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.

  • Original Article
  • Published:

Pediatrics

Newborn insula gray matter volume is prospectively associated with early life adiposity gain

Abstract

Background:

The importance of energy homeostasis brain circuitry in the context of obesity is well established, however, the developmental ontogeny of this circuitry in humans is currently unknown. Here, we investigate the prospective association between newborn gray matter (GM) volume in the insula, a key brain region underlying energy homeostasis, and change in percent body fat accrual over the first six months of postnatal life, an outcome that represents among the most reliable infant predictors of childhood obesity risk.

Methods:

A total of 52 infants (29 male, 23 female, gestational age at birth=39(1.5) weeks) were assessed using structural MRI shortly after birth (postnatal age at MRI scan=25.9(12.2) days), and serial Dual X-Ray Absorptiometry shortly after birth (postnatal age at DXA scan 1=24.6(11.4) days) and at six months of age (postnatal age at DXA scan 2=26.7(3.3) weeks).

Results:

Insula GM volume was inversely associated with change in percent body fat from birth to six-months postnatal age and accounted for 19% of its variance (β=−3.6%/S.D., P=0.001). This association was driven by the central-posterior portion of the insula, a region of particular importance for gustation and interoception. The direction of this effect is in concordance with observations in adults, and the results remained statistically significant after adjusting for relevant covariates and potential confounding variables.

Conclusions:

Altogether, these findings suggest an underlying neural basis of childhood obesity that precedes the influence of the postnatal environment. The identification of plausible brain-related biomarkers of childhood obesity risk that predate the influence of the postnatal obesogenic environment may contribute to an improved understanding of propensity for obesity, early identification of at-risk individuals, and intervention targets for primary prevention.

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

Access options

Buy this article

USD 39.95

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

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5

Similar content being viewed by others

References

  1. Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2013; 380: 2224–2260.

    Article  Google Scholar 

  2. Whitaker RC, Wright JA, Pepe MS, Seidel KD, Dietz WH . Predicting obesity in young adulthood from childhood and parental obesity. N Engl J Med 1997; 337: 869–873.

    Article  CAS  Google Scholar 

  3. Freedman DS, Khan LK, Dietz WH, Srinivasan SR, Berenson GS . Relationship of childhood obesity to coronary heart disease risk factors in adulthood: the Bogalusa Heart Study. Pediatrics 2001; 108: 712–718.

    Article  CAS  Google Scholar 

  4. Dabelea D, Harrod CS . Role of developmental overnutrition in pediatric obesity and type 2 diabetes. Nutr Rev 2013; 71 (Suppl 1): S62–S67.

    Article  Google Scholar 

  5. Dietz WH . Health consequences of obesity in youth: childhood predictors of adult disease. Pediatrics 1998; 101 (Suppl 2): 518–525.

    CAS  PubMed  Google Scholar 

  6. Freedman DS, Mei Z, Srinivasan SR, Berenson GS, Dietz WH . Cardiovascular risk factors and excess adiposity among overweight children and adolescents: the Bogalusa Heart Study. J Pediatr 2007; 150: 12–17.

    Article  Google Scholar 

  7. Forgat-Campagna A, Narayan KV . Type-2 diabetes in children: exemplifies the growing problem of chronic diseases. Br Med J 2001; 322: 377–378.

    Article  Google Scholar 

  8. Donkor HM, Grundt JH, Hurum J, Sundby AB, Skundberg T et al. 45 Effect of a Multimodal Intervention Program to Prevent Obesity in Early Childhood. Arch Dis Childhood 2012; 97 (Suppl 2): A12–A13.

    Article  Google Scholar 

  9. Ghoorah K, Campbell P, Kent A, Maznyczka A, Kunadian V . Obesity and cardiovascular outcomes: a review. Eur Heart J: Acute Cardiovas Care 2014; 5: 77–85.

    Google Scholar 

  10. Finegood DT, Merth TD, Rutter H . Implications of the foresight obesity system map for solutions to childhood obesity. Obesity 2010; 18: S13–S16.

    Article  Google Scholar 

  11. Morton GJ, Meek TH, Schwartz MW . Neurobiology of food intake in health and disease. Nat Rev Neurosci 2014; 15: 367.

    Article  CAS  Google Scholar 

  12. Kurth F, Zilles K, Fox PT, Laird AR, Eickhoff SB . A link between the systems: functional differentiation and integration within the human insula revealed by meta-analysis. Brain Struct Funct 2010; 214: 519–534.

    Article  Google Scholar 

  13. Small DM, Prescott J . Odor/taste integration and the perception of flavor. Exp Brain Res 2005; 166: 345–357.

    Article  Google Scholar 

  14. Simon SA, de Araujo IE, Gutierrez R, Nicolelis MA . The neural mechanisms of gustation: a distributed processing code. Nat Rev Neurosci 2006; 7: 890–901.

    Article  CAS  Google Scholar 

  15. Mufson EJ, Mesulam MM, Pandya DN . Insular interconnections with the amygdala in the rhesus monkey. Neuroscience 1981; 6: 1231–1248.

    Article  CAS  Google Scholar 

  16. Kadohisa M, Rolls ET, Verhagen JV . Neuronal representations of stimuli in the mouth: the primate insular taste cortex, orbitofrontal cortex and amygdala. Chem Senses 2005; 30: 401–419.

    Article  Google Scholar 

  17. Morton GJ, Cummings DE, Baskin DG, Barsh GS, Schwartz MW . Central nervous system control of food intake and body weight. Nature 2006; 443: 289–295.

    Article  CAS  Google Scholar 

  18. Baxter MG, Murray EA . The amygdala and reward. Nat Rev Neurosci 2002; 3: 563–573.

    Article  CAS  Google Scholar 

  19. Koontz MB, Gunzler DD, Presley L, Catalano PM . Longitudinal changes in infant body composition: association with childhood obesity. Pediatric Obesity 2014; 9: e141–e144.

    Article  CAS  Google Scholar 

  20. Baird J, Fisher D, Lucas P, Kleijnen J, Roberts H, Law C . Being big or growing fast: systematic review of size and growth in infancy and later obesity. Br Med J 2005; 331: 929.

    Article  Google Scholar 

  21. Druet C, Stettler N, Sharp S, Simmons RK, Cooper C, Davey Smith G et al. Prediction of childhood obesity by infancy weight gain: an individual-level meta-analysis. Paediatr Perinatal Epidemiol 2012; 26: 19–26.

    Article  Google Scholar 

  22. Stettler N, Kumanyika SK, Katz SH, Zemel BS, Stallings VA . Rapid weight gain during infancy and obesity in young adulthood in a cohort of African Americans. Am J Clin Nutr 2003; 77: 1374–1378.

    Article  CAS  Google Scholar 

  23. Avery JA, Kerr KL, Ingeholm JE, Burrows K, Bodurka J, Simmons WK . A common gustatory and interoceptive representation in the human mid-insula. Human Brain Mapping 2015; 36: 2996–3006.

    Article  Google Scholar 

  24. Prastawa M, Gilmore JH, Lin W, Gerig G . Automatic segmentation of MR images of the developing newborn brain. Medical Image Analysis 2005; 9: 457–466.

    Article  Google Scholar 

  25. O'Brien GD, Queenan JT, Campbell S . Assessment of gestational age in the second trimester by real-time ultrasound measurement of the femur length. American Journal of Obstetrics and Gynecology 1981; 139: 540–545.

    Article  CAS  Google Scholar 

  26. Stephani C, Vaca GF, Maciunas R, Koubeissi M, Lüders HO . Functional neuroanatomy of the insular lobe. Brain Struct Funct 2011; 216: 137–149.

    Article  CAS  Google Scholar 

  27. Kobayakawa T, Wakita M, Saito S, Gotow N, Sakai N, Ogawa H . Location of the primary gustatory area in humans and its properties, studied by magnetoencephalography. Chem Senses 2005; 30 (suppl 1): i226–i227.

    Article  Google Scholar 

  28. Nakamura Y, Tokumori K, Tanabe HC, Yoshiura T, Kobayashi K, Nakamura Y et al. Localization of the primary taste cortex by contrasting passive and attentive conditions. Exp Brain Res 2013; 227: 185–197.

    Article  Google Scholar 

  29. Simmons WK, Rapuano KM, Kallman SJ, Ingeholm JE, Miller B, Gotts SJ et al. Category-specific integration of homeostatic signals in caudal but not rostral human insula. Nat Neurosci 2013; 16: 1551–1552.

