A bioinformatics and genotyping approach exploring personalised nutrition.
| dc.contributor.advisor | Mohareb, Fady R. | |
| dc.contributor.advisor | Thompson, Andrew J. | |
| dc.contributor.author | Molitor, Corentin | |
| dc.date.accessioned | 2024-03-21T13:20:54Z | |
| dc.date.available | 2024-03-21T13:20:54Z | |
| dc.date.issued | 2021-11 | |
| dc.description.abstract | Personalised nutrition is at its early stages but shows the potential of improving the health of the general population, at a time when diabetes and obesity are becoming worldwide epidemics. However, it will need to be based on rigorous scientific research, as well as being accompanied by public policies and ethical considerations. Research is making great progress towards the understanding of the impact of genetics on complex diseases, which involve hundreds, or thousands, of variants, each having varying effect on the disease. Personalised medicine aims at harnessing this genetic information to tailor prevention and treatment according to each individual. Unfortunately, the links between the genotype and the phenotype are not yet fully understood. And while the content of publicly available genetic databases is exponentially growing, they are often using different formats and means of access, making it difficult to get complete information. Moreover, evaluating the genetic predisposition of an individual to a disease is not straightforward, and while Polygenic Risk Score models can help in this regard, they are often only based on common variants, which might lead to misevaluation of the risk for rare- variants carriers. In this thesis will be presented (i) VarGen, an R package to merge information from different genetic databases, which has the potential to infer new variant- disease relationships. (ii) a new method to improve Polygenic Risk Score models, which includes variants obtained from VarGen on top of the common variants from standard polygenic analyses. (iii) the results of a microRNA differential expression analysis, aiming at identifying the impact of microRNAs, on the development of severe Hypoxic-Ischemic Encephalopathy in new-borns. | en_UK |
| dc.description.coursename | PhD in Environment and Agrifood | en_UK |
| dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/21064 | |
| dc.language.iso | en_UK | en_UK |
| dc.publisher | Cranfield University | en_UK |
| dc.publisher.department | SWEE | en_UK |
| dc.rights | © Cranfield University, 2021. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder. | en_UK |
| dc.subject | VarGen | en_UK |
| dc.subject | R package | en_UK |
| dc.subject | polygenic risk scores | en_UK |
| dc.subject | genome wide association studies | en_UK |
| dc.subject | diabetes | en_UK |
| dc.subject | obesity | en_UK |
| dc.subject | body mass index | en_UK |
| dc.subject | microRNA | en_UK |
| dc.subject | hypoxic-ischemic encephalopathy | en_UK |
| dc.title | A bioinformatics and genotyping approach exploring personalised nutrition. | en_UK |
| dc.type | Thesis or dissertation | en_UK |
| dc.type.qualificationlevel | Doctoral | en_UK |
| dc.type.qualificationname | PhD | en_UK |