DNA Hypomethylation of DOCK1 Leading to High Expression Correlates with Neurologic Deterioration and Poor Function Outcomes after Spontaneous Intracerebral Hemorrhage

Identification and Analysis of DNA Methylation Inflammation-Related Key Genes in Intracerebral Hemorrhage

Inflammation and DNA methylation have been reported to play key roles in intracerebral hemorrhage (ICH). This study aimed to investigate new diagnostic biomarkers associated with inflammation and DNA methylation using a comprehensive bioinformatics approaches. GSE179759 and GSE125512 were collected from the Gene Expression Omnibus database, and 3222 inflammation-related genes (IFRGs) were downloaded from the Molecular Signatures Database. Key differentially expressed methylation-regulated and inflammation-related genes (DE-MIRGs) were identified by overlapping methylation-regulated differentially expressed genes (MeDEGs) between patients with ICH and control samples, module genes from weighted correlation network analysis, and IFRGs. Functional annotation of DE-MIRGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed to clarify the interrelationships between different DE-MIRGs. The key genes were categorized by least absolute shrinkage selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), and gene set enrichment analysis (GSEA). A total of 22 DE-MIRGs were acquired from 451 MeDEGs, 3222 IFRGs, and 302 module genes, and were mainly enriched in the GO terms of wound healing, blood coagulation, and hemostasis; and the KEGG pathways of PI3K/Akt signaling, focal adhesion, and regulation of actin cytoskeleton. A PPI network with 22 nodes and 87 edges was constructed based on the 22 DE-MIRGs, 11 of which were selected for key gene selection. Two 2 key genes (SELP and S100A4) were identified using LASSO and SVM-RFE. Finally, SELP was mainly enriched in cell morphogenesis involved in differentiation, cytoplasmic translation, and actin binding of GO terms, and the KEGG pathway including endocytosis, focal adhesion, and platelet activation. S100A4 was mainly enriched in GO terms including mitochondrial inner membrane; mitochondrial respirasome and lysosomal membrane; and the KEGG pathway of oxidative phosphorylation, regulation of actin cytoskeleton, and chemical carcinogenesis-reactive oxygen species. Twenty-two DE-MIRGs-associated inflammation and DNA methylation were identified between patients with ICH and normal controls, and two key genes (SELP and S100A4) were identified and regarded as biomarkers for ICH, which could provide the research foundation for further investigation of the pathological mechanism of ICH.

Retracted: DNA Hypomethylation of DOCK1 Leading to High Expression Correlates with Neurologic Deterioration and Poor Function Outcomes after Spontaneous Intracerebral Hemorrhage

[This retracts the article DOI: 10.1155/2021/1186458.].

A Prediction Model for Neurological Deterioration in Patients with Acute Spontaneous Intracerebral Hemorrhage

Aim

The aim of this study was to explore factors related to neurological deterioration (ND) after spontaneous intracerebral hemorrhage (sICH) and establish a prediction model based on random forest analysis in evaluating the risk of ND.

Methods

The clinical data of 411 patients with acute sICH at the Affiliated Hospital of Jining Medical University and Xuanwu Hospital of Capital Medical University between January 2018 and December 2020 were collected. After adjusting for variables, multivariate logistic regression was performed to investigate the factors related to the ND in patients with acute ICH. Then, based on the related factors in the multivariate logistic regression and four variables that have been identified as contributing to ND in the literature, we established a random forest model. The receiver operating characteristic curve was used to evaluate the prediction performance of this model.

Results

The result of multivariate logistic regression analysis indicated that time of onset to the emergency department (ED), baseline hematoma volume, serum sodium, and serum calcium were independently associated with the risk of ND. Simultaneously, the random forest model was developed and included eight predictors: serum calcium, time of onset to ED, serum sodium, baseline hematoma volume, systolic blood pressure change in 24 h, age, intraventricular hemorrhage expansion, and gender. The area under the curve value of the prediction model reached 0.795 in the training set and 0.713 in the testing set, which suggested the good predicting performance of the model.

Conclusion

Some factors related to the risk of ND were explored. Additionally, a prediction model for ND of acute sICH patients was developed based on random forest analysis, and the developed model may have a good predictive value through the internal validation.

Tet Enzymes-Mediated DNA 5hmC Modification in Cerebral Ischemic and Hemorrhagic Injury

5-Hydroxymethylcytosine (5hmC) has recently been found that plays an important role in many diseases; however, there are still few studies in the field of stroke. The purpose of this review is to introduce the influence and function of 5hmC in stroke, in order for more people can study it. In this review, we introduced the role of 5hmC in ischemia and hemorrhage stroke, and summarized the possible therapeutic prospects of 5hmC in stroke. In conclusion, we suggest that 5hmC may serve as a biomarker or therapeutic target for the treatment of stroke.