A multi-ancestry genetic analysis of type 2 diabetes
type: CreativeWork
description: Diabetes affects more than 589 million people worldwide. It is one of the leading causes of death and costs over $1 trillion in annual global health expenditures. Type 2 diabetes (T2D) comprises ~90% of diabetes cases, is characterised by pancreatic islet beta cell dysfunction and reduced insulin response in insulin-sensitive tissues, and is associated with a myriad of risk factors, including diet, obesity, activity measures, and genetics. Over the past century, there have been extensive research efforts to describe the regulation of insulin secretion and downstream mechanisms of action, leading to the development of several efficacious therapies. Yet, despite these successes, the underlying molecular and cellular mechanisms leading to T2D are not yet fully understood. Human genetics offers a promising avenue to guide future research efforts in common diseases, such as T2D, by identifying disease-associated loci. From those, we can nominate causal genes and molecular/cellular processes, inform therapeutic development, and identify individuals with high genetic predisposition for disease for early interventional strategies. To date, genetic analyses of T2D have observed heritability between 25-70% and have identified over 500 associated loci. However, understanding the complex genetics governing T2D heritability still faces challenges, limiting the translational value of these studies. Among the most difficult is the challenge to identify the causal mechanisms as >90% of T2D-associated signals lie in non-coding regions of the genome. Moreover, often-modest effect sizes and varying frequency of alleles across populations mean there are loci that we have yet to identify since the vast majority of current studies have been limited to western European and East Asian genetic ancestries. In this thesis, I describe my work to mitigate some of these shortcomings by expanding diversity in T2D genetic studies to improve both locus discovery and risk screening and by integratin…
abstract: Diabetes affects more than 589 million people worldwide. It is one of the leading causes of death and costs over $1 trillion in annual global health expenditures. Type 2 diabetes (T2D) comprises ~90% of diabetes cases, is characterised by pancreatic islet beta cell dysfunction and reduced insulin response in insulin-sensitive tissues, and is associated with a myriad of risk factors, including diet, obesity, activity measures, and genetics. Over the past century, there have been extensive research efforts to describe the regulation of insulin secretion and downstream mechanisms of action, leading to the development of several efficacious therapies. Yet, despite these successes, the underlying molecular and cellular mechanisms leading to T2D are not yet fully understood. Human genetics offers a promising avenue to guide future research efforts in common diseases, such as T2D, by identifying disease-associated loci. From those, we can nominate causal genes and molecular/cellular processes, inform therapeutic development, and identify individuals with high genetic predisposition for disease for early interventional strategies. To date, genetic analyses of T2D have observed heritability between 25-70% and have identified over 500 associated loci. However, understanding the complex genetics governing T2D heritability still faces challenges, limiting the translational value of these studies. Among the most difficult is the challenge to identify the causal mechanisms as >90% of T2D-associated signals lie in non-coding regions of the genome. Moreover, often-modest effect sizes and varying frequency of alleles across populations mean there are loci that we have yet to identify since the vast majority of current studies have been limited to western European and East Asian genetic ancestries. In this thesis, I describe my work to mitigate some of these shortcomings by expanding diversity in T2D genetic studies to improve both locus discovery and risk screening and by integratin…
author: Taylor, Henry
language: eng
keywords: genetic epidemiology, genomics, GWAS, human genetics, type 2 diabetes
license: https://www.repository.cam.ac.uk/bitstreams/691a736a-167a-477d-a5a2-050f8f927ebd/download
license: https://creativecommons.org/licenses/by/4.0/
date published: 2025-08-12
date modified: 2026-07-24T01:33:21Z
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.124763