Recipient organisationUniversity of ExeterSource-published name: University of Exeter
Funding£1.0M
PeriodDec 2025 — Nov 2028
In plain English
AI plain-English summary
One in 150 Northern Europeans carry two copies of a genetic variant that causes iron overload, yet most will never be diagnosed before irreversible organ damage sets in. This project tackles a critical gap: doctors cannot predict which patients with haemochromatosis will develop liver disease, diabetes, or dementia, and whether the standard treatment—routine blood removal—prevents all symptoms. Using genetic and medical record data from over 17 million UK patients and 500,000 UK Biobank participants, the researchers aim to identify the genetic and clinical factors that separate those who stay healthy from those who suffer severe outcomes. If successful, the work will produce a clinical prediction index called “H-risk” that flags undiagnosed patients based on routine GP data. Earlier diagnosis could shift treatment from managing late-stage organ failure to preventing it entirely. The discovery of rare mutations in novel genes may also reveal new drug targets for iron regulation. This is applied precision medicine: better screening, earlier intervention, and a direct reduction in the liver cancer, diabetes, and joint damage that currently define the disease for most patients.
View original technical description
Genetic haemochromatosis results in too much iron accumulating in the body. This can result in liver disease, liver cancer, diabetes, musculoskeletal problems, dementia, and early death. Changes in a person’s DNA (genetic variants) can predispose to haemochromatosis. The strongest risk factor is a genetic variant in the HFE gene, with 1 in 150 Northern Europeans carrying two copies (C282Y homozygotes), though other variants can also affect iron (e.g. HFE-H63D). There is substantial variability in symptoms and outcomes of haemochromatosis: presenting symptoms often appear non-specific (fatigue and joint pain), with most patients diagnosed late or missed entirely. In our study within UK Biobank, only 40-50% of C282Y homozygotes were diagnosed by age 80 (Lucas 2024). Many patients are diagnosed only after irreversible organ damage has occurred, and over half of diagnoses occur after age 60. Haemochromatosis can be partially treated by a routine procedure to remove blood (venesection) that reduces excess stored iron, reducing liver disease risk. However, it remains unclear which patients need early/intensive treatment, or whether venesection treatment alone prevents all the non-liver symptoms. We aim to discover genetic and clinical features that could help identify which people will develop organ damage in haemochromatosis, to prioritise patients for further investigation. Data for millions of people linking genetics and electronic medical records are becoming available for health research. We will leverage these to study the genetic and clinical modifiers of haemochromatosis to better understand the symptoms and progression of this disease over time. This project builds on our work in the UK Biobank cohort of 500,000 people, where we estimated the incidence of haemochromatosis complications across HFE genotype groups to older ages, modelling differences between males and females, and demonstrated the impact of known common iron-related genetic variants on risk of severe outcomes. The GEM-H project will significantly extend this by: 1) Discovering genetic factors that explain differences in clinical outcomes. Through the UK Biobank and United States ‘All of Us’ research studies, we now have data on >1billion genetic variants. Our pilot analysis has identified mutations that may explain why some C282Y homozygotes develop haemochromatosis, where others don’t. We will extend this work to explore why some non-C282Y homozygotes develop iron overload. 2) Uncovering the diverse pathways to haemochromatosis diagnosis and the factors driving variability in patient outcomes. In our own Patient Forum, it was clear that the symptoms and patterns of patient-healthcare interactions prior to diagnosis vary dramatically between patients. We will use UK-based primary care data from >17million patients (Clinical Practice Research Datalink, CPRD) to determine the clinical features (e.g., symptoms) preceding diagnosis, and effects on clinical outcomes. 3) Developing a haemochromatosis clinical prediction index (“H-risk”). We will develop a risk prediction model to identify undiagnosed patients likely to have haemochromatosis based on routinely available clinical features. To overcome inconsistent diagnostic practices, the predictive model will be developed in UK Biobank to identify C282Y homozygotes. We will then test the clinical utility of this model in CPRD to see how well it predicts clinically diagnosed haemochromatosis and associated clinical complications. Our results will reveal new biology (rare mutations in a novel gene can highlight potential drug targets for haemochromatosis) and improve precision medicine (clinical prediction models). These discoveries have the potential to improve diagnosis, leading to earlier intervention, reducing disease severity and improving patient quality of life.
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