Application of Tcf7hiCD8 + T cell in diagnosis or evaluation of atherosclerosis condition

Abstract

The invention relates to the field of atherosclerosis disease research, in particular to application of Tcf7hiCD8 + T cells in diagnosis or evaluation of atherosclerosis conditions. The Tcf7 is used as a core identification marker and is applied to an atherosclerosis environment, so that the Tcf7hiCD8 + T cell subset is successfully identified in the disease for the first time, the problem of missing detection caused by lack of key identification characteristics in the prior art is solved, and the cognitive blank in the field is filled.

Description

Technical Field

[0001] This invention relates to the field of atherosclerotic disease research, and particularly to Tcf7. hi Application of CD8+ T cells in the diagnosis or assessment of atherosclerosis. Background Technology

[0002] Atherosclerosis (AS) is a chronic inflammatory disease characterized by lipid deposition in the blood vessel wall, inflammatory responses, and plaque formation. Its pathological process involves complex regulation by various immune cells. Among them, T lymphocytes, especially CD8+ T cells, have been identified as a key immune cell subset involved in plaque formation, development, and instability, and their functional status is closely related to the progression of AS. Current research generally suggests that CD8+ T cells participate in local inflammatory responses in the AS plaque microenvironment mainly by releasing pro-inflammatory factors (such as IFN-γ and TNF-α) and cytotoxic molecules (such as granzymes), and under long-term chronic stimulation, they exhibit a terminal "exhaustion" state. This understanding forms an important foundation for current research on the immunopathological mechanisms of AS.

[0003] To elucidate the biological characteristics of CD8+ T cells in AS plaques, various analytical techniques have been developed. At the cellular characterization level, flow cytometry detects cell surface markers (such as CD3 and CD8) and intracellular functional molecules (such as IFN-γ and granzymes) to analyze the phenotype and effector function of immune cells isolated from plaques. Immunohistochemical staining can locate and semi-quantitatively assess CD8+ T cells in tissue sections. With the development of single-cell sequencing technology, current research has further utilized single-cell RNA sequencing (scRNA-seq) to perform unbiased analysis of the immune cell atlas within plaques, confirming the significant heterogeneity of CD8+ T cells in AS plaques and identifying specific subsets expressing cytotoxic effector molecules (such as GZMK and GZMB) and exhaustion-related molecules (such as PDCD1), providing a new perspective for understanding the functional diversity of CD8+ T cells.

[0004] Despite advancements in the phenotypic identification and functional analysis of CD8+ T cells, current technologies still have significant limitations in understanding the immune response of CD8+ T cells in AS. First, existing research largely focuses on the overall pro-inflammatory role and terminal differentiation state of CD8+ T cells, failing to explore whether there are subpopulations within this cell population possessing "stem cell-like" characteristics (such as self-renewal and differentiation potential). Such subpopulations have been shown to be crucial for maintaining long-term immune responses in other chronic inflammatory models, such as chronic infection and tumors. Second, due to the lack of specific identification methods for potential stem subpopulations, current technologies cannot effectively distinguish between stem-potential cells and terminally differentiated effector / exhausted cells within CD8+ T cells. This results in an incomplete understanding of the dynamic differentiation pathways, functional regulatory networks, and association mechanisms of CD8+ T cells within plaques with metabolic disorders (such as hyperlipidemia). These limitations not only restrict a deeper understanding of the immunopathological mechanisms of AS but also hinder the development of precision diagnostic and therapeutic strategies based on CD8+ T cell subpopulations. Summary of the Invention

[0005] Based on this, the purpose of this invention is to provide a Tcf7 hi Application of CD8+ T cells in the diagnosis or assessment of atherosclerosis.

[0006] To achieve the above objectives, the present invention can adopt the following technical solutions: This invention provides a Tcf7 hi Application of CD8+ T cell detection reagents in the preparation of products for diagnosing atherosclerosis or assessing its progression.

[0007] Preferably, the above applications include: diagnosing atherosclerosis or assessing disease progression by detecting one or more of the following indicators in biological samples: the proportion of Tcf7hiCD8+ T cells, the expression level of the Tcf7 gene, the expression level of the proliferation marker Mki67, the expression level of the pro-inflammatory cytokine IFNG, or the expression level of the exhaustion marker PD-L1.

[0008] More preferably, in the above applications, the biological sample is selected from arterial tissue, periarterial adipose tissue (PVAT), or peripheral blood.

[0009] More preferably, the above applications include: When the biological sample is peripheral blood, the proportion of Tcf7hiCD8+ T cells to CD8+ T cells in the peripheral blood is measured, combined with plasma total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels, to diagnose or assess the condition of ankylosing spondylitis (AS). When the proportion of Tcf7hiCD8+ T cells in peripheral blood is below 85% (with the average proportion of Tcf7hiCD8+ T cells in peripheral blood of healthy individuals being 92.39% as a reference), and TC ≥ 7.10 mmol / L and LDL-C ≥ 4.57 mmol / L, it indicates a high risk of AS or disease progression; and / or When the biological sample is atherosclerotic plaque tissue, the disease condition is assessed by detecting the ratio of Tcf7hiCD8+ T cells to Tcf7loCD8+ T cells in the plaque tissue. The Tcf7loCD8+ T cells are a subset of CD8+ T cells that express low levels of the Tcf7 gene and high levels of cytotoxic genes (Nkg7, Gzmb, Ctsw) and chemokines (Ccl5, Ccl4, Cxcr6). When the proportion of Tcf7hiCD8+ T cells to CD8+ T cells in the plaque tissue is less than 35.7% and the proportion of Tcf7loCD8+ T cells is greater than 60%, it indicates that AS is in an advanced stage.

[0010] Another aspect of the present invention provides a reagent / kit for diagnosing atherosclerosis or assessing its progression, the reagent / kit comprising a detection reagent that specifically identifies Tcf7hiCD8+ T cell markers.

[0011] Preferably, in the above-mentioned reagents / kits for diagnosing atherosclerosis or assessing its progression, the detection reagent that specifically identifies Tcf7hiCD8+ T cell markers is a reagent used to detect the expression level of one or more of the proliferation marker Mki67, the pro-inflammatory cytokine IFNG, or the depletion marker PD-L1 in Tcf7hiCD8+ T cells.

[0012] More preferably, in the above-mentioned reagents / kits for diagnosing atherosclerosis or assessing its progression, the detection reagent that specifically identifies the Tcf7hiCD8+ T cell marker is one or more of antibodies, nucleic acid probes, or primers.

[0013] More preferably, in the above-mentioned reagents / kits for diagnosing atherosclerosis or assessing its progression, the detection reagent is a fluorescently labeled antibody, which includes at least three of the following: anti-Tcf7 fluorescent antibody, anti-SELL fluorescent antibody, anti-CCR7 fluorescent antibody, and anti-Cd44 fluorescent antibody; the reagents / kits also include buffer, fixative, and permeabilization solution required for flow cytometry detection, and are accompanied by flow cytometry detection parameter setting instructions, which specify the fluorescence signal threshold used to distinguish Tcf7hiCD8+ T cells from other CD8+ T cell subsets.

[0014] More preferably, in the above-mentioned reagents / kits for diagnosing atherosclerosis or assessing its progression, the detection reagent is a nucleic acid detection reagent, including a specific primer pair for the Tcf7 gene, the sequence design of which is based on the conserved region of the Tcf7 gene; the nucleic acid detection reagent also includes specific primer pairs for the SELL, CCR7 and Cd44 genes, used to detect the expression level of the above genes by real-time quantitative PCR (qPCR) or reverse transcription PCR (RT-PCR) to determine the number of Tcf7hiCD8+ T cells.

[0015] In another aspect, the present invention provides a method for screening drugs for the treatment of atherosclerosis, the method comprising: using Tcf7 hi Changes in the function or number of CD8+ T cells were used as screening indicators; Tcf7 hi CD8+ T cells are a subset of CD8+ T cells that highly express the Tcf7 gene and simultaneously possess the expression characteristics of memory cell markers SELL+, CCR7+, and Il7r+, as well as effector cell markers Cd44+ and Nkg7+. Screening criteria include: changes in the proportion of Tcf7hiCD8+ T cells and changes in Tcf7 gene expression levels in biological samples after treatment with candidate drugs, or changes in the expression levels of proliferation markers (Mki67), pro-inflammatory cytokines (IFNG), and exhaustion markers (PD-L1) in these cells. If a candidate drug can increase the proportion of Tcf7hiCD8+ T cells, upregulate Tcf7 expression, or reduce the expression of exhaustion markers (PD-L1), while maintaining or enhancing the normal functional expression of proliferation markers (Mki67) and pro-inflammatory cytokines (IFNG), it is considered a potential therapeutic drug for AS. Biological samples are selected from at least one of arterial tissue, periarterial adipose tissue (PVAT), and peripheral blood.

[0016] Preferably, in the above screening method, the biological samples are derived from mouse models with LDLR gene deletion (LDLR- / -) and fed a high-fat diet (HFD); the screening method includes the following steps: (1) Construction of experimental and control groups: The experimental group consisted of LDLR- / -HFD mice given the candidate drug, and the control group consisted of LDLR- / -HFD mice not given the candidate drug; (2) Sample acquisition: Aortic tissue, thoracic aortic PVAT or peripheral blood samples were obtained from the two groups of mice respectively; (3) Indicator detection: The proportion of Tcf7hiCD8+ T cells, the expression level of Tcf7, and the expression levels of proliferation markers (Mki67), pro-inflammatory cytokines (IFNG), and exhaustion markers (PD-L1) in the two groups of samples were detected by flow cytometry or single-cell sequencing (ScRNA-seq). Result determination: If, compared with the control group, the experimental group showed an increase of ≥10% in the proportion of Tcf7hiCD8+ T cells, an upregulation of ≥15% in Tcf7 expression level, and a downregulation of ≥20% in PD-L1 expression level, then the candidate drug was determined to be a potential treatment for AS.

