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A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience

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Abstract

The CATHeterization GENetics (CATHGEN) biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010, we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date, race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations included interim information: vital status (verified via National Death Index search and supplemented by Social Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.

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Abbreviations

CATHGEN:

CATHeterization GENetics; sample and clinical data repository

dbGaP:

NCBI’s database of genotypes and phenotypes

DDCD:

Duke Databank for Cardiovascular Diseases; clinical database

DISCERN:

Duke search engine for clinical data from patient records

DNA:

Deoxyribonucleic acid

EDTA:

Ethylenediaminetetraacetic acid; anticoagulant

GWAS:

Genome-wide association study

IRB:

Institutional Review Board

LD:

Linkage disequilibrium

LDL-C:

Low-density lipoprotein-cholesterol

MAF:

Minor allele frequency

MS:

Mass spectrometry

MURDOCK Study:

Contiguous sample of 2024 CATHGEN participants

NCBI:

National Center for Biotechnology Information

NEFA:

Non-esterified fatty acids

PEDIGENE®:

Data repository for clinical and sample data

QTL:

Quantitative trait locus

RNA:

Ribonucleic acid

References

  1. Bhattacharya, S., Dunham, A. A., Cornish, M. A., Christian, V. A., Ginsburg, G. S., Tenenbaum, J. D., et al. (2012). The Measurement to Understand Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study community registry and biorepository. American Journal of Translational Research, 4(4), 458–470.

    PubMed Central  PubMed  Google Scholar 

  2. Halim, S. A., Neely, M. L., Pieper, K. S., Shah, S. H., Kraus, W. E., Hauser, E. R., et al. (2015). Simultaneous consideration of multiple candidate protein biomarkers for long-term risk for cardiovascular events. Circulation. Cardiovascular Genetics, 8(1), 168–177.

    Article  CAS  PubMed  Google Scholar 

  3. Jeyarajah, E. J., Cromwell, W. C., & Otvos, J. D. (2006). Lipoprotein particle analysis by nuclear magnetic resonance spectroscopy. Clinics in Laboratory Medicine, 26(4), 847–870.

    Article  PubMed  Google Scholar 

  4. Beineke, P., Fitch, K., Tao, H., Elashoff, M. R., Rosenberg, S., Kraus, W. E., et al. (2012). A whole blood gene expression-based signature for smoking status. BMC Medical Genomics, 5, 58.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Bhattacharya, S., Granger, C. B., Craig, D., Haynes, C., Bain, J., Stevens, R. D., et al. (2014). Validation of the association between a branched chain amino acid metabolite profile and extremes of coronary artery disease in patients referred for cardiac catheterization. Atherosclerosis, 232(1), 191–196.

    Article  CAS  PubMed  Google Scholar 

  6. Brunner, M. P., Shah, S. H., Craig, D. M., Stevens, R. D., Muehlbauer, M. J., Bain, J. R., et al. (2011). Effect of heparin administration on metabolomic profiles in samples obtained during cardiac catheterization. Circulation. Cardiovascular Genetics, 4(6), 695–700.

    Article  CAS  PubMed  Google Scholar 

  7. Connelly, J. J., Cherepanova, O. A., Doss, J. F., Karaoli, T., Lillard, T. S., Markunas, C. A., et al. (2013). Epigenetic regulation of COL15A1 in smooth muscle cell replicative aging and atherosclerosis. Human Molecular Genetics, 22(25), 5107–5120.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Connelly, J. J., Shah, S. H., Doss, J. F., Gadson, S., Nelson, S., Crosslin, D. R., et al. (2008). Genetic and functional association of FAM5C with myocardial infarction. BMC Medical Genetics, 9, 33.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Connelly, J. J., Wang, T., Cox, J. E., Haynes, C., Wang, L., Shah, S. H., et al. (2006). GATA2 is associated with familial early-onset coronary artery disease. PLoS Genetics, 2(8), e139.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Crosslin, D. R., Shah, S. H., Nelson, S. C., Haynes, C. S., Connelly, J. J., Gadson, S., et al. (2009). Genetic effects in the leukotriene biosynthesis pathway and association with atherosclerosis. Human Genetics, 125(2), 217–229.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Daniels, S. E., Beineke, P., Rhees, B., McPherson, J. A., Kraus, W. E., Thomas, G. S., et al. (2014). Biological and analytical stability of a peripheral blood gene expression score for obstructive coronary artery disease in the PREDICT and COMPASS studies. Journal of Cardiovascular Translational Research, 7(7), 615–622.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Davies, R. W., Wells, G. A., Stewart, A. F., Erdmann, J., Shah, S. H., Ferguson, J. F., et al. (2012). A genome-wide association study for coronary artery disease identifies a novel susceptibility locus in the major histocompatibility complex. Circulation. Cardiovascular Genetics, 5(2), 217–225.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Do, R., Stitziel, N. O., Won, H. H., Jorgensen, A. B., Duga, S., Angelica Merlini, P., et al. (2015). Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature, 518(7537), 102–106.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. Dungan, J. R., Hauser, E. R., Qin, X., & Kraus, W. E. (2013). The genetic basis for survivorship in coronary artery disease. Frontiers in Genetics, 4, 191.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Elashoff, M. R., Wingrove, J. A., Beineke, P., Daniels, S. E., Tingley, W. G., Rosenberg, S., et al. (2011). Development of a blood-based gene expression algorithm for assessment of obstructive coronary artery disease in non-diabetic patients. BMC Medical Genomics, 4, 26.

    Article  PubMed Central  PubMed  Google Scholar 

  16. Horne, B. D., Hauser, E. R., Wang, L., Muhlestein, J. B., Anderson, J. L., Carlquist, J. F., et al. (2009). Validation study of genetic associations with coronary artery disease on chromosome 3q13-21 and potential effect modification by smoking. Annals of Human Genetics, 73(Pt 6), 551–558.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  17. Kertai, M. D., Li, Y. W., Li, Y. J., Shah, S. H., Kraus, W. E., Fontes, M. L., et al. (2014). G protein-coupled receptor kinase 5 gene polymorphisms are associated with postoperative atrial fibrillation after coronary artery bypass grafting in patients receiving beta-blockers. Circulation. Cardiovascular Genetics, 7(5), 625–633.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  18. Kral, B. G., Mathias, R. A., Suktitipat, B., Ruczinski, I., Vaidya, D., Yanek, L. R., et al. (2011). A common variant in the CDKN2B gene on chromosome 9p21 protects against coronary artery disease in Americans of African ancestry. Journal of Human Genetics, 56(3), 224–229.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Lansky, A., Elashoff, M. R., Ng, V., McPherson, J., Lazar, D., Kraus, W. E., et al. (2012). A gender-specific blood-based gene expression score for assessing obstructive coronary artery disease in nondiabetic patients: results of the Personalized Risk Evaluation and Diagnosis in the Coronary Tree (PREDICT) trial. American Heart Journal, 164(3), 320–326.

    Article  PubMed  Google Scholar 

  20. Lappe, J. M., Horne, B. D., Shah, S. H., May, H. T., Muhlestein, J. B., Lappe, D. L., et al. (2011). Red cell distribution width, C-reactive protein, the complete blood count, and mortality in patients with coronary disease and a normal comparison population. Clinica Chimica Acta, 412(23-24), 2094–2099.

    Article  CAS  Google Scholar 

  21. Minear, M. A., Crosslin, D. R., Sutton, B. S., Connelly, J. J., Nelson, S. C., Gadson-Watson, S., et al. (2011). Polymorphic variants in tenascin-C (TNC) are associated with atherosclerosis and coronary artery disease. Human Genetics, 129(6), 641–654.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  22. Nolan, D. K., Sutton, B., Haynes, C., Johnson, J., Sebek, J., Dowdy, E., et al. (2012). Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5. BMC Genetics, 13, 12.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Peloso, G. M., Auer, P. L., Bis, J. C., Voorman, A., Morrison, A. C., Stitziel, N. O., et al. (2014). Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. American Journal of Human Genetics, 94(2), 223–232.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Rosenberg, S., Elashoff, M. R., Beineke, P., Daniels, S. E., Wingrove, J. A., Tingley, W. G., et al. (2010). Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients. Annals of Internal Medicine, 153(7), 425–434.

