Immune landscape and regulatory mechanisms in human atherosclerotic coronary plaques: Evidence from single-cell and bulk transcriptomics

Identification of lipid metabolism related immune markers in atherosclerosis through machine learning and experimental analysis

Background

Atherosclerosis is a significant contributor to cardiovascular disease, and conventional diagnostic methods frequently fall short in the timely and accurate detection of early-stage atherosclerosis. Abnormal lipid metabolism plays a critical role in the development of atherosclerosis. Consequently, the identification of new diagnostic markers is essential for the precise diagnosis of this condition.

Method

The datasets related to atherosclerosis utilized in this research were obtained from the GEO database (GSE2470, GSE24495, GSE100927 and GSE43292). The ssGSEA technique was first utilized to assess lipid metabolism scores in samples affected by atherosclerosis, thereby aiding in the discovery of important regulatory genes linked to lipid metabolism via WGCNA. Following this, differential expression analysis and functional evaluations were carried out, after which various machine learning approaches were employed to determine significant diagnostic genes for atherosclerosis. A diagnostic model was then developed and validated through several machine learning algorithms. Furthermore, molecular docking studies were conducted to analyze the binding affinity of these key markers with therapeutic agents for atherosclerosis. The ssGSEA technique was also used to measure immune cell scores in atherosclerotic samples, aiding the exploration of the connection between key diagnostic markers and immune cells. Finally, the expression variations of the identified pivotal genes were confirmed through experimental validation.

Result

WGCNA identified 302 lipid metabolism-related genes in atherosclerotic samples, and functional analysis revealed that these genes are associated with multiple immune pathways. Through further differential analysis and screening using machine learning algorithms, APLNR, PCDH12, PODXL, SLC40A1, TM4SF18, and TNFRSF25 were identified as key diagnostic genes for atherosclerosis. The diagnostic model we constructed was confirmed to predict the occurrence of atherosclerosis with high accuracy, and molecular docking studies indicated that these six key diagnostic genes have potential as drug targets. Additionally, the ssGSEA algorithm further validated the association of these diagnostic genes with various immune cells. Finally, the expression levels of these six genes were experimentally confirmed.

Conclusion

Our study introduces novel lipid metabolism-related diagnostic markers for atherosclerosis and emphasizes their potential as immune-related drug targets. This research provides a valuable approach for the predictive diagnosis and targeted therapy of atherosclerosis.

Cellular aspects of immunity involved in the development of atherosclerosis

Atherosclerosis, previously regarded as a lipid storage disease, has now been classified as a chronic inflammatory disease. The hardening of arterial vessels characterizes atherosclerosis due to the accumulation of lipids in the arterial walls, eliciting an inflammatory response. The development of atherosclerosis occurs in various stages and is facilitated by many clinical factors, such as hypertension, hyperlipidemia, and inflammatory status. A large arsenal of cells has been implicated in its development. This review will summarize the phases of atherosclerotic formation and all the cells involved in either promoting or inhibiting its development.

Single-cell analysis identified key macrophage subpopulations associated with atherosclerosis

Background

Atherosclerosis is a lipid-driven inflammatory disease characterized by plaque formation in major arteries. These plaques contain lipid-rich macrophages that accumulate through monocyte recruitment, local macrophage differentiation, and proliferation.

Objective

We identify the macrophage subsets that are closely related to atherosclerosis and reveal the key pathways in the progression of atherosclerotic disease.

Materials and methods

In this study, we characterize the single-cell landscape of atherosclerosis, identifying macrophage subsets closely related to the disease and revealing key pathways in its progression. Using analytical methods like CytoTRACE, Monocle2, Slingshot, and CellChat, we study macrophage differentiation and infer cell trajectory.

