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Brain Imaging and Behavior

, Volume 12, Issue 2, pp 532–546 | Cite as

Positron emission tomography assessment of cerebral glucose metabolic rates in autism spectrum disorder and schizophrenia

  • Serge A. Mitelman
  • Marie-Cecile Bralet
  • M. Mehmet Haznedar
  • Eric Hollander
  • Lina Shihabuddin
  • Erin A. Hazlett
  • Monte S. Buchsbaum
Original Research

Abstract

Several models have been proposed to account for observed overlaps in clinical features and genetic predisposition between schizophrenia and autism spectrum disorder. This study assessed similarities and differences in topological patterns and vectors of glucose metabolism in both disorders in reference to these models. Co-registered 18fluorodeoxyglucose PET and MRI scans were obtained in 41 schizophrenia, 25 ASD, and 55 healthy control subjects. AFNI was used to map cortical and subcortical regions of interest. Metabolic rates were compared between three diagnostic groups using univariate and multivariate repeated-measures ANOVA. Compared to controls, metabolic rates in schizophrenia subjects were decreased in the frontal lobe, anterior cingulate, superior temporal gyrus, amygdala and medial thalamic nuclei; rates were increased in the occipital cortex, hippocampus, basal ganglia and lateral thalamic nuclei. In ASD subjects metabolic rates were decreased in the parietal lobe, frontal premotor and eye-fields areas, and amygdala; rates were increased in the posterior cingulate, occipital cortex, hippocampus and basal ganglia. In relation to controls, subjects with ASD and schizophrenia showed opposite changes in metabolic rates in the primary motor and somatosensory cortex, anterior cingulate and hypothalamus; similar changes were found in prefrontal and occipital cortices, inferior parietal lobule, amygdala, hippocampus, and basal ganglia. Schizophrenia and ASD appear to be associated with a similar pattern of metabolic abnormalities in the social brain. Divergent maladaptive trade-offs, as postulated by the diametrical hypothesis of their evolutionary relationship, may involve a more circumscribed set of anterior cingulate, motor and somatosensory regions and the specific cognitive functions they subserve.

Keywords

Autism spectrum disorder Schizophrenia Positron emission tomography Fluorodeoxyglucose Social brain Diametrical diseases 

Notes

Grant support

This work was partly supported by NARSAD Young Investigator Award and NIMH MH 077146 grant to Serge A. Mitelman and by NIMH grants P50 MH 66392–01, MH 60023, and MH 56489 to Monte S. Buchsbaum.

Compliance and ethical standards

All procedures performed in this study were in accordance with the ethical standards of the Mount Sinai institutional research committee, as well as with the 1964 Helsinki declaration and its later amendments. The project was approved by the institutional review board of The Icahn School of Medicine at Mount Sinai.

Conflict of interest

Serge A. Mitelman declares that he has no conflict of interest to report.

Marie-Cecile Bralet declares that she has no conflict of interest to report.

M. Mehmet Haznedar declares that he has no conflict of interest to report.

Eric Hollander has received consultation fees from Transceit, Neuropharm, and Nastech.

Lina Shihabuddin declares that she has no conflict of interest to report.

Erin A. Hazlett declares that she has no conflict of interest to report.

Monte S. Buchsbaum declares that he has no conflict of interest to report.

Informed consent

Informed consent was obtained from all individual participants in the study.

