Advertisement

Journal of Autism and Developmental Disorders

, Volume 49, Issue 12, pp 4751–4760 | Cite as

Effects of Overweight or Obesity on Brain Resting State Functional Connectivity of Children with Autism Spectrum Disorder

  • Chanaka N. KahathuduwaEmail author
  • Blake West
  • Ann Mastergeorge
Original Paper

Abstract

Evidence on neurophysiological correlates of coexisting autism spectrum disorders (ASD) and overweight/obesity may elucidate mechanisms leading to the observed greater risk of obesity in children with ASD. An exploratory secondary data analysis was performed on resting state functional magnetic resonance imaging (rs-fMRI) data of children downloaded from the ABIDE Preprocessed database (n = 81). Children with isolated ASD showed hypo-connectivity between anterior and posterior default mode network (DMN) (p = 0.003; FWER). Children with coexisting ASD and overweight/obesity showed hyper-connectivity between anterior and posterior DMN (p = 0.015; FWER). More evidence is needed to confirm these contrasting rs-fMRI connectivity profiles and to explicate causal inferences regarding neurophysiological mechanisms associated with coexisting ASD and overweight/obesity.

Keywords

Autism spectrum disorder Obesity Overweight Brain Magnetic resonance imaging Functional neuroimaging Connectome 

Notes

Acknowledgements

The authors wish to acknowledge ABIDE Preprocessed (http://preprocessed-connectomes-project.org/abide/) for providing access to preprocessed neuroimaging data to perform the analyses presented in this manuscript.

Compliance with Ethical Standards

Conflict of interest

The authors have no other potential conflicts of interest to declare.

Supplementary material

10803_2019_4187_MOESM1_ESM.docx (185 kb)
Supplementary material 1 (DOCX 185 kb)

