Epsin Nanotherapy Regulates Cholesterol Transport to Fortify Atheroma Regression

Aiming at early-stage vulnerable plaques: A nanoplatform with dual-mode imaging and lipid-inflammation integrated regulation for atherosclerotic theranostics

The vulnerable plaques in atherosclerosis can cause severe outcome with great danger of acute cardiovascular events. Thus, timely diagnosis and treatment of vulnerable plaques in early stage can effectively benefit the clinical management of atherosclerosis. In this work, a targeting theranostic strategy on early-stage vulnerable plaques in atherosclerosis is realized by a LAID nanoplatform with X-CT and fluorescent dual-mode imaging and lipid-inflammation integrated regulation abilities. The iodinated contrast agents (ICA), phenylboronic acid modified astaxanthin and oxidized-dextran (oxDEX) jointly construct the nanoparticles loaded with the lipid-specific probe LFP. LAID indicates an active targeting to plaques along with the dual-responsive disassembly in oxidative stress and acidic microenvironment of atherosclerosis. The X-CT signals of ICA execute the location of early-stage plaques, while the LFP combines with lipid cores and realizes the recognition of vulnerable plaques. Meanwhile, the treatment based on astaxanthin is performed for restraining the progression of plaques. Transcriptome sequencing suggests that LAID can inhibit the lipid uptake and block NF-κB pathway, which synergistically demonstrates a lipid-inflammation integrated regulation to suppression the plaques growing. The in vivo investigations suggest that LAID delivers a favorable theranostics to the early-stage vulnerable plaques, which provides an impressive prospect for reducing the adverse prognosis of atherosclerosis.

The diversification of methods for studying cell-cell interactions and communication

No cell lives in a vacuum, and the molecular interactions between cells define most phenotypes. Transcriptomics provides rich information to infer cell-cell interactions and communication, thus accelerating the discovery of the roles of cells within their communities. Such research relies heavily on algorithms that infer which cells are interacting and the ligands and receptors involved. Specific pressures on different research niches are driving the evolution of next-generation computational tools, enabling new conceptual opportunities and technological advances. More sophisticated algorithms now account for the heterogeneity and spatial organization of cells, multiple ligand types and intracellular signalling events, and enable the use of larger and more complex datasets, including single-cell and spatial transcriptomics. Similarly, new high-throughput experimental methods are increasing the number and resolution of interactions that can be analysed simultaneously. Here, we explore recent progress in cell-cell interaction research and highlight the diversification of the next generation of tools, which have yielded a rich ecosystem of tools for different applications and are enabling invaluable discoveries.

A new perspective on the current and future development potential of ABCG1

ABCG1 is an essential protein involved in the efflux of intracellular cholesterol to the extracellular space, thus playing a critical role in reducing cholesterol accumulation in neighboring tissues. Bibliometric analysis pertains to the interdisciplinary field of quantitative examination of diverse documents using mathematical and statistical techniques. It integrates the investigation of structural and temporal patterns in academic publications with an exploration of subject focus and forms of uncertainty. This research paper examines the historical evolution, current areas of interest, and future development trends of ABCG1 through bibliometric analysis. This study aims to offer readers insights into the research status and emerging trends of ABCG1, thereby assisting researchers in the exciting field to explore novel research avenues. Following rigorous selection, research on ABCG1 has remained highly active over the past two decades. ABCG1 has even started to emerge in previously unrelated fields, such as the field of cancer research. According to the analysis conducted by Citespace, a lot of keywords and influential citations were identified. ABCG1 has been found to establish a connection between cancer and cardiovascular disease, highlighting their interrelationship. This review aims to assist readers who have limited familiarity with ABCG1 research in gaining a rapid understanding of its developmental trajectory. Additionally, it aims to offer researchers potential areas of focus for future studies related to ABCG1.

History and Development of ABCA1

ATP-binding cassette protein A1 (ABCA1) is a key protein in the transport of intracellular cholesterol to the extracellular and plays an important role in reducing cholesterol accumulation in surrounding tissues. Bibliometric analysis refers to the cross-science of quantitative analysis of a variety of documents by mathematical and statistical methods. It combines an analysis of structural and temporal patterns in scholarly publications with a description of topic concentration and types of uncertainty. This paper analyzes the history, hotspot, and development trend of ABCA1 through bibliometrics. It will provide readers with the research status and development trend of ABCA1 and help the hot research in this field explore new research directions. After screening, the research on ABCA1 is still in a hot phase in the past 20 years. ABCA1 is emerging in previously unrelated disciplines such as cancer. There were 551 keywords and 6888 breakout citations counted by CiteSpace. The relationship between cancer and cardiovascular disease has been linked by ABCA1. This review will guide readers who are not familiar with ABCA1 research to quickly understand the development process of ABCA1 and provide researchers with a possible future research focus on ABCA1.

An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis

Background

The role of complement component 1q (C1Q) related genes on human atherosclerotic plaques (HAP) is less known. Our aim is to establish C1Q associated hub genes using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis to diagnose and predict HAP patients more effectively and investigate the association between C1Q and HAP (ischemic stroke) using bidirectional Mendelian randomization (MR) analysis.