[0017] Preferably, in the above screening method, the screening index further includes Tcf7hiCD8+ T cells transforming into Tcf7. lo The degree of differentiation of CD8+ T cells; by detecting Tcf7 hi The degree of differentiation is determined by the change in the expression level of cytotoxic genes (Nkg7, Gzmb) in CD8+ T cells; if the candidate drug can downregulate the expression level of Nkg7 and Gzmb in Tcf7hiCD8+ T cells by ≥15%, it is further identified as a potential AS treatment drug.

[0018] More preferably, in the above screening method, when detecting by single-cell sequencing (ScRNA-seq), the transcriptome characteristics of Tcf7hiCD8+ T cells are also analyzed, specifically the expression levels of NK cell receptor genes (Klrk1, Klrc2, Klre1), Il12 receptor gene (Il12rb), and chemokine-related genes (Xcl1, Cxcr3). If the normal functional expression level of the above genes is maintained at ≥80% in the experimental group compared with the control group, the candidate drug is considered a potential AS treatment drug.

[0019] The beneficial effects of this invention include: (1) By using Tcf7 as a core identification marker and applying it to the atherosclerotic environment, this invention successfully identified the Tcf7hiCD8+ T cell subset in the disease for the first time, solving the problem of missed detection caused by the lack of this key identification feature in the prior art and filling the knowledge gap in this field. (3) This invention not only identified the existence of this cell, but also precisely analyzed its unique mixed phenotype, which simultaneously possesses stemness / memory characteristics (Tcf7, IL7R, CCR7, Sell) and early effector functions (Cd44, NKG7, XCL1). This contrasts sharply with the stem cell-like CD8+ T cells with different functional states reported in the fields of oncology and other existing technologies, revealing the special role of this cell in the specific pathological environment of AS, and providing a new perspective for understanding the heterogeneity of CD8+ T cells within plaques and the maintenance mechanism of immune response; (3) This invention, through comparative analysis of AS models on high-fat diets (HFD) and normal diets (ND), clarifies that high-fat diets, a core driver of AS, can lead to a decrease in the proportion of Tcf7hiCD8+ T cells, weakened stemness characteristics, enhanced pro-inflammatory and proliferative capacity, and drive their differentiation towards the terminal exhaustion phenotype. The revelation of this dynamic change pattern provides direct cellular evidence for understanding how metabolic disorders exacerbate AS inflammation; (4) Through clinical sample analysis, this invention has for the first time discovered and verified that the proportion of Tcf7+CD8+T cells in human peripheral blood is significantly negatively correlated with blood lipid levels (LDL-C, TC). This discovery not only verifies the conclusions of animal experiments, but more importantly, it directly links a specific immune cell subset with key clinical indicators of AS, providing a scientific basis for this cell subset as a potential non-invasive biomarker for assessing the activity or prognosis of AS, and has important clinical translation prospects. Attached Figure Description

