Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.771201
Title: Genetic basis of longevity and age-related diseases : evidence from genetic association studies
Author: Wang, Jingwei
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2019
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Abstract:
Ageing is a complex process that happens in almost all organisms. Many factors are involved in the ageing process. Age is a major risk factor for the onset of many diseases that severely affects life quality and lifespan in almost all known organisms, including humans. Studies focusing on ageing revealed that both biological and non-biological factors can affect the ageing process through direct or indirect manners. For example, in humans, the clustered distribution pattern of centenarians and supercentenarians in families and the plasticity of lifespan due to genetic manipulations and diet in model organisms further support the theory that ageing is a complex, multifactorial phenotype. Among the factors that could affect ageing and longevity in model organisms and in human populations, genetic factors are of prime importance. As the fundamental element that distinguishes one from another, on a per-species level as well as on an individual level, genetic make-up determines the style of growth, metabolism, and adaptation to external environment of organisms. The existence of genetic variation among species and individuals shaped the differentiation in metabolic pathways and phenotypes such as ageing. In this thesis, genetic factors were compiled and analysed to reveal their relationship with longevity and ageing. In this regard, an introduction of ageing theories and ageing research is described in Chapter 1. Following this, Human Longevity-Associated Genes (HLAGs) from hundreds of published longevity-genetic association studies were manually curated and implemented into a user-friendly database - the LongevityMap (http://genomics.senescence.info/longevity/). The process of implementing the LongevityMap is described in Chapter 2. In the following two chapters, the features (attributes) of those HLAGs collected in the LongevityMap were analysed. Functional enrichment analysis, which is a powerful tool to gather common functions from a list of genes, was utilised in analysing the HLAGs in the LongevityMap. The functional enrichment analysis of HLAGs revealed enriched clusters of important metabolic and cell signal pathways. Additionally, the metadata, such as the involvement of pathways, of those HLAGs, which represents the attributes of the gene set of HLAGs in LongevityMap, was also investigated. The analysis of this metadata revealed novel perspectives for ageing research. The results showed evidence of how candidate genes were selected for longevity-genetic association studies by researchers, as well as how researchers typically submitted and published the results. These explorations are described in Chapter 3 and Chapter 4. Although thousands of genes have been examined for their association with longevity, very few of them have been consistently observed in different studies. Based on this, perhaps genetic heterogeneity could affect our understanding of the process of ageing, including longevity and age-related diseases. Through this concept, we investigated the relationship between genetic heterogeneity and traits/diseases that has been proven to be ageing related. A measurement of nucleotide changes on the gene level was defined and termed as 'Genetic Diversity (GD)' (described in section 5.3.2.3) to represent the genetic heterogeneity on gene level. The analyses showed there was consistent correlation between gene length and the number of traits associated with the gene in Genome-Wide Association Studies (GWASs), but not between the GD and the number of traits associated with the gene. The GD of human Age-Related Traits/Disease (ARTD) associated genes, some cancers associated genes and Early Onset Disease(EOD) genes were also investigated. Results showed genetic heterogeneity in EOD genes were significantly higher than in ARTD or EOD genes. These analysis and results are described in Chapter 5. In conclusion, HLAGs identified by genetic association studies are a valuable resource for ageing research. Organising those HLAGs into the LongevityMap database further facilitates the usage of HLAGs data, even though publication/study biases may exist. The results from functional enrichment analysis and pathway analysis not only verified the importance of some key biological functional pathways in affecting lifespan but also gave some hits on other pathways that could contribute to ageing/longevity. Finally, correlation analyses showed GWAS results are affected by gene length or GD. GD is different in ARTD, cancer and EOD associated genes.
Supervisor: de Magalhães, João Pedro ; Jones, Andy Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.771201  DOI:
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