References

  1. Abu-Akel, A. M., Apperly, I. A., Wood, S. J., & Hansen, P. C. (2016). Autism and psychosis expressions diametrically modulate the right temporoparietal junction. Social Neuroscience, 3, 1–13.Google Scholar
  2. Adolphs, R. (2009). The social brain: neural basis of social knowledge. Annual Review of Psychology, 60, 693–716.CrossRefPubMedPubMedCentralGoogle Scholar
  3. Aoki, Y., Cortese, S., & Tansella, M. (2015). Neural bases of atypical emotional face processing in autism: a meta-analysis of fMRI studies. World Journal of Biological Psychiatry, 16(5), 291–300.CrossRefPubMedGoogle Scholar
  4. Apps, M. A., Rushworth, M. F., & Chang, S. W. (2016). The anterior cingulate gyrus and social cognition: tracking the motivation of others. Neuron, 90(4), 692–707.CrossRefPubMedPubMedCentralGoogle Scholar
  5. Báez-Mendoza, R., & Schultz, W. (2013). The role of the striatum in social behavior. Frontiers of Neuroscience, 7, 233.CrossRefGoogle Scholar
  6. Baron-Cohen, S. (2009). Autism: the empathizing-systemizing (E-S) theory. Annals of New York Academy of Sciences, 1156, 68–80.CrossRefGoogle Scholar
  7. Baron-Cohen, S. (2010). Empathizing, systemizing, and the extreme male brain theory of autism. Progress in Brain Research, 185, 167–175.CrossRefGoogle Scholar
  8. Baron-Cohen, S., Knickmeyer, R. C., & Belmonte, M. K. (2005). Sex differences in the brain: implications for explaining autism. Science, 310, 819–823.CrossRefPubMedGoogle Scholar
  9. Bertone, A., Mottron, L., & Faubert, J. (2004). Autism and schizophrenia: similar perceptual consequence, different neurobiological etiology? Behavioral and Brain Sciences, 27(4), 592–593.CrossRefGoogle Scholar
  10. Bralet, M.-C., Buchsbaum, M. S., DeCastro, A., Hazlett, E. A., Haznedar, M. M., Shihabuddin, L., & Mitelman, S. A. (2016). FDG-PET scans in patients with Kraepelinian and non-Kraepelinian schizophrenia. European Archives of Psychiatry and Clinical Neurosciences, 266(6), 481–494.CrossRefGoogle Scholar
  11. Brosnan, M., Lewton, M., & Ashwin, C. (2016). Reasoning on the autism spectrum: a dual process theory account. Journal of Autism and Developmental Disorders, 46, 2115–2125.CrossRefPubMedPubMedCentralGoogle Scholar
  12. Buchsbaum, M. S., & Hazlett, E. A. (1998). Positron emission tomography studies of abnormal glucose metabolism in schizophrenia. Schizophrenia Bulletin, 24(3), 343–364.CrossRefPubMedGoogle Scholar
  13. Ciaramidaro, A., Bölte, S., Schlitt, S., Hainz, D., Poustka, F., Weber, B., Bara, B. G., Freitag, C., & Walter, H. (2015). Schizophrenia and autism as contrasting minds: neural evidence for the hypo-hyper-intentionality hypothesis. Schizophrenia Bulletin, 41(1), 171–179.CrossRefPubMedGoogle Scholar
  14. Cox, R. W. (1996). AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages. Computers and Biomedical Research, 29(3), 162–173.CrossRefPubMedGoogle Scholar
  15. Crespi, B. J., & Badcock, C. (2008). Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences, 31(3), 241–161.PubMedGoogle Scholar
  16. Crespi, B. J., & Go, M. C. (2015). Diametrical diseases reflect evolutionary-genetic tradeoffs: evidence from psychiatry, neurology, rheumatology, oncology and immunology. Evolution, Medicine and Public Health, 2015(1), 216–253.CrossRefGoogle Scholar
  17. Crespi, B., Stead, P., & Elliot, M. (2010). Comparative genomics of autism and schizophrenia. Proceedings of the National Academy of Sciences of the United States of America, 107(Suppl 1), 1736–1741.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Davey, C. G., Pujol, J., & Harrison, B. J. (2016). Mapping the self in the brain’s default mode network. NeuroImage, 132, 390–397.CrossRefPubMedGoogle Scholar