[0020] Figure 1 Re-clustering and annotation of T and NK cell subsets; where A is the visualization of UMAP clustering of T and NK cell subsets; B is the proportion of different cell subsets; C is the further annotation of CD4+T and CD8+T cell populations; D is the expression of biomarker genes in each population; Figure 2 Gene differential expression analysis and GO enrichment analysis of T cell subsets; where A shows the top 5 genes visualized in the gene differential expression analysis of T cell subsets; B shows the top 5 genes visualized in the GO enrichment analysis of differentially expressed genes of T cell subsets. Figure 3 Differential gene expression analysis and GO enrichment analysis of CD8+ T cells; where A represents Tcf7. hi Differentially expressed genes between CD8T cells and other CD8+T cells; B shows GO enrichment analysis of differentially expressed genes; C shows Ucell gene set scoring to assess the function of each CD8+T cell. Figure 4 For different groups of Tcf7 hi Differences in the transcriptional profiles of CD8+ T cells; where A represents the differences in Tcf7 between different groups. hi Differentially expressed genes in CD8+ T cells; B shows KEGG enrichment analysis of differentially expressed genes; C shows Ucell gene set scoring to evaluate Tcf7. hi Functional status of different groups of CD8+ T cells; Figure 5 This is a pseudo-temporal analysis of CD8+ T cell subsets; where A represents the distribution of different CD8+ T cell subsets in the pseudo-temporal trajectory; and B represents the expression changes of key genes in the pseudo-temporal trajectory. Figure 6 Immunofluorescence of paraffin sections of mouse aortic root; where A is HE staining of paraffin sections of mouse aortic root (Scalebar, 100 μm); B is double staining of CD8 and Tcf7 with immunofluorescence (Scalebar, 50 μm). Figure 7 The results are shown in the flow cytometry analysis of the mouse aorta. A represents the gating strategy of CD8+ T cells detected by flow cytometry in the mouse aorta; B represents the gating strategy of Tcf7 levels in different groups and different types of CD8+ T cells detected by flow cytometry; C represents the proportion of CD8+ T cells in the mouse aorta among different groups; D represents the proportion of Tcf7+CD8+ T cells in the mouse aorta among different groups; E represents the proportion of different types of CD8+ T cells in the aorta of different groups of mice; and F represents the expression of Tcf7 in different CD8+ T cells in the aorta of different groups of mice (*P<0.05, **P<0.01, ***P<0.001, n=4). Figure 8 Validating Tcf7 in mouse aortic flow cytometry hi CD8T cell function; where A is the contour plot gating strategy for detecting different functional molecules by flow cytometry in the mouse aorta; B is the proliferation level of Tcf7+CD8+ T cells in the mouse aorta among different groups; C is the expression level of IFNG in Tcf7+CD8+ T cells in the mouse aorta among different groups; D is the expression level of PD-L1, a marker of CD8+Teff cell exhaustion, in the aorta of different groups of mice; (**P<0.01, n=4); Figure 9 To validate Tcf7 by flow cytometry in mouse peripheral blood PBMCs hi CD8+ T cells and their function; where A is the gating strategy for Tcf7 level detection in CD8+ T cells by flow cytometry; B is the Tcf7 expression level of CD8+ T cells in different groups; C is the difference in Tcf7 expression level among different CD8+ T cells; D is the gating strategy for Ki67 level detection in Tcf7+CD8+TCM cells by flow cytometry; EF is the Mki67 and IFNG expression levels of Tcf7+CD8+TCM cells in different groups; G is the detection of CD8+ T cell exhaustion level in different groups. (*P<0.05, **P<0.01, n=6); Figure 10To detect the proportion of Tcf7+CD8+ T cells in different PVAT tissues by flow cytometry; where A is the gating strategy for detecting Tcf7, Mki67, and IFNG markers in thoracic aortic PVAT and abdominal aortic PVAT by flow cytometry; B is the proportion of Tcf7+CD8+ T cells in thoracic aortic PVAT and abdominal aortic PVAT; C is the difference in Mki67 expression level of Tcf7+CD8+ T cells in thoracic aortic PVAT; D is the difference in Mki67 and IFNG expression levels of Tcf7+CD8+ T cells in thoracic aortic PVAT; E is the difference in PD-L1 expression level of CD8+ T cells in thoracic aortic PVAT; (*P<0.05, n=4); Figure 11 Analysis of the proportion of Tcf7+CD8T cells in different mouse tissues; where A is the gating strategy of Tcf7 level in CD8T cells in iWAT, BAT and eWAT detected by flow cytometry; B is the change of Tcf7+CD8T cell proportion in different adipose tissues in different groups. (*P<0.05, **P<0.01, n=4); Figure 12 Analysis of the proportion of Tcf7+CD8T cells in mouse spleen; where A is the gating strategy for detecting Tcf7 and Mki67 levels in CD8T cells by flow cytometry in spleen; B is the change in the proportion of different types of CD8T cells in different groups of spleen; C is the difference in the proportion of Tcf7+CD8T cells between the two groups; D is the difference in the level of Mki67 expression in Tcf7+CD8+T cells between the two groups; (**P<0.01, n=8); Figure 13 Transcriptional profiles of T cell subsets in human carotid atherosclerotic plaques are presented. A shows UMAP clustering visualization of T cell subsets in three carotid atherosclerotic plaque datasets (GSE155512, GSE159677, and GSE253903); B shows the expression percentage of TCF7 in each CD8+ T cell cluster; C shows the cell percentage of each CD8+ T cell cluster; and D shows the expression of T cell markers, cytotoxic / cytokine markers, and exhaustion gene markers in T cells of carotid atherosclerotic plaques. Figure 14 Transcriptional profiles of T cell subsets in human coronary atherosclerotic plaques; where A is the UMAP clustering visualization of T cell subsets in the coronary atherosclerotic plaque dataset (GSE196943); and B is the visualization of gene expression of relevant biomarkers. Figure 15Peripheral blood PBMCs were analyzed by flow cytometry in FH patients and healthy subjects. A shows the gating strategy for CD8+ T cells and CD8+ T cell Tcf7 levels detected by flow cytometry in different groups; B shows the proportion of peripheral blood CD8+ T cells in healthy subjects, heterozygous FH patients receiving cholesterol-lowering therapy (LLT-FH), and heterozygous FH patients not receiving cholesterol-lowering therapy (noLLT-FH); C shows the Tcf7 expression level of CD8+ T cells in different patient groups; D shows the gating strategy for detecting the proportion of different types of CD8+ T cells in the healthy group and the LLT-FH group; E shows the detection... Statistical results of the proportion of different types of CD8+ T cells in the healthy group and LLT-FH group; F represents the distribution of Tcf7 in different types of CD8+ T cells; G represents the gating strategy for detecting IFNG expression in Tcf7+CD8T cells in the healthy group and LLT-FH group; H represents the statistical results of detecting IFNG expression in Tcf7+CD8T cells in the healthy group and LLT-FH group; I represents the correlation analysis between the proportion of Tcf7+CD8T cells and the LDL-C level of all patients; (*P<0.05, **P<0.01, ***P<0.001, ****P<0.0001). Figure 16 ROC curves for 36 samples. Detailed Implementation

[0021] The embodiments described are provided to better illustrate the present invention, but are not intended to limit the scope of the invention to the embodiments described. Therefore, non-essential improvements and adjustments made to the embodiments by those skilled in the art based on the above description are still within the scope of protection of the present invention.

