Division of Cardiovascular Diseases Strategic Plan

Goals in Enabling Technologies and Methodologies for Cardiovascular Disease

1.1. Develop individualized/personalized medicine for cardiovascular diseases

Table of Contents

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Overview

Personalized medicine uses enabling technologies, along with clinical and environmental information about an individual, to tailor prevention, management, or treatment of a disease or condition for that individual.  These technologies include genetics, genomics, proteomics, and other ‘omics and bioengineering approaches.  Barriers may include timely translation of research findings, as well as a dearth of identification of molecular markers with proven clinical benefit, clinical trials, and application to clinical practice.  Novel research and translational strategies are needed to facilitate widespread use of personalized medicine in the clinic.

Strategies to Accomplish this Goal May Entail:

Basic Research:

  • Support comprehensive molecular approaches to identify genes/biomarkers for health and disease, or for response to therapy.
  • Develop new molecular approaches and technologies for characterizing an individual or animal model over time so that molecular and/or risk profiles/patterns can be developed, evaluated, and validated. Examples include:
    • Use of nanosystems to identify genetic variants that play a role in health and disease (especially for rare diseases such as congenital and pediatric heart diseases in which only a small sample size exists).
    • Apply a systems biology/medicine approach to pharmacogenomic studies of anti-hypertensive drugs.
    • Establish genetic, gene expression, proteomic, or other profiles of persons highly susceptible to acute coronary syndromes (ACS).

Translational Research:

  • Facilitate clinical research to provide an evidence base for the effect of genetics/genomics, and other ‘omics, on human health and disease. An example may be the development of novel approaches for discovering the clinical relevance of chromosomal regions identified by genome-wide association studies of disease where the candidate gene approach has not worked or is not appropriate because there are no known genes (e.g., the chromosome 9p21 association with coronary artery disease (CAD) and myocardial infarction (MI)). 
  • Develop new technologies to determine patterns of disease, disease progression, and prevention and treatment strategies.
    • Apply these technologies to human diseases to prevent or reverse the phenotypic expression of myocardial and rhythm disorders such as hypertrophic caridomyopathy (HCM) or sudden cardiac death (SCD).
    • Use innovative proteomic approaches to categorize and detect disease.
    • Develop bioengineering tools to assess energy balance and obesity.
  • Develop integrative approaches for combining results, data, and information from studies of genetics, genomics, proteomics, other ‘omics, imaging, and nanotechnology so that all relevant information for a particular disease or trait can be assessed and evaluated for a tailored clinical strategy. An example may be the use of proteomics and metabolomics coupled with other genetic information (e.g., family medical history) and environmental and lifestyle factors to generate a cardiovascular (CV) disease susceptibility pattern and/or risk profile to potentiate earlier prevention strategies, diagnosis, or therapy (e.g., for conditions such as atrial fibrillation, heart failure, or atherosclerosis).
  • Interpret and mine data, and integrate data with existing knowledge to extract the most complete and accurate information for evaluation, hypothesis development, and clinical application.
  • Improve the measurement and harmonization of phenotypes to facilitate wide-spread data sharing, collaboration, and data integration.
  • Consider and incorporate the ethical, legal, and social implication issues in research pertaining to personalized medicine.

Clinical Research:

  • Use in silico and statistical modeling/simulation strategies to design and inform genetic/pharmacogenetics clinical trials, so results can eventually be used for tailoring treatment or prevention. An example is the development of an in silico model to design and inform an anti-hypertensive pharmacogenetics clinical trial.
  • Develop and test novel technologies for diagnostics and treatment. An example is the use of molecular patterns to identify specific subclasses of obese or overweight individuals to enable design and evaluation of individualized prevention strategies or medical treatments.
  • Perform early-stage and preclinical trials that incorporate novel findings from gene identification and functional studies.
  • Use clinical studies (ongoing or new) to determine the importance of newly discovered molecular markers and signatures in treatment or intervention responses. Some examples may be conducting genetic, genomic, or proteomic studies ancillary to ongoing clinical trials.

Contributing Sources:

September 2008

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