Identification of functional variants in the Alzheimer’s disease candidate gene ABCA7

Clement, Naomi Susan (2017) Identification of functional variants in the Alzheimer’s disease candidate gene ABCA7. PhD thesis, University of Nottingham.

PDF (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (4MB) | Preview


Late onset Alzheimer’s disease (LOAD) is the commonest form of dementia, affecting approximately 850,000 patients in the UK alone, predicted to exceed one million by 2025. The cause of LOAD is complex, but several large Genome Wide Association Studies have highlighted 21 genetic loci associated with this devastating disease and the ATP-Binding Cassette Protein, family A, member 7 (ABCA7) is one of these genetic loci. However, the exact reasons behind this association are still unknown, focusing work on identifying functional, pathogenic mutations within this locus.

A total of 240 exonic variations within ABCA7 were therefore annotated in order to identify ones potentially altering the functionality of ABCA7. A total of five variants were predicted to be damaging by in silico annotation tools: rs3752233; rs59851484; rs3752237; rs114782266 and a novel mutation at genomic position 19:1056958. These were genotyped in the ARUK DNA Bank resource and three (rs59851484, rs3752239 and 19:1056958) showed tentative association with LOAD. However, lack of power in this study prevented any definitive associations from being formed. A further two variants were examined within functional cell assays. rs881768 had been predicted to affect the splicing of the ABCA7 protein and appeared to do so within minigene cellular assays. However, this did not appear to be the case when RNA from brain tissue harbouring this variation was examined. rs2020000 was examined through the dual luciferase assays, with the minor allele seeming to down regulate the reporter protein by approximately 30% (p<0.02) in these in vitro assays.

Functional variations within the ABCA7 locus do play a role in LOAD risk and improvements within functional databases and annotation programmes will assist in identifying these causative mutations, in order to put a halt to LOAD, as well as other destructive complex disorders.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Morgan, K.
Ilyas, M.
Keywords: Alzheimer's disease, Genetics, Genetic loci, Pathogenic mutations
Subjects: R Medicine > RC Internal medicine
W Medicine and related subjects (NLM Classification) > WT Geriatrics. Chronic disease
Faculties/Schools: UK Campuses > Faculty of Medicine and Health Sciences > School of Life Sciences
Item ID: 41405
Depositing User: Clement, Naomi
Date Deposited: 17 Jul 2017 04:40
Last Modified: 13 Oct 2017 01:21

Actions (Archive Staff Only)

Edit View Edit View