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Mol Autism. 2019 Nov 7;10:38. doi: 10.1186/s13229-019-0285-1. eCollection 2019.

RNA sequencing of identical twins discordant for autism reveals blood-based signatures implicating immune and transcriptional dysregulation.

Author information

1
1Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
2
2Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, UK.
3
3Edinburgh Genomics, University of Edinburgh, Edinburgh, Scotland UK.
4
4King's Genomics Centre, King's College London, London, UK.
5
5Social Genetic and Developmental Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
6
6School of Life Sciences, University of Essex, Colchester, UK.
7
7University of Exeter Medical School, University of Exeter, Exeter, UK.
8
8Department of Health Sciences, University of Leicester, Leicester, UK.

Abstract

Background:

A gap exists in our mechanistic understanding of how genetic and environmental risk factors converge at the molecular level to result in the emergence of autism symptoms. We compared blood-based gene expression signatures in identical twins concordant and discordant for autism spectrum condition (ASC) to differentiate genetic and environmentally driven transcription differences, and establish convergent evidence for biological mechanisms involved in ASC.

Methods:

Genome-wide gene expression data were generated using RNA-seq on whole blood samples taken from 16 pairs of monozygotic (MZ) twins and seven twin pair members (39 individuals in total), who had been assessed for ASC and autism traits at age 12. Differential expression (DE) analyses were performed between (a) affected and unaffected subjects (N = 36) and (b) within discordant ASC MZ twin pairs (total N = 11) to identify environmental-driven DE. Gene set enrichment and pathway testing was performed on DE gene lists. Finally, an integrative analysis using DNA methylation data aimed to identify genes with consistent evidence for altered regulation in cis.

Results:

In the discordant twin analysis, three genes showed evidence for DE at FDR < 10%: IGHG4, EVI2A and SNORD15B. In the case-control analysis, four DE genes were identified at FDR < 10% including IGHG4, PRR13P5, DEPDC1B, and ZNF501. We find enrichment for DE of genes curated in the SFARI human gene database. Pathways showing evidence of enrichment included those related to immune cell signalling and immune response, transcriptional control and cell cycle/proliferation. Integrative methylomic and transcriptomic analysis identified a number of genes showing suggestive evidence for cis dysregulation.

Limitations:

Identical twins stably discordant for ASC are rare, and as such the sample size was limited and constrained to the use of peripheral blood tissue for transcriptomic and methylomic profiling. Given these primary limitations, we focused on transcript-level analysis.

Conclusions:

Using a cohort of ASC discordant and concordant MZ twins, we add to the growing body of transcriptomic-based evidence for an immune-based component in the molecular aetiology of ASC. Whilst the sample size was limited, the study demonstrates the utility of the discordant MZ twin design combined with multi-omics integration for maximising the potential to identify disease-associated molecular signals.

KEYWORDS:

Autism spectrum disorder; DNA methylation; Discordance; Epigenomics; Gene expression; Immune; MZ twins; RNA-seq; Transcriptomics

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