Building a comprehensive aortic aneurysm and dissection prediction model incorporating genetic and non-genetic factors

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There is an urgent need to identify individuals at risk of aortic aneurysms and dissections as the condition is usually silent until a catastrophic complication such as rupture or dissection occurs. Early identification of those at elevated risk may allow preventative measures, such as blood pressure control and prophylactic surgery, to be instituted. Screening the entire population for thoracic aortic disease with cross-sectional imaging is not practical, safe or financially feasible. Screening may be justified, however, in high risk individuals (for example first degree relatives of patients). The current screening program for abdominal aortic aneurysm has a low-yield (~1% of all those scanned have a AAA) and approximately 10% of aortic ruptures occur below the age of screening currently advocated in the UK. AAA screening is also limited by the fact that females are not offered screening (despite representing 42% of AAA related deaths). In breast cancer it has been shown that addition of genetic and or clinical information to national screening programs has the potential to reduce the proportion of the population eligible for formal screening tests, identify younger individuals at highest risk (currently ineligible for screening) and reduce the harms of screening (such as overdiagnosis/treatment). These factors are relevant in AAD but as yet have not been evaluated.Susceptibility to AAD has a strong genetic component and low-risk common genetic variants, intermediate risk rare variants and highly penetrant very rare genetic variants all play a role. Under a precision medicine model, the use of genetic and/or other clinical data may identify individuals at high risk of aortic diseases may allow development of personalised screening and prevention measures. In this program of research we aim to quantify the absolute risk of AAD, stratified by age, gender, clinical and genetic risk factors using both the UKBiobank and primary incidence data derived from the OxVasc study. When this has been performed we will be able to model the potential feasibility of stratified screening algorithm.As an extension to this, we aim to characterise the phenotypic consequence of rare, intermediate risk variants that are carried by asymptomatic individuals in the population. In order to do this we will evaluate imaging findings of such carriers in the UKBiobank and also perform a recall by genotype study for individuals recruited to the UKInterval study. Carriers of rare, intermediate risk variants will be recalled for detailed phenotypic evaluation including advanced aortic imaging studies.