Results

The 8,417 macrophages were divided into six subtypes, macrophages: C0 C1QC+ macrophages, C1 SPP1+ macrophages, C2 FCN1+ macrophages, C3 IGKC+ macrophages, C4 FCER1A+ macrophages, C5CALD1+ macrophages. The results of gene set enrichment analysis, Monocle2, and Slingshot suggest that C2 FCN1+ macrophages may play an important role in the progression of atherosclerosis. C2 FCN1+ macrophages interact with endothelial cells via CCL, CXCL, APP, and other pathways to regulate the progression of atherosclerosis.

Conclusion

We identify a key macrophage subgroup (C2 FCN1+ macrophages) associated with atherosclerosis, which interacts with endothelial cells via CCL, CXCL, APP, and other pathways to regulate disease progression.

Multi-Omics Research on Angina Pectoris: A Novel Perspective

Angina pectoris (AP), a clinical syndrome characterized by paroxysmal chest pain, is caused by insufficient blood supply to the coronary arteries and sudden temporary myocardial ischemia and hypoxia. Long-term AP typically induces other cardiovascular events, including myocardial infarction and heart failure, posing a serious threat to patient safety. However, AP's complex pathological mechanisms and developmental processes introduce significant challenges in the rapid diagnosis and accurate treatment of its different subtypes, including stable angina pectoris (SAP), unstable angina pectoris (UAP), and variant angina pectoris (VAP). Omics research has contributed significantly to revealing the pathological mechanisms of various diseases with the rapid development of high-throughput sequencing approaches. The application of multi-omics approaches effectively interprets systematic information on diseases from the perspective of genes, RNAs, proteins, and metabolites. Integrating multi-omics research introduces novel avenues for identifying biomarkers to distinguish different AP subtypes. This study reviewed articles related to multi-omics and AP to elaborate on the research progress in multi-omics approaches (including genomics, transcriptomics, proteomics, and metabolomics), summarized their applications in screening biomarkers employed to discriminate multiple AP subtypes, and delineated integration methods for multi-omics approaches. Finally, we discussed the advantages and disadvantages of applying a single-omics approach in distinguishing diverse AP subtypes. Our review demonstrated that the integration of multi-omics technologies is preferable for quick and precise diagnosis of the three AP types, namely SAP, UAP, and VAP.

CFL1 restores the migratory capacity of bone marrow mesenchymal stem cells in primary Sjögren's syndrome by regulating CCR1 expression

BACKGROUND

Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease. There is no relevant research on whether the migratory ability of bone marrow mesenchymal stem cells (BM-MSC) is impaired in patients with pSS (pSS-BMMSC).

METHODS

Trajectories and velocities of BM-MSC were analyzed. Transwell migration assay and wound healing assay were used to investigate the migratory capacity of BM-MSC. The proliferative capacity of BM-MSC was evaluated by EDU and CCK8 assay. RNA-seq analysis was then performed to identify the underlying mechanism of lentivirus-mediated cofilin-1 overexpression BM-MSC (BMMSCCFL1). The therapeutic efficacy of BMMSCCFL1 was evaluated in NOD mice.

RESULTS

The migratory capacity of pSS-BMMSC was significantly reduced compared to normal volunteers (HC-BMMSC). The expression of the motility-related gene CFL1 was decreased in pSS-BMMSC. Lentivirus-mediated CFL1 overexpression of pSS-BMMSC promoted the migration capacity of pSS-BMMSC. Furthermore, RNA-seq revealed that CCR1 was the downstream target gene of CFL1. To further elucidate the mechanism of CFL1 in regulating BM-MSC migration and proliferation via the CCL5/CCR1 axis, we performed a rescue experiment using BX431 (a CCR1-specific inhibitor) to inhibit CCR1. The results showed that CCR1 inhibitors suppressed the migration and proliferation capacity of MSC induced by CFL1.

CONCLUSION

The pSS-BMMSC leads to impaired migration and proliferation, and overexpression of CFL1 can rescue the functional deficiency and alleviate disease symptoms in NOD mice. Mechanically, CFL1 can regulate the expression level of the downstream CCL5/CCR1 axis to enhance the migration and proliferation of BM-MSC.