Abstract Body (Do not enter title and authors here): Background
Familial hypercholesterolemia (FH) is an inherited disorder resulting in high levels of LDL-C from birth. Premeature coronary heart disease occurs in half of affected men by age 50 years. While many genetic variants that cause FH are well understood, many other variants in FH genes are of uncertain clinical significance. Furthermore, the variability in residual cardiovascular risk of FH carriers after statin treatment is not fully understood. We here investigate whether metabolomic and genomic data from the UK Biobank cohort can aid in interpretation of candidate pathogenic FH variants, and characterise future risk of severe cardiac events in FH carriers.

Methods
We have quantified 249 metabolomic parameters in 490,830 blood samples from UK Biobank cohort. Among 186,483 participants with exome sequence data we identified 896 who carried known pathogenic FH variants and 405 who carried variants of unknown significance in an established FH gene. We fitted a logistic predictive model to identify pathogenic mutations using LDL levels, statin use and 17 principal components of the metabolomic parameters. We further tested whether metabolomic and genomic scores for predicting future risk of myocardial infarction (MI), trained in the general population (i.e. individuals without FH), could predict risk in FH carriers.

Results
A model including all metabolites had a higher accuracy at identifying known pathogenic FH variants compared to LDL and statin use alone. Our model identified 8 FH variants marked as uncertain significance in ClinVar with significant evidence of predicted pathogenicity. We found that our metabolomic risk score predicted 10-year risk of MI among FH carriers (HR=1.96 per SD, p = 0.0011). This was stronger than the effect in the general population (HR = 1.64 per SD, p = 2.5e-168). A combined metabolomic and polygenic risk score had an even larger effect at predicting MI in carriers (HR = 3.06 per SD, p = 2.0e-6), and was significantly better at predicting MI in carriers than in non-carriers (HR = 3.06 vs 1.88 per SD, interaction p = 0.042).

Conclusion
Familial hypercholesterolemia is an important source of risk for early cardiovascular disease. Population-scale metabolomics can help distinguish pathogenic from benign variants that have not yet been characterised. Metabolomic and genomic scores can also identify individuals at most elevated risk, and provide even more information to FH individuals than in the general population.