Investigation of analytical bioinformatic approaches to genomic and transcriptomic data

Crawford, Karen 2022. Investigation of analytical bioinformatic approaches to genomic and transcriptomic data. PhD Thesis, Cardiff University. Item availability restricted.

Preview	PDF - Accepted Post-Print Version Download (19MB) | Preview
	PDF (Cardiff University Electronic Publication Form) - Supplemental Material Restricted to Repository staff only Download (139kB)

Abstract

Alzheimer’s disease (AD) is a devastating form of neurodegeneration that is characterised by the formation of amyloid plaques and tau tangles in the brain. Genome-wide association studies (GWAS) have identified over 70 risk loci. How these functionally relate to AD is still yet to be fully explored. The work presented in this thesis aims to integrate and interrogate three publicly available genetic and RNA-sequencing datasets. This is with the aim to increase our understanding of the mechanisms underlying AD biology. This was achieved by utilising a variety of bioinformatic analyses. Chapter 1 introduces the background of AD, an overview of the relevant literature and the aims of this thesis. Chapter 2 gives an overview of some of the bioinformatic methodology used throughout this thesis. Chapter 3 uses linear mixed-effect models in addition to principal component analysis to combine the ROSMAP, MSBB and MayoRNAseq bulk brain RNAsequencing datasets into a single dataset. This dataset was then utilised in chapter 4 to perform a differential gene expression analysis followed by a gene ontology enrichment analysis. This identified that GWAS prioritised genes are not enriched in differential gene expression derived from case-control bulk RNA-sequencing data. This analysis also implicated pathways associated with mitochondrial processes and the endoplasmic reticulum in AD. Chapter 5 explores a cis- and trans- eQTL analysis of differentially expressed genes that were identified in chapter 4. This identified SST, TAC1, MAF1 and SCGN as potential candidate risk genes for AD. Chapter 6 compares the results of the differential gene expression analysis (from chapter 4) to three published Transcriptome-Wide Association studies (TWAS) results. This identified that in AD, TWAS signals are not enriched in bulk brain DGE analysis. Chapter 7 is a discussion of the results of this thesis and directions for possible future study.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Medicine
Date of First Compliant Deposit:	16 January 2023
Last Modified:	10 Feb 2024 02:15
URI:	https://orca.cardiff.ac.uk/id/eprint/155904

Actions (repository staff only)

Edit Item