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Why Autism Must be Taken Apart

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Abstract

Although accumulated evidence has demonstrated that autism is found with many varied brain dysfunctions, researchers have tried to find a single brain dysfunction that would provide neurobiological validity for autism. However, unitary models of autism brain dysfunction have not adequately addressed conflicting evidence, and efforts to find a single unifying brain dysfunction have led the field away from research to explore individual variation and micro-subgroups. Autism must be taken apart in order to find neurobiological treatment targets. Three research changes are needed. The belief that there is a single defining autism spectrum disorder brain dysfunction must be relinquished. The noise caused by the thorny brain-symptom inference problem must be reduced. Researchers must explore individual variation in brain measures within autism.

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References

  • Allely, C. S., Gillberg, C., & Wilson, P. (2013). Neurobiological abnormalities in the first few years of life in individuals later diagnosed with autistic spectrum disorder: A review of recent data. Behavioural Neurology. doi:10.3233/BEN-130350.

    Google Scholar 

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

    Google Scholar 

  • Aoki, Y., Abe, O., Nippashi, Y., & Yamasue, H. (2013). Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: A meta-analysis of diffusion tensor imaging tractography studies. Molecular Autism, 4(1), 25. doi:10.1.1186/2040-2392-4-25.

    Article  PubMed Central  PubMed  Google Scholar 

  • Blumberg, S. J., Bramlett, M. D., Kogan, M. D., Schieve, L. A., Jones, J. R., & Lu, M. C. (2013). Changes in prevalence of parent-reported autism spectrum disorder in school-aged US children: 2007 to 2011–2012. National health statistics reports, 65, 1–11. Hyattsville, MD: National Center for Health Statistics.

    Google Scholar 

  • Campbell, M. G., Kohane, I. S., & Kong, S. W. (2013). Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome. BMC Medical Genomics, 6(1), 34. doi:10.1186/1755-8794-6-34.

    Article  PubMed Central  PubMed  Google Scholar 

  • Chaste, P., Klei, L., Sanders, S. J., Murtha, M. T., Hus, V., Lowe, J. K., et al. (2013). Adjusting head circumference for covariates in autism: clinical correlates of a highly heritable continuous trait. Biological Psychiatry, 74(8), 576–584. doi:10.1016/j.biopsych.2013.04.018.

    Article  PubMed  Google Scholar 

  • Ciesielski, K. T., Harris, R. J., Hart, B. L., & Pabst, H. F. (1997). Cerebellar hypoplasia and frontal lobe cognitive deficits in disorders of early childhood. Neuropsychologia, 35(5), 643–655. doi:10.1016/S0028-3932(96)00119-4.

    Article  PubMed  Google Scholar 

  • Ciesielski, K. T., & Knight, J. E. (1994). Cerebellar abnormality in autism: a nonspecific effect of early brain damage? Acta Neurobiologiae Experimentalis, 54, 151–154.

    PubMed  Google Scholar 

  • Coleman, M., & Gillberg, C. (2012). The autisms. Oxford: Oxford University Press.

    Google Scholar 

  • Courchesne, E., Yeung-Courchesne, R., Hesselink, J. R., & Jernigan, T. L. (1988). Hypoplasia of cerebellar vermal lobules VI and VII in autism. New England Journal of Medicine, 318(21), 1349–1354.

    Article  PubMed  Google Scholar 

  • Cuthbert, B. N., & Insel, T. R. (2013). Toward the future of psychiatric diagnosis: the seven pillars of RDoC. BMC Medicine, 11(1), 126. doi:10.1186/1741-7015-11-126.

    Article  PubMed Central  PubMed  Google Scholar 

  • Delorme, R., Ey, E., Toro, R., Leboyer, M., Gillberg, C., & Bourgeron, T. (2013). Progress toward treatments for synaptic defects in autism. Nature Medicine, 19(6), 685–694. doi:10.1038/nm.3193.

    Article  PubMed  Google Scholar 

  • Di Martino, A., Yan, C. G., Li, Q., Denio, E., Castellanos, F. X., Alaerts, K., et al. (2013). The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Molecular Psychiatry,. doi:10.1038/mp.2013.78.

