Genetic and lifestyle modifiers of haemochromatosis-related clinical outcomes in HFE C282Y homozygotes: prospective cohort study in UK Biobank

BackgroundThe iron overload disease haemochromatosis is primarily caused by HFE p.C282Y homozygosity, yet penetrance of clinical outcomes (including liver disease/cancer) varies. We estimated the effect of genetic and lifestyle factors on disease penetrance and expressivity in C282Y homozygotes. MethodsWe analysed 2,893 C282Y homozygous UK Biobank participants (n=1,295 male). We ascertained haemochromatosis from medical records, liver disease/cancer, osteoarthritis, joint replacement surgeries, and dementia diagnoses. We derived polygenic scores (PGS) for iron biomarkers including hepcidin and transferrin saturation (TSAT). Sex-stratified logistic regression assessed associations with clinical outcomes. We used time-to-event regression estimating effects of age, lifestyle, and PGS. We estimated effects of rare HFE variants using whole genome sequencing data. ResultsIn male HFE C282Y homozygotes, higher TSAT PGS increased likelihood of diagnosis of haemochromatosis, and separately any clinical consequence (ORtop-vs-bottom-PGS-quintile=1.83, 95%CI: 1.26-2.66, p=0.001). Cumulative incidence of assessed haemochromatosis clinical outcomes in men by age 80 was 64.5% (highest quintile) versus 51.6% (lowest) (p-value for difference=0.025). In females, TSAT PGS increased haemochromatosis likelihood (cumulative incidence: 45.3% vs. 23.3% [highest/lower quintile], p=0.00001) but not liver disease. PGS for other iron biomarkers were not significantly associated with clinical outcomes. Rare heterozygous predicted loss-of-function variants in HFE increased haemochromatosis likelihood in non-C282Y homozygotes (aggregate-OR=14.8, 95%CI 4.7-41.1, p=0.003), highlighting the importance of sequencing undiagnosed individuals to find rare causes of haemochromatosis. ConclusionHigher genetically predicted transferrin saturation significantly increased risk of clinical outcomes in HFE C282Y homozygotes. Combined with modifiable lifestyle factors, genetic information could refine risk stratification and personalise iron monitoring, following validation.