An Allosteric Shift in CD11c Affinity Activates a Proatherogenic State in Arrested Intermediate Monocytes

Identification of potential biomarkers in cardiovascular calcification based on bioinformatics combined with single-cell RNA-seq and multiple machine learning analysis

BACKGROUND

The molecular and genetic mechanisms underlying vascular calcification remain unclear. This study aimed to determine the differences in calcification marker-related gene expression in macrophages.

METHODS

The expression profiling datasets GSE104140 and GSE235995 were analysed to identify differentially expressed genes (DEGs) between fibroatheroma with calcification and diffuse intimal thickening. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, Weighted Gene Co-expression Network Analysis (WGCNA), and Gene Set Enrichment Analysis (GSEA) were performed to assess functional characteristics. Hub genes were identified through a protein-protein interaction (PPI) network and machine learning approaches. Single-cell RNA sequencing data (GSE159677) validated the expression of calcification-related genes in macrophages, while Mendelian randomization analysis explored their potential causal relationship with coronary calcification. Further validation was conducted using enzyme-linked immunosorbent assay (ELISA) on coronary calcification samples and immunohistochemistry in ApoE-/- mice. Intravascular ultrasound was performed to assess coronary calcification severity.

RESULTS AND CONCLUSIONS

Two key biomarkers, ITGAX and MYD88, were identified as diagnostic indicators of cardiovascular calcification. Both biomarkers were significantly upregulated in calcified samples and were strongly associated with immune processes. Single-cell RNA sequencing confirmed their high expression in multiple immune cell types. Additionally, molecular docking analysis revealed that retinoic acid interacted with both biomarkers, suggesting potential therapeutic relevance. Immunohistochemical and ELISA analyses further validated their elevated expression in calcified samples. These findings provide novel insights into the molecular mechanisms of vascular calcification and highlight potential diagnostic and therapeutic targets.

Exploring blood immune cells in the protective effects of gut microbiota on rheumatic heart disease based on Mendelian randomization analysis

Rheumatic Heart Disease (RHD) remains a significant health burden, particularly in regions with scarce healthcare resources, research on its immunological aspects remains insufficient. This study employed a two-sample Mendelian Randomization approach, utilizing GWAS data from the largest available datasets for gut microbiota and immune cells as exposures, with outcome data for Rheumatic Valve Diseases (RVD) and Rheumatic Heart Disease affecting other parts of the heart (RHD-other) obtained from the FinnGen study. The primary analytical method was the Inverse Variance Weighted (IVW) approach, complemented by heterogeneity analyses and MR-Egger regression to assess horizontal pleiotropy. Furthermore, a two-step mediation analysis was conducted to investigate the potential mediating role of immune cells in the association between gut microbiota and RHD. This study revealed significant inverse associations between gut microbiota abundance and Rheumatic Heart Disease (RHD) risk. Specifically, the gut abundance of genus Blautia was negatively correlated with RHD-other risk (P_IVW: 0.00932, OR [95%CI]: 0.000734[3.22e-06, 0.16937]), and genus Ruminococcaceae UCG005 showed a similar negative association (P_IVW: 0.038, OR [95%CI]: 0.165[0.02994, 0.90811]). Additionally, the proportions of CD4-CD8- T cell %leukocyte and CD4-CD8- T cell %T cell were inversely related to RHD-other risk (P_IVW: 0.02222, OR [95%CI]: 5.08027 [1.26133, 20.46191] and P: 0.01601, OR[95%CI]: 6.55576 [1.4196, 30.27582], respectively). Moreover, IgD on IgD + CD24 + B cells was found to be negatively correlated with RHD-other risk (P_IVW: 0.01867, OR [95%CI]: 2.17171 [1.1380, 4.14443]). The study also highlighted the protective effects of gut microbiota through mediation analyses: Blautia's impact via IgD on IgD + CD24 + B cells showed a mediation proportion of 8.62514%; Ruminococcaceae UCG005's influence via CD4-CD8- T cell %T cell and CD4-CD8- T cell %leukocyte resulted in mediation proportions of 35.25817% and 30.86827%, respectively. Significant inverse associations were observed between gut microbiota abundance and risk of Rheumatic Heart Disease (RHD), with specific findings for Rheumatic Valve Disease (RVD) and RHD affecting other parts of the heart (RHD-other). For RHD-other, higher abundance of Blautia (OR: 0.0007, 95% CI: 3.22e-06 to 0.169, p = 0.009) and Ruminococcaceae UCG005 (OR: 0.165, 95% CI: 0.030 to 0.908, p = 0.038) were associated with lower risk. Additionally, lower proportions of CD4-CD8- T cells (%leukocyte and %T cell) and IgD on IgD + CD24 + B cells were inversely related to RHD-other risk (ORs: 5.08 and 6.56, p = 0.022 and p = 0.016, respectively). For RVD, higher abundance of Candidatus Soleaferrea was protective (OR: 0.670, 95% CI: 0.460 to 0.976, p = 0.037), while higher levels of CD11c on granulocytes were associated with increased risk (OR: 1.310, 95% CI: 1.023 to 1.679, p = 0.032). Mediation analyses indicated that gut microbiota influence RHD risk through distinct immune pathways, with Blautia affecting RHD-other via IgD on B cells (8.62% mediation), Ruminococcaceae UCG005 via CD4-CD8- T cells (%T cell: 35.26%, %leukocyte: 30.87%). Genus Candidatus Soleaferrea affecting RVD through CD11c on granulocyte (15.01% mediation). The study concludes that higher gut abundance of Candidatus Soleaferrea protects against RVD through the mechanism involving CD11c on granulocytes. Additionally, Blautia exerts a protective effect against RHD-other through its influence on IgD on IgD + CD24 + B cells. Similarly, the abundance of genus Ruminococcaceae UCG005 provides protection against RHD-other by influencing CD4-CD8- T cell %T cell and CD4-CD8- T cell %leukocyte.

