Type 1 diabetes (T1D) is a chronic autoimmune condition hallmarked by insulin-secreting beta-cells mass decline and resultant hyperglycaemia when approximately 70-80% of beta-cells have been destroyed. Methods measuring the level of cell-free (cf) DNA containing fragments of the beta-cell-specific insulin gene (INS), released from dying beta-cells into the circulation have been reported as a potential method for detecting real-time beta-cell death and may represent an effective strategy for monitoring beta-cell destruction in individuals at-risk of future T1D, those with T1D and recipients of islet transplants. INS-based assays have been reported but proven difficult to replicate. The aim of this study, therefore, was to identify additional beta-cell genome specific differentially methylated loci which could be multiplexed for high-throughput analysis by droplet digital PCR. A genome-wide approach was used to obtain DNA methylation signatures in islets and PBMC using the Illumina InfiniumHumanMethylationEPIC BeadChip. Through bioinformatic analyses, 3866 CpG loci were differentially hypomethylated, and 4990 CpG loci were differentially hypermethylated in islets when compared to the PBMC methylome. Combining the EPIC analysis with methylation signatures from other tissues conducted by the Roadmap and ENCODE studies decreased the number of differentially methylated loci into islet specific 425 hypomethylated and 228 hypermethylated CpG targets. Subsequently, a multiplex methylation sensitive assay was developed based on a combination of beta-cell-specific differentially methylated regions (DMRs) of the combined promoter for MIR-200c/MIR-141 and exon 2 of the INS. The data presented in this thesis demonstrates that the developed multiplex biomarker discriminated circulating beta-cell cfDNA fragments in the circulation of recently diagnosed paediatric T1D patients, individuals at increased risk of developing T1D and in the circulation of T1D patients post-islet transplantation. The newly developed assay will be further validated in the future by testing larger cohorts with longitudinal sampling to determine the its usefulness in measuring rates of T1D progression.
|Date of Award||6 Nov 2018|
- The University of Bristol
|Supervisor||Kathleen M Gillespie (Supervisor) & Alistair Williams (Supervisor)|