Differential multi-omics analysis of pulmonary arterial hypertension microvascular endothelial cells for differential drug response

Post-translational modification crosstalk in pulmonary arterial hypertension: mechanisms and therapeutic implications

Integrative multi-omics analysis of metabolite–protein interaction networks across different stages of coronary heart disease

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)—specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)—through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage—a network configuration consistent with a tightly coupled “molecular storm”. These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Integrated Multi-Omics Identifies Core Molecular Targets in Cerebral Venous Sinus Thrombosis-Induced Brain Injury

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.

Single-Cell Proteomics Uncovers Cell-Specific Proteins in Vascular Health and Marfan Syndrome Disease

Background: The vascular system is the largest organ in the body and underlies most chronic diseases, yet the molecular mechanisms that govern its plasticity remain poorly defined. Methods: We applied single-cell proteomics for the first time in vascular disease, integrating it with single-cell transcriptomics to map protein regulation in healthy and Marfan syndrome (MFS) aortas. Results: This approach uncovered cell type– and state-specific proteins missed at the transcriptional level. Notably, we identified a decoupling of fibrillin 1 RNA and protein abundance, suggesting altered protein regulation as a potential contributor to aortic degeneration. Single-cell proteomics further resolved modulated smooth muscle cell (modSMC) states enriched for matrix effectors (AEBP1, HTRA1, FN1) and uniquely protein-level regulators (GLIPR2, ITGB2, CD151). Conclusions: Together, these findings establish the first human single-cell proteomic atlas of the aorta, reveal altered FBN1 protein regulation in both human and mouse MFS, and position single-cell proteomics as a transformative framework for decoding vascular plasticity and identifying actionable effectors in disease.

Integrative transcriptomic and single-cell analysis identifies anoikis-related molecular signatures in vascular calcification

Abstract Background Vascular calcification (VC) is a life-threatening complication of chronic kidney disease (CKD) driven by vascular smooth muscle cell (VSMC) osteogenic transdifferentiation. Anoikis, a form of adhesion-dependent apoptosis, is involved in cardiovascular remodeling, yet its regulatory role in CKD-associated VC remains unexplored. Methods We performed an integrative transcriptomic and single‑cell analysis using a human in vitro VSMC calcification model and a rat in vivo CKD‑VC model. Differentially expressed genes were identified under a unified threshold (FDR < 0.05, |log2FC| > 1). Strict one‑to‑one ortholog mapping was applied. Differentially expressed anoikis‑related genes were screened, followed by functional enrichment, three machine‑learning algorithms, and external validation. Results We identified 48 differentially expressed anoikis‑related genes, with the signal derived mainly from human VSMCs rather than cross‑species conservation. The cell adhesion molecule pathway was significantly dysregulated. Seven hub genes were identified: BDNF, CRYAB, CYP1B1, DAPK1, HAS2, PDGFRB, and PLAU. The seven‑gene model achieved an AUC of 0.811 in the independent validation cohort. Single‑cell analysis revealed cell‑type‑specific expression patterns, with the highest anoikis module scores in osteoblast‑like cells and macrophages. Conclusions This study identifies novel anoikis‑related molecular signatures associated with VC. These genes are involved in cell adhesion, VSMC homeostasis, chaperone‑mediated cytoprotection, and matrix remodeling. Our exploratory findings provide new insights into VC pathogenesis and require further functional and clinical validation in CKD‑specific cohorts.

Integrated multi-omics profiling of the early post-infarct heart reveals a hub gene network associated with myeloid-driven inflammation

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.