    PubMed  Google Scholar 

  • Dove, D., Warren, Z., McPheeters, M. L., Taylor, J. L., Sathe, N. A., & Van der Veenstra-Weele, J. (2012). Medications for adolescents and young adults with autism spectrum disorders: A systematic review. Pediatrics, 130(4), 717–726. doi:10.1542/peds.2012-0683.

    Article  PubMed  Google Scholar 

  • Doyle, C. A., & McDougle, C. J. (2012). Pharmacologic treatments for the behavioral symptoms associated with autism spectrum disorders across the lifespan. Dialogues in Clinical Neuroscience, 14(3), 263–279.

    PubMed Central  PubMed  Google Scholar 

  • Fatemi, S. H. (2013). Cerebellum and autism. Cerebellum, 12, 778–779. doi:10.1007/s12311-013-0484-9.

    Article  PubMed  Google Scholar 

  • Gillberg, G. (2010). The ESSENCE in child psychiatry: Early symptomatic syndromes eliciting neurodevelopmental clinical examinations. Research in Developmental Disabilities, 31(6), 1543–1555. doi:10.1016/j.ridd.2010.06.002.

    Article  PubMed  Google Scholar 

  • Gordon, I., Van der Wyk, B. C., Bennett, R. H., Cordeaux, C., Lucas, M. V., Eilbott, J. A., & Pelphrey, K. A. (2013). Oxytocin enhances brain function in children with autism. Proceedings of the National Academy of Sciences, 201312857. doi:10.1073/pnas.1312857110.

  • Horder, J., Lavender, T., Mendez, M. A., O’Gorman, R., Daly, E., Craig, M. C., et al. (2013). Reduced subcortical glutamate/glutamine in adults with autism spectrum disorders: A 1HMRS study. Translational psychiatry, 3(7), e279. doi:10.1038/tp.2013.53.

    Article  PubMed Central  PubMed  Google Scholar 

  • Insel, T. (2013). Transforming diagnosis, Director’s blog, April 29 2013, National Institutes of Mental Health. Available from: http://www.nimh.nih.gov/about/director/2013/transforming-diagnosis.shtml.

  • Jonas, R. K., Montojo, C. A., & Bearden, C. E. (2013). The 22q11.2 deletion syndrome as a window into complex neuropsychiatric disorders over the lifespan. Biological Psychiatry,. doi:10.1016/j.biopsych.2013.07.019.

    PubMed  Google Scholar 

  • Jones, W., & Klin, A. (2013). Attention to eyes is present but in decline in 2–6-month-old infants later diagnosed with autism. Nature,. doi:10.1038/nature12715.

    Google Scholar 

  • Kell, A. J., Koldewyn, K., & Kanwisher, N. G. (2013). The functional organization of the ventral visual pathway in adults with autism. Journal of Vision, 13(9), 832. doi:10.1167/13.9.832.

    Article  Google Scholar 

  • Kupfer, D. J., & Regier, D. A. (2011). Neuroscience, clinical evidence, and the future of psychiatric classification in DSM-5. American Journal of Psychiatry, 168(7), 672–674. doi:10.1176/appi.ajp.2011.11020219.

    Article  PubMed  Google Scholar 

  • Lai, M.-C., Lombardo, M. V., Chakrabarti, B., & Baron-Cohen, S. (2013). Subgrouping the autism ‘‘spectrum’’: Reflections on DSM-5. PLoS Biology, 11(4), e1001544. doi:10.1371/journal.pbio.1001544.

    Article  PubMed Central  PubMed  Google Scholar 

  • Lee, M., Martin-Ruiz, C., Graham, A., Jaros, E., Perry, R., Iversen, P., et al. (2002). Nicotinic receptor abnormalities in the cerebellar cortex in autism. Brain, 125(7), 1483–1495. doi:10.1093/brain/awf160.

    Article  PubMed  Google Scholar 

  • Levitt, J. G., O’Neill, J., & Alger, J. R. (2013). Magnetic resonance spectroscopy studies of autistic spectrum disorders. In S. Blüml & A. Panigrahy (Eds.), MR spectroscopy of pediatric brain disorders (pp. 213–227). New York: Springer.