Methods

HAP scRNA-seq and bulk-RNA data were download from the Gene Expression Omnibus (GEO) database. The C1Q-related hub genes was screened using the GBM, LASSO and XGBoost algorithms. We built machine learning models to diagnose and distinguish between types of atherosclerosis using generalized linear models and receiver operating characteristics (ROC) analyses. Further, we scored the HALLMARK_COMPLEMENT signaling pathway using ssGSEA and confirmed hub gene expression through qRT-PCR in RAW264.7 macrophages and apoE-/- mice. Furthermore, the risk association between C1Q and HAP was assessed through bidirectional MR analysis, with C1Q as exposure and ischemic stroke (IS, large artery atherosclerosis) as outcomes. Inverse variance weighting (IVW) was used as the main method.

Results

We utilized scRNA-seq dataset (GSE159677) to identify 24 cell clusters and 12 cell types, and revealed seven C1Q associated DEGs in both the scRNA-seq and GEO datasets. We then used GBM, LASSO and XGBoost to select C1QA and C1QC from the seven DEGs. Our findings indicated that both training and validation cohorts had satisfactory diagnostic accuracy for identifying patients with HPAs. Additionally, we confirmed SPI1 as a potential TF responsible for regulating the two hub genes in HAP. Our analysis further revealed that the HALLMARK_COMPLEMENT signaling pathway was correlated and activated with C1QA and C1QC. We confirmed high expression levels of C1QA, C1QC and SPI1 in ox-LDL-treated RAW264.7 macrophages and apoE-/- mice using qPCR. The results of MR indicated that there was a positive association between the genetic risk of C1Q and IS, as evidenced by an odds ratio (OR) of 1.118 (95%CI: 1.013-1.234, P = 0.027).

Conclusion

The authors have effectively developed and validated a novel diagnostic signature comprising two genes for HAP, while MR analysis has provided evidence supporting a favorable association of C1Q on IS.

Inhibiting Phosphatidylcholine Remodeling in Adipose Tissue Increases Insulin Sensitivity

Cell membrane phosphatidylcholine (PC) composition is regulated by lysophosphatidylcholine acyltransferase (LPCAT); changes in membrane PC saturation are implicated in metabolic disorders. Here, we identified LPCAT3 as the major isoform of LPCAT in adipose tissue and created adipocyte-specific Lpcat3-knockout mice to study adipose tissue lipid metabolism. Transcriptome sequencing and plasma adipokine profiling were used to investigate how LPCAT3 regulates adipose tissue insulin signaling. LPCAT3 deficiency reduced polyunsaturated PCs in adipocyte plasma membranes, increasing insulin sensitivity. LPCAT3 deficiency influenced membrane lipid rafts, which activated insulin receptors and AKT in adipose tissue, and attenuated diet-induced insulin resistance. Conversely, higher LPCAT3 activity in adipose tissue from ob/ob, db/db, and high-fat diet-fed mice reduced insulin signaling. Adding polyunsaturated PCs to mature human or mouse adipocytes in vitro worsened insulin signaling. We suggest that targeting LPCAT3 in adipose tissue to manipulate membrane phospholipid saturation is a new strategy to treat insulin resistance.

ARTICLE HIGHLIGHTS

Early hyperlipidemia triggers metabolomic reprogramming with increased SAH, increased acetyl-CoA-cholesterol synthesis, and decreased glycolysis

To identify metabolomic reprogramming in early hyperlipidemia, unbiased metabolome was screened in four tissues from ApoE-/- mice fed with high fat diet (HFD) for 3 weeks. 30, 122, 67, and 97 metabolites in the aorta, heart, liver, and plasma, respectively, were upregulated. 9 upregulated metabolites were uremic toxins, and 13 metabolites, including palmitate, promoted a trained immunity with increased syntheses of acetyl-CoA and cholesterol, increased S-adenosylhomocysteine (SAH) and hypomethylation and decreased glycolysis. The cross-omics analysis found upregulation of 11 metabolite synthetases in ApoE‾/‾ aorta, which promote ROS, cholesterol biosynthesis, and inflammation. Statistical correlation of 12 upregulated metabolites with 37 gene upregulations in ApoE‾/‾ aorta indicated 9 upregulated new metabolites to be proatherogenic. Antioxidant transcription factor NRF2-/- transcriptome analysis indicated that NRF2 suppresses trained immunity-metabolomic reprogramming. Our results have provided novel insights on metabolomic reprogramming in multiple tissues in early hyperlipidemia oriented toward three co-existed new types of trained immunity.

Integrated single-cell RNA-seq analysis reveals the vital cell types and dynamic development signature of atherosclerosis

Introduction: In the development of atherosclerosis, the remodeling of blood vessels is a key process involving plaque formation and rupture. So far, most reports mainly believe that macrophages, smooth muscle cells, and endothelial cells located at the intima and media of artery play the key role in this process. Few studies had focused on whether fibroblasts located at adventitia are involved in regulating disease process.

Methods and results: In this study, we conducted in-depth analysis of single-cell RNA-seq data of the total of 18 samples from healthy and atherosclerotic arteries. This study combines several analysis methods including transcription regulator network, cell-cell communication network, pseudotime trajectory, gene set enrichment analysis, and differential expression analysis. We found that SERPINF1 is highly expressed in fibroblasts and is involved in the regulation of various signaling pathways.

Conclusion: Our research reveals a potential mechanism of atherosclerosis, SERPINF1 regulates the formation and rupture of plaques through the Jak-STAT signaling pathway, which may provide new insights into the pathological study of disease. Moreover, we suggest that SRGN and IGKC as potential biomarkers for unstable arterial plaques.