You described something BUT DID NOTHING that will get survivors recovered! You spectacularly failed! That is the goal of stroke research: GETTING SURVIVORS RECOVERED! Biomarkers DO NOTHING for stroke recovery!
Integrating WGCNA and SVM-RFE identifies hub molecular biomarkers driving ischemic stroke progression
ABSTRACT Background
Stroke
is the second most common cause of death worldwide and the leading
cause of long-term severe disability with neurological impairment
worsening within hours after stroke onset and being especially involved
with motor function. So far, there are no established and reliable
biomarkers to prognose stroke. Early detection of biomarkers that can
prognose stroke is of great importance for clinical intervention and
prevention of clinical deterioration of stroke.
Methods
TGSE119121
dataset was retrieved from the Gene Expression Integrated Database
(Gene Expression Omnibus, GEO) and weighted gene co-expression network
analysis (WGCNA) was conducted to identify the key modules that could
regulate disease progression. Moreover, functional enrichment analysis
was conducted to study the biological functions of the key module genes.
The GSE16561 dataset was further analyzed by the Support Vector
Machines coupled with Recursive Feature Elimination (SVM-RFE)algorithm
to identify the top genes regulating disease progression. The hub genes
revealed by WGCNA were associated with disease progression using the
receiver operating characteristic curve (ROC) analysis. Subsequently,
functional enrichment of the hub genes was performed by deploying gene
set variation analysis (GSVA). The changes at gene level were
transformed into the changes at pathway level to identify the biological
function of each sample. Finally, the expression level of the hub gene
in the rat infarction model of MCAO was measured using RT-qPCR for
validation.
Results
WGCNA
analysis revealed four hub genes: DEGS1, HSDL2, ST8SIA4 and STK3. The
result of GSVA showed that the hub genes were involved in stroke
progression by regulating the p53 signal pathway, the PI3K signal
pathway, and the inflammatory response pathway. The results of RT-qPCR
indicated that the expression of the four HUB genes was increased
significantly in the rat model of MCAO.
Conclusion
Several
genes, such as DEGS, HSDL2, ST8SIA4 and STK3, were identified and
associated with the progression of the disease. Moreover, it was
hypothesized that these genes may be involved in the progression stroke
by regulating the P53 signal, the PI3K signal, and the inflammatory
response pathway, respectively. These genes have potential prognostic
value and may serve as biomarkers for predicting stroke progression.