The sentinels of coronary artery disease: heterogeneous monocytes

Monocytes are heterogeneous immune cells that play a crucial role in the inflammatory response during atherosclerosis, influencing the progression and outcome of the disease. In the pathogenesis of atherosclerotic diseases, such as coronary artery disease (CAD), monocytes not only serve as the initial sensors of endogenous and exogenous pathogenic factors, but also function as intermediators that bridge the circulatory system and localized lesions. In the bloodstream, heterogeneous monocytes, acting as sentinels, are rapidly recruited to atherosclerotic lesions, where they exhibit a heightened capacity to respond to various pathological stimuli upon detecting signals from damaged vascular endothelial cells. Clinical studies have demonstrated that the heterogeneity of monocytes in CAD patients presents both diversity and complexity, varying across different disease subtypes and pathological stages. This review explores the heterogeneity of monocytes in CAD, focusing on alterations in monocyte subset numbers, proportions, and the expression of functional receptors, as well as their correlations with clinical features. Additionally, we propose strategies to enhance the clinical utility value of monocyte heterogeneity and outline future research directions in the field of CAD. With the widespread application of high-parameter flow cytometry and single-cell sequencing technologies, it is anticipated that a comprehensive understanding of monocyte heterogeneity in CAD will be achieved, enabling the identification of disease-specific monocyte subtypes. This could offer new opportunities for improving the diagnosis and treatment of CAD.

Motion blur microscopy: in vitro imaging of cell adhesion dynamics in whole blood flow

Imaging and characterizing the dynamics of cellular adhesion in blood samples is of fundamental importance in understanding biological function. In vitro microscopy methods are widely used for this task but typically require diluting the blood with a buffer to allow for transmission of light. However, whole blood provides crucial signaling cues that influence adhesion dynamics, which means that conventional approaches lack the full physiological complexity of living microvasculature. We can reliably image cell interactions in microfluidic channels during whole blood flow by motion blur microscopy (MBM) in vitro and automate image analysis using machine learning. MBM provides a low cost, easy to implement alternative to intravital microscopy, for rapid data generation where understanding cell interactions, adhesion, and motility is crucial. MBM is generalizable to studies of various diseases, including cancer, blood disorders, thrombosis, inflammatory and autoimmune diseases, as well as providing rich datasets for theoretical modeling of adhesion dynamics.

The multifaceted life of macrophages in white adipose tissue: Immune shift couples with metabolic switch

White adipose tissue (WAT) is a vital endocrine organ that regulates energy balance and metabolic homeostasis. In addition to fat cells, WAT harbors macrophages with distinct phenotypes that play crucial roles in immunity and metabolism. Nutrient demands cause macrophages to accumulate in WAT niches, where they remodel the microenvironment and produce beneficial or detrimental effects on systemic metabolism. Given the abundance of macrophages in WAT, this review summarizes the heterogeneity of WAT macrophages in physiological and pathological conditions, including their alterations in quantity, phenotypes, characteristics, and functions during WAT growth and development, as well as healthy or unhealthy expansion. We will discuss the interactions of macrophages with other cell partners in WAT including adipose stem cells, adipocytes, and T cells in the context of various microenvironment niches in lean or obese condition. Finally, we highlight how adipose tissue macrophages merge immunity and metabolic changes to govern energy balance for the organism.