References

  1. Anderson, J. S., Druzgal, T. J., Froehlich, A., DuBray, M. B., Lange, N., Alexander, A. L., et al. (2011). Decreased interhemispheric functional connectivity in autism. Cerebral Cortex,21(5), 1134–1146.  https://doi.org/10.1093/cercor/bhq190.CrossRefPubMedGoogle Scholar
  2. Andersson, J. L., Jenkinson, M., & Smith, S. (2007). Non-linear registration, aka Spatial normalisation FMRIB technical report TR07JA2. FMRIB Analysis Group of the University of Oxford.Google Scholar
  3. Assaf, M., Jagannathan, K., Calhoun, V. D., Miller, L., Stevens, M. C., Sahl, R., et al. (2010). Abnormal functional connectivity of default mode sub-networks in autism spectrum disorder patients. Neuroimage,53(1), 247–256.  https://doi.org/10.1016/j.neuroimage.2010.05.067.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Atladóttir, H., Henriksen, T. B., Schendel, D. E., & Parner, E. T. (2012). Autism after infection, febrile episodes, and antibiotic use during pregnancy: An exploratory study. Pediatrics,130(6), e1447–1454.  https://doi.org/10.1542/peds.2012-1107.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Baio, J., Wiggins, L., Christensen, D. L., Maenner, M. J., Daniels, J., Warren, Z., et al. (2018). Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillance Summary,67(6), 1–23.  https://doi.org/10.15585/mmwr.ss6706a1.CrossRefGoogle Scholar
  6. Berthoud, H.-R. (2002). Multiple neural systems controlling food intake and body weight. Neuroscience and Biobehavioral Reviews,26(4), 393–428.CrossRefGoogle Scholar
  7. Binks, M., Kahathuduwa, C. N., & Davis, T. (2017). Challenges in accurately modeling the complexity of human ingestive behavior: The influence of portion size and energy density of food on fMRI food-cue reactivity. American Journal of Clinical Nutrition,105(2), 289–290.  https://doi.org/10.3945/ajcn.116.150813.CrossRefPubMedGoogle Scholar
  8. Braun, J. M. (2017). Early-life exposure to EDCs: Role in childhood obesity and neurodevelopment. Nature Reviews Endocrinology,13(3), 161–173.  https://doi.org/10.1038/nrendo.2016.186.CrossRefPubMedGoogle Scholar
  9. Bryden, K. E., & Kopala, L. C. (1999). Body mass index increase of 58% associated with olanzapine. American Journal of Psychiatry,156(11), 1835–1836.  https://doi.org/10.1176/ajp.156.11.1835.CrossRefPubMedGoogle Scholar
  10. Buescher, A. V., Cidav, Z., Knapp, M., & Mandell, D. S. (2014). Costs of autism spectrum disorders in the United Kingdom and the United States. JAMA Pediatrics,168(8), 721–728.  https://doi.org/10.1001/jamapediatrics.2014.210.CrossRefPubMedGoogle Scholar
  11. Chao, S. H., Liao, Y. T., Chen, V. C., Li, C. J., McIntyre, R. S., Lee, Y., et al. (2018). Correlation between brain circuit segregation and obesity. Behavioural Brain Research,337, 218–227.  https://doi.org/10.1016/j.bbr.2017.09.017.CrossRefPubMedGoogle Scholar
  12. Chin, S. H., Kahathuduwa, C. N., Stearns, M. B., Davis, T., & Binks, M. (2018). Is hunger important to model in fMRI visual food-cue reactivity paradigms in adults with obesity and how should this be done? Appetite,120, 388–397.  https://doi.org/10.1016/j.appet.2017.09.012.CrossRefPubMedGoogle Scholar
  13. Craddock, R. C., & Bellec, P. (2015). Preprocessed connectomes project: Abide. http://preprocessed-connectomes-project.github.io/abide.
  14. Demetriou, E. A., Lampit, A., Quintana, D. S., Naismith, S. L., Song, Y. J. C., Pye, J. E., et al. (2018). Autism spectrum disorders: A meta-analysis of executive function. Molecular Psychiatry,23(5), 1198–1204.  https://doi.org/10.1038/mp.2017.75.CrossRefPubMedGoogle Scholar
  15. Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., et al. (2014). The autism brain imaging data exchange: Towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular Psychiatry,19(6), 659–667.  https://doi.org/10.1038/mp.2013.78.CrossRefPubMedGoogle Scholar
  16. Dominick, K. C., Davis, N. O., Lainhart, J., Tager-Flusberg, H., & Folstein, S. (2007). Atypical behaviors in children with autism and children with a history of language impairment. Research in Developmental Disabilities,28(2), 145–162.  https://doi.org/10.1016/j.ridd.2006.02.003.CrossRefPubMedGoogle Scholar
  17. Doucet, G. E., Rasgon, N., McEwen, B. S., Micali, N., & Frangou, S. (2018). Elevated Body Mass Index is associated with increased integration and reduced cohesion of sensory-driven and internally guided resting-state functional brain networks. Cerebral Cortex,28(3), 988–997.  https://doi.org/10.1093/cercor/bhx008.CrossRefPubMedGoogle Scholar
  18. Duan, X., Chen, H., He, C., Long, Z., Guo, X., Zhou, Y., et al. (2017). Resting-state functional under-connectivity within and between large-scale cortical networks across three low-frequency bands in adolescents with autism. Progress in Neuro-Psychopharmacology and Biological Psychiatry,79(Pt B), 434–441.  https://doi.org/10.1016/j.pnpbp.2017.07.027.CrossRefPubMedGoogle Scholar
  19. Easson, A. K., Fatima, Z., & McIntosh, A. R. (2019). Functional connectivity-based subtypes of individuals with and without autism spectrum disorder. Network Neuroscience,3(2), 344–362.  https://doi.org/10.1162/netn_a_00067.CrossRefPubMedPubMedCentralGoogle Scholar
  20. Eklund, A., Nichols, T. E., & Knutsson, H. (2016). Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proceedings of the National Academy of Sciences of the United States of America,113(28), 7900–7905.  https://doi.org/10.1073/pnas.1602413113.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Fournier, K. A., Hass, C. J., Naik, S. K., Lodha, N., & Cauraugh, J. H. (2010). Motor coordination in autism spectrum disorders: A synthesis and meta-analysis. Journal of Autism and Developmental Disorders,40(10), 1227–1240.  https://doi.org/10.1007/s10803-010-0981-3.CrossRefGoogle Scholar
  22. Franzen, J. D., Heinrichs-Graham, E., White, M. L., Wetzel, M. W., Knott, N. L., & Wilson, T. W. (2013). Atypical coupling between posterior regions of the default mode network in attention-deficit/hyperactivity disorder: A pharmaco-magnetoencephalography study. Journal of Psychiatry and Neuroscience,38(5), 333–340.  https://doi.org/10.1503/jpn.120054.CrossRefPubMedGoogle Scholar
  23. Hack, M., Taylor, H. G., Schluchter, M., Andreias, L., Drotar, D., & Klein, N. (2009). Behavioral outcomes of extremely low birth weight children at age 8 years. Journal of Developmental and Behavioral Pediatrics,30(2), 122–130.  https://doi.org/10.1097/DBP.0b013e31819e6a16.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Hong, S. J., de Wael, R. V., Bethlehem, R. A., Lariviere, S., Paquola, C., Valk, S. L., et al. (2019). Atypical functional connectome hierarchy in autism. Nature Communications,10(1), 1022.  https://doi.org/10.1038/s41467-019-08944-1.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Hull, J. V., Jacokes, Z. J., Torgerson, C. M., Irimia, A., & Van Horn, J. D. (2016). Resting-state functional connectivity in autism spectrum disorders: A review. Frontiers in Psychiatry,7, 205.  https://doi.org/10.3389/fpsyt.2016.00205.CrossRefPubMedGoogle Scholar
  26. Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis,5(2), 143–156.CrossRefGoogle Scholar
  27. Jung, Y., Lee, A. M., McKee, S. A., & Picciotto, M. R. (2017). Maternal smoking and autism spectrum disorder: Meta-analysis with population smoking metrics as moderators. Scientific Reports,7(1), 4315.  https://doi.org/10.1038/s41598-017-04413-1.CrossRefPubMedPubMedCentralGoogle Scholar
  28. Karalunas, S. L., Hawkey, E., Gustafsson, H., Miller, M., Langhorst, M., Cordova, M., et al. (2018). Overlapping and distinct cognitive impairments in attention-deficit/hyperactivity and autism spectrum disorder without intellectual disability. Journal of Abnormal Child Psychology.  https://doi.org/10.1007/s10802-017-0394-2.CrossRefPubMedPubMedCentralGoogle Scholar
  29. Kennedy, D. P., & Courchesne, E. (2008). The intrinsic functional organization of the brain is altered in autism. Neuroimage,39(4), 1877–1885.  https://doi.org/10.1016/j.neuroimage.2007.10.052.CrossRefPubMedGoogle Scholar