[0022] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. Singular expressions include plural expressions unless they have a distinct meaning in the context. As used herein, it should be understood that terms such as “comprising,” “having,” “including,” are intended to indicate the presence of features, numbers, operations, components, parts, elements, materials, or combinations thereof. The terminology of the invention is disclosed in the specification and is not intended to exclude the possibility that one or more other features, numbers, operations, components, parts, elements, materials, or combinations thereof may be present or added. As used herein, “ / ” may be interpreted as “and” or “or,” depending on the context.

[0023] To better understand the present invention, specific examples are provided below to further illustrate the content of the present invention, but the content of the present invention is not limited to the examples below.

[0024] Example 1 (1) Mouse grouping Different groups of mice (LDLR) - / -HFD, LDLR - / - ScRNA-seq (single-cell sequencing) studies were conducted on aortic single-cell suspensions from ND and WTND aortas; among them, LDLR - / - HFD mice were LDLR gene-deleted mice fed a high-fat diet (Research Diet, 12108C). - / - ND mice are mice with gene deletion and fed a normal diet, while WTND mice are wild-type mice fed a normal diet (healthy controls).

[0025] (2) UMAP cluster analysis of T and NK cell subsets To gain a deeper understanding of the transcriptomic characteristics of T cell subsets, UMAP clustering was performed again on T and NK cell subsets, and the subsets were further analyzed based on markers and highly specific expressed genes of different T cell types. Figure 1 D), the annotation yielded 9 T cell subsets, including CD8+ T cells, CD4+ T cells, two CD4+CD8+ T (double-positive T, DPT) cells that highly express proliferation genes and Rag1, respectively, γδ T cells, NK cells, NKT cells, and Tox T cells. hi T cells (see) Figure 1 A). Within the entire cell population, CD8+ T cells constitute the largest subpopulation (41.68%). Figure 1 B).

[0026] Furthermore, this CD8+ T cell subset is further annotated (see [link to documentation]). Figure 1 C) Three cell subsets were defined in CD8+ T cells, including two cell subsets that highly express Tcf7. One subset is labeled NaiveCD8+ T cells (Sell+Ccr7+Cd44-), and the other subset exhibits expression characteristics of both effector (Cd44+Nkg7+) and memory (Sell+Ccr7+Il7r+) cell subsets, labeled Tcf7. hi CD8+ T cells. In addition, there exists a subset of CD8+ T cells that express low levels of Tcf7 but high levels of the cytotoxic genes NK cell granule protein 7 (Nkg7) and granzyme B (Gzmb), labeled Tcf7. lo CD8+ T cells.

[0027] (3) Gene analysis of CD8+ T cell subsets Differential analysis was performed among different cell subpopulations to extract the above-mentioned cell subpopulations (NaiveCD8+ T cell subpopulation, Tcf7). hi CD8+ T cell subsets and Tcf7 loThe top 5 differentially expressed genes in the CD8+ T cell subset were identified, and a heatmap was created followed by GO enrichment analysis. The transcriptional characteristics of the CD8+ T cell subset are as follows: Tcf7 hi CD8+ T cells and naiveCD8+ T cells share similar transcriptional characteristics; however, Tcf7 cells do not. hi Compared to naive CD8+ T cells, CD8+ T cells additionally upregulate the expression of genes such as T cell activation (Xcl1), early proliferation (Cd7), and cytotoxicity (Ctla2a); while Tcf7... lo CD8+ T cells compared to Tcf7 hi CD8+ T cells upregulated cytotoxicity-related genes (Nkg7, Gzmb, and Ctsw) and chemokines (Ccl5, Ccl4, and Cxcr6). Figure 2 A). Furthermore, GO enrichment analysis showed that Tcf7 hi CD8+ T cells highly upregulate cytoplasmic translation, synaptic translation, and pathways related to lymphocyte differentiation. Figure 2 B). The above results demonstrate the heterogeneity in phenotype and function among different CD8+ T cell subsets.

[0028] (4) Tcf7 hi Differential gene expression analysis of CD8+ T cell subsets compared with other cell types Further comparison of Tcf7 hi Differential gene expression between CD8+ T cells and two other CD8+ T cell types, as shown in the following results Figure 3 As shown in A, compared to the other two CD8+ T cell subsets, Tcf7 hi CD8+ T cells highly express NK cell receptors (NKCRs) (Klrk1, Klrc2, and Klre1), Il15 or Il12 receptors (Il12rb), chemokines and receptor-related genes (Xcl1, Cxcr3, and Il18rap), and the T cell activation molecule Cd44. Additionally, Tcf7... hi CD8+ T cell subsets highly express annexin A2 (Anxa2) and SMAD family member 3 (SMAD3). Further GO enrichment analysis of differentially expressed genes yielded the following results: Figure 3 As shown in Figure B, the results indicate that Tcf7 hi CD8+ T cells are enriched in lymphocyte differentiation, T cell differentiation, immune response activation, and regulatory signaling pathways. These results indicate that Tcf7... hi CD8+ T cells possess a certain capacity for proliferation and differentiation, while also exhibiting pro-inflammatory characteristics.

