Clustering autism: Using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity

J. Ellegood, E. Anagnostou, B. A. Babineau, Jacqueline Crawley, L. Lin, M. Genestine, E. Dicicco-Bloom, J. K Y Lai, J. A. Foster, O. Peñagarikano, D. H. Geschwind, L. K. Pacey, D. R. Hampson, C. L. Laliberté, A. A. Mills, E. Tam, L. R. Osborne, M. Kouser, F. Espinosa-Becerra, Z. XuanC. M. Powell, A. Raznahan, D. M. Robins, N. Nakai, J. Nakatani, T. Takumi, M. C. Van Eede, T. M. Kerr, C. Muller, R. D. Blakely, J. Veenstra-Vander Weele, R. M. Henkelman, J. P. Lerch

Research output: Contribution to journalArticlepeer-review

129 Scopus citations

Abstract

Autism is a heritable disorder, with over 250 associated genes identified to date, yet no single gene accounts for >1-2% of cases. The clinical presentation, behavioural symptoms, imaging and histopathology findings are strikingly heterogeneous. A more complete understanding of autism can be obtained by examining multiple genetic or behavioural mouse models of autism using magnetic resonance imaging (MRI)-based neuroanatomical phenotyping. Twenty-six different mouse models were examined and the consistently found abnormal brain regions across models were parieto-temporal lobe, cerebellar cortex, frontal lobe, hypothalamus and striatum. These models separated into three distinct clusters, two of which can be linked to the under and over-connectivity found in autism. These clusters also identified previously unknown connections between Nrxn1α, En2 and Fmr1; Nlgn3, BTBR and Slc6A4; and also between X monosomy and Mecp2. With no single treatment for autism found, clustering autism using neuroanatomy and identifying these strong connections may prove to be a crucial step in predicting treatment response.

Original languageEnglish (US)
Pages (from-to)118-125
Number of pages8
JournalMolecular Psychiatry
Volume20
Issue number1
DOIs
StatePublished - Feb 5 2015

ASJC Scopus subject areas

  • Molecular Biology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience

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