Our current understanding of autism spectrum disorders (ASD) delineates a highly heritable, yet etiologically heterogeneous disease. Forward genetic approaches to find disease associated mutations or common variation have been successful and continue to offer considerable power. Yet, given the accumulating evidence for very significant heterogeneity and environmental influences, complementary approaches to classic forward genetics become necessary. Genetic polymorphism and mutation data to date have identified dozens of causal or contributory variants, yet our preliminary data from autism brain suggest that common molecular pathways are involved in a significant subset of cases. This convergence at the tissue level suggests that other mechanisms, specifically epigenetic changes, combined with genetic background, are contributing to such final common pathways. We propose to further test this hypothesis by taking a comprehensive and integrative genome-wide approach to assessing brain gene-expression, miRNA levels and the related, causal epigenetic mechanisms in ASD etiology. The work proposed here, which brings together three principal investigators with a publication track record and clear expertise in all of the methods and approaches necessary, comprises a unique international collaborative group capable of performing this work using state of the art techniques. We will perform RNA-seq analyses of four cerebral cortical regions and cerebellum from ASD cases and controls, to assess mRNA, miRNA, and splicing isoform regulation. In parallel, we will identify key differences in chromatin state and DNA methylation across multiple brain regions in the same ASD and control individuals used in the expression analyses using ChIP-Seq and MeDIP . We will thus assess the mechanisms by which changes in DNA methylation, histone modification, and DNA sequence contribute to the observed differences in gene expression, and we will explore the hypothesis that epigenetic processes mediate susceptibility for ASD via long-term changes in transcriptional regulation. This work, which represents an unprecedented effort to unify these often disparate data (usually produced without integration in mind), will delineate potential shared molecular pathways in ASD and the underlying mechanism of these differences at the level of miRNA, the chromatin regulatory apparatus, and DNA methylation. In addition, these data will be made available to the community in a web-based format to be of maximum utility.

Public Health Relevance

Autism is a common neuropsychiatric disorder with largely unknown causes and significant societal burden. Genetic studies have focused on DNA sequence changes in autism, but here we propose to explore the epigenetic landscape of the disorder, which importantly reflects the intersection of gene and environment interactions. The proposed studies will therefore answer a major question in autism research: whether diverse genetic and environmental etiologies converge on shared biological pathways that may be amenable to common therapeutic approaches.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH094714-03
Application #
8496121
Study Section
Special Emphasis Panel (ZMH1-ERB-M (02))
Program Officer
Senthil, Geetha
Project Start
2011-08-25
Project End
2015-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$748,775
Indirect Cost
$155,091
Name
University of California Los Angeles
Department
None
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
Jeste, Shafali S; Geschwind, Daniel H (2014) Disentangling the heterogeneity of autism spectrum disorder through genetic findings. Nat Rev Neurol 10:74-81
Stein, Jason L; de la Torre-Ubieta, Luis; Tian, Yuan et al. (2014) A quantitative framework to evaluate modeling of cortical development by neural stem cells. Neuron 83:69-86
Belgard, T G; Jankovic, I; Lowe, J K et al. (2014) Population structure confounds autism genetic classifier. Mol Psychiatry 19:405-7
Geschwind, Daniel H; Rakic, Pasko (2013) Cortical evolution: judge the brain by its cover. Neuron 80:633-47