A common molecular signature in ASD gene expression: following Root 66 to autism.

L Diaz-Beltran,D P Wall,F J Esteban

doi:10.1038/tp.2015.112

Abstract

Several gene expression experiments on autism spectrum disorders have been conducted using both blood and brain tissue. Individually, these studies have advanced our understanding of the molecular systems involved in the molecular pathology of autism and have formed the bases of ongoing work to build autism biomarkers. In this study, we conducted an integrated systems biology analysis of 9 independent gene expression experiments covering 657 autism, 9 mental retardation and developmental delay and 566 control samples to determine if a common signature exists and to test whether regulatory patterns in the brain relevant to autism can also be detected in blood. We constructed a matrix of differentially expressed genes from these experiments and used a Jaccard coefficient to create a gene-based phylogeny, validated by bootstrap. As expected, experiments and tissue types clustered together with high statistical confidence. However, we discovered a statistically significant subgrouping of 3 blood and 2 brain data sets from 3 different experiments rooted by a highly correlated regulatory pattern of 66 genes. This Root 66 appeared to be non-random and of potential etiologic relevance to autism, given their enriched roles in neurological processes key for normal brain growth and function, learning and memory, neurodegeneration, social behavior and cognition. Our results suggest that there is a detectable autism signature in the blood that may be a molecular echo of autism-related dysregulation in the brain.

Highlights

Autism is regarded as one condition among a genetically heterogeneous group of neurodevelopmental syndromes with high prevalence[1] that has a wide range of phenotypes, collectively grouped together as autism spectrum disorder (ASD)
There is no unifying hypothesis about the molecular pathology of autism, it is clear that the disorder is highly heritable and results from the combination of genetic, neurologic, immunologic and environmental factors
To determine relatedness across biosets, we converted the lists into a binary matrix of gene presence/absence and performed distancebased clustering with pairwise similarity measured via the Jaccard coefficient

Summary

Introduction

Autism is regarded as one condition among a genetically heterogeneous group of neurodevelopmental syndromes with high prevalence[1] that has a wide range of phenotypes, collectively grouped together as autism spectrum disorder (ASD). The unifying clinical features across the spectrum involve fundamental impairments in social interaction, communication deficits and highly restrictive interest and/or repetitive behaviors.[2,3] there is no unifying hypothesis about the molecular pathology of autism, it is clear that the disorder is highly heritable and results from the combination of genetic, neurologic, immunologic and environmental factors. It remains unclear whether its genetic component stems from the combination of a few common variants or of many rare variants.[4,5]. Despite the large amounts of data available, the general lack of replication across studies suggests that more data will be needed to fully characterize the genetic models responsible for the various forms of autism

Methods

Results

Discussion

Conclusion