  19. Delis, D., Kramer, J., Kaplan, E., & Ober, B. (1987). The California verbal learning test. New York: Psychological Corporation.Google Scholar
  20. Dichter, G. S. (2012). Functional magnetic resonance imaging of autism spectrum disorders. Dialogues in Clinical Neuroscience, 14(3), 319–351.PubMedPubMedCentralGoogle Scholar
  21. Elsabbagh, M., & Johnson, M. H. (2016). Autism and the social brain: the first-year puzzle. Biological Psychiatry, 80(2), 94–99.CrossRefPubMedGoogle Scholar
  22. Frith, C. D. (2007). The social brain? Philosophical Transactions of the Royal Society of London, Series B Biological Sciences, 362(1480), 671–678.CrossRefGoogle Scholar
  23. Glezerman, T.B. (2013). Autism and the brain: neurophenomenological interpretation. New York: Springer, pp. 194 and 228–231.Google Scholar
  24. Harrison, B. J., Yücel, M., Pujol, J., & Pantelis, C. (2007). Task-induced deactivation of midline cortical regions in schizophrenia assessed with fMRI. Schizophrenia Research, 91(1–3), 82–86.CrossRefPubMedGoogle Scholar
  25. Hartwright, C. E., Apperly, I. A., & Hansen, P. C. (2014). Representation, control, or reasoning? Distinct functions for theory of mind within the medial prefrontal cortex. Journal of Cognitive Neuroscience, 26(4), 683–698.CrossRefPubMedGoogle Scholar
  26. Hazlett, E. A., Buchsbaum, M. S., Hsieh, P., Haznedar, M. M., Platholi, J., LiCalzi, E. M., Cartwright, C., & Hollander, E. (2004a). Regional glucose metabolism within cortical Brodmann areas in healthy individuals and autistic patients. Neuropsychobiology, 49(3), 115–125.CrossRefPubMedGoogle Scholar
  27. Hazlett, E. A., Buchsbaum, M. S., Kemether, E., Bloom, R., Platholi, J., Brickman, A. M., Shihabuddin, L., Tang, C., & Byne, W. (2004b). Abnormal glucose metabolism in the mediodorsal nucleus of the thalamus in schizophrenia. American Journal of Psychiatry, 161(2), 305–314.CrossRefPubMedGoogle Scholar
  28. Hazlett, E. A., Byne, W., Brickman, A. M., Mitsis, E. M., Newmark, R., Haznedar, M. M., Knatz, D. T., Chen, A. D., & Buchsbaum, M. S. (2010). Effects of sex and normal aging on regional brain activation during verbal memory performance. Neurobiology of Aging, 31(5), 826–838.CrossRefPubMedGoogle Scholar
  29. Haznedar, M. M., Buchsbaum, M. S., Hazlett, E. A., LiCalzi, E. M., Cartwright, C., & Hollander, E. (2006). Volumetric analysis and three-dimensional glucose metabolic mapping of the striatum and thalamus in patients with autism spectrum disorders. American Journal of Psychiatry, 163(7), 1252–1263.CrossRefPubMedGoogle Scholar
  30. Hommer, R. E., & Swedo, S. E. (2015). Schizophrenia and autism – related disorders. Schizophrenia Bulletin, 41(2), 313–314.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Horwitz, B., Rumsey, J. M., Grady, C. L., & Rapoport, S. I. (1988). The cerebral metabolic landscape in autism. Intercorrelations of regional glucose utilization. Archives of Neurology, 45(7), 749–755.CrossRefPubMedGoogle Scholar
  32. Katz, J., d’Albis, M.-A., Boisgontier, J., Poupon, C., Mangin, J.-F., Guevara, P., Duclap, D., Hamdani, N., Petit, J., Monnet, D., Le Corvoisier, P., Leboyer, M., Delorme, R., & Houenou, J. (2016). Similar white matter but opposite grey matter changes in schizophrenia and high-functioning autism. Acta Psychiatrica Scandinavica, 134(1), 31–39.CrossRefPubMedGoogle Scholar
  33. Keefe, R. S., Mohs, R. C., Losonszy, M. F., Davidson, M., Silverman, J. M., Kendler, K. S., Horvath, T. B., Nora, R., & Davis, K. L. (1987). Characteristics of very poor outcome schizophrenia. American Journal of Psychiatry, 144, 889–895.CrossRefPubMedGoogle Scholar
