AUTHOR=Li Dan , Lin Hong , Li Luyifei 

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

JOURNAL=Frontiers in Physiology

VOLUME=11

YEAR=2020

URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2020.604241

DOI=10.3389/fphys.2020.604241

ISSN=1664-042X

ABSTRACT=<p>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 (<italic>n</italic> = 177) and without heart failure (<italic>n</italic> = 136) using multiple feature selection strategies and identified 38 HF signature genes. The support vector machine (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 <italic>SMOC2</italic> may play important roles in HF. Other genes, such as <italic>FCN3</italic>, <italic>HMGN2</italic>, and <italic>SERPINA3</italic>, also showed great promises. Our results can facilitate the early detection of heart failure and can reveal its molecular mechanisms.</p>