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The idiopathic inflammatory myopathies (IIM) are heterogeneous rare autoimmune conditions characterised by weakness and inflammation of skeletal muscle. The major subtypes of IIM are polymyositis (PM), dermatomyositis (DM) and inclusion body myositis. IIM are complex diseases likely caused by a combination of genetic susceptibility and environmental triggers including exposure to statins, infections and ultraviolet (UV) radiation. A clearer understanding of IIM pathology is important for the development of novel treatments. The aim of this PhD was to investigate the mechanisms involved in the pathogenesis and progression of IIM using three different approaches. In chapter 3 ('Systematic Protein-Protein Interaction and Pathway Analyses in the Idiopathic Inflammatory Myopathies'), an in silico approach was taken to identify potential protein-protein interactions between proteins that may be affected by single-nucleotide polymorphisms (SNPs) associated with IIM and the targets of autoantibodies associated with IIM. This study identified HSPA1A/B, UBE3B, PSMD3 and TRAF6 as genes to prioritise and pointed towards the ubiquitin proteasome pathway as a potentially important pathway in IIM. In chapter 4 ('Genetic background may contribute to the latitude-dependent prevalence of dermatomyositis and anti-TIF1-gamma autoantibodies in adult patients with myositis'), a genetic epidemiology approach was used to investigate the contribution of genetic background versus UV exposure to the distribution of DM in an international cohort of IIM cases and controls (using latitude as a proxy for UV exposure). This study found a novel negative association of the DM autoantibody anti-TIF1-gamma with latitude in the IIM cohort. SNPs associated with PM or DM and Human Leukocyte Antigen (HLA) alleles associated with DM autoantibodies, were modelled for association with latitude in healthy populations. The majority of SNPs and the HLA alleles were found to be associated with latitude in the same direction as the prevalence of the clinical phenotypes in the IIM cohort (negative for DM, positive for PM). Overall, these analyses lent some support to the hypothesis that genetic background, in addition to UV exposure, may contribute to the distribution of DM versus PM. In chapter 5 ('MicroRNA and mRNA profiling in the idiopathic inflammatory myopathies') next generation RNA sequencing was used to profile miRNA and mRNA in whole blood samples from PM, DM and IBM compared to controls. Gene ontology and pathway analyses were performed using GOseq and Ingenuity Pathway Analysis. Dysregulation of miRNAs and opposite dysregulation of predicted target mRNAs in IIM subgroups was validated using RTqPCR and investigated by transfecting human skeletal muscle cells with miRNA mimic. Overall, miRNA and mRNA profiling identified dysregulation of interferon signalling, innate immune and anti-viral responses and T-helper cell pathways. The transfection experiments indicated a possible role for miR-96-5p regulation of ADK in pathogenesis of IIM. Overall, these studies have contributed to our understanding of IIM susceptibility and disease progression and suggested avenues for future research which may ultimately lead to the development of improved diagnosis and treatments for this rare and debilitating group of diseases.

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.

Patients with idiopathic inflammatory myopathies (IIMs) face several unmet needs which can prevent the attainment of optimal clinical outcomes. Each manuscript presented in this thesis addresses one such unmet need. In Chapter 4 ('Patient-centred standards of care for adults with myositis', accepted for publication at BMC Rheumatology), standards of care for adults with IIM are presented. The evidence base for therapy in IIM is limited, but these standards of care will support healthcare professionals and enable benchmarking of services against agreed optimum standards. In Chapter 5 ('The EuroMyositis Registry: An international collaborative tool to facilitate myositis research', published in Annals of Rheumatic Disease), pooled data regarding 3,067 cases from 11 countries are analysed. Several important new associations are described, including the strong influence of extramuscular involvement on disease severity in IIM. In Chapter 6 ('Using serum troponins to screen for cardiac involvement and assess disease activity in the idiopathic inflammatory myopathies', under peer review at Rheumatology) increased IIM disease activity in those with abnormal levels of cardiac troponin T (cTnT) or I (cTnI), including in those with a normal creatine kinase, is demonstrated. cTnI testing also appeared useful in screening for cardiac involvement. In Chapter 7 ('Cytosolic 5'-nucleotidase 1A autoantibody profile and clinical characteristics in inclusion body myositis', published in Annals of Rheumatic Disease) differences in mortality risk, clinical and histopathological features between anti-cytosolic 5'-nucleotidase 1A autoantibody positive and negative inclusion body myositis patients are described. In Chapter 8 ('Muscle amyloid accumulation and disease activity in inclusion body myositis: A florbetapir positron emission tomography study') positron emission tomography of muscle using a beta-amyloid tracer is presented. Significantly higher levels of muscle amyloid were identified in the inclusion body myositis group compared to a disease control group with polymyositis.

Background: Massively parallel sequencing technologies (next-generation sequencing, NGS) have accelerated understanding of human genomics. The adoption of NGS in the study of human disease has transformed discovery and diagnostic genomics. These advantages have been especially evident for human disorders characterized by immense heterogeneity. These include Mendelian disorders, rare diseases that are often clinically and genetically heterogeneous and are underpinned for each individual by mutations in a single gene. However, a number of limitations exist in the application of NGS technologies for the study of Mendelian disorders, including the capability to detect and interpret the complete spectrum of variation within the human genome. Methods: Using inherited retinal diseases (IRD) as a model set of heterogeneous disorders, the investigations presented in this thesis have assessed trends in large cohorts of individuals, assessed the utility of different NGS approaches for the discovery of disease-causing genomic variation, and developed novel informatics strategies to detect and identify disease-causing variants from NGS datasets. The NGS approaches applied include whole exome sequencing, whole genome sequencing and large gene panels. Results: This research has advanced knowledge of the genetic basis of IRD, demonstrated the advantage of personalized genomic medicine for individuals with IRD, identified limitations in currently employed NGS diagnostic services, and developed informatics strategies to overcome identified limitations across a range of heterogeneous Mendelian disorders. Importantly, through the application of read-depth strategies for the identification of copy number variation (CNV), this research has increased the versatility of NGS datasets generated and analysed in clinically accredited laboratories. Conclusions: The analysis frameworks applied in this research have set a paradigm for the analysis and integration of the 100,000 genomes project datasets within national genome medicine centres. These investigations have also identified a number of outstanding challenges for the analysis of NGS datasets in the context of Mendelian disorders that represent important and interesting topics for future research, including the expansion of analysis strategies to detect pathogenic non-coding and regulatory variation.