    Article  PubMed Central  PubMed  Google Scholar 

  25. Rosenberg, S., Elashoff, M. R., Lieu, H. D., Brown, B. O., Kraus, W. E., Schwartz, R. S., et al. (2012). Whole blood gene expression testing for coronary artery disease in nondiabetic patients: major adverse cardiovascular events and interventions in the PREDICT trial. Journal of Cardiovascular Translational Research, 5(3), 366–374.

    Article  PubMed Central  PubMed  Google Scholar 

  26. Sehnert, A. J., Daniels, S. E., Elashoff, M., Wingrove, J. A., Burrow, C. R., Horne, B., et al. (2008). Lack of association between adrenergic receptor genotypes and survival in heart failure patients treated with carvedilol or metoprolol. Journal of the American College of Cardiology, 52(8), 644–651.

    Article  CAS  PubMed  Google Scholar 

  27. Shah, A. A., Craig, D. M., Sebek, J. K., Haynes, C., Stevens, R. C., Muehlbauer, M. J., et al. (2012). Metabolic profiles predict adverse events after coronary artery bypass grafting. Journal of Thoracic and Cardiovascular Surgery, 143(4), 873–878.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Shah, S. H., Bain, J. R., Muehlbauer, M. J., Stevens, R. D., Crosslin, D. R., Haynes, C., et al. (2010). Association of a peripheral blood metabolic profile with coronary artery disease and risk of subsequent cardiovascular events. Circulation. Cardiovascular Genetics, 3(2), 207–214.

    Article  CAS  PubMed  Google Scholar 

  29. Shah, S. H., Freedman, N. J., Zhang, L., Crosslin, D. R., Stone, D. H., Haynes, C., et al. (2009). Neuropeptide Y gene polymorphisms confer risk of early-onset atherosclerosis. PLoS Genetics, 5(1), e1000318.

    Article  PubMed Central  PubMed  Google Scholar 

  30. Shah, S. H., Granger, C. B., Hauser, E. R., Kraus, W. E., Sun, J. L., Pieper, K., et al. (2010). Reclassification of cardiovascular risk using integrated clinical and molecular biosignatures: design of and rationale for the Measurement to Understand the Reclassification of Disease of Cabarrus and Kannapolis (MURDOCK) Horizon 1 cardiovascular disease study. American Heart Journal, 160(3), 371–379.

    Article  PubMed  Google Scholar 

  31. Shah, S. H., Hauser, E. R., Crosslin, D., Wang, L., Haynes, C., Connelly, J., et al. (2008). ALOX5AP variants are associated with in-stent restenosis after percutaneous coronary intervention. Atherosclerosis, 201(1), 148–154.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. Shah, S. H., Sun, J. L., Stevens, R. D., Bain, J. R., Muehlbauer, M. J., Pieper, K. S., et al. (2012). Baseline metabolomic profiles predict cardiovascular events in patients at risk for coronary artery disease. American Heart Journal, 163(5), 844–850. doi:10.1016/j.ahj.2012.02.005. e841.

    Article  CAS  PubMed  Google Scholar 

  33. Singh, A., Babyak, M. A., Nolan, D. K., Brummett, B. H., Jiang, R., Siegler, I. C., et al. (2014). Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene. European Journal of Human Genetics. doi:10.1038/ejhg.2014.189.

    Google Scholar 

  34. Strauss, B. W., Valentiner, E. M., Bhattacharya, S., Smerek, M. M., Dunham, A. A., Newby, L. K., et al. (2014). Improving population representation through geographic health information systems: mapping the MURDOCK study. American Journal of Translational Research, 6(4), 402–412.

