A 3-gene panel improves the prediction of left ventricular dysfunction after acute myocardial infarction

Adeline Boileau, Torkia Lalem, Melanie Vausort, Lu Zhang, Yvan Devaux*, On behalf of the Cardiolinc network (www.cardiolinc.org)

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

12 Citations (Scopus)

Abstract

Background: Identification of patients at risk of poor outcome after acute myocardial infarction (MI) would allow tailoring healthcare to each individual. However, lack of prognostication tools renders this task challenging. Previous investigations suggested that blood transcriptome analysis may inform about prognosis after MI. We aim to independently confirm the value of gene expression profiles in the blood to predict left ventricular (LV) dysfunction after MI. Methods and results: Five genes (LMNB1, MMP9, TGFBR1, LTBP4 and TNXB) selected from previous studies were measured in peripheral blood samples obtained at reperfusion in 449 MI patients. 79 patients had LV dysfunction as attested by an ejection fraction (EF) ≤ 40% at 4-month follow-up and 370 patients had a preserved LV function (EF > 40%). LMNB1, MMP9 and TGFBR1 were up-regulated in patients with LV dysfunction and LTBP4 was down-regulated, as compared with patients with preserved LV function. The 5 genes were significant univariate predictors of LV dysfunction. In multivariable analyses adjusted with traditional risk factors and corrected for model overfitting, a panel of 3 genes − TNXB, TGFBR1 and LTBP4 – improved the prediction of a clinical model (p = 0.00008) and provided a net reclassification index of 0.45 [0.23–0.69], p = 0.0002 and an integrated discrimination improvement of 0.05 [0.02–0.09], p = 0.001. Bootstrap internal validation confirmed the incremental predictive value of the 3-gene panel. Conclusion: A 3-gene panel can aid to predict LV dysfunction after MI. Further independent validation is required before considering these findings for molecular diagnostic assay development.

Original languageEnglish
Pages (from-to)28-35
Number of pages8
JournalInternational Journal of Cardiology
Volume254
DOIs
Publication statusPublished - 1 Mar 2018

Keywords

  • Biomarker
  • Gene expression
  • Left ventricular dysfunction
  • Myocardial infarction
  • Prognosis

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