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Multiple Feature Selection Strategies Identified Novel Cardiac Gene Expression Signature for Heart Failure

Dan Li, Hong Lin, Luyifei Li

2020Frontiers in Physiology20 citationsDOIOpen Access PDF

Abstract

Heart failure (HF) is a serious condition in which the support of blood pumped by the heart is insufficient to meet the demands of body at a normal cardiac filling pressure. Approximately 26 million patients worldwide are suffering from heart failure and about 17–45% of patients with heart failure die within 1-year and the majority die within 5-years admitted to a hospital. The molecular mechanisms underlying the progression of heart failure have been poorly studied. We compared the gene expression profiles between patients with heart failure (n=177) and without heart failure (n=136) using multiple feature selection strategies and identified 38 HF signature genes. The SVM classifier based on these 38 genes evaluated with leave-one-out cross validation (LOOCV) achieved great performance with sensitivity of 0.983 and specificity of 0.963. The network analysis suggested that the hub gene SMOC2 may play important roles in HF. Other genes, such as FCN3, HMGN2 and SERPINA3, also showed great promises. Our results can facilitate the early detection of heart failure and reveal its molecular mechanisms.

Topics & Concepts

Heart failureFeature selectionMedicineSupport vector machineInternal medicineCardiologyBioinformaticsComputer scienceArtificial intelligenceBiologyMachine Learning in BioinformaticsGDF15 and Related BiomarkersProtein Hydrolysis and Bioactive Peptides
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