[0029] In addition, the functional status of three CD8+ T cell subsets was further assessed using Ucell gene set scoring analysis (exhaustion, toxicity, proliferation, and stemness scores), and the results are as follows: Figure 3 As shown in Figure C, the results indicate that NaiveCD8+ T cells and Tcf7... hi CD8+ T cells possess significant stem cell activity, while Tcf7... lo CD8+ T cells reflect characteristics of cell exhaustion and cytotoxicity. In the scoring analysis of CD8+ T cell subsets among different groups, exhaustion and proliferative capacity were enhanced under HFD conditions, while stemness characteristics were significantly weakened, indicating that dedifferentiation in AS progression may be accompanied by exhaustion phenotypic transformation.

[0030] (5) Tcf7 of different groups hi Differential analysis of CD8+ T cell transcriptome profiles Further comparison of different groups of Tcf7 hi The transcriptome differences of CD8+ T cells were as follows: Figure 4 As shown in Figure A, the results show that compared to LDLR - / - Tcf7 in ND group HFD mice hi CD8+ T cells upregulated Fos and Jun family genes, the early T cell activator Cd69, the pro-inflammatory cytokine Ifng, and the chemokine Ccl4. Fos and Jun expression can be activated by the MAPK signaling pathway; their encoded proteins can form the transcription factor complex AP-1 (activator protein-1), playing a crucial role in cell proliferation, differentiation, apoptosis, and responses to environmental stimuli. Furthermore, the HFD group upregulated the expression of the transcription factor Nr4a1, which is known to induce apoptosis and promote T cell exhaustion by antagonizing AP-1-mediated gene expression.

[0031] Furthermore, KEGG analysis of differentially expressed genes revealed Tcf7. hi CD8+ T cells are enriched in pathways such as the TCR signaling pathway, MAPK signaling pathway, apoptosis, fluid shear stress and atherosclerosis signaling pathway, and the PD-1 (a protein encoded by Pdcd1) checkpoint pathway. Figure 4 B).

[0032] Furthermore, the Ucell gene set scores were evaluated across different groups, and the results showed that in LDLR - / - Tcf7 in HFD group hi The proliferation and exhaustion of CD8+ T cells were enhanced, while the stemness characteristics were weakened. Figure 4 C).

[0033] The above results indicate that HFD drives Tcf7 hiCD8+ T cells proliferate with loss of stemness and transition to a pro-inflammatory and exhaustive phenotype. Tcf7 lo CD8+ T cell subsets represent a cytotoxic CD8+ T cell subset characterized by exhaustion. Under continuous stimulation by HFD, Tcf7... hi CD8+ T cells may transform into Tcf7 cells. lo CD8+ T cells differentiated.

[0034] (6) Monocle2 pseudo-time series analysis of CD8+ T cell subsets To further understand the fate lineage relationships among CD8+ T cell subsets, a Monocle2 pseudo-time series analysis was performed on the CD8+ T cell subsets. The results are as follows: Figure 5 As shown in Figure A, the results indicate that the naive CD8+ T cell subset is in the initial stage of its trajectory, and Tcf7... hi CD8 T cells are in the middle of their trajectory, while Tcf7 lo The CD8+ T cell subset is at the end of its trajectory, indicating that it may be in the late stage of differentiation.

[0035] In addition, the expression changes of some key genes with pseudo-time series were examined, and the results are as follows: Figure 5 As shown in Figure B, the results indicate that the expression of Tcf7 and Ccr7 gradually decreased with pseudo-time-sequence changes, while the expression of memory-related genes (Sell, Il7r) decreased in Tcf7. hi CD8T cell expression peaks and gradually decreases towards the end. Effector markers Cd44, pro-inflammatory cytokines (Gzmk and Ifng), and apoptosis-inducing genes (Tox and Fasl) show significant increases with pseudotime-dependent changes.

[0036] The above results indicate that Tcf7 plays a role in atherosclerosis. hi CD8+ T cells may gradually transform into cytotoxic Tcf7 cells. lo CD8+ T cells differentiate and gradually exhibit signs of exhaustion.

[0037] (7) Fluorescent section test By analyzing LDLR - / - CD8 and Tcf7 co-staining in mouse aortic root sections yielded the following results: Figure 6 A and Figure 6 As shown in Figure B, the results indicated that CD8+ T cells were significantly enriched in the plaque area, while Tcf7+CD8+ T cells were abundant in both the artery and the plaque. Compared to the experimental group, the control group showed higher Tcf7 expression in the artery, indicating a decrease in Tcf7 expression levels during AS progression.

