22561
Noncoding RNAs and Autism: The Impact of Employing Integrated Approaches

Thursday, May 12, 2016: 11:30 AM-1:30 PM
Hall A (Baltimore Convention Center)
Z. Talebizadeh, Children's Mercy Hospital, Kansas City, MO
Background:  

The field of noncoding RNAs (ncRNAs) is perhaps still in its infancy. However, because of the fascinating concept that they represent, regulation of gene expression, ncRNAs have become a topic of intense interest in understanding the underlying mechanism of human diseases. ncRNAs do not code for protein, but because of their influence on gene expression they may provide the key to uncover missing links in understanding the etiology of complex human diseases. Despite growing line of evidence indicating the essential role of ncRNAs in the brain function, they have been understudied in autism spectrum disorders (ASD). 

Objectives:   Among the main challenges in identifying causative genes for ASD are the extensive heterogeneity in the presentation of ASD and gene-environment interactions. Some of the undetected disease-causing mutations may alter gene regulation, whereas the candidate gene’s genomic sequence remains intact. To address this critical gap, the existing and ongoing large-scale autism genetic sequencing and expression data need to be also analyzed with respect to assessing the gene regulatory factors. 

Methods:  Integrated approaches (i.e., utilizing two or more phenotypic and genetic/epigenetic factors as well as bioinformatics and data mining pipelines) would be beneficial in detecting biologically relevant and replicated findings that move the autism field forward.

Results: We highlight findings derived from a few integrative approaches, which had resulted in promising discoveries and provided practical examples of how uncovering genetic causes of autism may be accelerated. 

Conclusions: The selected examples describe integrating different layers of genetic factors, including ncRNAs, thereby connecting the dots, which is expected to lead to the construction of autism-specific system biology networks (i.e., autism interactomes).