Hernandez, DMG; (2016) Genetic variation and DNA methylation in the context of neurological disease. Doctoral thesis , UCL (University College London).

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Abstract

Understanding genetic control of biological processes is an important goal in the post-genome era. GWA studies have been successful in identifying loci linked to disease and recently in revealing disease risk alleles. However, pinpointing key genes and their alterations within associated loci remains a central challenge. Described is the completion of a large, international metaanalysis and replication study of existing PD GWA data, confirming 6 previously identified loci and identifying and confirming an additional 5 novel loci; thus, expanding our understanding of the genetic basis of PD. Following this is an effort to annotate the consequences of genetic variation within the context of normal human brain tissue by generating and integrating data to investigate the effects of common genetic variability on DNA methylation in four brain regions of 150 neurologically normal individuals, 600 samples total. Genome-wide SNP data is generated and 27,578 CpG sites assessed in each brain region. Results show methylation patterns differ between brain regions, genotype is correlated with methylation levels and DNA methylation QTL occur more often in sites outside of CpG islands. Next, an expanded map of DNA methylation in human brain assessing 486,428 CpG sites is generated and proximal CpG sites are integrated with known PD loci implicated by GWA studies; thus, gaining potential mechanistic insight into pathogenesis of disease. Significant DNA methylation QTL for 19 of 28 PD risk loci are identified, demonstrating the correlation of risk alleles for neurological disease with a biologically relevant trait in human brain tissue is a manageable goal. Lastly, analyses show CpG sites within normal human brain exhibit significant age-associated increases in methylation with an enrichment of changes at CpG islands of functionally related transcripts; thus, providing a footing for future integration of age-related epigenetic changes into disease models exhibiting age as a primary risk factor.

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