[0038] (8) Expression of Tcf7 protein in aortic CD8+ T cell subsets Detection via flow cytometry (gated strategies such as...) Figure 7 As shown in Figure A), the expression of Tcf7 protein in the mouse aortic CD8+ T cell subset was verified, and the results are as follows: Figure 7 As shown in C, the results show that compared to LDLR - / - ND group mice, LDLR - / - The proportion of CD8+ T cells in the aorta of mice in the HFD group was significantly increased (34.25% vs. 42.23%, p<0.05), while the proportion of Tcf7+CD8+ T cells was significantly decreased (63.36% vs. 32.38%, p<0.01).

[0039] Additionally, through flow cytometry (gated strategies such as...) Figure 7 (As shown in B) The proportion of different types of CD8+ T cells and the expression distribution of Tcf7 in different CD8+ T cells were detected, and the results are as follows: Figure 7 As shown in Figure D, the results indicated that in the ND group, the CD8+ T cells in the mouse aorta were predominantly central memory T cells (Tcm). In contrast, in the HFD group, effector CD8+ T cells (CD8+Teff) were significantly increased (29.34% vs. 56.61%, p < 0.01), becoming the dominant type.

[0040] Furthermore, compared to CD8+ Teff cells, Tcf7 is highly expressed primarily in CD8+ Tcm cells (see...). Figure 7 E and Figure 7 Furthermore, in the HFD group, Tcf7 expression was significantly reduced in both CD8+ Tcm (74.19% vs. 31.56%, p < 0.01) and CD8+ Teff (20.85% vs. 6.13%, p < 0.05) cells. These flow cytometry results are consistent with single-cell transcriptomics results, confirming the expression characteristics of Tcf7 in CD8+ T cell subsets of the mouse aorta.

[0041] (9) Tcf7 hi Expression levels of the cytokine IFNG and the proliferation marker Mki67 in CD8+ T cells Previous single-cell sequencing results indicated that Tcf7 hi CD8+ T cells exhibit enhanced proliferation and pro-inflammatory phenotypes under HFD conditions, and may differentiate into CD8+ T cells with an exhausted phenotype, thus increasing their proliferation. This can be observed through flow cytometry (using gating strategies such as...). Figure 8 As shown in A), Tcf7 was detected in different groups. hi The expression levels of the cytokine IFNG and the proliferation marker Mki67 in CD8+ T cells showed that HFD-fed LDLR- / - Tcf7 in mouse aorta hi The levels of IFNG (18.96% vs. 33.52%, p<0.01) and Mki67 (5.40% vs. 11.92%, p<0.01) in CD8+ T cells were significantly higher than those in the control group's aorta. Figure 8 B and Figure 8 C). Furthermore, the expression level of PD-L1 (a ligand of PD-1), a marker of CD8+ Teff cells exhaustion, was significantly increased in the experimental group (7.03% vs. 16.35%, p < 0.01) (see [link to relevant documentation]). Figure 8 D). The above results confirm Tcf7. hi CD8+ T cells exhibit enhanced pro-inflammatory and proliferative characteristics driven by high cholesterol and may differentiate into exhausted T cells with low Tcf7 expression.

[0042] (10) Tcf7 hi Peripheral blood detection of CD8+ T cell subsets Using flow cytometry (gating strategy, etc.) Figure 9 As shown in A), Tcf7 was discussed. hi Whether CD8+ T cell subsets are present in mouse peripheral blood. Results showed that LDLRs fed a normal diet and HFD were different. - / - Tcf7 was present in the peripheral blood of mice. hi CD8+ T cell subsets (see...) Figure 9 B). Compared to the ND group, the proportion of peripheral blood Tcf7+CD8+ T cells in the HFD group mice decreased (41.50% vs. 30.41%, p < 0.05) (see B). Figure 9 C). Mouse peripheral blood CD8+ T cells were predominantly quiescent naive CD8+ T cells. In the HFD group, the proportion of naive CD8+ T cells and CD8+ Tcm cells decreased, while the proportion of CD8+ Teff cells increased (2.92% vs. 13.81%, p < 0.01). Further evaluation of Tcf7 expression in different CD8+ T cells revealed higher Tcf7 expression in CD8+ Tcm cells than in CD8+ Teff cells (78.75% vs. 65.67%, p < 0.01), and this was more pronounced in the HFD group (71.16% vs. 50.98%, p < 0.0001). Furthermore, Tcf7 expression was decreased in both CD8+ TCM and CD8+ Teff cells in the HFD group.

[0043] Using flow cytometry (gating strategy, etc.) Figure 9 (As shown in D) The levels of Mki67, IFNG, and PD-L1 were detected, and Tcf7 in mouse peripheral blood was further analyzed. hiWhether CD8+ T cell subsets also responded to high cholesterol-driven changes in cell function, the results are as follows: Figure 9 E, Figure 9 F and Figure 9 As shown in G, the results show that, compared to LDLR - / - ND group, LDLR - / - In the HFD group, the levels of Mki67 (8.14% vs. 11.27%, p<0.05) and IFNG (18.72% vs. 31.02%, p<0.001) in Tcf7+CD8+ T cells were increased, while the exhaustion level was enhanced (1.25% vs. 2.41%, p<0.05).

[0044] The above results indicate that Tcf7 possesses dryness characteristics. hi CD8+ T cell subsets are also maintained in circulation and influence inflammation levels through functional regulation, which may promote AS progression.

