Clonally expanded memory CD8+ T cells accumulate in atherosclerotic plaques and are pro-atherogenic in aged mice

Endothelial Immunosuppression in Atherosclerosis : Translational Control by Elavl1/HuR

Atherosclerotic plaques are defined by the accumulation of lipids and immune cells beneath the endothelium of the arterial intima. CD8 T cells are among the most abundant immune cell types in plaque, and conditions linked to their activation correlate with increased levels of cardiovascular disease. As lethal effectors of the immune response, CD8 T cell activation is suppressed at multiple levels. These checkpoints are critical in dampening autoimmune responses, and limiting damage in cardiovascular disease. Endothelial cells are well known for their role in recruiting CD8 T and other hematopoietic cells to low and disturbed flow (LDF) arterial regions that develop plaque, but whether they locally influence CD8 effector functions is unclear. Here, we show that endothelial cells can actively suppress CD8 T cell responses in settings of chronic plaque inflammation, but that this behavior is governed by expression of the RNA-binding protein Embryonic Lethal, Abnormal Vision-Like 1 (Elavl1). In response to immune cell recruitment in plaque, the endothelium dynamically shifts splicing of pre-mRNA and their translation to enhance expression of immune-regulatory proteins including C1q and CD27. This program is immuno-suppressive, and limited by Elavl1. We show this by Cdh5(PAC)-CreERT2-mediated deletion of Elavl1 (ECKO), and analysis of changes in translation by Translating Ribosome Affinity Purification (TRAP). In ECKO mice, the translational shift in chronic inflammation is enhanced, leading to increased ribosomal association of C1q components and other critical regulators of immune response and resulting in a ~70% reduction in plaque CD8 T cells. CITE-seq analysis of the remaining plaque T cells shows that they exhibit lower levels of markers associated with T cell receptor (TCR) signaling, survival, and activation. To understand whether the immunosuppressive mechanism occurred through failed CD8 recruitment or local modulation of T cell responses, we used a novel in vitro co-culture system to show that ECKO endothelial cells suppress CD8 T cell expansion-even in the presence of wild-type myeloid antigen-presenting cells, antigen-specific CD8 T cells, and antigen. Despite the induction of C1q mRNA by T cell co-culture in both wild-type and ECKO endothelial cells, we find C1q protein abundantly expressed only in co-culture with ECKO cells. Together, our data define a novel immune-suppressive transition in the endothelium, reminiscent of the transition of T cells to T-regs, and demonstrate the regulation of this process by Elavl1.

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images

Stroke is a major threat to life and health in modern society, especially in the aging population. Stroke may cause sudden death or severe sequela-like hemiplegia. Although computed tomography (CT) and magnetic resonance imaging (MRI) are standard diagnosis methods, and artificial intelligence models have been built based on these images, shortage in medical resources and the time and cost of CT/MRI imaging hamper fast detection, thus increasing the severity of stroke. Here, we developed a convolutional neural network model by integrating four networks, Xception, ResNet50, VGG19, and EfficientNetb1, to recognize stroke based on 2D facial images with a cross-validation area under curve (AUC) of 0.91 within the training set of 185 acute ischemic stroke patients and 551 age- and sex-matched controls, and AUC of 0.82 in an independent data set regardless of age and sex. The model computed stroke probability was quantitatively associated with facial features, various clinical parameters of blood clotting indicators and leukocyte counts, and, more importantly, stroke incidence in the near future. Our real-time facial image artificial intelligence model can be used to rapidly screen and prediagnose stroke before CT scanning, thus meeting the urgent need in emergency clinics, potentially translatable to routine monitoring.

Development of a Spectral Flow Cytometry Analysis Pipeline for High-Dimensional Immune Cell Characterization

Flow cytometry is a widely used technique for immune cell analysis, offering insights into cell composition and function. Spectral flow cytometry allows for high-dimensional analysis of immune cells, overcoming limitations of conventional flow cytometry. However, analyzing data from large antibody panels can be challenging using traditional bi-axial gating strategies. Here, we present a novel analysis pipeline designed to improve analysis of spectral flow cytometry. We employ this method to identify rare T cell populations in aging. We isolated splenocytes from young (2-3 months) and aged (18-19 months) female mice then stained these with a panel of 20 fluorescently labeled antibodies. Spectral flow cytometry was performed, followed by data processing and analysis using Python within a Jupyter Notebook environment to perform batch correction, unsupervised clustering, dimensionality reduction, and differential expression analysis. Our analysis of 3,776,804 T cells from 11 spleens revealed 34 distinct T cell clusters identified by surface marker expression. We observed significant differences between young and aged mice, with certain clusters enriched in one age group over the other. Naïve, effector memory, and central memory CD8+ and CD4+ T cell subsets exhibited age-associated changes in abundance and marker expression. Additionally, γδ T cell clusters showed differential abundance between age groups. By leveraging high-dimensional analysis methods borrowed from single-cell RNA sequencing analysis, we identified age-related differences in T cell subsets, providing insights into the immune aging process. This approach offers a robust, free, and easily implemented analysis pipeline for spectral flow cytometry data that may facilitate the discovery of novel therapeutic targets for age-related immune dysfunction.

Granzyme serine proteases in inflammation and rheumatic diseases

Granzymes (granule-secreted enzymes) are a family of serine proteases that have been viewed as redundant cytotoxic enzymes since their discovery more than 30 years ago. Predominantly produced by cytotoxic lymphocytes and natural killer cells, granzymes are delivered into the cytoplasm of target cells through immunological synapses in cooperation with the pore-forming protein perforin. After internalization, granzymes can initiate cell death through the cleavage of intracellular substrates. However, evidence now also demonstrates the existence of non-cytotoxic, pro-inflammatory, intracellular and extracellular functions that are granzyme specific. Under pathological conditions, granzymes can be produced and secreted extracellularly by immune cells as well as by non-immune cells. Depending on the granzyme, accumulation in the extracellular milieu might contribute to inflammation, tissue injury, impaired wound healing, barrier dysfunction, osteoclastogenesis and/or autoantigen generation.

Immunometabolism in atherosclerotic disorders

Cardiovascular diseases (CVDs), including atherosclerosis, myocardial infarction and heart failure, are the leading causes of morbidity and mortality worldwide. Emerging evidence suggests a crucial role for immune cell dysfunction and inflammation in the progression of this complex set of diseases. Recent advances demonstrate that immune cells, tightly linked to CVD pathogenesis, are sensitive to environmental signals and respond by engaging immunometabolic networks that shape their behavior. Inflammatory cues and altered nutrient availability within atherosclerotic plaques or following ischemia synergize to elicit metabolic shifts in immune cells that influence the course of disease pathology. Understanding these metabolic adaptations and how they contribute to cellular dysfunction may reveal novel therapeutic approaches for the treatment of CVD. Here we provide a comprehensive summary of the metabolic reprogramming that occurs in immune cells and their progenitors during CVD, offering insights into the potential therapeutic interventions to mitigate disease progression.