Heart failure is a rapidly growing health problem, leading to death from arrhythmias or pump failure. Alterations in myocyte neurohumoral regulation, ion currents, calcium (Ca2+) handling, and contractility, accompanied by ventricular hypertrophy and structural remodeling all contribute to heart failure. Understanding the interactions of these complex biochemical and biophysical functions requires quantitative systems models that also integrate over multiple physical scales. Well-characterized and readily perturbed experimental systems are needed to validate computational models. There are now many gene-targeted mouse models that recapitulate major pathophysiological and clinical features of heart failure. The wealth of multi-scale data on alterations in signaling, electrophysiology, Ca2+ handling, myofilament function and tissue structure that can be measured in mice cannot be obtained in humans, but the new models proposed here will provide a systematic framework to extrapolate findings to the clinical setting. Ca2+-calmodulin dependent protein kinase (CaMKII) is upregulated and more active in heart failure, and is a key regulator of cellular subsystems contributing to acute mechanical and electrical dysfunction as well as chronic cardiac remodeling in heart failure. CaMKII overexpression leads to heart failure in mice, while CaMKII knockout or inhibition can protect against failure. While other pathways are also important, we focus here on mouse models in which multiple key heart failure phenotypes are all affected by null- or over-expression of CaMKII. We will take advantage of ongoing studies in our labs to extend the rich set of experimental data required for model formulation and validation. The investigators propose a closely integrated combination of novel experimental and computational studies that take advantage of strong interdisciplinary synergy between the PIs (Bers at UCD &McCulloch at UCSD) and collaborating faculty at Davis (Colleen Clancy and Leighton Izu), San Diego (Joan Heller Brown and Jeffrey Omens) and the University of Virginia (Jeffrey Saucerman).
The aims test our overall hypothesis that Ca2+-CaMKII signaling controls multiple multi-scale processes that synergize in maladaptive electrophysiological, Ca2+ handling, contractile and hypertrophic remodeling leading to heart failure, including: (1) crosstalk between 2-adrenergic receptor and CaMKII signaling;(2) triggered arrhythmia susceptibility at the subcellular, cellular, tissue and organ scales;(3) cardiac mechanical dysfunction at cell, tissue and organ scales;and (4) hypertrophic transcription and maladaptive remodeling in response to stress.
Each aim i ncludes the formulation and sensitivity analysis of new models, validation studies making use of genetically engineered mice, and testing of specific hypotheses. Models and data will be distributed freely and widely making use of software and database infrastructure supported by the National Biomedical Computation Resource at UCSD, via the CellML repository, and through new releases of LabHeart software tool developed by the UC Davis group.

Public Health Relevance

Heart failure is a growing public health problem that affects over 5 million Americans and has poor five-year survival. It is a complex syndrome that affects the hormonal, electrical and mechanical functions of the heart. This proposal uses the tools of systems biology, especially computer models and genetically engineered model organisms, to synthesize information on the diverse alterations in the failing heart into an integrated computer model for better understanding and treatment heart failure.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL105242-01A1
Application #
8211851
Study Section
Special Emphasis Panel (ZRG1-VH-D (50))
Program Officer
Larkin, Jennie E
Project Start
2012-03-01
Project End
2017-02-28
Budget Start
2012-03-01
Budget End
2013-02-28
Support Year
1
Fiscal Year
2012
Total Cost
$737,086
Indirect Cost
$110,816
Name
University of California San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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