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Investigating the role of microRNAs in autism
[Thesis]. Manchester, UK: The University of Manchester; 2018.
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Abstract
Autism is a neurodevelopmental disorder involving difficulties with social communication and interaction and repetitive or restricted behaviour and interests, as well as other associated traits. Although autism is known to be highly heritable, the genetic basis of risk is still poorly understood. MicroRNAs are small non-protein coding RNAs which are highly conserved through evolution and which help regulate key developmental pathways. Previous studies showing microRNA dysregulation in autism suggest that better understanding of microRNA variants, expression and post-transcriptional regulation may help reveal underlying pathways involved in autism. MicroRNAs have also been proposed as biomarkers for better diagnosis and early intervention, leading to improved outcomes for affected individuals. In this work, we investigate the role of microRNAs in autism through small RNA sequencing of 42 autistic individuals and 10 controls, and analysis of variants in whole genome sequence data. We identified significant differential expression of 24 microRNAs, of which 5 had been previously reported as affected in autism. We developed algorithms which identified post-transcriptional regulation of microRNAs through arm usage changes, isomiRs and A-I editing. Previous work on dysregulated microRNAs hsa-miR-146a-5p, hsa-miR-132-5p and others suggest a role for Fragile X syndrome pathways in non-syndromic autism cases. We examined the set of single nucleotide variations in microRNAs in a whole genome sequencing dataset for 671 probands. We identified 101 rare SNVs within microRNA seed regions, but no de novo mutations. Target prediction suggested these SNVs could lead to radical changes in the set of regulated mRNAs. In addition to our study of microRNAs in autism, we also investigated research methods in this field. We found poor practice in computational analysis of microRNA functional enrichment which led to hundreds of published reports of significantly enriched pathways and functions in different diseases, conditions and biological states. We demonstrated that bias in the set of genes targeted by microRNAs in general meant that reported significant enrichments were in fact no stronger than for randomly selected microRNAs. Following concerns about poor engagement between the autism and research communities, we held workshops with 30 focus group and interview participants. We found that failure to build participatory autism research projects had led to reduced trust, recruitment problems, skewed research goals and poor dissemination. We developed recommendations for improved practice in collaboration with the autism community. Together, our work provides a framework for improved practice in both autism research and microRNA bioinformatic analysis. Our analysis of microRNAs in autism through small RNA sequencing data reveals important dysregulated pathways and contributes to a better understanding of microRNA post-transcriptional regulation in autism.