Journal Articles

Simultaneous Consideration of Multiple Candidate Protein Biomarkers for Long-Term Risk for Cardiovascular Events

November 24, 2014

Simultaneous Consideration of Multiple Candidate Protein Biomarkers for Long-Term Risk for Cardiovascular Events, Circ Cardiovasc Genet. 2014 Nov 24, Halim SA1, Neely ML2, Pieper KS2, Shah SH3, Kraus WE4, Hauser ER5, Califf RM6, Granger CB1, Newby LK7.

  • 1Division of Cardiology & Duke Clinical Research Institute, Duke University Medical Center, Durham, NC.
  • 2Duke Clinical Research Institute, Duke University Medical Center, Durham, NC.
  • 3Division of Cardiology, Duke Clinical Research Institute & Duke Center for Human Genetics, Duke University Medical Center, Durham, NC.
  • 4Division of Cardiology, Duke University Medical Center, Durham, NC.
  • 5Duke Center for Human Genetics, Duke University Medical Center, Durham, NC.
  • 6Division of Cardiology & Duke Translational Medicine Institute, Duke University Medical Center, Durham, NC.
  • 7Division of Cardiology & Duke Clinical Research Institute, Duke University Medical Center, Durham, NC kristin.newby@duke.edu.

Abstract

BACKGROUND:

-Although individual protein biomarkers are associated with cardiovascular risk, rarely have multiple proteins been considered simultaneously to identify which set of proteins best predicts risk.

METHODS AND RESULTS:

-In a nested case-control study of 273 death/myocardial infarction (MI) cases and 273 age- (within 10 years), sex-, and race-matched and event-free controls from among 2023 consecutive patients (median follow-up 2.5 years) with suspected coronary disease, plasma levels of 53 previously reported biomarkers of cardiovascular risk were determined in a core laboratory. Three penalized logistic regression models were fit using the elastic net to identify panels of proteins independently associated with death/MI: proteins alone (Model 1); proteins in a model constrained to retain clinical variables (Model 2); and proteins and clinical variables available for selection (Model 3). Model 1 identified 6 biomarkersstrongly associated with death/MI: ICAM-1, MMP-3, NT-proBNP, IL-6, sCD40L, and IGFBP2. In Model 2, only sCD40L remained strongly associated with death/MI when all clinical risk predictors were retained. Model 3 identified a set of 6 biomarkers (ICAM-1, MMP-3, NT-proBNP, IL-6, sCD40L, and IGFBP2) and 5 clinical variables (age, red-cell distribution width, diabetes, hemoglobin, and New York Heart Association class) strongly associated with death/MI.

CONCLUSIONS:

-Simultaneously assessing the association between multiple putative protein biomarkers of cardiovascular risk and clinical outcomes is useful in identifying relevant biomarker panels for further assessment.

Comments are closed.

Connect With Us