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Title: Pathway and gene-based analysis of genome wide association studies (GWAS)
Author: Eleftherochorinou, Charikleia
ISNI:       0000 0004 2711 9204
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2012
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My PhD thesis comprises the development and application of novel strategies to analyse genome-wide association studies (GWAS) in the context of functional pathways. I propose pathway and gene-centric methodologies as complementary tools to the conventional singlemarker analyses to mine further the GWAS hidden information. I developed the cumulative trend (CT) test statistic that assesses the cumulative genetic variation of single nucleotide polymorphisms (SNPs) of genes that interact in the same biological pathway and tests the association between a disease and the pathway as an entity. I applied this methodology to the genotypic data of the Wellcome Trust Case Control Consortium (WTCCC) study on Crohn’s disease (CD), type I diabetes (T1D), rheumatoid arthritis (RA), bipolar disorder, hypertension, type II diabetes, coronary artery disease; I identified highly significant associations between the autoimmune diseases (CD, T1D, RA) and inflammatory pathways; almost no association was identified between the same pathways and the non-inflammatory conditions. I extended my approach to a pathway-based gene stability selection methodology, which selects associated genes in the context of associated pathways. This methodology can be used to prioritise genes for follow up studies. I applied it on two GWAS of RA with different ethnic background and typed on different platforms and I demonstrated replication at the pathway, gene and in-silico functional levels. I finally extended my approach on family trios designed GWAS. I applied it on two casecontrol and family trio datasets of Kawasaki disease (KD). I explored the association between the TGF-β pathway and KD susceptibility. The involvement of this pathway in KD was further validated at the gene expression and protein levels. My proposed methodologies were tested on real datasets and provided reproducible results, which indicates rigor and robustness. I would therefore suggest their application to single or multiple GWAS as a complement to conventional single-SNP analysis.
Supervisor: Levin, Michael ; Coin, Lachlan ; Herberg, Jethro Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral