Baillie, Kenneth

Pairo-Castineira, Erola

Zechner, Marie

2024-11-21T13:36:46Z

2024-11-21T13:36:46Z

2024-11-21

The genetic basis of most diseases is complex. They are the result of many genetic variants which each confer part of the disease risk. A rapidly expanding number of genome-wide association studies (GWAS) offers a wealth of information on disease genetics and promises to advance our understanding of disease. However, translating this knowledge to novel clinical insights remains a fundamental challenge. In an attempt to address this issue, I exploit the fact that pleiotropy – the phenomenon whereby a single genetic variant can affect multiple seemingly unrelated traits – is widespread throughout the human genome. This can be used to elucidate disease mechanisms by highlighting which diseases are likely to share common molecular architecture, which can improve our understanding of less well-known diseases and reveal opportunities for drug repurposing. Additionally, combining data from multiple diseases which share an associated variant improves statistical power for the genomic region, enabling discoveries that would not have been detected in one GWAS alone. In the first part of this thesis, I utilised this approach to understand the molecular underpinnings of pathology in critical Covid-19. The Covid-19 pandemic was an unprecedented healthcare challenge and in spite of rapid scientific progress, death and severe illness from Covid-19 is still a worldwide threat to human health. In an effort to improve treatment options, I aimed to obtain further insight into the functional mechanisms behind critical Covid-19 by studying where it genetically intersects with other diseases. I explored pleiotropy between critical Covid-19 and a large range of diseases on a genome-wide and localised scale by analysing a curated dataset of 228 disease GWAS. Calculating their overall genetic correlation using high-definition likelihood inference analysis revealed multiple disease connections with critical Covid-19, suggesting causal genetic overlap with other diseases. I then performed a genome-wide multi-trait colocalization analysis using the Bayesian algorithm HyPrColoc (Hypothesis Prioritisation for multi-trait Colocalization) to isolate shared causal variants. Seven pleiotropic variants were detected as shared between critical Covid-19 and other diseases, including idiopathic pulmonary fibrosis, asthma, Crohn’s disease, systemic lupus erythematosus, psoriasis, rheumatoid arthritis, allergic disease, hypothyroidism and hypertension. A novel Covid-19 association with a variant in the gene SLC39A8, which is known to be widely pleiotropic, suggests pathways involving the divalent metal ion transporter ZIP8 as potential therapeutic targets. Pathway enrichment analysis of genes with expression identified to be affected by the pleiotropic variants pointed to the cellular checkpoint PD-1 as a possible drug target. This protein controls multiple downstream pathways that have been implicated in Covid-19. In the second part of this thesis, I investigated whether shared genetic variants can pinpoint drug repurposing opportunities, as common underlying molecular mechanisms between diseases may indicate that a drug used for one disease could successfully treat another. Pleiotropic variants between the 228 disease GWAS were identified via genomewide colocalization analysis using HyPrColoc. Potential repurposing candidates were selected by finding drugs currently used or in clinical trials for one of two diseases sharing a variant and testing if the drug targets matched genes functionally connected to the shared variant. This method identified 3625 drug repurpose candidates, suggesting an untapped potential in drug repurposing opportunities. Notably, there was particularly strong support for the use of TYK2 inhibitors in the treatment of autoimmune hypothyroidism. In this thesis I highlight functional mechanisms shared between critical Covid-19 and other diseases, identifying molecular pathways for potential therapeutic interventions. My results indicate that pleiotropic genetic variants are a valuable source of information for drug repurposing studies.

https://hdl.handle.net/1842/42679

http://dx.doi.org/10.7488/era/5373

en

The University of Edinburgh

genome-wide association studies

disease genetics

HyPrColoc (Hypothesis Prioritisation for multi-trait Colocalization)

pleiotropic variants

SLC39A8

genomewide colocalization analysis

TYK2 inhibitor

autoimmune hypothyroidism

Genetic pleiotropy in disease as a source of drug target discovery

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy