{"doi":"10.17615/m4tm-1251","title":"Metabolomics and Incident Hypertension Among Blacks: The Atherosclerosis Risk in Communities Study","abstract":"Development of hypertension is influenced by genes, environmental effects and their interactions, and the human metabolome is a measurable manifestation of gene-environment interaction. We explored the metabolomic antecedents of developing incident hypertension in a sample of African Americans, a population with a high prevalence of hypertension and its comorbidities. We examined 896 (565 females, aged 45–64 years) African American normotensives from the Atherosclerosis Risk in Communities (ARIC) Study, whose metabolome was measured in serum collected at the baseline examination and analyzed by high throughput methods. The analyses presented here focus on 204 stably measured metabolites over a period of 4–6 weeks. Weibull parametric models considering interval censored data were used to assess the hazard ratio for incident hypertension. We used a modified Bonferroni correction accounting for the correlations among metabolites to define a threshold for statistical significance (p<3.9×10−4). During 10-years of follow-up, 38% of baseline normotensives developed hypertension (N=344). With adjustment for traditional risk factors and estimated glomerular filtration rate, each +1-standard deviation difference in baseline 4-hydroxyhippurate, a product of gut microbial fermentation, was associated with 17% higher risk of hypertension (p=2.5×10−4), which remained significant after adjusting for both baseline systolic and diastolic blood pressure (p=3.8×10−4). After principal component analyses, a sex steroids pattern was significantly associated with risk of incident hypertension (highest versus lowest quintile hazard ratio, 1.72; 95% CI, 1.05 to 2.82; p for trend=0.03), and stratified analyses suggested that this association was consistent in both genders. Metabolomic analyses identify novel pathways in the etiology of hypertension.","journal":"UNC Libraries","year":2020,"id":112152,"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":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7416,"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":444602,"name":"T. H. Mosley","orcid":null,"position":1,"is_corresponding":false},{"id":532403,"name":"D. Alexander","orcid":null,"position":2,"is_corresponding":false},{"id":532404,"name":"J. A. Nettleton","orcid":null,"position":3,"is_corresponding":false},{"id":532405,"name":"G. Heiss","orcid":null,"position":4,"is_corresponding":false},{"id":532406,"name":"B. Yu","orcid":null,"position":5,"is_corresponding":false},{"id":31772,"name":"Y. Zheng","orcid":"0000-0002-4617-3252","position":6,"is_corresponding":false},{"id":431554,"name":"E. Boerwinkle","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:13:13.874980Z","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":[]}