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2016 ; 7
(45
): 73541-73551
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Identification of long non-coding RNAs biomarkers for early diagnosis of
myocardial infarction from the dysregulated coding-non-coding co-expression
network
#MMPMID27634901
Sun C
; Jiang H
; Sun Z
; Gui Y
; Xia H
Oncotarget
2016[Nov]; 7
(45
): 73541-73551
PMID27634901
show ga
Long non-coding RNAs (lncRNAs) have recently been shown as novel promising
diagnostic or prognostic biomarkers for various cancers. However, lncRNA
expression patterns and their predictive value in early diagnosis of myocardial
infarction (MI) have not been systematically investigated. In our study, we
performed a comprehensive analysis of lncRNA expression profiles in MI and found
altered lncRNA expression pattern in MI compared to healthy samples. We then
constructed a lncRNA-mRNA dysregulation network (DLMCEN) by integrating aberrant
lncRNAs, mRNAs and their co-dysregulation relationships, and found that some of
mRNAs were previously reported to be involved in cardiovascular disease,
suggesting the functional roles of dysregulated lncRNAs in the pathogenesis of
MI. Therefore, using support vector machine (SVM) and leave one out
cross-validation (LOOCV), we developed a 9-lncRNA signature (termed 9LncSigAMI)
from the discovery cohort which could distinguish MI patients from healthy
samples with accuracy of 95.96%, sensitivity of 93.88% and specificity of 98%,
and validated its predictive power in early diagnosis of MI in another completely
independent cohort. Functional analysis demonstrated that these nine lncRNA
biomarkers in the 9LncSigAMI may be involved in myocardial innate immune and
inflammatory response, and their deregulation may lead to the dysfunction of the
inflammatory and immune system contributing to MI recurrence. With prospective
validation, the 9LncSigAMI identified by our work will provide additional
diagnostic information beyond other known clinical parameters, and increase the
understanding of the molecular mechanism underlying the pathogenesis of MI.