    Chapter  Google Scholar 

  • Licinio, J., & Wong, M.-L. (2013). A novel conceptual framework for psychiatry: Vertically and horizontally integrated approaches to redundancy and pleiotropism that co-exist with a classification of symptom clusters based on DSM-5. Molecular Psychiatry, 18, 846–848. doi:10.1038/mp.2013.90.

    Article  PubMed  Google Scholar 

  • Marcotte, L., Aronica, E., Baybis, M., & Crino, P. B. (2012). Cytoarchitectural alterations are widespread in cerebral cortex in tuberous sclerosis complex. Acta Neuropathologica, 123(5), 685–693. doi:10.1007/s00401-012-0950-3.

    Article  PubMed  Google Scholar 

  • Moreno-De-Luca, A., Myers, S. M., Challman, T. D., Moreno-De-Luca, D., Evans, D. W., & Ledbetter, D. H. (2013). Developmental brain dysfunction: Revival and expansion of old concepts based on new genetic evidence. The Lancet Neurology, 12(4), 406–414. doi:10.1016/S1474-4422(13)70011-5.

    Article  Google Scholar 

  • Murdoch, J. D., & State, M. W. (2013). Recent developments in the genetics of autism spectrum disorders. Current Opinion in Genetics and Development, 23(3), 310–315. doi:10.1016/j.gde.2013.02.003.

    Article  PubMed  Google Scholar 

  • Peters, J. M., Taquet, M., Vega, C., Jeste, S. S., Sanchez Fernandez, I., Tan, J., et al. (2013). Brain functional networks in syndromic and non-syndromic autism: A graph theoretical study of EEG connectivity. BMC Medicine, 11(1), 54. doi:10.1186/1741-7015-11-54.

    Article  PubMed Central  PubMed  Google Scholar 

  • Philip, R., Dauvermann, M. R., Whalley, H. C., Baynham, K., Lawrie, S. M., & Stanfield, A. C. (2012). A systematic review and meta-analysis of the fMRI investigation of autism spectrum disorders. Neuroscience and Biobehavioral Reviews, 36(2), 901–942. doi:10.1016/j.neubiorev.2011.10.008.

    Article  PubMed  Google Scholar 

  • Pina-Camacho, L., Villero, S., Fraguas, D., Joost Boada, L., Janssen, J., Navas-Sánchez, F. J., et al. (2012). Autism spectrum disorder: Does neuroimaging support the DSM-5 proposal for a symptom dyad? A systematic review of functional magnetic resonance imaging and diffusion tensor imaging studies. Journal of Autism and Developmental Disorders, 42(7), 1326–1341. doi:10.1007/s10803-011-1360-4.

    Article  PubMed  Google Scholar 

  • Raznahan, A., Wallace, G. L., Antezana, L., Greenstein, D., Lenroot, R., Thurm, A., et al. (2013). Compared to what? Early brain overgrowth in autism and the perils of population norms. Biological Psychiatry, 74(8), 563–575. doi:10.1016/j.biopsych.2013.03.022.

    Article  PubMed  Google Scholar 

  • Redcay, E., Moran, J. M., Mavros, P. L., Tager-Flusberg, H., Gabrieli, J. D., & Whitfield-Gabrieli, S. (2013). Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder. Frontiers in Human Neuroscience, 7(573), 2013. doi:10.3389/fnhum.2013.00573.

    Google Scholar 

  • Roullet, F. I., Lai, J. K., & Foster, J. A. (2013). In utero exposure to valproic acid and autism: A current review of clinical and animal studies. Neurotoxicology and Teratology, 36, 47–56. doi:10.1016/j.ntt.2013.01.004.

    Article  PubMed  Google Scholar 

  • Saygin, A. P., Cook, J., & Blakemore, S. J. (2010). Unaffected perceptual thresholds for biological and non-biological form-from-motion perception in autism spectrum conditions. PloS One, 5(10), e13491. doi:10.1371/journal.pone.0013491.

  • Schumann, C. M., & Nordahl, C. W. (2011). Bridging the gap between MRI and postmortem research in autism. Brain Research, 1380, 175–186. doi:10.1016/j.brainres.2010.09.061.

    Article  PubMed Central  PubMed  Google Scholar 

  • Shen, M. D., Nordahl, C. W., Young, G. S., Wootton-Gorges, S. L., Lee, A., Liston, S. E., et al. (2013). Early brain enlargement and elevated extra-axial fluid in infants who develop autism spectrum disorder. Brain, 136(9), 2825–2835. doi:10.1093/brain/awt166.