  34. Lee, S. H., Ripke, S., Neale, B. M., Faraone, S. V., et al. (2013). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45(9), 984–994.CrossRefPubMedGoogle Scholar
  35. Leech, R., & Sharp, D. J. (2014). The role of the posterior cingulate cortex in cognition and disease. Brain, 137(1), 12–32.CrossRefPubMedGoogle Scholar
  36. Lehrer, D. S., Christian, B. T., Mantil, J., Murray, A. C., Buchsbaum, B. R., Oakes, T. R., Byne, W., Kemether, E. M., & Buchsbaum, M. S. (2005). Thalamic and prefrontal FDG uptake in never medicated patients with schizophrenia. American Journal of Psychiatry, 162(5), 931–938.CrossRefPubMedGoogle Scholar
  37. Mitelman, S. A., Bralet, M.-C., Haznedar, M. M., Hollander, E., Shihabuddin, L., Hazlett, E. A., & Buchsbaum, M. S. (2016). Diametrical relationship between gray and white matter volumes in autism spectrum disorder and schizophrenia. Brain Imaging and Behavior. doi: 10.1007/s11682-016-9648-9.Google Scholar
  38. Mitelman, S. A., Byne, W., Kemether, E. M., Hazlett, E. A., & Buchsbaum, M. S. (2005). Metabolic disconnection between the mediodorsal nucleus of the thalamus and cortical Brodmann’s areas of the left hemisphere in schizophrenia. American Journal of Psychiatry, 162(9), 1733–1735.CrossRefPubMedGoogle Scholar
  39. Otti, A., Wohlschlaeger, A. M., & Noll-Hussong, M. (2015). Is the medial prefrontal cortex necessary for theory of mind? PloS One, 10(8), e0135912.CrossRefPubMedPubMedCentralGoogle Scholar
  40. Pagani, M., Manouilenko, I., Stone-Elander, S., Odh, R., Salmaso, D., Hatherly, R., Brolin, F., Jacobsson, H., Larsson, S. A., & Bejerot, S. (2012). Brief report: alterations in cerebral blood flow as assessed by PET/CT in adults with autism spectrum disorder with normal IQ. Journal of Autism and Developmental Disorders, 42(2), 313–318.CrossRefPubMedGoogle Scholar
  41. Pfefferbaum, A., Chanraud, S., Pitel, A. L., Müller-Oehring, E., Shankaranarayanan, A., Alsop, D. C., Rohlfing, T., & Sullivan, E. V. (2011). Cerebral blood flow in posterior cortical nodes of the default mode network decreases with task engagement but remains higher in most brain regions. Cerebral Cortex, 21(1), 233–244.CrossRefPubMedGoogle Scholar
  42. Piggott, M. A., Marshall, E. F., Thomas, N., Lloyd, S., Court, J. A., Jaros, E., Costa, D., Perry, R. H., & Perry, E. K. (1999). Dopaminergic activities in the human striatum: rostrocaudal gradients of uptake sites and of D1 and D2 but not of D3 receptor binding or dopamine. Neuroscience, 90(2), 433–445.CrossRefPubMedGoogle Scholar
  43. Poeppl, T. B., Langguth, B., Rupprecht, R., Safron, A., Bzdok, D., Laird, A. R., & Eickhoff, S. B. (2016). The neural basis of sex differences in sexual behavior: a quantitative meta-analysis. Frontiers in Neuroendocrinology, 3022(16), 28–43.CrossRefGoogle Scholar
  44. Rapoport, J. L., Giedd, J. N., & Gogtay, N. (2012). Neurodevelopmental model of schizophrenia: update 2012. Molecular Psychiatry, 17(12), 1228–1238.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Schöll, M., Damián, A., & Engler, H. (2014). Fluorodeoxyglucose PET in neurology and psychiatry. PET Clinics, 9(4), 371–390.CrossRefPubMedGoogle Scholar
  46. Siegel Jr., B. V., Asarnow, R., Tanguay, P., Call, J. D., Abel, L., Ho, A., Lott, I., & Buchsbaum, M. S. (1992). Regional cerebral glucose metabolism and attention in adults with a history of childhood autism. Journal of Neuropsychiatry and Clinical Neurosciences, 4(4), 406–414.CrossRefPubMedGoogle Scholar
