

11306_2019_1537_MOESM2_ESM.pdf

Supplementary material 2 (PDF 22 kb) Supplementary figure 1: Changes in metabolites by 1 SD increase in body mass index, adjusted for age and sex. Legend supplementary figure 1: Changes in mean and 95% confidence interval per 1-SD increase in BMI.* indicate significant associations after multiple regression modelling (p value < 0.05). Estimates and 95% CI’s in bold illustrate significance after adjustment for false discovery rate (FDR, according to Benjamini-Hochberg)

11306_2019_1537_MOESM3_ESM.pdf

Supplementary material 3 (PDF 24 kb) Supplementary figure 2: Changes in metabolites by 1 SD increase in total body fat  %, adjusted for age and sex. Legend supplementary Figure 2: Changes in mean and 95% confidence interval per 1-SD increase in total body fat %. *indicate significant associations after multiple regression modelling (p-value < 0.05). Estimates and 95% CI’s in bold illustrate significance after adjustment for false discovery rate (FDR, according to Benjamini-Hochberg)

11306_2019_1537_MOESM4_ESM.pdf

Supplementary material 4 (PDF 24 kb) Supplementary figure 3: Changes in metabolites by 1 SD increase in truncal fat  %, adjusted for age and sex. Legend supplementary figure 3: Changes in mean and 95% confidence interval per 1-SD increase in truncal fat  %. * indicate significant associations after multiple regression modelling (p-value < 0.05). Estimates and 95% CI’s in bold illustrate significance after adjustment for false discovery rate (FDR, according to Benjamini-Hochberg)

11306_2019_1537_MOESM5_ESM.pdf

Supplementary material 5 (PDF 22 kb) Supplementary figure 4: Changes in metabolites by 1 SD increase in waist circumference, adjusted for age and sex. Legend supplementary figure 4: Changes in mean and 95% confidence interval per 1-SD increase in waist circumference. * indicate significant associations after multiple regression modelling (p-value < 0.05). Estimates and 95% CI’s in bold illustrate significance after adjustment for false discovery rate (FDR, according to Benjamini-Hochberg)

11306_2019_1537_MOESM6_ESM.pdf

Supplementary material 6 (PDF 22 kb) Supplementary Fig. 5: Changes in metabolites by 1 SD increase in waist to height ratio, adjusted for age and sex. Legend supplementary Fig. 5: Changes in mean and 95% confidence interval per 1-SD increase in waist to height ratio. * indicate significant associations after multiple regression modelling (p-value < 0.05). Estimates and 95% CI’s in bold illustrate significance after adjustment for false discovery rate (FDR, according to Benjamini-Hochberg)

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Saner, C., Harcourt, B.E., Pandey, A. et al. Sex and puberty-related differences in metabolomic profiles associated with adiposity measures in youth with obesity. Metabolomics 15, 75 (2019). https://doi.org/10.1007/s11306-019-1537-y

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