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BMC Medical Genomics

, 4:83

Prognostics and diagnostics-biomarkers

Abstract

BackgroundPrediction of left ventricular LV remodeling after acute myocardial infarction MI is clinically important and would benefit from the discovery of new biomarkers.

MethodsBlood samples were obtained upon admission in patients with acute ST-elevation MI who underwent primary percutaneous coronary intervention. Messenger RNA was extracted from whole blood cells. LV function was evaluated by echocardiography at 4-months.

ResultsIn a test cohort of 32 MI patients, integrated analysis of microarrays with a network of protein-protein interactions identified subgroups of genes which predicted LV dysfunction ejection fraction ≤ 40% with areas under the receiver operating characteristic curve AUC above 0.80. Candidate genes included transforming growth factor beta receptor 1 TGFBR1. In a validation cohort of 115 MI patients, TGBFR1 was up-regulated in patients with LV dysfunction P < 0.001 and was associated with LV function at 4-months P = 0.003. TGFBR1 predicted LV function with an AUC of 0.72, while peak levels of troponin T TnT provided an AUC of 0.64. Adding TGFBR1 to the prediction of TnT resulted in a net reclassification index of 8.2%. When added to a mixed clinical model including age, gender and time to reperfusion, TGFBR1 reclassified 17.7% of misclassified patients. TGFB1, the ligand of TGFBR1, was also up-regulated in patients with LV dysfunction P = 0.004, was associated with LV function P = 0.006, and provided an AUC of 0.66. In the rat MI model induced by permanent coronary ligation, the TGFB1-TGFBR1 axis was activated in the heart and correlated with the extent of remodeling at 2 months.

ConclusionsWe identified TGFBR1 as a new candidate prognostic biomarker after acute MI.

Electronic supplementary materialThe online version of this article doi:10.1186-1755-8794-4-83 contains supplementary material, which is available to authorized users.

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Autor: Yvan Devaux - Melanie Bousquenaud - Sophie Rodius - Pierre-Yves Marie - Fatiha Maskali - Lu Zhang - Francisco Azuaje - Dani

Fuente: https://link.springer.com/



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