    Article  PubMed  Google Scholar 

  • Silver, W. G., & Rapin, I. (2012). Neurobiological basis of autism. Pediatric Clinics of North America, 59(1), 45–61. doi:10.1016/j.pcl.2011.10.010.

    Article  PubMed  Google Scholar 

  • Skudlarski, P., Schretlen, D. J., Thaker, G. K., Stevens, M. C., Keshavan, M. S., Sweeney, J. A., et al. (2013). Diffusion tensor imaging white matter endophenotypes in patients with schizophrenia or psychotic bipolar disorder and their relatives. American Journal of Psychiatry, 170(8), 886–898. doi:10.1176/appi.ajp.2013.12111448.

    Article  PubMed  Google Scholar 

  • Stigler, K. A., McDonald, B. C., Anand, A., Saykin, A. J., & McDougle, C. J. (2011). Structural and functional magnetic resonance imaging of autism spectrum disorders. Brain Research, 1380, 146–161. doi:10.1016/j.brainres.2010.11.076.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tsai, P. T., Chu, Y., Greene-Colozzi, E., Sadowski, A. R., Leech, J. M., Steinberg, J., et al. (2012). Autistic-like behaviour and cerebellar dysfunction in Purkinje cell Tsc1 mutant mice. Nature, 488(7413), 647–651. doi:10.1038/nature11310.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tye, C., & Bolton, P. (2013). Neural connectivity abnormalities in autism: Insights from the tuberous sclerosis model. BMC Medicine, 11, 55. doi:10.1186/1741-7015-11-55.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tyszka, J. M., Kennedy, D. P., Paul, L. K., & Adolphs, R. (2013). Largely typical patterns of resting-state functional connectivity in high-functioning adults with autism. Cerebral Cortex,. doi:10.1093/cercor/bht040.

    PubMed  Google Scholar 

  • Unwin, L. M., Maybery, M. T., Wray, J. A., & Whitehouse, A. J. (2013). A “bottom-up” approach to aetiological research in autism spectrum disorders. Frontiers in human neuroscience, 7(606), 2013. doi:10.3389/fnhum.2013.00606.

    Google Scholar 

  • Vasa, R. A., Ranta, M., Huisman, T. A., Pinto, P. S., Tillman, R. M., & Mostofsky, S. H. (2012). Normal rates of neuroradiological findings in children with high functioning autism. Journal of Autism and Developmental Disorders, 42(8), 1662–1670. doi:10.1007/s10803-001-1407-6.

    Article  PubMed Central  PubMed  Google Scholar 

  • Washington, S. D., Gordon, E. M., Brar, J., Warburton, S., Sawyer, A. T., Wolfe, A., et al. (2013). Dysmaturation of the default mode network in autism. Human Brain Mapping,. doi:10.1002/hbm.22252.

    PubMed Central  PubMed  Google Scholar 

  • Waterhouse, L. (2008). Autism overflows: Increasing prevalence and proliferating theories. Neuropsychology Review, 18(4), 273–286. doi:10.1007/s11065-008-9074-x.

    Article  PubMed  Google Scholar 

  • Waterhouse, L. (2013). Rethinking autism: Variation and complexity. Waltham: Academic Press.

    Google Scholar 

  • Weisenfeld, N. I., Peters, J. M., Tsai, P. T., Prabhu, S. P., Dies, K. A., Sahin, M., et al. (2013). A magnetic resonance imaging study of cerebellar volume in tuberous sclerosis complex. Pediatric Neurology, 48(2), 105–110. doi:10.1016/j.pediatrneurol.2012.10.011.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ziats, M. N., & Rennert, O. M. (2013). The cerebellum in autism: Pathogenic or an anatomical beacon? Cerebellum, 12(5), 776–777. doi:10.1007/s12311-013-0483-x.

    Article  PubMed  Google Scholar 

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Waterhouse, L., Gillberg, C. Why Autism Must be Taken Apart. J Autism Dev Disord 44, 1788–1792 (2014). https://doi.org/10.1007/s10803-013-2030-5

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