title: Integrated metabolomics and genomics: systems approaches to biomarkers and mechanisms of cardiovascular disease.
abstract: The genetic architecture underlying the heritability of cardiovascular disease is incompletely understood. Metabolomics is an emerging technology platform that has shown early success in identifying biomarkers and mechanisms of common chronic diseases. Integration of metabolomics, genetics, and other omics platforms in a systems biology approach holds potential for elucidating novel genetic markers and mechanisms for cardiovascular disease. We review important studies that have used metabolomic profiling in cardiometabolic diseases, approaches for integrating metabolomics with genetics and other molecular profiling platforms, and key studies showing the potential for such studies in deciphering cardiovascular disease genetics, biomarkers, and mechanisms.
authors.affiliation: From the Duke Molecular Physiology Institute (S.H.S., C.B.N.), Division of Cardiology, Department of Medicine (S.H.S., C.B.N.), Department of Pharmacology and Cancer Biology and Division of Endocrinology, Department of Medicine, and the Sarah W. Stedman Nutrition and Metabolism Center (C.B.N.), Duke University, Durham, NC. svati.shah@duke.edu.
authors.forename: Svati H
authors.initials: SH
authors.lastname: Shah
authors.affiliation: From the Duke Molecular Physiology Institute (S.H.S., C.B.N.), Division of Cardiology, Department of Medicine (S.H.S., C.B.N.), Department of Pharmacology and Cancer Biology and Division of Endocrinology, Department of Medicine, and the Sarah W. Stedman Nutrition and Metabolism Center (C.B.N.), Duke University, Durham, NC.
authors.forename: Christopher B
authors.initials: CB
authors.lastname: Newgard
mesh_terms: D015415:Biomarkers / Q000378:metabolism*; D002318:Cardiovascular Diseases / Q000235:genetics* / Q000378:metabolism*; D005260:Female; D005819:Genetic Markers; D023281:Genomics; D006801:Humans; D008297:Male; D055432:Metabolomics
chemical_list: D015415:Biomarkers; D005819:Genetic Markers
keywords: genomics; metabolism; metabolomics; risk factor