  30. Kohane, I. S., McMurry, A., Weber, G., MacFadden, D., Rappaport, L., Kunkel, L., et al. (2012). The co-morbidity burden of children and young adults with autism spectrum disorders. PLoS ONE,7(4), e33224.  https://doi.org/10.1371/journal.pone.0033224.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Kumar, S., & Kelly, A. S. (2017). Review of childhood obesity: From epidemiology, etiology, and comorbidities to clinical assessment and treatment. Mayo Clinic Proceedings,92(2), 251–265.  https://doi.org/10.1016/j.mayocp.2016.09.017.CrossRefPubMedGoogle Scholar
  32. Lee, J. M., Kyeong, S., Kim, E., & Cheon, K. A. (2016). Abnormalities of inter- and intra-hemispheric functional connectivity in autism spectrum disorders: A study using the autism brain imaging data exchange database. Frontiers in Neuroscience,10, 191.  https://doi.org/10.3389/fnins.2016.00191.CrossRefPubMedPubMedCentralGoogle Scholar
  33. Lenard, N. R., & Berthoud, H. R. (2008). Central and peripheral regulation of food intake and physical activity: Pathways and genes. Obesity (Silver Spring),16(Suppl 3), S11–22.  https://doi.org/10.1038/oby.2008.511.CrossRefGoogle Scholar
  34. Lindberg, J., Norman, M., Westrup, B., Öhrman, T., Domellöf, M., & Berglund, S. K. (2015). Overweight, obesity, and body composition in 3.5- and 7-year-old swedish children born with marginally low birth weight. Journal of Pediatrics,167(6), 1246–1252.  https://doi.org/10.1016/j.jpeds.2015.08.045.CrossRefPubMedGoogle Scholar
  35. Magriplis, E., Farajian, P., Panagiotakos, D. B., Risvas, G., & Zampelas, A. (2017). Maternal smoking and risk of obesity in school children: Investigating early life theory from the GRECO study. Preventive Medicine Reports,8, 177–182.  https://doi.org/10.1016/j.pmedr.2017.10.001.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Maillard, A. M., Ruef, A., Pizzagalli, F., Migliavacca, E., Hippolyte, L., Adaszewski, S., et al. (2015). The 16p11.2 locus modulates brain structures common to autism, schizophrenia and obesity. Molecular Psychiatry,20(1), 140–147.  https://doi.org/10.1038/mp.2014.145.CrossRefPubMedGoogle Scholar
  37. Matheson, B. E., & Douglas, J. M. (2017). Overweight and obesity in children with autism spectrum disorder (ASD): A critical review investigating the etiology, development, and maintenance of this relationship. Review Journal of Autism and Developmental Disorders,4, 142–156.CrossRefGoogle Scholar
  38. McCoy, S. M., Jakicic, J. M., & Gibbs, B. B. (2016). Comparison of obesity, physical activity, and sedentary behaviors between adolescents with autism spectrum disorders and without. Journal of Autism and Developmental Disorders,46(7), 2317–2326.  https://doi.org/10.1007/s10803-016-2762-0.CrossRefPubMedGoogle Scholar
  39. McDougle, C. J. (2016). Atypical antipsychotic-induced weight gain in children and adolescents: Sometimes less is more. JAMA Psychiatry,73(9), 899–901.  https://doi.org/10.1001/jamapsychiatry.2016.1213.CrossRefPubMedGoogle Scholar
  40. McPartland, J. C., Law, K., & Dawson, G. (2016). Autism spectrum disorder. In H. S. Friedman (Ed.), Encyclopedia of mental health (pp. 124–130). Oxford: Academic Press.CrossRefGoogle Scholar
  41. Mevel, K., & Fransson, P. (2016). The functional brain connectome of the child and autism spectrum disorders. Acta Paediatrica,105(9), 1024–1035.  https://doi.org/10.1111/apa.13484.CrossRefPubMedGoogle Scholar
  42. Michalaki, E., Margetaki, K., Roumeliotaki, T., Vafeiadi, M., Karachaliou, M., Sarri, K., et al. (2018). Air pollution during pregnancy and childhood obesity risk: Potential protective effect of diet. Clinical Nutrition ESPEN,24, 187.  https://doi.org/10.1016/j.clnesp.2018.01.057.CrossRefGoogle Scholar
  43. Mueller, N. T., Whyatt, R., Hoepner, L., Oberfield, S., Dominguez-Bello, M. G., Widen, E. M., et al. (2015). Prenatal exposure to antibiotics, cesarean section and risk of childhood obesity. International Journal of Obesity (London),39(4), 665–670.  https://doi.org/10.1038/ijo.2014.180.CrossRefGoogle Scholar
  44. Ogden, C. L., Carroll, M. D., & Flegal, K. M. (2014). Prevalence of obesity in the United States. JAMA,312(2), 189–190.  https://doi.org/10.1001/jama.2014.6228.CrossRefPubMedGoogle Scholar
  45. Papageorgiou, I., Astrakas, L. G., Xydis, V., Alexiou, G. A., Bargiotas, P., Tzarouchi, L., et al. (2017). Abnormalities of brain neural circuits related to obesity: A diffusion tensor imaging study. Magnetic Resonance Imaging,37, 116–121.  https://doi.org/10.1016/j.mri.2016.11.018.CrossRefPubMedGoogle Scholar
  46. Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014). Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage,84, 320–341.  https://doi.org/10.1016/j.neuroimage.2013.08.048.CrossRefPubMedGoogle Scholar
  47. Raz, R., Levine, H., Pinto, O., Broday, D. M., Yuval, & Weisskopf, M. G. (2018). Traffic-related air pollution and autism spectrum disorder: A population-based nested case-control study in Israel. American Journal of Epidemiology,187(4), 717–725.  https://doi.org/10.1093/aje/kwx294.CrossRefPubMedGoogle Scholar
  48. Saad, Z. S., Reynolds, R. C., Jo, H. J., Gotts, S. J., Chen, G., Martin, A., et al. (2013). Correcting brain-wide correlation differences in resting-state FMRI. Brain Connectivity,3(4), 339–352.  https://doi.org/10.1089/brain.2013.0156.CrossRefPubMedPubMedCentralGoogle Scholar
  49. Sambataro, F., Blasi, G., Fazio, L., Caforio, G., Taurisano, P., Romano, R., et al. (2010). Treatment with olanzapine is associated with modulation of the default mode network in patients with Schizophrenia. Neuropsychopharmacology,35(4), 904–912.  https://doi.org/10.1038/npp.2009.192.CrossRefPubMedGoogle Scholar
  50. Sanchez, C. E., Barry, C., Sabhlok, A., Russell, K., Majors, A., Kollins, S. H., et al. (2018). Maternal pre-pregnancy obesity and child neurodevelopmental outcomes: A meta-analysis. Obesity Reviews,19(4), 464–484.  https://doi.org/10.1111/obr.12643.CrossRefPubMedGoogle Scholar
  51. Satterthwaite, T. D., Elliott, M. A., Gerraty, R. T., Ruparel, K., Loughead, J., Calkins, M. E., et al. (2013). An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data. Neuroimage,64, 240–256.  https://doi.org/10.1016/j.neuroimage.2012.08.052.CrossRefPubMedGoogle Scholar
  52. Scahill, L., Jeon, S., Boorin, S. J., McDougle, C. J., Aman, M. G., Dziura, J., et al. (2016). Weight gain and metabolic consequences of risperidone in young children with autism spectrum disorder. Journal of the American Academy of Child and Adolescent Psychiatry,55(5), 415–423.  https://doi.org/10.1016/j.jaac.2016.02.016.CrossRefPubMedPubMedCentralGoogle Scholar
  53. Seymour, K. E., Reinblatt, S. P., Benson, L., & Carnell, S. (2015). Overlapping neurobehavioral circuits in ADHD, obesity, and binge eating: Evidence from neuroimaging research. CNS Spectrums,20(4), 401–411.  https://doi.org/10.1017/S1092852915000383.CrossRefPubMedPubMedCentralGoogle Scholar
  54. Sharp, W. G., Berry, R. C., McCracken, C., Nuhu, N. N., Marvel, E., Saulnier, C. A., et al. (2013). Feeding problems and nutrient intake in children with autism spectrum disorders: A meta-analysis and comprehensive review of the literature. Journal of Autism and Developmental Disorders,43(9), 2159–2173.  https://doi.org/10.1007/s10803-013-1771-5.CrossRefPubMedGoogle Scholar
  55. Shetreat-Klein, M., Shinnar, S., & Rapin, I. (2014). Abnormalities of joint mobility and gait in children with autism spectrum disorders. Brain & Development,36(2), 91–96.  https://doi.org/10.1016/j.braindev.2012.02.005.CrossRefGoogle Scholar
  56. Shinawi, M., Sahoo, T., Maranda, B., Skinner, S. A., Skinner, C., Chinault, C., et al. (2011). 11p14.1 microdeletions associated with ADHD, autism, developmental delay, and obesity. American Journal of Medical Genetics Part A,155A(6), 1272–1280.  https://doi.org/10.1002/ajmg.a.33878.CrossRefPubMedGoogle Scholar
  57. Starck, T., Nikkinen, J., Rahko, J., Remes, J., Hurtig, T., Haapsamo, H., et al. (2013). Resting state fMRI reveals a default mode dissociation between retrosplenial and medial prefrontal subnetworks in ASD despite motion scrubbing. Frontiers in Human Neuroscience,7, 802.  https://doi.org/10.3389/fnhum.2013.00802.CrossRefPubMedPubMedCentralGoogle Scholar
