A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience

J Cardiovasc Transl Res. 2015 Nov;8(8):449-57. doi: 10.1007/s12265-015-9648-y. Epub 2015 Aug 14.

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.

Keywords: Air pollution; Biomarkers; Biorepository; Cardiometabolic disease; Cardiovascular disease; Genetics; Genomics; Geocoding; Metabolomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Biological Specimen Banks* / organization & administration
  • Cardiovascular Diseases / diagnosis
  • Cardiovascular Diseases / genetics*
  • Cardiovascular Diseases / therapy
  • Databases, Genetic*
  • Gene Expression Profiling
  • Gene-Environment Interaction
  • Genetic Association Studies
  • Genetic Markers
  • Genetic Predisposition to Disease
  • Genetic Testing / methods
  • Genomics / methods*
  • Genomics / organization & administration
  • Humans
  • Intellectual Property
  • Models, Organizational
  • Phenotype
  • Predictive Value of Tests
  • Prognosis
  • Risk Factors
  • Specimen Handling
  • Time Factors

Substances

  • Genetic Markers