By applying integrated multi-omics profiling to a modified rat model, this study systematically mapped the molecular landscape of CVST-induced brain injury and provided a basis for further investigation into the mechanisms underlying CVST and for the design of novel treatment approaches.
Abstract
Background: Cerebral venous sinus thrombosis (CVST) is a critical cause of brain injury and intracranial hypertension. However, its underlying molecular mechanisms remain poorly understood, limiting the development of targeted therapies. This study aims to systematically identify key molecular targets and signaling pathways involved in CVST-induced brain lesions using multi-omics approaches in a modified rat model of CVST. Methods: An optimized rat CVST model was established. Cortical tissues were collected from Sham-operated, 2-day post-CVST, and 7-day post-CVST groups for transcriptomic, proteomic, and single-cell transcriptomic sequencing. Bioinformatics analyses were performed to identify differentially expressed genes/proteins, followed by functional enrichment, protein–protein interaction network construction, and hub-gene screening. Further investigations included drug enrichment analysis, molecular docking, and molecular dynamics, as well as the prediction of competing endogenous RNA networks, transcription factor analysis, and expression profiling of potential edema-related therapeutic targets. Results: Multi-omics analyses revealed dynamic changes in gene and protein expression in the brain after CVST, along with associated pathways involved in immune inflammatory responses and tissue repair. Integrative analysis identified 12 core genes (Cd44, Cd40, Sdc1, Myd88, Icam1, Stat3, Jak2, Ptgs2, Aldh1a1, Hspb1, Pxdn, and Casp3). Single-cell RNA sequencing validated their expression and delineated cell-type specificity. Molecular docking hinted at the high binding potential of glucocorticoids such as dexamethasone and methylprednisolone to several core targets (JAK2, PTGS2, and CD44), with all docked complexes showing binding energies below −8.2 kcal/mol. Further molecular dynamics simulations indicated that methylprednisolone forms a stable complex with CD44, driven primarily by van der Waals and electrostatic interactions. Additionally, dynamic levels of several potential edema-related targets (Kcnn4, Piezo1, Trpv4, and Atp1a2) were observed. Conclusions: In summary, by applying integrated multi-omics profiling to a modified rat model, this study systematically mapped the molecular landscape of CVST-induced brain injury. A number of candidate targets and signaling pathways emerged from our analysis, along with several compounds of potential therapeutic interest. Collectively, these results provide a basis for further investigation into the mechanisms underlying CVST and for the design of novel treatment approaches.
Emerging evidence suggests that tryptophan metabolism (TrM) is dysregulated in acute myocardial infarction (AMI), but the underlying mechanisms remain unclear. In this study, we integrated weighted gene co-expression network analysis, differential expression analysis, and four machine learning algorithms to identify key TrM-related genes in AMI. The diagnostic model was further validated by quantitative polymerase chain reaction (qPCR), and functional enrichment, immune infiltration, molecular docking, molecular dynamics simulation, and single-cell analyses were performed to investigate the potential mechanisms and therapeutic targets. Five candidate genes were identified, among which ADM, MCEMP1, and TSPO were selected to construct a diagnostic model. Immune infiltration analysis revealed that monocytes and neutrophils were closely associated with AMI progression and correlated with these key genes. Molecular docking and molecular dynamics simulations demonstrated a stable interaction between TSPO and ONO-2952. Furthermore, single-cell and SCENIC analyses identified monocytes as key cell populations and TFEC and CEBPD as potential transcriptional regulators of key gene expression. Collectively, this study provides a comprehensive characterization of TrM-related molecular alterations in AMI and identifies ADM, MCEMP1, and TSPO as potential diagnostic key genes, offering new insights into disease mechanisms and candidate targets for future therapeutic investigation.
Lei Wang, Cheng Tao· Journal of Visualized Experi...· 0 citations
TIM-4 is established as a critical driver of neuroinflammation-associated neuronal death in TBI, representing a promising therapeutic target for TBI-related cognitive dysfunction.
Liang Chen, Yan-Yan Li, Li Han et al.· Frontiers in Cell and Develo...· 0 citations
Traumatic brain injury (TBI) is particularly
challenging to treat due to its complex nature and the
initiation of complex pathogenic pathways. It is crucial
to understand the series of events that might lead to
subsequent brain injury in TBI. In order to identify
frequent and important cellular interactions, we used
previously published single-cell sequencing data
(GSE89866 and GSE101901) from both animal and
human TBI patient data to uncover common and
significant cellular interaction. We created
neurovascular unit (NVU) consisting of astrocytes,
pericytes, neurons, endothelial cells and microglia
cellular network using ligand receptor (LR)
interaction. We used the newly curated LR pairings list
to map ligand-receptor pairs between different NVU
cell types in order to build this intracellular network.
This LR interaction is visualised through Cytoscape,
while intercellular interactions were depicted by Circos
plots. Functional enrichment assessment was
conducted utilizing DAVID Bioinformatics Resources
to find significant Gene Ontology terms and KEGG
pathways related to these connections. Our
investigation revealed 69 ligands, 59 receptors and 128
LR interactions, demonstrating substantial
intercellular communication across all cell types in
brain. Astrocytes emerge as the most important
interactome partners, with highest interaction density
(~49%) with prominent autocrine and paracrine
signalling roles.
Network analysis showed astrocytic LRP1 as a central
signalling hub interacting with several ligands, also
common with human (GSE101901) dataset. It indicates
its crucial function in regulating neurovascular
responses after TBI. Overall, this study offers a
systems-level framework of NVU interaction and
highlights astrocyte-specific LRP1 as a possible
therapeutic target for modifying neurovascular
dysfunction following TBI. Multiple astrocyte pathways
such as astrocyte-astrocyte, astrocyte-neuron,
astrocyte-microglia were significantly enriched that
are associated in TBI pathogenesis.
A. Rana, Gaurav Kumar· Research journal of biotechn...· 0 citations
Pulmonary arterial hypertension (PAH) represents a heterogeneous group of disorders that involves complex molecular dysregulations, which are not fully captured by single-omics analyses. We apply our network-based multi-omics analysis framework, DrDimont, to transcriptomic, proteomic, phosphoproteomic, and kinase screening data from lung microvascular endothelial cells of PAH patients and controls. Thereby, we extend the functionality of DrDimont to incorporate kinase–kinase interactions during the construction of condition-specific multi-omics networks. Kinase interactions are inferred from phosphorylations of screened substrates that are weighted by kinase-substrate predictions. Differential interaction scores from the network-based analysis between PAH and control uncover alterations centered on kinases, in particular top hits relating to MAPK signaling, such as MAPK13, MAP2K, or upstream IRAK1, and other MAPK/MAP2K family members. Further highly differential nodes were ACADSB, GPX7, DSE (for proteins), and AIM1, LY96, CHSY3 (for mRNAs). When prioritizing drug candidates by mapping drug targets onto the differential network, we find high scores for the drug tacrolimus (FK506) and several anti-neoplastic MAPK inhibitors (e.g., selumetinib, trametinib), as well as agents acting on general proliferation via (mitochondrial) DNA transcription (e.g., epirubicin, topotecan). Integrating kinase activity screens into our explainable multi-omics network-based analyses reveals kinase-centered alterations and therapeutic hypotheses in PAH that complement single-layer classical differential expression analyses.
P. Hiort, A. Weiss, Janina Krentz et al.· bioRxiv· 0 citations
A high-resolution map of transcriptional and cellular dynamics during the EIP of AMI is delineates a coordinated network of inflammatory mediators linked to early myeloid cell recruitment and activation, revealing a coordinated network of inflammatory mediators linked to early myeloid cell activation.
Zeyang Wang, Jinhu Shi, Yinchuan Lai et al.· Frontiers in Cardiovascular...· 0 citations
Background Hypertensive cerebral hemorrhage (HCH) accounts for the majority of spontaneous intracerebral hemorrhage (ICH) cases. Cognitive impairment (CI) is a major contributor to long-term disability following ICH, yet the molecular mechanisms underlying CI in hypertensive ICH remain poorly understood. Therefore, identifying biomarkers capable of effectively diagnosing or predicting CI in HCH is particularly critical for managing patients with hypertensive cerebral hemorrhage with cognitive impairment (HCHwCI). Methods In this research, clinical samples underwent transcriptome sequencing analysis. Identification of biomarkers associated with CI in HCH was achieved through differential expression analysis, protein-protein interaction (PPI) network construction, and expression level evaluation. Subsequently, to investigate the molecular mechanisms of the biomarkers in HCHwCI, comprehensive analyses were performed, including gene set enrichment analysis (GSEA), molecular regulatory network construction, drug prediction, and molecular docking. Finally, the expression of biomarkers was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Results Using 247 differentially expressed CI-related genes (CRGs), we identified CXCL8 and FCGR3B as significantly upregulated biomarkers in HCH patients with CI, a finding subsequently validated by RT-qPCR. CXCL8 and FCGR3B were also found to be significantly enriched in oxidative phosphorylation and other related pathways. The molecular regulation study found that 67 microRNAs (miRNAs) were predicted to regulate CXCL8, and 58 miRNAs were predicted to regulate FCGR3B. Among them, hsa-miR-3168 and hsa-miR-567 jointly regulated both CXCL8 and FCGR3B. In addition, there were 29 transcription factors (TFs) were predicted to target CXCL8, and there were 2 TFs were predicted to target FCGR3B, such as the pairs of CXCL8-STAT6 and FCGR3B-YY1. Moreover, through drug prediction, there were 542 drugs targeting CXCL8 and FCGR3B (such as methotrexate and hydrogen peroxide). Among them, the | Total Score | of FCGR3B and clozapine is 6.3 kcal/mol, and the | Total Score | of CXCL8 and 6401-97-4 is 5.1 kcal/mol, both indicating good binding activity in silico, serving as a proof-of-concept for the computational docking approach. Conclusion In this study, two potential biomarkers, CXCL8 and FCGR3B, were preliminarily identified through transcriptome sequencing combined with biological validation methods to provide novel insights into future therapeutic strategies and research directions for HCHwCI.
Yao Tang, Bo Yang, Xingmei Luo· Frontiers in Molecular Biosc...· 0 citations
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