  58. Thamotharan, S., Lange, K., Zale, E. L., Huffhines, L., & Fields, S. (2013). The role of impulsivity in pediatric obesity and weight status: A meta-analytic review. Clinical Psychology Review,33(2), 253–262.  https://doi.org/10.1016/j.cpr.2012.12.001.CrossRefPubMedGoogle Scholar
  59. Trasande, L., & Elbel, B. (2012). The economic burden placed on healthcare systems by childhood obesity. Expert Review of Pharmacoeconomics & Outcomes Research,12(1), 39–45.  https://doi.org/10.1586/erp.11.93.CrossRefGoogle Scholar
  60. Uddin, L. Q., Supekar, K., & Menon, V. (2010). Typical and atypical development of functional human brain networks: Insights from resting-state FMRI. Frontiers in Systems Neuroscience,4, 21.  https://doi.org/10.3389/fnsys.2010.00021.CrossRefPubMedPubMedCentralGoogle Scholar
  61. Wan, H., Zhang, C., Li, H., Luan, S., & Liu, C. (2018). Association of maternal diabetes with autism spectrum disorders in offspring: A systemic review and meta-analysis. Medicine (Baltimore),97(2), e9438.  https://doi.org/10.1097/MD.0000000000009438.CrossRefGoogle Scholar
  62. Weng, S. J., Wiggins, J. L., Peltier, S. J., Carrasco, M., Risi, S., Lord, C., et al. (2010). Alterations of resting state functional connectivity in the default network in adolescents with autism spectrum disorders. Brain Research,1313, 202–214.  https://doi.org/10.1016/j.brainres.2009.11.057.CrossRefPubMedGoogle Scholar
  63. Werling, D. M., & Geschwind, D. H. (2013). Sex differences in autism spectrum disorders. Current Opinion in Neurology,26(2), 146–153.CrossRefGoogle Scholar
  64. Wiggins, J. L., Peltier, S. J., Ashinoff, S., Weng, S. J., Carrasco, M., Welsh, R. C., et al. (2011). Using a self-organizing map algorithm to detect age-related changes in functional connectivity during rest in autism spectrum disorders. Brain Research,1380, 187–197.  https://doi.org/10.1016/j.brainres.2010.10.102.CrossRefPubMedGoogle Scholar
  65. Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage,14(6), 1370–1386.CrossRefGoogle Scholar
  66. Wu, N., Chen, Y., Yang, J., & Li, F. (2017). Childhood obesity and academic performance: The role of working memory. Frontiers in Psychology,8, 611.  https://doi.org/10.3389/fpsyg.2017.00611.CrossRefPubMedPubMedCentralGoogle Scholar
  67. Xu, T., Yang, Z., Jiang, L., Xing, X.-X., & Zuo, X.-N. (2015). A connectome computation system for discovery science of brain. Science Bulletin,60(1), 86–95.CrossRefGoogle Scholar
  68. Yan, C. G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R. C., Di Martino, A., et al. (2013). A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage,76, 183–201.  https://doi.org/10.1016/j.neuroimage.2013.03.004.CrossRefPubMedPubMedCentralGoogle Scholar
  69. Zhang, S., Liu, H., Zhang, C., Wang, L., Li, N., Leng, J., et al. (2015). Maternal glucose during pregnancy and after delivery in women with gestational diabetes mellitus on overweight status of their children. BioMed Research International,2015, 543038.  https://doi.org/10.1155/2015/543038.CrossRefPubMedPubMedCentralGoogle Scholar
  70. Zheng, Z., Zhang, L., Li, S., Zhao, F., Wang, Y., Huang, L., et al. (2017). Association among obesity, overweight and autism spectrum disorder: A systematic review and meta-analysis. Scientific Reports,7(1), 11697.  https://doi.org/10.1038/s41598-017-12003-4.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Chanaka N. Kahathuduwa
    • 1
    • 2
    • 3
    Email author
  • Blake West
    • 1
  • Ann Mastergeorge
    • 1
    • 4
  1. 1.Department of Human Development and Family Studies, College of Human SciencesTexas Tech UniversityLubbockUSA
  2. 2.Department of Psychiatry, School of MedicineTexas Tech University Health Sciences CenterLubbock, TXUSA
  3. 3.Department of Laboratory Science and Primary Care, School of Health ProfessionsTexas Tech University Health Sciences CenterLubbockUSA
  4. 4.The Burkhart Center for Autism Education and ResearchTexas Tech UniversityLubbockUSA

Personalised recommendations