Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The genomics of childhood eating behaviours

Nature Human Behaviour volume 5, pages 625–630 (2021)Cite this article

Subjects

An Author Correction to this article was published on 16 February 2021

This article has been updated

Abstract

Eating behaviours may be expressions of genetic risk for obesity and are potential antecedents of later eating disorders. However, childhood eating behaviours are heterogeneous and transient. Here we show associations between polygenic scores for body mass index (BMI-PGS) and anorexia nervosa (AN-PGS) with eating behaviour trajectories during the first 10 years of life using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), n = 7,825. Results indicated that 1 s.d. increase in the BMI-PGS was associated with a 30–37% increased risk for early- and mid-childhood overeating. In contrast, 1 s.d. increase in BMI-PGS was associated with a 20% decrease in risk of persistent high levels of undereating and a 15% decrease in risk of persistent fussy eating. There was no evidence for a significant association between AN-PGS and eating behaviour trajectories. Our results support the notion that child eating behaviours share common genetic variants associated with BMI.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Eating behaviour trajectories during the first 10 years of life.
Fig. 2: BMI-PGS and AN-PGS by trajectories of undereating, fussy eating and overeating.

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code availability

All code associated with the analyses is available upon request.

Change history

References

  1. Ng, M. et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the global burden of disease study 2013. Lancet 384, 766–781 (2014).

    PubMed  PubMed Central  Google Scholar 

  2. Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in ~ 700000 individuals of European ancestry. Hum. Mol. Genet. 27, 3641–3649 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Swinburn, B. A. et al. Obesity 1. The global obesity pandemic: shaped by global drivers and local environments. Lancet 378, 804–814 (2011).

    Article  PubMed  Google Scholar 

  4. Llewellyn, C. & Wardle, J. Behavioural susceptibility to obesity: gene–environment interplay in the development of weight. Physiol. Behav. 152, 494–501 (2015).

    Article  CAS  PubMed  Google Scholar 

  5. Parkinson, K. N., Drewett, R. F., Le Couteur, A. S., Adamson, A. J. & Gateshead Milennium Study Core Team. Do maternal ratings of appetite in infants predict later child eating behaviour questionnaire scores and body mass index? Appetite 54, 186–190 (2010).

  6. Syrad, H., Johnson, L., Wardle, J. & Llewellyn, C. H. Appetitive traits and food intake patterns in early life. Am. J. Clin. Nutr. 103, 231–235 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Llewellyn, C. H., van Jaarsveld, C. H. M., Johnson, L., Carnell, S. & Wardle, J. Nature and nurture in infant appetite: analysis of the Gemini twin birth cohort. Am. J. Clin. Nutr. 91, 1172–1179 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Keskitalo, K. et al. The Three-Factor Eating Questionnaire, body mass index, and responses to sweet and salty fatty foods: a twin study of genetic and environmental associations. Am. J. Clin. Nutr. 88, 263–271 (2008).

    Article  CAS  PubMed  Google Scholar 

  9. Llewellyn, C. H., van Jaarsveld, C. H. M., Plomin, R., Fisher, A. & Wardle, J. Inherited behavioural susceptibility to adiposity in infancy: a multivariate genetic analysis of appetite and weight in the Gemini birth cohort. Am. J. Clin. Nutr. 95, 633–639 (2012).

    Article  CAS  PubMed  Google Scholar 

  10. Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Herle, M. et al. Eating behaviour trajectories in the first ten years of life and their relationship with BMI. Int. J. Obesity 44, 1766–1775 (2020).

  12. Wray, N. R. et al. Research review: polygenic methods and their application to psychiatric traits. J. Child Psychol. Psychiatry 55, 1068–1087 (2014).

    Article  PubMed  Google Scholar 

  13. Llewellyn, C. H., Trzaskowski, M., van Jaarsveld, C. H. M., Plomin, R. & Wardle, J. Satiety mechanisms in genetic risk of obesity. JAMA Pediatr. 168, 338–344 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Steinsbekk, S., Belsky, D., Guzey, I. C., Wardle, J. & Wichstrom, L. Polygenic risk, appetite traits, and weight gain in middle childhood: a longitudinal study. JAMA Pediatr. 170, e154472 (2016).

  15. Konttinen, H. et al. Appetitive traits as behavioural pathways in genetic susceptibility to obesity: a population-based cross-sectional study. Sci. Rep. 5, 14726 (2015).

  16. de Lauzon-Guillain, B. et al. Mediation and modification of genetic susceptibility to obesity by eating behaviours. Am. J. Clin. Nutr. 106, 996–1004 (2017).

    Article  PubMed  Google Scholar 

  17. Jacob, R. et al. The role of eating behaviour traits in mediating genetic susceptibility to obesity. Am. J. Clin. Nutr. 108, 445–452 (2018).