Motion Blur Microscopy

Imaging and characterizing the dynamics of cellular adhesion in blood samples is of fundamental importance in understanding biological function. In vitro microscopy methods are widely used for this task, but typically require diluting the blood with a buffer to allow for transmission of light. However whole blood provides crucial mechanical and chemical signaling cues that influence adhesion dynamics, which means that conventional approaches lack the full physiological complexity of living microvasculature. We propose to overcome this challenge by a new in vitro imaging method which we call motion blur microscopy (MBM). By decreasing the source light intensity and increasing the integration time during imaging, flowing cells are blurred, allowing us to identify adhered cells. Combined with an automated analysis using machine learning, we can for the first time reliably image cell interactions in microfluidic channels during whole blood flow. MBM provides a low cost, easy to implement alternative to intravital microscopy, the in vivo approach for studying how the whole blood environment shapes adhesion dynamics. We demonstrate the method's reproducibility and accuracy in two example systems where understanding cell interactions, adhesion, and motility is crucial-sickle red blood cells adhering to laminin, and CAR-T cells adhering to E-selectin. We illustrate the wide range of data types that can be extracted from this approach, including distributions of cell size and eccentricity, adhesion durations, trajectories and velocities of adhered cells moving on a functionalized surface, as well as correlations among these different features at the single cell level. In all cases MBM allows for rapid collection and processing of large data sets, ranging from thousands to hundreds of thousands of individual adhesion events. The method is generalizable to study adhesion mechanisms in a variety of diseases, including cancer, blood disorders, thrombosis, inflammatory and autoimmune diseases, as well as providing rich datasets for theoretical modeling of adhesion dynamics.

Dietary Effects on Monocyte Phenotypes in Subjects With Hypertriglyceridemia and Metabolic Syndrome

In patients with hypertriglyceridemia, a short-term low-saturated fat vs high-saturated fat diet induced lower plasma lipids and improved monocyte phenotypes. These findings highlight the role of diet fat content and composition for monocyte phenotypes and possibly cardiovascular disease risk in these patients. (Effects of Dietary Interventions on Monocytes in Metabolic Syndrome; NCT03591588).

Inflammatory Links Between Hypertriglyceridemia and Atherogenesis

PURPOSE OF REVIEW

Recent studies indicate an association between hypertriglyceridemia (HTG) and atherosclerotic cardiovascular disease (ASCVD). The purpose of this review is to discuss the potential mechanism connecting HTG and ASCVD risk and the potential efficacy of HTG-targeting therapies in ASCVD prevention.

RECENT FINDINGS

HTG, with elevations in triglyceride-rich lipoproteins (TGRL) and their remnants, are causal ASCVD risk factors. The mechanisms whereby HTG increases ASCVD risk are not well understood but may include multiple factors. Inflammation plays a crucial role in atherosclerosis. TGRL compared to low-density lipoproteins (LDL) correlate better with inflammation. TGRL remnants can penetrate endothelium and interact with macrophages leading to foam cell formation and inflammation in arterial walls, thereby contributing to atherogenesis. In addition, circulating monocytes can take up TGRL and become lipid-laden foamy monocytes, which infiltrate the arterial wall and may also contribute to atherogenesis. Novel therapies targeting HTG or inflammation are in development and have potential of reducing residual ASCVD risk associated with HTG. Clinical and preclinical studies show a causal role of HTG in promoting ASCVD, in which inflammation plays a vital role. Novel therapies targeting HTG or inflammation have potential of reducing residual ASCVD risk.

CITEMOXMBD: A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells

Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here, we design a flexible single-cell multimodal analysis framework, called CITEMO, to integrate the transcriptome and antibody-derived tags (ADT) data to capture cell heterogeneity from the multi omics perspective. CITEMO uses Principal Component Analysis (PCA) to obtain a low-dimensional representation of the transcriptome and ADT, respectively, and then employs PCA again to integrate these low-dimensional multimodal data for downstream analysis. To investigate the effectiveness of the CITEMO framework, we apply CITEMO to analyse the cell subtypes of Cord Blood Mononuclear Cells (CBMC) samples. Results show that the CITEMO framework can comprehensively analyse single-cell multimodal samples and accurately identify cell subtypes. Besides, we find some specific immune cells that co-express multiple ADT markers. To better describe the co-expression phenomenon, we introduce the co-expression entropy to measure the heterogeneous distribution of the ADT combinations. To further validate the robustness of the CITEMO framework, we analyse Human Bone Marrow Cell (HBMC) samples and identify different states of the same cell type. CITEMO has an excellent performance in identifying cell subtypes and states for multimodal omics data. We suggest that the flexible design idea of CITEMO can be an inspiration for other single-cell multimodal tasks. The complete source code and dataset of the CITEMO framework can be obtained from https://github.com/studentiz/CITEMO.

Lipid Droplets, Phospholipase A2, Arachidonic Acid, and Atherosclerosis

Lipid droplets, classically regarded as static storage organelles, are currently considered as dynamic structures involved in key processes of lipid metabolism, cellular homeostasis and signaling. Studies on the inflammatory state of atherosclerotic plaques suggest that circulating monocytes interact with products released by endothelial cells and may acquire a foamy phenotype before crossing the endothelial barrier and differentiating into macrophages. One such compound released in significant amounts into the bloodstream is arachidonic acid, the common precursor of eicosanoids, and a potent inducer of neutral lipid synthesis and lipid droplet formation in circulating monocytes. Members of the family of phospholipase A₂, which hydrolyze the fatty acid present at the sn-2 position of phospholipids, have recently emerged as key controllers of lipid droplet homeostasis, regulating their formation and the availability of fatty acids for lipid mediator production. In this paper we discuss recent findings related to lipid droplet dynamics in immune cells and the ways these organelles are involved in regulating arachidonic acid availability and metabolism in the context of atherosclerosis.