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Next Steps in Cardiovascular Disease Genomic Research-Sequencing, Epigenetics, and Transcriptomics

期刊

CLINICAL CHEMISTRY
卷 58, 期 1, 页码 113-126

出版社

AMER ASSOC CLINICAL CHEMISTRY
DOI: 10.1373/clinchem.2011.170423

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资金

  1. Evans Center for Interdisciplinary Biomedical Research ARC on Atrial Fibrillation at Boston University
  2. Deutsche Forschungsgemeinschaft (German Research Foundation) [SCHN 1149/3-1]
  3. National Institute of Environmental Health Sciences [P30ES000002, R21ES019773, R01ES015172]
  4. NIH [1R01HL092577, 5R21DA027021, 5R01HL104156, 1K24HL105780, 1RC1HL101056, 1R01HL102214, 1R01AG028321]
  5. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL104156, K24HL105780, RC1HL101056, R01HL102214, R01HL092577] Funding Source: NIH RePORTER
  6. NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES [R01ES015172, P30ES000002, R21ES019773] Funding Source: NIH RePORTER
  7. NATIONAL INSTITUTE ON AGING [R01AG028321] Funding Source: NIH RePORTER
  8. NATIONAL INSTITUTE ON DRUG ABUSE [R21DA027021] Funding Source: NIH RePORTER

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BACKGROUND: Genomic research in cardiovascular disease (CVD) has progressed rapidly over the last 5 years. In most cases, however, these groundbreaking observations have not yet been accompanied by clinically applicable tools for risk prediction, diagnosis, or therapeutic interventions. CONTENT: We reviewed the scientific literature published in English for novel methods and promising genomic targets that would permit large-scale screening and follow-up of recent genomic findings for CVD. We anticipate that advances in 3 key areas will be critical for the success of these projects. First, exome-centered and whole-genome next-generation sequencing will identify rare and novel genetic variants associated with CVD and its risk factors. Improvements in methods will also greatly advance the field of epigenetics and gene expression in humans. Second, research is increasingly acknowledging that static DNA sequence variation explains only a fraction of the inherited phenotype. Therefore, we expect that multiple epigenetic and gene expression signatures will be related to CVD in experimental and clinical settings. Lever-aging existing large-scale consortia and clinical biobanks in combination with electronic health records holds promise for integrating epidemiological and clinical genomics data. Finally, a systems biology approach will be needed to integrate the accumulated multidimensional data. SUMMARY: Novel methods in sequencing, epigenetics, and transcriptomics, plus unprecedented large-scale cooperative efforts, promise to generate insights into the complexity of CVD. The rapid accumulation and integration of knowledge will shed light on a considerable proportion of the missing heritability for CVD. (C) 2011 American Association for Clinical Chemistry

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