Linking Metabolomics to Pharmacogenomics Cardiovascular disease (CVD) is the leading cause of mortality in men and women in the United States, accounting for 1 in every 2.8 deaths in 2005. The economic burden from CVD is enormous with an estimated total direct and indirect cost of CVD and stroke in the United States for 2009 of $475.3 billion. Antihypertensives and anti-platelet therapy are major classes of therapies used for the treatment and prevention of CVD. Controlling blood pressure and preventing platelet aggregation are major contributors toward reducing CVD events. While these therapies have demonstrated a remarkable degree of consistency in their ability to reduce risk for both CVD and stroke, residual CVD risk remains high, and potential drug-related adverse events are significant concerns. A deeper understanding of pathways implicated in variation in response could lead to more effective approaches for preventing and treating CVD and could result in """"""""personalized"""""""" drug therapy. We propose a partnership between the Metabolomics Network for Drug Response Phenotype and two centers of excellence within the Pharmacogenomics Research Network (PGRN)(both networks funded by NIGMS) for the purpose of gaining deeper understanding of mechanisms of variation in response to commonly used cardiovascular drugs: antihypertensives (atenolol and hydrochlorothiazide ) and antiplatelet therapies (clopidogrel and aspirin). We will leverage large investments already made by NIH in pharmacogenomics studies and state of art capabilities built by the Metabolomics Network to define pathways implicated in variation in response to those drugs. The scientific collaboration between the metabolomics network and the PGRN centers will create an environment in which a cooperative, iterative process of hypothesis generation and testing will be applied to achieve the union of metabolomics, pharmacologic and pharmacogenomic sciences. This """"""""union"""""""" will accelerate advances in our understanding of mechanisms of drug action and individual variation in the drug response phenotype making it possible to move toward a goal of truly """"""""personalized"""""""" or """"""""individualized"""""""" drug therapy. We hope to contribute to the mission of the American Recovery and Reinvestment Act by accelerating research in a clinically important area that relates to cardiovascular health. We will hire and train researchers in metabolomics, a new field that has been earmarked as important to develop under the NIH roadmap initiative. Additionally, we will contribute to advances in this field by building resources for the metabolomics community that includes standards for metabolomics, a national metabolomics database and metabolic pathway database that couples information about human metabolic pathways with the human genome.

Public Health Relevance

Antihypertensive and antiplatelet therapies are among the largest classes of drugs prescribed for cardiovascular disease prevention and treatment. Not all people respond similarly to treatment and while some benefit others do not and some develop intolerable side effects. In this proposal we bring the power of new metabolomics technologies together with pharmacogenomics technologies in defining pathways implicated in response to these major classes of therapies. Such knowledge can lead to more effective and personalized therapies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
High Impact Research and Research Infrastructure Programs (RC2)
Project #
5RC2GM092729-02
Application #
7943056
Study Section
Special Emphasis Panel (ZGM1-PPBC-0 (MT))
Program Officer
Okita, Richard T
Project Start
2009-09-30
Project End
2012-08-31
Budget Start
2010-09-01
Budget End
2012-08-31
Support Year
2
Fiscal Year
2010
Total Cost
$2,211,244
Indirect Cost
Name
Duke University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Liu, Duan; Ray, Balmiki; Neavin, Drew R et al. (2018) Beta-defensin 1, aryl hydrocarbon receptor and plasma kynurenine in major depressive disorder: metabolomics-informed genomics. Transl Psychiatry 8:10
Athreya, Arjun; Iyer, Ravishankar; Neavin, Drew et al. (2018) Augmentation of Physician Assessments with Multi-Omics Enhances Predictability of Drug Response: A Case Study of Major Depressive Disorder. IEEE Comput Intell Mag 13:20-31
Elbadawi-Sidhu, Mona; Baillie, Rebecca A; Zhu, Hongjie et al. (2017) Pharmacometabolomic signature links simvastatin therapy and insulin resistance. Metabolomics 13:
de Oliveira, Felipe A; Shahin, Mohamed H; Gong, Yan et al. (2016) Novel plasma biomarker of atenolol-induced hyperglycemia identified through a metabolomics-genomics integrative approach. Metabolomics 12:
Neavin, Drew; Kaddurah-Daouk, Rima; Weinshilboum, Richard (2016) Pharmacometabolomics informs Pharmacogenomics. Metabolomics 12:
Paley, Suzanne; Krummenacker, Markus; Karp, Peter D (2016) Representation and inference of cellular architecture for metabolic reconstruction and modeling. Bioinformatics 32:1074-9
Gupta, M; Neavin, D; Liu, D et al. (2016) TSPAN5, ERICH3 and selective serotonin reuptake inhibitors in major depressive disorder: pharmacometabolomics-informed pharmacogenomics. Mol Psychiatry 21:1717-1725
Rotroff, Daniel M; Oki, Noffisat O; Liang, Xiaomin et al. (2016) Pharmacometabolomic Assessment of Metformin in Non-diabetic, African Americans. Front Pharmacol 7:135
Shahin, Mohamed H; Gong, Yan; McDonough, Caitrin W et al. (2016) A Genetic Response Score for Hydrochlorothiazide Use: Insights From Genomics and Metabolomics Integration. Hypertension 68:621-9
Ellero-Simatos, Sandrine; Beitelshees, Amber L; Lewis, Joshua P et al. (2015) Oxylipid Profile of Low-Dose Aspirin Exposure: A Pharmacometabolomics Study. J Am Heart Assoc 4:e002203

Showing the most recent 10 out of 28 publications