{"doi":"10.1161/jaha.119.015299","title":"Epigenomic Assessment of Cardiovascular Disease Risk and Interactions With Traditional Risk Metrics","abstract":"Background Epigenome-wide association studies for cardiometabolic risk factors have discovered multiple loci associated with incident cardiovascular disease (CVD). However, few studies have sought to directly optimize a predictor of CVD risk. Furthermore, it is challenging to train multivariate models across multiple studies in the presence of study- or batch effects. Methods and Results Here, we analyzed existing DNA methylation data collected using the Illumina HumanMethylation450 microarray to create a predictor of CVD risk across 3 cohorts: Women's Health Initiative, Framingham Heart Study Offspring Cohort, and Lothian Birth Cohorts. We trained Cox proportional hazards-based elastic net regressions for incident CVD separately in each cohort and used a recently introduced cross-study learning approach to integrate these individual scores into an ensemble predictor. The methylation-based risk score was associated with CVD time-to-event in a held-out fraction of the Framingham data set (hazard ratio per SD=1.28, 95% CI, 1.10-1.50) and predicted myocardial infarction status in the independent REGICOR (Girona Heart Registry) data set (odds ratio per SD=2.14, 95% CI, 1.58-2.89). These associations remained after adjustment for traditional cardiovascular risk factors and were similar to those from elastic net models trained on a directly merged data set. Additionally, we investigated interactions between the methylation-based risk score and both genetic and biochemical CVD risk, showing preliminary evidence of an enhanced performance in those with less traditional risk factor elevation. Conclusions This investigation provides proof-of-concept for a genome-wide, CVD-specific epigenomic risk score and suggests that DNA methylation data may enable the discovery of high-risk individuals who would be missed by alternative risk metrics.","journal":"Journal of the American Heart Association","year":2020,"id":61882,"datarank":1.8195908062377,"base_score":4.007333185232471,"endowment":4.007333185232471,"self_citation_contribution":0.6010999777848708,"citation_network_contribution":1.218490828452829,"self_endowment_contribution":0.6010999777848708,"citer_contribution":1.218490828452829,"corpus_percentile":null,"corpus_rank":null,"citation_count":54,"citer_count":44,"citers_with_citation_signal":37,"citers_with_endowment":37,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.913,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":326886,"name":"Alba Fernández‐Sanlés","orcid":"0000-0002-3587-8177","position":1,"is_corresponding":false},{"id":326887,"name":"Prasad Patil","orcid":"0009-0007-6092-2268","position":2,"is_corresponding":false},{"id":326888,"name":"Paola Sebastiani","orcid":"0000-0001-6419-1545","position":3,"is_corresponding":false},{"id":326889,"name":"Paul F. Jacques","orcid":"0000-0001-5567-3147","position":4,"is_corresponding":false},{"id":256443,"name":"John M. Starr","orcid":"0009-0007-0801-0165","position":5,"is_corresponding":false},{"id":109450,"name":"Ian J. Deary","orcid":"0000-0002-1733-263X","position":6,"is_corresponding":false},{"id":326890,"name":"Qing Liu","orcid":"0000-0003-3173-9492","position":7,"is_corresponding":false},{"id":281196,"name":"Simin Liu","orcid":"0000-0003-2098-3844","position":8,"is_corresponding":false},{"id":1147,"name":"Roberto Elosúa","orcid":"0000-0001-8235-0095","position":9,"is_corresponding":false},{"id":24957,"name":"Dawn L. DeMeo","orcid":"0000-0001-9653-0636","position":10,"is_corresponding":false},{"id":88925,"name":"José M. Ordovás","orcid":"0000-0002-7581-5680","position":11,"is_corresponding":false},{"id":326885,"name":"Kenneth E. Westerman","orcid":"0000-0001-7619-1868","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-18T21:09:47.114172Z","pmid":"32308120","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":[]}