{"doi":"10.1101/2022.05.05.22274399","title":"A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage","abstract":"ABSTRACT Background Intracerebral hemorrhage (ICH), the most fatal form of stroke, has an estimated heritability of 29%. Applying a meta-scoring approach, we developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors. Methods Using a meta-analytic approach, we combined genome-wide association data from individuals of European ancestry for ICH and ICH-related traits in a meta-genomic risk score (metaGRS) consisting of 2.6 million variants. We tested associations with ICH and the predictive performance of the metaGRS in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). Furthermore, we tested associations with risk of incident ICH in the population-based UK Biobank cohort (486,784 individuals, 1,526 events, median follow-up 11.3 years). Results One SD increment in the metaGRS was significantly associated with 45% higher odds for ICH (OR 1.45; 95%CI: 1.30-1.63) in age- and sex-adjusted models and 31% higher odds for ICH (OR: 1.31, 95%CI: 1.16-1.48) in models further adjusted for clinical risk factors. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (OR: 4.83, 95%CI: 1.56-21.2). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared with clinical risk factors alone (c-index: 0.695 vs. 0.686). The metaGRS showed similar associations for both lobar and non-lobar ICH, which were independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (HR: 1.15, 95%CI: 1.09-1.21). The associations were significant within both a relatively high-risk population of users of antithrombotic medications, 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.","journal":"medRxiv","year":2022,"id":300120,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9422,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":625434,"name":"Marios K. Georgakis","orcid":"0000-0003-3507-3659","position":1,"is_corresponding":false},{"id":654921,"name":"Stacie L Demel","orcid":"0000-0002-3000-8420","position":2,"is_corresponding":false},{"id":523912,"name":"Padmini Sekar","orcid":"0000-0002-3734-5075","position":3,"is_corresponding":false},{"id":561978,"name":"Jaeyoon Chung","orcid":"0000-0002-6431-9454","position":4,"is_corresponding":false},{"id":302170,"name":"Rainer Malik","orcid":"0000-0001-9212-2520","position":5,"is_corresponding":false},{"id":580486,"name":"Hyacinth I. Hyacinth","orcid":"0000-0002-1991-7463","position":6,"is_corresponding":false},{"id":550883,"name":"Mary E. Comeau","orcid":"0000-0001-7079-8781","position":7,"is_corresponding":false},{"id":256546,"name":"Guido J. Falcone","orcid":"0000-0002-6407-0302","position":8,"is_corresponding":false},{"id":130814,"name":"Carl D. Langefeld","orcid":null,"position":9,"is_corresponding":false},{"id":268233,"name":"Jonathan Rosand","orcid":"0000-0002-1014-9138","position":10,"is_corresponding":false},{"id":74995,"name":"Daniel Woo","orcid":"0000-0002-2466-7155","position":11,"is_corresponding":false},{"id":274758,"name":"Christopher D. Anderson","orcid":"0000-0002-0053-2002","position":12,"is_corresponding":false},{"id":748370,"name":"Evangelos P. Myserlis","orcid":"0000-0002-7310-624X","position":0,"is_corresponding":true}],"reference_count":54,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:31:49.412501Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}