    Article  PubMed  Google Scholar 

  18. Tharner, A. et al. Toward an operative diagnosis of fussy/picky eating: a latent profile approach in a population-based cohort. Int. J. Behav. Nutr. Phys. Act. 11, 14 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  19. de Barse, L. M. et al. Longitudinal association between preschool fussy eating and body composition at 6 years of age: the generation R study. Int. J. Behav. Nutr. Phys. Act. 12, 153 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Mallan, K. M., Fildes, A., Magarey, A. M. & Daniels, L. A. The relationship between number of fruits, vegetables, and noncore foods tried at age 14 months and food preferences, dietary intake patterns, fussy eating behaviour, and weight status at age 3.7 years. J. Acad. Nutr. Diet. 116, 630–637 (2016).

    Article  PubMed  Google Scholar 

  21. Smith, A. D. et al. Food fussiness and food neophobia share a common etiology in early childhood. J. Child Psychol. Psychiatry 58, 189–196 (2017).

    Article  PubMed  Google Scholar 

  22. Villarejo, C. et al. Lifetime obesity in patients with eating disorders: increasing prevalence, clinical and personality correlates. Eur. Eat. Disord. Rev. 20, 250–254 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yilmaz, Z., Gottfredson, N. C., Zerwas, S. C., Bulik, C. M. & Micali, N. Developmental premorbid body mass index trajectories of adolescents with eating disorders in a longitudinal population cohort. J. Am. Acad. Child Adolesc. Psychiatry 58, 191–199 (2019).

    Article  PubMed  Google Scholar 

  24. Stice, E. & Desjardins, C. D. Interactions between risk factors in the prediction of onset of eating disorders: exploratory hypothesis generating analyses. Behav. Res Ther. 105, 52–62 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Herle, M. et al. A longitudinal study of eating behaviours in childhood and later eating disorder behaviours and diagnoses. Br. J. Psychiatry 216, 113–119 (2019).

  26. Nicholls, D., Statham, R., Costa, S., Micali, N. & Viner, R. M. Childhood risk factors for lifetime bulimic or compulsive eating by age 30 years in a British national birth cohort. Appetite 105, 266–273 (2016).

    Article  CAS  PubMed  Google Scholar 

  27. Stice, E., Davis, K., Miller, N. P. & Marti, C. N. Fasting increases risk for onset of binge eating and bulimic pathology: a 5-year prospective study. J. Abnorm. Psychol. 117, 941–946 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Watson, H. J. et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat. Genet. 51, 1207–1214 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Yilmaz, Z. et al. Anorexia nervosa and obsessive compulsive polygenic risk score: associations with adolescent eating disorder phenotypes. Eur. Neuropsychopharm. 29, S818–S819 (2019).

    Article  Google Scholar 

  30. Herle, M., Smith, A. D., Kininmonth, A. & Llewellyn, C. The role of eating behaviours in genetic susceptibility to obesity. Curr. Obes. Rep. 9, 512–521 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Steinsbekk, S. & Wichstrom, L. Predictors of change in BMI from the age of 4 to 8. J. Pediatr. Psychol. 40, 1056–1064 (2015).

    Article  PubMed  Google Scholar 

  32. Syrad, H. et al. Meal size is a critical driver of weight gain in early childhood. Sci. Rep. 6, 28368 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Samuel, T. M., Musa-Veloso, K., Ho, M., Venditti, C. & Shahkhalili-Dulloo, Y. A narrative review of childhood picky eating and its relationship to food intakes, nutritional status, and growth. Nutrients 10, 1992 (2018).

    Article  PubMed Central  Google Scholar 

  34. Wray, N. R., Kemper, K. E., Hayes, B. J., Goddard, M. E. & Visscher, P. M. Complex trait prediction from genome data: contrasting EBV in livestock to PRS in humans: genomic prediction. Genetics 211, 1131–1141 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Webber, L., Cooke, L., Hill, C. & Wardle, J. Child adiposity and maternal feeding practices a longitudinal analysis. Am. J. Clin. Nutr. 92, 1423–1428 (2010).

    Article  CAS  PubMed  Google Scholar 

  36. Rodgers, R. F. et al. Maternal feeding practices predict weight gain and obesogenic eating behaviours in young children: a prospective study. Int. J. Behav. Nutr. Phy. Act. 10, 24 (2013).

    Article  Google Scholar 

  37. Jansen, P. W. et al. Bi-directional associations between child fussy eating and parents’ pressure to eat: who influences whom? Physiol. Behav. 176, 101–106 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Selzam, S. et al. Evidence for gene–environment correlation in child feeding: links between common genetic variation for BMI in children and parental feeding practices. PLoS Genet. 14, e1007757 (2018).

