One in 30 adults unknowingly carries a blister-like bulge on a brain artery that could burst and kill them. Doctors must decide whether to operate—risking a 5% chance of stroke—or leave the aneurysm alone and hope it never ruptures. Currently, they have almost no reliable way to predict which aneurysms will bleed. This project will collect DNA from 6,000 patients with brain aneurysms, sequence the entire genomes of 1,000 of them, and compare those sequences with data from 300,000 healthy people. The goal is to find rare and common genetic variants that drive both aneurysm formation and rupture. The researchers will then build a polygenic risk score—a personalised genetic test—and combine it with clinical and imaging data to create the most accurate rupture-prediction models ever developed. If successful, this would transform a gamble into a calculation. A patient diagnosed with an aneurysm could receive a personalised rupture risk estimate that accounts for their genetic makeup, allowing doctors to treat only those who truly need it and spare others unnecessary surgery. It could also identify molecular pathways for drug targets, potentially offering a non-surgical treatment option.
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Intracranial aneurysms are common and present in 3% of adults. They largely cause no symptoms, but occasionally rupture (˜1% of aneurysms rupture per annum) with catastrophic consequences (30% mortality, and high morbidity in survivors). They can be treated prophylactically (surgically or endovascularly) but treatment carries a 5% risk of stroke. The decision to treat is therefore difficult and needs personalisation, but there are few strong predictors of rupture to inform these decisions. The Risk of Aneurysm Rupture study (ROAR) was set up to address this issue and has collected data from 22,000 patients with intracranial aneurysms. This sample size is more than double the entire global literature. Previous studies are further limited by short length of follow-up (1-5 years). As patients are commonly diagnosed in their fifties and have life expectancies of over 30 years it has not been possible to calculate lifetime rupture risk which is critical for making treatment decisions. ROAR is therefore using national databases of hospital admissions and deaths to detect events of aneurysm rupture that will provide lifelong follow-up. There is a strong genetic component to the development of intracranial aneurysms. Twin studies have estimated heritability to be 41% and 16.4% of patients have an affected parent/sibling. Despite this, there is no genetic test to identify who is at risk and only a fraction of the heritability has been explained. What little is known relates to common polymorphisms with small effects in patients with sporadic aneurysms. Rare variants with larger effects are thought to play a critical role in heritability but have never been investigated. It is also strongly suspected that genetics play a significant role in the processes that lead to aneurysm rupture in addition to their role in development. However, data is limited to a single underpowered study and no current rupture risk prediction model includes family history or genetics. These genetic risk factors therefore need to be identified and added to predictive models to select patients for treatment. Our proposal is for a defining study of the genetics of aneurysm development and rupture. DNA from 6,000 ROAR patients (ROAR-DNA) will be collected. 1,000 with extreme phenotypes will undergo whole-genome sequencing (WGS). These will be combined with WGS data from 1,500 publicly available cases and 300,000 healthy controls. Rare and common variants associated with aneurysm formation and rupture will be identified using burden and single variant tests. Rare variants identified will be added to a customised genotyping array, which will be used to type the remaining 5,000 ROAR-DNA patients and over 3,000 patients from our ongoing GO-SAH study of ruptured aneurysms. The significance and effect-size of both rare and common variants will be determined by a final meta-analysis involving over 10,000 patients with rare variant data. The study aims to identify rare and common genetic variants: Associated with aneurysm formation – To select for aneurysm screening Associated with aneurysm rupture – To select for aneurysm treatment That identify underlying molecular pathways – To target therapeutically Aim 2 will go on to develop a polygenic risk score, which will be combined with detailed baseline clinical and imaging data from ROAR to build the most accurate aneurysm rupture prediction models available. Crucially, these models will be personalised to estimate an individual’s rupture risk incorporating both traditional factors and genetic predisposition for the first time.
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