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

目前迫切需要识别有动脉瘤和夹层风险的个体，因为这种情况通常是沉默的，直到发生灾难性的并发症，如破裂或夹层。早期识别高危人群可以采取预防措施，如血压控制和预防性手术。用横断显像筛查全体人群的胸主动脉疾病是不实用、不安全、也不经济可行的。然而，对于高危个体（例如患者的一级亲属），筛查可能是合理的。目前腹主动脉瘤的筛查项目的检出率很低（约1%的被扫描者为AAA级），大约10%的主动脉破裂发生在英国目前提倡的筛查年龄以下。AAA筛查也受到女性未接受筛查的限制（尽管女性占AAA相关死亡人数的42%）。在乳腺癌方面，研究表明，在国家筛查方案中加入遗传和/或临床信息，有可能降低有资格接受正式筛查试验的人口比例，确定风险最高的年轻个体（目前不符合筛查条件），并减少筛查的危害（如过度诊断/治疗）。这些因素与AAD有关，但尚未得到评估。AAD易感性具有较强的遗传成分，低风险的常见遗传变异、中等风险的罕见遗传变异和高渗透的非常罕见遗传变异均起作用。在精准医疗模式下，利用遗传和/或其他临床数据可以识别出主动脉疾病高危人群，从而制定个性化筛查和预防措施。在这个研究项目中，我们的目标是量化AAD的绝对风险，根据年龄、性别、临床和遗传风险因素进行分层，使用UKBiobank和来自OxVasc研究的主要发病率数据。当这已经执行，我们将能够模拟潜在的可行性分层筛选算法。作为延伸，我们的目标是描述人群中无症状个体携带的罕见的中等风险变异的表型后果。为了做到这一点，我们将评估UKBiobank中这些携带者的影像学发现，并对UKInterval研究中招募的个体进行基因型召回研究。罕见的，中等风险变异的携带者将被召回进行详细的表型评估，包括高级主动脉成像研究。

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.