  39. Thompson, M. E. Parental feeding and childhood obesity in preschool-age children: recent findings from the literature. Issues Compr. Pediatr. Nurs. 33, 205–267 (2010).

    Article  PubMed  Google Scholar 

  40. Musher-Eizenman, D. R., de Lauzon-Guillain, B., Holub, S. C., Leporc, E. & Charles, M. A. Child and parent characteristics related to parental feeding practices. A cross-cultural examination in the US and France. Appetite 52, 89–95 (2009).

    Article  PubMed  Google Scholar 

  41. Kininmonth, A. R., Smith, A. D., Llewellyn, C. H. & Fildes, A. Socioeconomic status and changes in appetite from toddlerhood to early childhood. Appetite 146, 104517 (2020).

    Article  PubMed  Google Scholar 

  42. Palla, L. & Dudbridge, F. A fast method that uses polygenic scores to estimate the variance explained by genome-wide marker panels and the proportion of variants affecting a trait. Am. J. Hum. Genet. 97, 250–259 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Fraser, A. et al. Cohort profile: the Avon Longitudinal Study of Parents and Children: ALSPAC Mothers Cohort. Int. J. Epidemiol. 42, 97–110 (2013).

    Article  PubMed  Google Scholar 

  44. Euesden, J., Lewis, C. M. & O’Reilly, P. F. PRSice: polygenic risk score software. Bioinformatics 31, 1466–1468 (2015).

    Article  CAS  PubMed  Google Scholar 

  45. Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. This work was specifically funded by the UK Medical Research Council and the Medical Research Foundation (MR/R004803/1). N.M. and C.M.B. report funding from the National Institute of Mental Health (R21 MH115397). The UK Medical Research Council and Wellcome (grant no. 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. A comprehensive list of funding is available on the ALSPAC website. D.S.F. works in a Unit that receives funds from the University of Bristol and the UK Medical Research Council (MC_UU_00011/6). M.H. is supported by a fellowship from the UK Medical Research Council (MR/T027843/1). C.M.B. acknowledges funding from the Swedish Research Council (538-2013-8864), National Institute of Mental Health (R01 MH109528) and the Klarman Family Foundation. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Great Ormond Street Institute of Child Health, University College London, London, UK

    Moritz Herle, Bianca De Stavola & Nadia Micali

  2. Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Moritz Herle

  3. Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland

    Mohamed Abdulkadir & Nadia Micali

  4. Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK

    Christopher Hübel

  5. NIHR Biomedical Research Centre, South London and Maudsley Hospital, London, UK

    Christopher Hübel

  6. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Christopher Hübel & Cynthia M. Bulik

  7. Medical Research Council Integrative Epidemiology, University of Bristol, Bristol, UK

    Diana Santos Ferreira

  8. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK

    Diana Santos Ferreira

  9. Maudsley Centre for Child and Adolescent Eating Disorders, Michael Rutter Centre for Children and Young People, Maudsley Hospital, London, UK

    Rachel Bryant-Waugh

  10. The Charles Bronfman Institute for Personalized Medicine, Icahn Mount Sinai School of Medicine, New York, NY, USA

    Ruth J. F. Loos

  11. Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Cynthia M. Bulik

  12. Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Cynthia M. Bulik

  13. Child and Adolescent Psychiatry Division, Department of Child and Adolescent Health, Geneva University Hospital, Geneva, Switzerland

    Nadia Micali

Authors
  1. Moritz Herle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohamed Abdulkadir
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christopher Hübel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Diana Santos Ferreira
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rachel Bryant-Waugh
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ruth J. F. Loos
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Cynthia M. Bulik
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bianca De Stavola
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nadia Micali
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.H., C.M.B., B.D.S., R.J.F.L., R.B.-W. and N.M. and devised the research. M.H., M.A., C.H. and B.D.S. analysed the data. All authors (M.H., M.A., C.H., D.S.F., R.J.F.L., R.B.-W., C.M.B, B.D.S, N.M.) interpreted the data and drafted the manuscript. All authors approved the submitted version and have agreed to be personally accountable for author’s own contributions.

Corresponding author

Correspondence to Nadia Micali.

Ethics declarations

Competing interests

C.M.B. is a Scientific Advisory Board Member for, and grant recipient from, Shire Pharmaceuticals (Takeda Pharmaceuticals); a consultant for Idorsia Pharmaceuticals; and author and royalty recipient from Pearson. All other authors declare no competing interests.

Additional information

Peer review information Nature Human Behaviour thanks Adam Locke, Jordi Merino and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Stavroula Kousta.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Tables 1–6 and Supplementary Fig. 1.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Herle, M., Abdulkadir, M., Hübel, C. et al. The genomics of childhood eating behaviours. Nat Hum Behav 5, 625–630 (2021). https://doi.org/10.1038/s41562-020-01019-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-020-01019-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing