| Literature DB >> 33267666 |
Holger Winkels1, Dennis Wolf1.
Abstract
The infiltration and accumulation of pro- and anti-inflammatory leukocytes within the intimal layer of the arterial wall is a hallmark of developing and progressing atherosclerosis. While traditionally perceived as macrophage- and foam cell-dominated disease, it is now established that atherosclerosis is a partial autoimmune disease that involves the recognition of peptides from ApoB (apolipoprotein B), the core protein of LDL (low-density lipoprotein) cholesterol particles, by CD4+ T-helper cells and autoantibodies against LDL and ApoB. Autoimmunity in the atherosclerotic plaque has long been understood as a pathogenic T-helper type-1 driven response with proinflammatory cytokine secretion. Recent developments in high-parametric cell immunophenotyping by mass cytometry, single-cell RNA-sequencing, and in tools exploring antigen-specificity have established the existence of several unforeseen layers of T-cell diversity with mixed TH1 and T regulatory cells transcriptional programs and unpredicted fates. These findings suggest that pathogenic ApoB-reactive T cells evolve from atheroprotective and immunosuppressive CD4+ T regulatory cells that lose their protective properties over time. Here, we discuss T-cell heterogeneity in atherosclerosis with a focus on plasticity, antigen-specificity, exhaustion, maturation, tissue residency, and its potential use in clinical prediction.Entities:
Keywords: atherosclerosis; autoantibodies; autoimmunity; immunophenotyping; peptide
Year: 2020 PMID: 33267666 PMCID: PMC7837690 DOI: 10.1161/ATVBAHA.120.312137
Source DB: PubMed Journal: Arterioscler Thromb Vasc Biol ISSN: 1079-5642 Impact factor: 8.311
Figure 1.Distinct vascular T-cell phenotypes in the healthy and atherosclerotic mouse aortas. Overview of the 4 major T-cell phenotypes identified by single-cell RNA-sequencing with key gene expression, frequencies, and regulated pathways during atherosclerosis progression. Gene signatures were retrieved by differentially expressed genes among all leukocytes across several studies. Frequencies of clusters were retrieved by an analysis of the original data set (*),[39] or estimations based on the original publication (**).[46] CD indicates chow diet–consuming mice; CTL, cytotoxic T-cell–mediated apoptosis; HFD, high-fat diet–consuming mice; IFN-γ, interferon-gamma; and WD, Western diet–consuming mice. ***Regulated pathways between CD and WD-fed mice were retrieved from study by Winkels et al.[39] Schematics adapted from “Smart Servier Medical Art.”
Figure 2.Proposed fate of T regulatory cells in atherosclerosis. In the course of atherosclerosis, regulatory T cells (Treg) with an immunosuppressive and atheroprotective function lose their protective properties. In atherosclerotic plaques or lymph nodes, former Tregs are characterized by an entire loss (exTreg) or an inactivity of FoxP3 (Teff-like, CCR5+ Teff). We propose that several classes of signals may induce such inactivity or loss of FoxP3. These include extrinsic signals (hypercholesterolemia, chronic low-grade inflammation, endothelial dysfunction, and plaque hypoxia) and overwhelming immune-signaling caused by repetitive (auto-) antigen presentation and costimulation. Intrinsic proinflammatory signaling events and epigenetic modifications may partially be promoted by such extrinsic stimuli and/or intracellular cholesterol accumulation. In addition, several modulators of FoxP3 have been identified. Destabilized Tregs can develop into distinct phenotypes, which can express several opposing TFs and canonical T-cell cytokines simultaneously: (1) TH1/TH17 Tregs, (2) TH17 Tregs, (3) TH1 Tregs, and (4) follicular T helper cells (TFH). Because of the composite TH1/TH17/TH2/TFH phenotype and the expression of CXCR6 (C-X-C chemokine receptor type 6), it has been speculated that ApoB (apolipoprotein B)-specific T cells (ApoB+) correspond to the Cxcr6+ T-cell subset in single-cell RNA sequencing studies. However, it is not clear if an ApoB+ cell evolves from pure a FoxP3+ Treg (shown in green) or only exists in the reported composite phenotype. Likewise, the relationship of the 4 switched Treg phenotypes and the existence of more intermediate phenotypes remains unclear. Schematics adapted from “Smart Servier Medical Art.” Transcription factors displayed in brackets indicates only a low level of residual gene or protein expression. Bcl-6 indicates B-cell lymphoma protein-6; DBC1, deleted in breast cancer-1; FoxP, Forkhead box protein P; IFN-γ, interferon-gamma; IL, interleukin; IRF4, interferon regulatory factor-4; LDL, low-density lipoprotein; NFκB, nuclear factor κ-light-chain-enhancer; Pak, protein kinase; Runx, Runt-related transcription factor; TCR, T-cell receptor; and TGF-β, transforming growth factor-β.
Figure 3.Novel high-parametric and functional immunophenotyping to develop future risk prediction tools. In humans, T cells can be routinely sampled from surgically excised carotid, peripheral arterial atherosclerotic plaques, and peripheral blood. Mass cytometry (cytometry by time of flight [CyTOF]), single cell RNA-sequencing (scRNA-seq), or a combination of antibody-staining and scRNA-seq in cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) have the potential to uncover unique, even rare, cell populations with distinct identities and potentially specialized roles in atherosclerosis (atherosclerosis-specific T cell). The addition of functional layers by staining with tetramers of MHC-II (major histocompatibility complex II) loaded with peptides from autoantigens and with T-cell receptor (TCR) sequencing in a combination with CyTOF or scRNA-seq integrates the cell surface proteome and transcriptome with antigen-specificity. Such integration generates cell type-specific gene signature, which—vice versa—are detectable in silico in bulk RNA-sequencing data sets, an approach referred to as RNA-deconvolution, liquid biopsy, or virtual flow cytometry. The correlation with clinical outcome data will be helpful to discover clinically relevant cell types. Their transcriptomes or frequencies in blood or tissue may predict the clinical outcomes or identify novel targets for future immunomodulatory cell therapy. TF indicates transcription factor. Schematics adapted from “Smart Servier Medical Art.”