An electronic medical record-linked biorepository to identify novel biomarkers for atherosclerotic cardiovascular disease

Authors

  • Zi Ye Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA and Division of Cardiovascular disease, Shanghai Huashan Hospital, Fudan University, Shanghai, China
  • Fara S Kalloo Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
  • Angela K Dalenberg Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
  • Iftikhar J Kullo Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA

Abstract

Background: Atherosclerotic vascular disease (AVD), a leading cause of morbidity and mortality, is increasing in prevalence in the developing world. We describe an approach to establish a biorepository linked to medical records with the eventual goal of facilitating discovery of biomarkers for AVD. 

Methods: The Vascular Disease Biorepository at Mayo Clinic was established to archive DNA, plasma, and serum from patients with suspected AVD. AVD phenotypes, relevant risk factors and comorbid conditions were ascertained by electronic medical record (EMR)-based electronic algorithms that included diagnosis and procedure codes, laboratory data and text searches to ascertain medication use. 

Results: Up to December 2012, 8800 patients referred for vascular ultrasound examination and non-invasive lower extremity arterial evaluation were approached, of whom 5268 consented. The mean age of the initial 2182 patients recruited was 70.4 ± 11.2 years, 62.6% were men and 97.6% were whites. The prevalences of AVD phenotypes were: carotid artery stenosis 48%, abdominal aortic aneurysm 21% and peripheral arterial disease 38%. Positive predictive values for electronic phenotyping algorithms were>0.90 for cases (and>0.95 for controls) for each AVD phenotype, using manual review of the EMR as the gold standard. The prevalences of risk factors and comorbidities were as follows: hypertension 78%, diabetes 29%, dyslipidemia 73%, smoking 70%, coronary heart disease 37%, heart failure 12%, cerebrovascular disease 20% and chronic kidney disease 19%. 

Conclusions: Our study demonstrates the feasibility of establishing a biorepository of plasma, serum and DNA, with relatively rapid annotation of clinical variables using EMR-based algorithms.

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Published

2017-04-18

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Research articles