Uncovering shared genetic and molecular mechanisms in multiple long-term conditions through multi-trait and multiomics approaches

About the Project

This project is an example of the type of approaches that can be applied to a wide range of multiple long-term conditions.

Thyroid disorders are common, affecting an estimated 1 in 20 people in the UK (British Thyroid Foundation, 2025). Thyroid disorders have long been known to impact cardiovascular function, producing some of the classical signs and symptoms of thyroid disease (Cappola et al, 2019). More recently, observational studies have shown that even minor changes in circulating thyroid hormone levels, in the absence of overt thyroid disease, can increase vascular morbidity and mortality by 20-80% (Jabbar et al, 2016). Under- and overtreatment of hypothyroidism has also been associated with substantially increased risk of cardiovascular events and mortality (Lillejang-Johansen et al, 2019). This risk is thought to be mediated by broad and diverse effects, including on lipid metabolism, cardiac electrophysiology and arrhythmias, myocardial function and haemodynamics (Cappola et al, 2019).

However, there remain substantial gaps in knowledge regarding the precise biological mechanism underlying many of these effects, and whether and how they might effectively be targeted for therapeutic intervention. Given that cardiovascular and thyroid disease are both common, producing a burden of morbidity and mortality that will continue to increase as the population ages, research to better understand their interaction and how best to manage this is of growing importance.

We hypothesise that thyroid hormones influence risk of onset of cardiovascular diseases, and that identifying novel genetic and molecular pathways will reveal new therapeutic targets. Using multi-trait and multi-omics analyses, this project will:

• Analyse large-scale multiomics data from diverse cohorts such as UK Biobank, AllofUS, and Leicester’s EXCEED cohort.
• Characterize shared genetic architecture and variants linking thyroid hormone, cardiometabolic traits and cardiovascular disease.
• Apply Mendelian Randomization analysis to identify proteins/metabolites with causal roles in thyroid-associated cardiovascular disease.
• Conduct pathway enrichment analysis and protein network analysis to uncover the shared pathways and aetiological factors driving both thyroid dysfunction and cardiovascular disease.
• Develop pathway partitioned polygenic risk scores, and evaluate its performance in stratification and prediction of cardiovascular disease.

Training and Environment

You will be based in the world-leading Genetic Epidemiology research group. The group currently hosts 17 PhD students and has an exceptional track record in developing talented postgraduate researchers who go on to successful postdoctoral careers in academia and in industry. You will have access to the NIHR Biomedical Research Centre, high-performance computing facilities, and expert supervision in statistical genetics, genetic epidemiology, and bioinformatics. Our strong collaborations with clinical and functional genomics experts will provide you with opportunities to gain further insights into translation. You will be encouraged to take up opportunities for experience of public outreach and engagement.

Expected Outcomes

The project will uncover shared genetic architecture and variants underpinning shared biological factors for thyroid hormone, cardiometabolic traits and cardiovascular disease, identify proteins/metabolites with causal roles in thyroid-associated cardiovascular disease, and develop polygenic risk scores for personalised genetic prediction. These findings will contribute to personalised medicine, helping clinicians and patients make better-informed decisions. You will present your emerging findings to academics and clinicians at relevant conferences, and will be encouraged to contribute to publications.