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Expression Profiling of Autism Candidate Genes during Human Brain Development Implicates Central Immune Signaling Pathways

Overview of attention for article published in PLOS ONE, September 2011
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Title
Expression Profiling of Autism Candidate Genes during Human Brain Development Implicates Central Immune Signaling Pathways
Published in
PLOS ONE, September 2011
DOI 10.1371/journal.pone.0024691
Pubmed ID
Authors

Mark N. Ziats, Owen M. Rennert

Abstract

The Autism Spectrum Disorders (ASD) represent a clinically heterogeneous set of conditions with strong hereditary components. Despite substantial efforts to uncover the genetic basis of ASD, the genomic etiology appears complex and a clear understanding of the molecular mechanisms underlying Autism remains elusive. We hypothesized that focusing gene interaction networks on ASD-implicated genes that are highly expressed in the developing brain may reveal core mechanisms that are otherwise obscured by the genomic heterogeneity of the disorder. Here we report an in silico study of the gene expression profile from ASD-implicated genes in the unaffected developing human brain. By implementing a biologically relevant approach, we identified a subset of highly expressed ASD-candidate genes from which interactome networks were derived. Strikingly, immune signaling through NFκB, Tnf, and Jnk was central to ASD networks at multiple levels of our analysis, and cell-type specific expression suggested glia--in addition to neurons--deserve consideration. This work provides integrated genomic evidence that ASD-implicated genes may converge on central cytokine signaling pathways.

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The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
India 1 <1%
Portugal 1 <1%
Iceland 1 <1%
United Kingdom 1 <1%
Unknown 123 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 27%
Researcher 17 13%
Student > Bachelor 12 9%
Student > Master 12 9%
Student > Doctoral Student 10 8%
Other 27 21%
Unknown 18 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 38%
Medicine and Dentistry 19 15%
Neuroscience 15 11%
Biochemistry, Genetics and Molecular Biology 13 10%
Psychology 6 5%
Other 6 5%
Unknown 22 17%