    Article  CAS  Google Scholar 

  30. Entringer S, Buss C, Swanson JM, Cooper DM, Wing DA, Waffarn F et al. Fetal programming of body composition, obesity, and metabolic function: the role of intrauterine stress and stress biology. J Nutr Metab 2012; 2012: 632548.

    Article  Google Scholar 

  31. Buss C, Entringer S, Wadhwa PD . Fetal programming of brain development: intrauterine stress and susceptibility to psychopathology. Sci Signal 2012; 5: 1–15.

    Article  Google Scholar 

  32. Volkow ND, Wang GJ, Tomasi D, Baler RD . Obesity and addiction: neurobiological overlaps. Obesity Rev 2013; 14: 2–18.

    Article  CAS  Google Scholar 

  33. Peng Y, Gillis-Smith S, Jin H, Tränkner D, Ryba NJ, Zuker CS . Sweet and bitter taste in the brain of awake behaving animals. Nature 2015; 527: 512–515.

    Article  CAS  Google Scholar 

  34. Tomasi D, Wang GJ, Wang R, Backus W, Geliebter A, Telang F et al. Association of body mass and brain activation during gastric distention: implications for obesity. PLoS ONE 2009; 4: e6847.

    Article  Google Scholar 

  35. Stoeckel LE, Weller RE, Cook EW, Twieg DB, Knowlton RC, Cox JE . Widespread reward-system activation in obese women in response to pictures of high-calorie foods. NeuroImage 2008; 41: 636–647.

    Article  Google Scholar 

  36. DelParigi A, Chen K, Salbe AD, Reiman EM, Tataranni PA . Sensory experience of food and obesity: a positron emission tomography study of the brain regions affected by tasting a liquid meal after a prolonged fast. NeuroImage 2005; 24: 436–443.

    Article  Google Scholar 

  37. Malik S, McGlone F, Bedrossian D, Dagher A . Ghrelin modulates brain activity in areas that control appetitive behavior. Cell Metab 2008; 7: 400–409.

    Article  CAS  Google Scholar 

  38. Vandenbergh J, DuPont P, Fischler B, Bormans G, Persoons P, Janssens J et al. Regional brain activation during proximal stomach distention in humans: a positron emission tomography study. Gastroenterology 2005; 128: 564–573.

    Article  Google Scholar 

  39. Wang GJ, Tomasi D, Backus W, Wang R, Telang F, Geliebter A et al. Gastric distention activates satiety circuitry in the human brain. Neuroimage 2008; 39: 1824–1831.

    Article  Google Scholar 

  40. Baicy K, London ED, Monterosso J, Wong ML, Delibasi T, Sharma A et al. Leptin replacement alters brain response to food cues in genetically leptin-deficient adults. Proc Natl Acad Sci 2007; 104: 18276–18279.

    Article  CAS  Google Scholar 

  41. Kurth F, Levitt JG, Phillips OR, Luders E, Woods RP, Mazziotta JC et al. Relationships between gray matter, body mass index, and waist circumference in healthy adults. Hum Brain Map 2013; 34: 1737–1746.

    Article  Google Scholar 

  42. Janowitz D, Wittfeld K, Terock J, Freyberger HJ, Hegenscheid K, Völzke H et al. Association between waist circumference and gray matter volume in 2344 individuals from two adult community-based samples. NeuroImage 2015; 122: 149–157.

    Article  Google Scholar 

  43. Pannacciulli N, Del Parigi A, Chen K, Le DS, Reiman EM, Tataranni PA . Brain abnormalities in human obesity: a voxel-based morphometric study. NeuroImage 2006; 31: 1419–1425.

    Article  Google Scholar 

  44. Carnell S, Gibson C, Benson L, Ochner CN, Geliebter A . Neuroimaging and obesity: current knowledge and future directions. Obesity Rev 2012; 13: 43–56.

    Article  CAS  Google Scholar 

  45. Pannacciulli N, Le DS, Chen K, Reiman EM, Krakoff J . Relationships between plasma leptin concentrations and human brain structure: a voxel-based morphometric study. Neurosci Lett 2007; 412: 248–253.

    Article  CAS  Google Scholar 

  46. Peters J, Dauvermann M, Mette C, Platen P, Franke J, Hinrichs T et al. Voxel-based morphometry reveals an association between aerobic capacity and grey matter density in the right anterior insula. Neuroscience 2009; 163: 1102–1108.

