Alzheimer’s disease is a chronic, neurodegenerative disease characterised by amyloid plaque accumulation, neurofibrillary tangles and eventual neuronal cell loss. The complex aetiology exhibited in late-onset Alzheimer’s disease presents a considerable challenge in the field of genetics, with identified variants from genome-wide association studies collectively only explaining about a third of disease incidence. As such, new avenues are being explored to elucidate underlying mechanisms associated with disease onset and progression. In 2014, the first epigenome-wide association studies in Alzheimer’s disease were published, identifying several, novel differentially methylated loci in the nuclear genome in cortical brain samples, highlighting that epigenetic mechanisms may play a role in disease aetiology. Further, a growing body of evidence has implicated mitochondrial dysfunction as an early feature of disease pathogenesis. Despite this, few studies have investigated the role of mitochondrial DNA epigenetics in Alzheimer’s disease. Indeed, the relatively nascent field of mitochondrial epigenetics has largely been restricted to candidate-based gene approaches to identify differential methylation associated with disease. The main aim of this thesis was therefore to design an experimental and bioinformatic pipeline for the analysis of mitochondrial DNA methylation in post- mortem human brain tissue; first in healthy non-demented control donors, and subsequently in individuals with Alzheimer’s disease. Our work therefore represents the first epigenome wide studies of mitochondrial DNA methylation at single nucleotide resolution, providing a framework not only for mitochondrial DNA methylation in Alzheimer’s disease, but also in a number of complex diseases characterised by mitochondrial dysfunction.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:716829 |
Date | January 2017 |
Creators | Devall, Matthew Adrian Michael |
Contributors | Lunnon, Katie ; Weedon, Michael ; Mill, Jonathan |
Publisher | University of Exeter |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/10871/28434 |
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