Computational studies on ageing and age-related diseases
type: CreativeWork
description: Age is the major risk factor for a variety of non-communicable diseases. As life expectancy increases, ageing poses significant challenges to the individual, society, and healthcare systems. Ageing is a complex process involving multiple interconnected cellular and organismal phenotypes. Thus, understanding the molecular mechanisms and finding potential interventions is challenging and requires systems-level approaches. In this PhD I have addressed three main questions about ageing, using high-throughput data and computational methods. My first study considers interindividual heterogeneity in gene expression during ageing. Previous studies had suggested that phenotype, epigenome and gene expression become more heterogeneous with age. However, the list of genes and pathways reported as heterogeneous in late age showed differences in the literature and did not resolve whether the increase in heterogeneity is a time-dependent process starting at birth or is restricted to the ageing period (i.e. after 20 years of age). Using different data pre-processing steps and heterogeneity measures on the same transcriptome dataset, we have shown that the inconsistency in the literature could reflect technical issues as well as biological variability. Next, applying a meta-analysis scheme that relies on consistent results across multiple datasets to increase reproducibility, we have shown that the increase in inter-individual heterogeneity starts after the age of 20. Moreover, the genes that become more heterogeneous during ageing have a higher number of transcriptional regulators (miRNAs and transcription factors) and are associated with known longevity pathways. My second study focuses on the link between ageing and age-related diseases. Many diseases show age-dependency, but the molecular nature of this relationship is not fully understood. Using UK Biobank data, I have characterised 116 common diseases based on their age-of-onset profiles and genetic associations. I first showe…
abstract: Age is the major risk factor for a variety of non-communicable diseases. As life expectancy increases, ageing poses significant challenges to the individual, society, and healthcare systems. Ageing is a complex process involving multiple interconnected cellular and organismal phenotypes. Thus, understanding the molecular mechanisms and finding potential interventions is challenging and requires systems-level approaches. In this PhD I have addressed three main questions about ageing, using high-throughput data and computational methods. My first study considers interindividual heterogeneity in gene expression during ageing. Previous studies had suggested that phenotype, epigenome and gene expression become more heterogeneous with age. However, the list of genes and pathways reported as heterogeneous in late age showed differences in the literature and did not resolve whether the increase in heterogeneity is a time-dependent process starting at birth or is restricted to the ageing period (i.e. after 20 years of age). Using different data pre-processing steps and heterogeneity measures on the same transcriptome dataset, we have shown that the inconsistency in the literature could reflect technical issues as well as biological variability. Next, applying a meta-analysis scheme that relies on consistent results across multiple datasets to increase reproducibility, we have shown that the increase in inter-individual heterogeneity starts after the age of 20. Moreover, the genes that become more heterogeneous during ageing have a higher number of transcriptional regulators (miRNAs and transcription factors) and are associated with known longevity pathways. My second study focuses on the link between ageing and age-related diseases. Many diseases show age-dependency, but the molecular nature of this relationship is not fully understood. Using UK Biobank data, I have characterised 116 common diseases based on their age-of-onset profiles and genetic associations. I first showe…
author: Donertas, Handan Melike
language: eng
keywords: ageing, age-related diseases, drug repurposing, transcriptomics, GWAS
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/9eb6950c-5b3b-4f5c-91d4-b405ec46d8ec/download
license: https://creativecommons.org/licenses/by/4.0/
date published: 2020-04-17
date modified: 2026-07-22T22:24:06Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.58440