Discovering pathways to autism spectrum disorder by using
functional and integrative genomics approaches to assess monozygotic twin differences
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Abstract
Autism spectrum disorder (ASD) is a common developmental disorder typified
by deficits in social communication and stereotyped behaviours. Despite evidence
of a strong genetic basis to the disorder, molecular studies have thus far had little
success in identifying risk variants or other biomarkers, and presently there is
no unified pathomechanistic explanation. Monozygotic (MZ) twins show incomplete
concordance in autistic traits, which suggests that alternative risk pathways
involving non-shared environmental (NSE) factors could also have an important
role to play in ASD. In this thesis, we describe microarray and RNA-seq studies
characterising gene expression in a sample of 53 ASD MZ twin pairs from TEDS.
The overall aims were to: 1) establish convergent evidence for genes and pathways
involved in the etiology of ASD comparing affected and unaffected subjects
across the sample 2) to identify those responsive to the environment by examining
differences within the discordant pairs. We found a number of genes were differentially
expressed including DEPDC1B - the most significant finding in cases
vs controls, which also showed consistent down regulation within pairs. We further
identified IGHG4, IGHG3, IGHV3-66, HSPA8P14, HSPA13, SLC15A2, and
found that these results were enriched for transcriptional control, immune, and
PI3K/AKT signalling pathways. We suggest that as these were found to be perturbed
in the discordant twins, they could represent ASD risk pathways sensitive
to the NSE. Next, we investigated integrative genomics methods for performing
meta-dimensional analysis using the expression data along with methylation data
on the same cohort. After applying regression-based joint analysis methods, and
meta-analysis p-value combination methods to our datasets, a number of genes
obtained nominal significance across the datasets, including potential genes of interest:
NLGN2, UBE3A, OXTR. We suggest these represent genes with evidence for
being functionally relevant to ASD