{"doi":"10.1161/str.43.suppl_1.a12","title":"Abstract 12: Heritability of Ischemic Stroke and its Subtypes","abstract":"<jats:p>\n            <jats:bold>Background and Purpose:</jats:bold>\n            Family-based methods for estimating heritability cannot discriminate between shared genetic and shared environmental exposures. Recently, methods have been developed for estimating heritability in population samples using genome-wide SNPs. We used the approach developed by Visscher and colleagues to estimate the heritability of ischemic stroke in Caucasian subjects. In addition to evaluating the overall heritability of ischemic stroke, we assessed whether stroke heritability varies by age, gender, and stroke subtype.\n          </jats:p>\n          <jats:p>\n            <jats:bold>Methods:</jats:bold>\n            Using publicly available software (GCTA and PLINK), we estimated ischemic stroke heritability stratified by age and gender using genome-wide association (GWA) data from three Caucasian ischemic stroke studies: Ischemic Stroke Genetics Study (ISGS), Bio-Repository of DNA in Stroke (BRAINS), and Genetics of Early-Onset Stroke (GEOS). Weighted means of site-specific heritability point estimates were combined according to a standard fixed effects model.\n          </jats:p>\n          <jats:p>\n            <jats:bold>Results:</jats:bold>\n            <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"g2248_1.gif\"/>\n          </jats:p>\n          <jats:p>\n            <jats:bold>Conclusions:</jats:bold>\n            A SNP-based approach may be useful in discerning differences in ischemic stroke heritability between different cohorts and subtypes. Overall, our analysis estimated ischemic stroke heritability to be 31% (SE = 7%), with a suggestion of higher heritability for younger cases. Small vessel stroke showed the highest heritability (58 ± 19%), with cardioembolic showing the lowest heritability (16 ± 14%). It should be emphasized that heritability estimates are population-specific and that the method used only reflects the heritability captured by common SNP variants measured in GWA studies, and not phenotypic variability explained by rare variants.\n          </jats:p>","journal":"Stroke","year":2012,"id":47014,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":217190,"name":"Michael A Nalls","orcid":null,"position":1,"is_corresponding":false},{"id":217191,"name":"John W Cole","orcid":null,"position":2,"is_corresponding":false},{"id":111174,"name":"Pankaj Sharma","orcid":null,"position":3,"is_corresponding":false},{"id":217192,"name":"James F Meschia","orcid":null,"position":4,"is_corresponding":false},{"id":217193,"name":"Yu-Ching Cheng","orcid":null,"position":5,"is_corresponding":false},{"id":217194,"name":"Steven J Kittner","orcid":null,"position":6,"is_corresponding":false},{"id":217195,"name":"Jeffrey R O'Connell","orcid":null,"position":7,"is_corresponding":false},{"id":217196,"name":"Braxton D Mitchell","orcid":null,"position":8,"is_corresponding":false},{"id":217189,"name":"Andrew E Bluher","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Abstract 12: Heritability of Ischemic Stroke and its Subtypes","abstract":"<jats:p>\n            <jats:bold>Background and Purpose:</jats:bold>\n            Family-based methods for estimating heritability cannot discriminate between shared genetic and shared environmental exposures. Recently, methods have been developed for estimating heritability in population samples using genome-wide SNPs. We used the approach developed by Visscher and colleagues to estimate the heritability of ischemic stroke in Caucasian subjects. In addition to evaluating the overall heritability of ischemic stroke, we assessed whether stroke heritability varies by age, gender, and stroke subtype.\n          </jats:p>\n          <jats:p>\n            <jats:bold>Methods:</jats:bold>\n            Using publicly available software (GCTA and PLINK), we estimated ischemic stroke heritability stratified by age and gender using genome-wide association (GWA) data from three Caucasian ischemic stroke studies: Ischemic Stroke Genetics Study (ISGS), Bio-Repository of DNA in Stroke (BRAINS), and Genetics of Early-Onset Stroke (GEOS). Weighted means of site-specific heritability point estimates were combined according to a standard fixed effects model.\n          </jats:p>\n          <jats:p>\n            <jats:bold>Results:</jats:bold>\n            <jats:inline-graphic xmlns:xlink=\"http://www.w3.org/1999/xlink\" xlink:href=\"g2248_1.gif\"/>\n          </jats:p>\n          <jats:p>\n            <jats:bold>Conclusions:</jats:bold>\n            A SNP-based approach may be useful in discerning differences in ischemic stroke heritability between different cohorts and subtypes. Overall, our analysis estimated ischemic stroke heritability to be 31% (SE = 7%), with a suggestion of higher heritability for younger cases. Small vessel stroke showed the highest heritability (58 ± 19%), with cardioembolic showing the lowest heritability (16 ± 14%). It should be emphasized that heritability estimates are population-specific and that the method used only reflects the heritability captured by common SNP variants measured in GWA studies, and not phenotypic variability explained by rare variants.\n          </jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"18998783","pmcid":null,"openalex_id":"https://openalex.org/W2268458112","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.22241775,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://journals.lww.com/00007670-201202001-00024","host_type":"publisher"},{"url":"https://doi.org/10.1161/str.43.suppl_1.a12","host_type":"journal"}],"fields_of_study":["Cardiovascular Health and Risk Factors"],"mesh_terms":[],"keywords":["Heritability","Medicine","Stroke (engine)","Missing heritability problem","Genome-wide association study","Genetic association","Population","Ischemic stroke","SNP","Single-nucleotide polymorphism","Demography","Genetics","Internal medicine","Biology","Genotype","Environmental health","Gene"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Reduced inequalities"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-15T04:56:06.317269Z","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":[]}