A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage

Abstract

Background: Intracerebral hemorrhage (ICH) has an estimated heritability of 29%. We developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors. Methods: We combined genome-wide association data from individuals of European ancestry for ICH and related traits in a meta-genomic risk score ([metaGRS]; 2.6 million variants). We tested associations with ICH and its predictive performance in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). We tested associations with risk of incident ICH in the population-based UK Biobank cohort (486 784 individuals, 1526 events, median follow-up 11.3 years). Results: One SD increment in the metaGRS was significantly associated with 31% higher odds for ICH (95% CI, 1.16–1.48) in age-, sex- and clinical risk factor-adjusted models. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (odds ratio, 4.83 [95% CI, 1.56–21.2]). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared to the clinical risk factors alone (c-index, 0.695 versus 0.686). The metaGRS showed similar associations for lobar and nonlobar ICH, independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (hazard ratio, 1.15 [95% CI, 1.09–1.21]). The associations were significant within both a relatively high-risk population of antithrombotic medications users, as well as among a relatively low-risk population with a good control of vascular risk factors and no use of anticoagulants. Conclusions: We developed and validated a genomic risk score that predicts lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry. Whether implementation of the score in risk prognostication models for high-risk populations, such as patients under antithrombotic treatment, could improve clinical decision making should be explored in future studies.