    Article  CAS  Google Scholar 

  47. Jauch-Chara K, Binkofski F, Loebig M, Reetz K, Jahn G, Melchert UH et al. Blunted brain energy consumption relates to insula atrophy and impaired glucose tolerance in obesity. Diabetes 2015; 64: 2082–2091.

    Article  CAS  Google Scholar 

  48. Smucny J, Cornier MA, Eichman LC, Thomas EA, Bechtell JL, Tregellas JR . Brain structure predicts risk for obesity. Appetite 2012; 59: 859–865.

    Article  Google Scholar 

  49. McCloskey K, Burgner D, Carlin JB, Skilton MR, Cheung M, Dwyer T et al. Infant adiposity at birth and early postnatal weight gain predict increased aortic intima-media thickness at 6 weeks of age: a population-derived cohort study. Clin Sci 2016; 130: 443–450.

    Article  CAS  Google Scholar 

  50. Monteiro PO, Victora CG . Rapid growth in infancy and childhood and obesity in later life–a systematic review. Obesity Rev 2005; 6: 143–154.

    Article  CAS  Google Scholar 

  51. Ong KK, Emmett P, Northstone K, Golding J, Rogers I, Ness AR et al. Infancy weight gain predicts childhood body fat and age at menarche in girls. J Clin Endocrinol Metab 2009; 94: 1527–1532.

    Article  CAS  Google Scholar 

  52. Kruithof CJ, Gishti O, Hofman A, Gaillard R, Jaddoe VW . Infant weight growth velocity patterns and general and abdominal adiposity in school-age children. The Generation R Study. Eur J Clin Nutr 2016; 70: 1144–1150.

    Article  CAS  Google Scholar 

  53. Magnus MC, Olsen SF, Granström C, Joner G, Skrivarhaug T, Svensson J et al. Infant growth and risk of childhood-onset type 1 diabetes in children from 2 Scandinavian birth cohorts. JAMA Pediatr 2015; 169: e153759.

    Article  Google Scholar 

  54. Ekelund U, Ong KK, Linné Y, Neovius M, Brage S, Dunger DB et al. Association of weight gain in infancy and early childhood with metabolic risk in young adults. J Clin Endocrinol Metab 2007; 92: 98–103.

    Article  CAS  Google Scholar 

  55. Huxley RR, Shiell AW, Law CM . The role of size at birth and postnatal catch-up growth in determining systolic blood pressure: a systematic review of the literature. J Hypertension 2000; 18: 815–831.

    Article  CAS  Google Scholar 

  56. Sonnenschein-van der Voort AMM, Arends LR, de Jongste JC, Annesi-Maesano I, Arshad SH, Barros H et al. Preterm birth, infant weight gain, and childhood asthma risk: a meta-analysis of 147,000 European children. J Allergy Clin Immunol 2014; 133: 1317–1329.

    Article  Google Scholar 

  57. Li R, O'Connor L, Buckley D, Specker B . Relation of activity levels to body fat in infants 6 to 12 months of age. J Pediatr 1995; 126: 353–357.

    Article  CAS  Google Scholar 

  58. Morel A, Gallay MN, Baechler A, Wyss M, Gallay DS . The human insula: architectonic organization and postmortem MRI registration. Neuroscience 2013; 236: 117–135.

    Article  CAS  Google Scholar 

  59. Van Leemput K, Bakkour A, Benner T, Wiggins G, Wald LL, Augustinack J et al. Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI. Hippocampus 2009; 19: 549–557.

    Article  Google Scholar 

  60. Lakens D . Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front Psychol 2013; 4: 863.

    Article  Google Scholar 

  61. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH . Genetic studies of body mass index yield new insights for obesity biology. Nature 2015; 518: 197–206.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

Support for this work was provided by R01 MH091351 to CB and PDW, R01 HD-065825 to SE and PDW, R01 HD-060628 to PDW, and UCI Institute for Clinical and Translational Science (CTSA grant) UL1 TR000153.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to C Buss.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rasmussen, J., Entringer, S., Kruggel, F. et al. Newborn insula gray matter volume is prospectively associated with early life adiposity gain. Int J Obes 41, 1434–1439 (2017). https://doi.org/10.1038/ijo.2017.114

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/ijo.2017.114

This article is cited by

Search

Quick links