Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health

  1. Nikos Stratakis  Is a corresponding author
  2. Alexandros P Siskos
  3. Eleni Papadopoulou
  4. Anh N Nguyen
  5. Yinqi Zhao
  6. Katerina Margetaki
  7. Chung-Ho E Lau
  8. Muireann Coen
  9. Lea Maitre
  10. Silvia Fernández-Barrés
  11. Lydiane Agier
  12. Sandra Andrusaityte
  13. Xavier Basagaña
  14. Anne Lise Brantsaeter
  15. Maribel Casas
  16. Serena Fossati
  17. Regina Grazuleviciene
  18. Barbara Heude
  19. Rosemary RC McEachan
  20. Helle Margrete Meltzer
  21. Christopher Millett
  22. Fernanda Rauber
  23. Oliver Robinson
  24. Theano Roumeliotaki
  25. Eva Borras
  26. Eduard Sabidó
  27. Jose Urquiza
  28. Marina Vafeiadi
  29. Paolo Vineis
  30. Trudy Voortman
  31. John Wright
  32. David V Conti
  33. Martine Vrijheid
  34. Hector C Keun
  35. Leda Chatzi
  1. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, United States
  2. Cancer Metabolism & Systems Toxicology Group, Division of Cancer, Department of Surgery & Cancer and Division of Systems Medicine, Department of Metabolism, Digestion & Reproduction, Imperial College London, Hammersmith Hospital Campus, United Kingdom
  3. Norwegian Institute of Public Health, Norway
  4. Department of Epidemiology, Erasmus University Medical Center, Netherlands
  5. MRC Centre for Environment and Health, School of Public Health, Imperial College London, United Kingdom
  6. Oncology Safety, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, United Kingdom
  7. ISGlobal, Spain
  8. Universitat Pompeu Fabra, Spain
  9. CIBER Epidemiologia y Salud Pública, Spain
  10. Inserm, CNRS, University Grenoble Alpes, Team of environmental epidemiology applied to reproduction and respiratory health, IAB, France
  11. Department of Environmental Sciences, Vytautas Magnus University, Lithuania
  12. Centre for Research in Epidemiology and Statistics, Université de Paris, Inserm, Inra, France
  13. Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, United Kingdom
  14. Public Health Policy Evaluation Unit, School of Public Health, Imperial College, United Kingdom
  15. Department of Preventive Medicine, School of Medicine, University of São Paulo, Brazil
  16. Center for Epidemiological Research in Nutrition and Health, University of São Paulo, Brazil
  17. Department of Social Medicine, Faculty of Medicine, University of Crete, Greece
  18. Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Spain

Decision letter

  1. Edward D Janus
    Reviewing Editor; University of Melbourne, Australia
  2. Martin R Pollak
    Senior Editor; Harvard Medical School, United States

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health" for consideration by eLife. Your article has been reviewed by 1 peer reviewer and the evaluation has been overseen by a Reviewing Editor and Martin Pollak as the Senior Editor. The reviewer has opted to remain anonymous.

The reviewer has discussed their review with the Reviewing Editor who has drafted this to help you prepare a revised submission.

Essential revisions:

1) The one omission is the effects of activity levels and total caloric consumption. There is an attempt to link body weight to C-peptide associations, but in a revision, it would be nice to also include MBI as a parameter for the concentrations of metabolites.

Reviewer #1 (Recommendations for the authors):

The only additional recommendation from the public review is to rework figure one to make it easier to follow the metabolites per spiral plot. Following them down to the inner circle is more difficult than it needs to be.

For supplemental figures 3 and 4, the abbreviations for the cohorts needs to be referenced.

https://doi.org/10.7554/eLife.71332.sa1

Author response

Reviewer #1 (Recommendations for the authors):

The only additional recommendation from the public review is to rework figure one to make it easier to follow the metabolites per spiral plot. Following them down to the inner circle is more difficult than it needs to be.

We have modified the figure depicting the diet-metabolite associations (now Figure 3) to facilitate readership. Please note that the numbering of all figures have been changed as all figures previously included as supplementary material have now been moved to the main text to adhere to the journal’s guidelines.

For supplemental figures 3 and 4, the abbreviations for the cohorts needs to be referenced.

We have now referenced the abbreviations for the cohorts in all relevant figures. These are now figures 5A and 5B. Please note that the numbering of all figures have been changed as all figures previously included as supplementary material have now been moved to the main text to adhere to the journal’s guidelines.

Modified text in figure:

Figure 5. Cohort-specific associations of the diet quality indicators of interest with C-peptide in childhood. Panel A illustrates the associations for adherence to the Mediterranean diet, which was assessed via the KIDMED score (expressed per unit increase). Panel B illustrates the associations for ultra-processed food (UPF) intake (expressed per 5% increase of total daily food intake). Β coefficients (95% CIs) by cohort were obtained using linear regression models adjusted for maternal age, maternal education level, maternal pre-pregnancy BMI, family affluence status, child sex, child age, child BMI, child sedentary behavior, child ethnicity, and postprandial interval. Combined estimates were obtained by using a fixed-effects meta-analysis. Squares represent the cohort-specific effect estimates; diamond represents the combined estimate; and horizontal lines denote 95% CIs. BiB, Born in Bradford cohort; EDEN, the Étude des Déterminants pré et postnatals du développement et de la santé de l’Enfant study; INMA, INfancia y Medio Ambiente cohort; KANC, Kaunas Cohort; MoBa, Norwegian Mother, Father and Child Cohort Study; RHEA, Rhea Mother Child Cohort study.

References:

1. Serrano-Sanchez JA, Marti-Trujillo S, Lera-Navarro A, Dorado-Garcia C, Gonzalez-Henriquez JJ, Sanchis-Moysi J. Associations between screen time and physical activity among Spanish adolescents. PLoS One. 2011;6(9):e24453.

2. Pearson N, Braithwaite RE, Biddle SJ, van Sluijs EM, Atkin AJ. Associations between sedentary behaviour and physical activity in children and adolescents: a meta-analysis. Obes Rev. 2014;15(8):666-675.

3. Aira T, Vasankari T, Heinonen OJ, et al. Physical activity from adolescence to young adulthood: patterns of change, and their associations with activity domains and sedentary time. Int J Behav Nutr Phys Act. 2021;18(1):85.

4. Lau CE, Siskos AP, Maitre L, et al. Determinants of the urinary and serum metabolome in children from six European populations. BMC Med. 2018;16(1):202.

5. Jakes RW, Day NE, Luben R, et al. Adjusting for energy intake--what measure to use in nutritional epidemiological studies? Int J Epidemiol. 2004;33(6):1382-1386.

6. Kühn S, Düzel S, Colzato L, et al. Food for thought: association between dietary tyrosine and cognitive performance in younger and older adults. Psychological Research. 2019;83(6):1097-1106.

7. Brosnan JT, Brosnan ME. Branched-Chain Amino Acids: Enzyme and Substrate Regulation. The Journal of Nutrition. 2006;136(1):207S-211S.

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9. Lynch CJ, Adams SH. Branched-chain amino acids in metabolic signalling and insulin resistance. Nat Rev Endocrinol. 2014;10(12):723-736.

https://doi.org/10.7554/eLife.71332.sa2

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  1. Nikos Stratakis
  2. Alexandros P Siskos
  3. Eleni Papadopoulou
  4. Anh N Nguyen
  5. Yinqi Zhao
  6. Katerina Margetaki
  7. Chung-Ho E Lau
  8. Muireann Coen
  9. Lea Maitre
  10. Silvia Fernández-Barrés
  11. Lydiane Agier
  12. Sandra Andrusaityte
  13. Xavier Basagaña
  14. Anne Lise Brantsaeter
  15. Maribel Casas
  16. Serena Fossati
  17. Regina Grazuleviciene
  18. Barbara Heude
  19. Rosemary RC McEachan
  20. Helle Margrete Meltzer
  21. Christopher Millett
  22. Fernanda Rauber
  23. Oliver Robinson
  24. Theano Roumeliotaki
  25. Eva Borras
  26. Eduard Sabidó
  27. Jose Urquiza
  28. Marina Vafeiadi
  29. Paolo Vineis
  30. Trudy Voortman
  31. John Wright
  32. David V Conti
  33. Martine Vrijheid
  34. Hector C Keun
  35. Leda Chatzi
(2022)
Urinary metabolic biomarkers of diet quality in European children are associated with metabolic health
eLife 11:e71332.
https://doi.org/10.7554/eLife.71332

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https://doi.org/10.7554/eLife.71332