Transcriptomic analysis of autistic brain reveals convergent molecular pathology

Irina Voineagu, Xinchen Wang, Patrick Johnston, Jennifer K. Lowe, Yuan Tian, Steve Horvath, Jonathan Mill, Rita M. Cantor, Benjamin J. Blencowe and Daniel H. Geschwind ()
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Irina Voineagu: Program in Neurogenetics and Neurobehavioral Genetics, David Geffen School of Medicine, University of California
Xinchen Wang: Donnelly Centre, University of Toronto, Toronto, Ontario M5G 1L6, Canada
Patrick Johnston: Institute of Psychiatry, King’s College London, London SE5 8AF, UK
Jennifer K. Lowe: Program in Neurogenetics and Neurobehavioral Genetics, David Geffen School of Medicine, University of California
Yuan Tian: Program in Neurogenetics and Neurobehavioral Genetics, David Geffen School of Medicine, University of California
Steve Horvath: University of California Los Angeles
Jonathan Mill: Institute of Psychiatry, King’s College London, London SE5 8AF, UK
Rita M. Cantor: University of California Los Angeles
Benjamin J. Blencowe: Donnelly Centre, University of Toronto, Toronto, Ontario M5G 1L6, Canada
Daniel H. Geschwind: Program in Neurogenetics and Neurobehavioral Genetics, David Geffen School of Medicine, University of California

Nature, 2011, vol. 474, issue 7351, 380-384

Abstract: A shared aetiology for autism? Despite high heritability, autism is genetically very heterogeneous. This raises the question of whether there are many different pathologies presenting as autistic spectrum disorder (ASD), or whether the myriad genetic causes converge on a few biological pathways affected in most individuals, which could be therapeutically targeted. A study using transcriptome and gene co-expression network analysis suggests that the latter, convergent model is the case. The gene expression patterns that typically distinguish frontal and temporal cortex are much less pronounced in the ASD brain, and specific splicing abnormalities and modules of co-expressed genes associated with autism are enriched for previously identified genetic association signals. This points to transcriptional and splicing dysregulation as underlying mechanisms of neuronal dysfunction in this disorder.

Date: 2011
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DOI: 10.1038/nature10110

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