  47. Siegel Jr., B. V., Nuechterlein, K. F., Abel, L., Wu, J. C., & Buchsbaum, M. S. (1995). Glucose metabolic correlates of continuous performance test performance in adults with a history of infantile autism, schizophrenia, and controls. Schizophrenia Research, 17(1), 85–94.CrossRefPubMedGoogle Scholar
  48. Stevenson, J. L., & Gernsbacher, M. A. (2013). Abstract spatial reasoning as an autistic strength. PloS One, 8(3), e59329.CrossRefPubMedPubMedCentralGoogle Scholar
  49. Stoléru, S., Fonteille, V., Cornélis, C., Joyal, C., & Moulier, V. (2012). Functional neuroimaging studies of sexual arousal and orgasm in healthy men and women: a review and meta-analysis. Neuroscience and Behavioral Reviews, 36, 1481–1509.CrossRefGoogle Scholar
  50. Tamminga, C. A., Stan, A. D., & Wagner, A. D. (2010). The hippocampal formation in schizophrenia. American Journal of Psychiatry, 167(10), 1178–1193.CrossRefPubMedGoogle Scholar
  51. van Overwalle, F. (2011). A dissociation between social mentalizing and general reasoning. NeuroImage, 54(2), 1589–1599.CrossRefPubMedGoogle Scholar
  52. Whitfield-Gabrieli, S., Thermenos, H. W., Milanovic, S., Tsuang, M. T., Faraone, S. V., McCarley, R. W., Shenton, M. E., Green, A. I., Nieto-Castanon, A., LaViolette, P., Wojcik, J., Gabrieli, J. D., & Seidman, L. J. (2009). Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proceedings of the National Academy of Sciences of the United States of America, 106(11), 4572.CrossRefGoogle Scholar
  53. Woods, R. P., Mazziotta, J. C., & Cherry, S. R. (1993). MRI-PET registration with automated algorithm. Journal of Computer Assisted Tomography, 17, 536–546.CrossRefPubMedGoogle Scholar
  54. Yahata, N., Morimoto, J., Hashimoto, R., Lisi, G., Shibata, K., Kawakubo, Y., Kuroda, M., Yamada, T., Megumi, F., Imamizu, H., Nañez Sr., J. E., Takahashi, H., Okamoto, Y., Kasai, K., Kato, N., Sasaki, Y., Wanatabe, T., & Kawato, M. (2016). A small number of abnormal brain connections predicts adult autism spectrum disorder. Nature Communications, 14(7), 11254.CrossRefGoogle Scholar
  55. Zürcher, N. R., Bhanot, A., McDougle, C. J., & Hooker, J. M. (2015). A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: current state and future research opportunities. Neuroscience and Biobehavioral Reviews, 52, 56–73.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Serge A. Mitelman
    • 1
    • 2
  • Marie-Cecile Bralet
    • 3
    • 4
    • 5
  • M. Mehmet Haznedar
    • 1
    • 6
  • Eric Hollander
    • 7
  • Lina Shihabuddin
    • 1
  • Erin A. Hazlett
    • 1
    • 8
  • Monte S. Buchsbaum
    • 9
  1. 1.Departments of Psychiatry and NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkUSA
  2. 2.Department of Psychiatry, Division of Child and Adolescent PsychiatryElmhurst Hospital CenterElmhurstUSA
  3. 3.Crisalid Unit (FJ5), CHI Clermont de l’OiseClermontFrance
  4. 4.Inserm Unit U669, Maison de SolennParisFrance
  5. 5.GDR 3557 Recherche PsychiatrieParisFrance
  6. 6.Outpatient Psychiatry Care Center, James J. Peters VA Medical CenterBronxUSA
  7. 7.Autism and Obsessive-Compulsive Spectrum Program, Anxiety and Depression Program, Department of Psychiatry and Behavioral ScienceAlbert Einstein College of Medicine and Montefiore Medical CenterBronxUSA
  8. 8.Research and Development and VISN 2 Mental Illness Research, Education, and Clinical CenterJames J. Peters VA Medical CenterBronxUSA
  9. 9.Departments of Psychiatry and RadiologyUniversity of California, San Diego School of Medicine, NeuroPET CenterSan DiegoUSA

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