    PubMed Central  PubMed  Google Scholar 

  35. Sutton, B. S., Crosslin, D. R., Shah, S. H., Nelson, S. C., Bassil, A., Hale, A. B., et al. (2008). Comprehensive genetic analysis of the platelet activating factor acetylhydrolase (PLA2G7) gene and cardiovascular disease in case-control and family datasets. Human Molecular Genetics, 17(9), 1318–1328. doi:10.1093/hmg/ddn020.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  36. Vargas, J., Lima, J. A., Kraus, W. E., Douglas, P. S., & Rosenberg, S. (2013). Use of the Corus(R) CAD gene expression test for assessment of obstructive coronary artery disease likelihood in symptomatic non-diabetic patients. PLoS Curr, 5

  37. Voora, D., Cyr, D., Lucas, J., Chi, J. T., Dungan, J., McCaffrey, T. A., et al. (2013). Aspirin exposure reveals novel genes associated with platelet function and cardiovascular events. Journal of the American College of Cardiology, 62(14), 1267–1276.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Wang, L., Hauser, E. R., Shah, S. H., Pericak-Vance, M. A., Haynes, C., Crosslin, D., et al. (2007). Peakwide mapping on chromosome 3q13 identifies the kalirin gene as a novel candidate gene for coronary artery disease. American Journal of Human Genetics, 80(4), 650–663.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. Wang, L., Hauser, E. R., Shah, S. H., Seo, D., Sivashanmugam, P., Exum, S. T., et al. (2008). Polymorphisms of the tumor suppressor gene LSAMP are associated with left main coronary artery disease. Annals of Human Genetics, 72(Pt 4), 443–453.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Ward-Caviness, C., Haynes, C., Blach, C., Dowdy, E., Gregory, S. G., Shah, S. H., et al. (2013). Gene-smoking interactions in multiple Rho-GTPase pathway genes in an early-onset coronary artery disease cohort. Human Genetics, 132(12), 1371–1382.

    Article  CAS  PubMed  Google Scholar 

  41. Ward-Caviness, C. K., Kraus, W. E., Blach, C., Haynes, C. S., Dowdy, E., Miranda, M. L., et al. (2015). Association of roadway proximity with fasting plasma glucose and metabolic risk factors for cardiovascular disease in a cross-sectional study of cardiac catheterization patients. Environ Health Perspect, (in press).

  42. Wingrove, J. A., Daniels, S. E., Sehnert, A. J., Tingley, W., Elashoff, M. R., Rosenberg, S., et al. (2008). Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis. Circulation. Cardiovascular Genetics, 1(1), 31–38.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

Collections and generation of molecular data were generated in part through research agreements with the following: BG Medicine, Inc.; CardioDx, Inc.; Qiagen, Inc.; and Liposcience, Inc. GWAs and whole genome gene expression data were generated through NIH-funded studies to WEK (HL101621) and SHS (HL095987). Metabolomic data were generated through grants to SHS (HL095987, AHA Fellow-to-Faculty). An internal grant award from the MURDOCK Study (David H. Murdock Institute for Business and Culture, 1UL1 RR024128 from the National Center for Research Resources NCRR) to LKN was also helpful and appreciated. We wish to thank Dr. Marie Lynn Miranda and the Duke School of the Environment for developing geocoding addresses for CATHGEN participants.

Compliance with Ethical Standards

Funding

Through Duke, collections and generation of molecular data were generated in part through research agreements with the following: BG Medicine, Inc.; CardioDx, Inc.; Qiagen, Inc.; Liposcience, Inc..; and US Environmental Protection Agency. GWAs and whole genome gene expression data were generated through NIH-funded studies to WEK (HL101621) and SHS (HL095987). Metabolomic data were generated through grants to SHS (HL095987, AHA Fellow-to-Faculty).

Conflict of Interest

GSG has a financial interest in CardioDx, Inc. No other authors have potential conflicts of interest.

Compliance with Ethical Standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

All CATHGEN subjects were consented for participation in the biorepository and cardiovascular related research. Subject consent, data collection, sample collection, and analyses were approved through the Duke Institutional Review Board.

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Correspondence to William E. Kraus.

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Editor-in-Chief Jennifer L. Hall oversaw the review of this article

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Kraus, W.E., Granger, C.B., Sketch, M.H. et al. A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience. J. of Cardiovasc. Trans. Res. 8, 449–457 (2015). https://doi.org/10.1007/s12265-015-9648-y

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