1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Integrative gene expression analysis of peripheral blood from autism spectrum disorder cases
Paper ID : 1448-ICB10
Authors:
Parimah Emadi Safavi1, Seyed Shahriar Arab2, javad zahiri *3
1Department of Biophysics, Tarbiat Modares University, Tehran
2Biophysics department, Tarbiat Modares University
3Department of Neuroscience University of California, San Diego
Abstract:
Autism spectrum disorders is an umbrella term used for the set of neurodevelopmental conditions with early childhood onset characterized by difficulties in social interactions and repetitive behaviors. Recent advances in high-throughput sequencing and public data sharing have provided us with new opportunities to investigate the underlying mechanisms of such complex diseases. nevertheless, identification of disorder heritability and gene regulatory signatures is still a challenge since each gene mutation involved in the disease only stands for a minor subset of autistic cases. Accordingly, transcriptomic analysis is a great approach since provides us the ability to identify pathways associated with disease-related genes. In this research, we used publicly available microarray datasets of peripheral blood of autistic people and typically developed cases in search of candidate risk genes. We incorporated disease genes from the Simon Foundation Autism Research Initiative database and gene sets of interest from prior literature for their association with our differentially expressed genes in blood datasets. Our pathway enrichment analyses results have shown critical pathways such as those in chromatin remodeling and cell adhesion which are crucial to neuron plasticity. These processes are an essential part of brain development in early childhood. It is remarkable since autism emerges by the time brain development happens which is evident that our other differentially expressed genes can introduce candidate risk genes in autism. These findings prove the applicability of data integration in the search for potential risk genes and pathways with almost high confidence. Our analysis would be a candidate reproducible method to illuminate pathways, heritability, and etiology of autism spectrum disorders.
Keywords:
autism spectrum disorder; data integration; microarray; peripheral blood; gene expression
Status : Paper Accepted (Poster Presentation)