Cardiac remodeling is a central feature of human heart failure and shows substantial variation in human subjects. A decade of research in murine models and research in humans performed by the Principal Investigator show that a discreet set of cardiac transcription factors integrate stress signals to cause cardiac remodeling. Our central hypothesis is that common genetic variation in a core set of cardiac transcription factors (MEF2, NKX, NFAT, GATA, FOX) is in large part responsible for the variable course of cardiac remodeling in humans. We will address this hypothesis by performing SNP- and haplotype-based association studies of candidate transcription factors in two existing cohort studies that capture the common phenotypes of remodeling encountered in clinical practice.
In Aim 1 we will test the hypothesis that variation in candidate transcription factors is associated with concentric cardiac remodeling in the Chronic Renal Insufficiency Cohort study (CRIC), a large cohort with a high prevalence of concentric remodeling.
In Aim 2 we will perform similar analyses in the Penn Heart Failure Study, a large single-center cohort initiated by the applicant with a high prevalence of eccentric remodeling.
In aim 3 we will collaborate with an expert molecular biologist at Penn, Dr. Edward Morrisey, to determine the mechanisms by which the observed risk variants alter transcription factor function using in vitro techniques. This application uses genomic approaches to study cardiac transcription factors directly in human subjects with common forms of heart disease. The use of two established cohorts with large sample sizes and quantitative echocardiography will provide the phenotypic data necessary to address our hypotheses definitively, and will capitalize on investments already made in establishing large, well-phenotyped cohorts. By focusing on factors of central importance in animal models that have not been adequately studied in humans, our findings will translate years of basic research into a mechanistic understanding of human cardiac remodeling. Most importantly, we expect to determine and validate genomic predictors of cardiac remodeling that may have clinical applications as tools to predict prognosis and to select high-risk patients for aggressive therapy. ? ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL088577-02
Application #
7474692
Study Section
Cardiovascular and Sleep Epidemiology (CASE)
Program Officer
Adhikari, Bishow B
Project Start
2007-08-01
Project End
2012-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
2
Fiscal Year
2008
Total Cost
$711,646
Indirect Cost
Name
University of Pennsylvania
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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French, Benjamin; Wang, Le; Ky, Bonnie et al. (2016) Prognostic Value of Galectin-3 for Adverse Outcomes in Chronic Heart Failure. J Card Fail 22:256-62
French, Benjamin; Saha-Chaudhuri, Paramita; Ky, Bonnie et al. (2016) Development and evaluation of multi-marker risk scores for clinical prognosis. Stat Methods Med Res 25:255-71
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AbouEzzeddine, Omar F; French, Benjamin; Mirzoyev, Sultan A et al. (2016) From statistical significance to clinical relevance: A simple algorithm to integrate brain natriuretic peptide and the Seattle Heart Failure Model for risk stratification in heart failure. J Heart Lung Transplant 35:714-21
Löffler, Adrián Ignacio; Cappola, Thomas P; Fang, James et al. (2015) Effect of renal function on prognosis in chronic heart failure. Am J Cardiol 115:62-8
Jia, Cheng; Guan, Weihua; Yang, Amy et al. (2015) MetaDiff: differential isoform expression analysis using random-effects meta-regression. BMC Bioinformatics 16:208
Liu, Yichuan; Morley, Michael; Brandimarto, Jeffrey et al. (2015) RNA-Seq identifies novel myocardial gene expression signatures of heart failure. Genomics 105:83-9
Vorovich, Esther; French, Benjamin; Ky, Bonnie et al. (2014) Biomarker predictors of cardiac hospitalization in chronic heart failure: a recurrent event analysis. J Card Fail 20:569-76
Zhang, Kathleen W; French, Benjamin; May Khan, Abigail et al. (2014) Strain improves risk prediction beyond ejection fraction in chronic systolic heart failure. J Am Heart Assoc 3:e000550

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