Cardiovascular disease (CVD) represents the major source of morbidity and mortality. Despite maximal therapeutic intervention, significant risks remain. There is a critical need for discovery of pathways linked to CVD pathogenesis. The proposed studies combine unbiased metabolomics approaches, with more quantitative targeted analyses, and mechanistic animal models and human studies, to define novel analytes and pathways linked to CVD pathogenesis.
In aim 1, we propose new mechanistic studies in animal models of disease, and in humans, centered around a new and unpublished pathway discovered recently during performance of our initial unbiased metabolomics studies. We have accrued substantial preliminary data in both mouse models and human clinical investigations showing a dietary nutrient abundant in red meat is metabolized by gut flora and is linked to atherosclerosis. Unpublished targeted metabolomics studies, isotope tracer studies in germ free mice and humans ? antibiotic suppression, and additional mechanistic animal model studies, collectively indicate at least three distinct metabolites produced by gut flora may possess direct biological activity impacting upon atherosclerosis susceptibility and cholesterol metabolism.
In aim 2 we propose to substantially extend upon our initial unbiased metabolomics investigations using two distinct and well defined clinical cohorts. Studies in subjects undergoing elective cardiac evaluations and for whom long term follow-up is available will enable us to discover new analytes and pathways associated with development of atherosclerotic heart disease and its adverse complications heart attack, heart failure and death. While metabolomics studies in another, a clinical trial monitored by sequential coronary intravascular ultrasound [IVUS]), will allow us to define analytes and pathways associated with response to therapy for high potency statins. Successful completion of our proposed research program will provide opportunities for development of both novel diagnostic tests and therapeutic approaches for the treatment and prevention of atherosclerotic heart disease and its major complications. It will also further establish gut flora-dependent metabolism of an abundant nutrient in red meat as a new pathway for cardiovascular disease pathogenesis discovered through unbiased metabolomics.

Public Health Relevance

Despite the identification of numerous genetic and clinical risk factors for cardiovascular disease, we can still only explain in a small fraction of patients why that individual develops the disease, and many novel pathways contributing to disease still remain unexplored. The present studies will help identify novel pathways of clinical relevance with mechanistic links to cardiovascular disease pathogenesis and adverse sequelae such as myocardial infarction and heart failure, with the hope to better diagnose and treat or prevent disease progression. (End of Abstract)

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Exploratory Grants (P20)
Project #
1P20HL113452-01
Application #
8287207
Study Section
Special Emphasis Panel (ZHL1-CSR-Q (F2))
Program Officer
Srinivas, Pothur R
Project Start
2012-04-15
Project End
2017-02-28
Budget Start
2012-04-15
Budget End
2013-02-28
Support Year
1
Fiscal Year
2012
Total Cost
$711,453
Indirect Cost
$151,723
Name
Cleveland Clinic Lerner
Department
Other Basic Sciences
Type
Schools of Medicine
DUNS #
135781701
City
Cleveland
State
OH
Country
United States
Zip Code
44195
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Li, Daniel Y; Tang, W H Wilson (2018) Contributory Role of Gut Microbiota and Their Metabolites Toward Cardiovascular Complications in Chronic Kidney Disease. Semin Nephrol 38:193-205
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Li, Wei; Kennedy, David; Shao, Zhili et al. (2018) Paraoxonase 2 prevents the development of heart failure. Free Radic Biol Med 121:117-126
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Tang, W H Wilson; Wang, Zeneng; Li, Xinmin S et al. (2017) Increased Trimethylamine N-Oxide Portends High Mortality Risk Independent of Glycemic Control in Patients with Type 2 Diabetes Mellitus. Clin Chem 63:297-306
Blaženovi?, Ivana; Kind, Tobias; Torbašinovi?, Hrvoje et al. (2017) Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy. J Cheminform 9:32

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