In 2009, two large genome wide association studies (GWAS) found associations between common single nucleotide polymorphisms (SNPs) at three loci (CLU, PICALM and CR1) and Alzheimer’s disease (AD) risk. The causal variants underlying these associations and how these impact on AD susceptibility remain unclear. Target enrichment and next generation sequencing (NGS) were used to completely resequence the three associated loci in 96 AD patients in an attempt to uncover potentially causative and rare variants that may explain the observed association signals. A pipeline was developed for the handling of pooled NGS data following a comparison of several different combinations of programs. 33 exonic SNPs were found within the three genes, along with over 1000 non-coding variants. To identify the variants most likely to be affecting AD risk, a two pronged approach was adopted. The variants were imputed in a large case-control cohort (2067 cases, 7376 controls) to test for association with AD, and the likely functional consequences of the variants were assessed using in silico resources. Several of the analysed variants showed suggestive or significant association with AD in the imputed data, and/or were predicted to have consequences on the function or regulation of the genes, suggesting avenues for future research in AD genetics. The whole method of pooled, targeted NGS and prioritisation using imputed data for association testing and in silico resources for functional analysis represents a new strategy for tracking down the illusive causation of GWAS signals.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:625526 |
Date | January 2014 |
Creators | Lord, Jenny |
Publisher | University of Nottingham |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://eprints.nottingham.ac.uk/14273/ |
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