[0045] (11) The proportion of Tcf7+CD8+ T cells in aortic PVAT and abdominal aortic PVAT To verify the origin of this cell population, further flow cytometry (using gating strategies such as...) was performed. Figure 10 As shown in Figure A, LDLR was detected. - / - The proportion of Tcf7+CD8+ T cells in the thoracic aortic PVAT and abdominal aortic PVAT of mice. The results showed that Tcf7+CD8+ T cells were mainly present in the thoracic aortic PVAT of mice, while the proportion of Tcf7+CD8+ T cells in the thoracic aorta decreased after HFD feeding (19.97% vs. 8.15%, p < 0.05) (see...). Figure 10 B).

[0046] Furthermore, the expression levels of Mki67 and IFNG in Tcf7+CD8+ T cells of the thoracic aorta PVAT were further analyzed. Compared with LDLR - / - ND group, LDLR - / - The HFD group showed higher expression levels of Mki67 (5.00% vs. 9.60%, p < 0.05) and IFNG (9.62% vs. 13.77%, p < 0.05) (see [link to HFD group]). Figure 10 C and Figure 10 D). Furthermore, the HFD group showed significantly higher PD-L1 expression levels in CD8+ T cells (1.80% vs. 3.69%, p < 0.05) (see [reference needed]). Figure 10 E). The above results confirm that Tcf7 is highly expressed mainly in the thoracic aortic PVAT tissue, and the expression characteristics of Tcf7+CD8+ T cells in PVAT are consistent with those in the aorta.

[0047] (12) Tcf7hi The relationship between CD8+ T cells and fat Previous studies have shown that white adipose tissue can induce aortic autoimmune disease (AS) in obese patients by promoting circulating lipid metabolism disorders and inflammatory responses through the release of pro-inflammatory factors. Furthermore, rodent studies have shown that white adipose tissue (BAT) not only has a thermogenic effect but also plays a role in maintaining healthy metabolism and inhibiting inflammation. To investigate the role of Tcf7 in the aorta... hi Whether the CD8+ T cell population is present in other adipose tissues can be determined by flow cytometry (using a gated strategy, etc.). Figure 11 As shown in Figure A, the expression level of Tcf7 in CD8+ T cells in different adipose tissues (iWAT, BAT, and eWAT) was analyzed.

[0048] The results are as follows Figure 11 As shown in Figure B, the results indicated that Tcf7+CD8+ T cells were present in all adipose tissues, but accounted for only about 15% of CD8+ T cells in white adipose tissue. Furthermore, under HFD conditions, the proportion of Tcf7+CD8+ T cells was significantly reduced in iWAT (16.28% vs. 4.79%, p < 0.05) and eWAT (18.52% vs. 2.10%, p < 0.0001); while in BAT, the overall proportion of Tcf7+CD8+ T cells was low (only about 5%).

[0049] (13) Status of CD8+ T cells in mouse spleen Furthermore, a search of the Human Protein Atlas database (online website: https: / / www.proteinatlas.org / ) revealed that Tcf7 is highly expressed in tissues such as the spleen, lymph nodes, and bone marrow. Therefore, embodiments of the present invention utilize flow cytometry (gating strategy, such as...) Figure 12 (As shown in Figure A) The expression level of Tcf7 in CD8+ T cells of mouse spleen was detected. The results showed that LDLR - / - In mouse spleens, CD8+ T cells were predominantly naive T cells and memory T cells. Compared to the ND group, the proportion of naive T cells decreased in the HFD group (83.99% vs. 76.14%, p < 0.01), while the proportion of memory CD8+ T cells increased (15.15% vs. 22.89%, p < 0.05) (see [link to HFD group]). Figure 12 B). The proportion of Tcf7+CD8+ T cells showed a higher trend in the spleen of the HFD group (69.69% vs. 75.84%, p > 0.05) (see B). Figure 12 C). Further analysis showed that Tcf7+CD8+ T cells in the HFD group had a higher Mki67 expression level than those in the ND group (2.62% vs. 6.21%, p < 0.01). Figure 12D). The above results indicate that under HFD conditions, the spleen enhances the reserve of memory T cell populations, which may be recruited to sites of inflammation through circulating subsets of these cells.

[0050] Example 2 To verify the presence of Tcf7 in human AS plaques hi CD8+ T cells were used in a meta-analysis of three carotid atherosclerotic plaque datasets (GSE155512, GSE159677, and GSE253903) from the GEO database. The samples were from elderly (≥65 years old) male and female patients who underwent carotid endarterectomy. CD8A-expressing cell subsets were extracted and subjected to re-clustering analysis (see [link to analysis]). Figure 13 A) A total of 9 cell clusters were obtained. The three carotid artery datasets showed similar transcriptional profiles. The results showed that cell cluster 5 in all datasets conformed to TCF7. hi CD8+ T cells are characterized by the expression of memory cell markers (CCR7, SELL, and CD44), and the highest expression rate of TCF7 (35.7%) among all cell clusters (see...). Figure 13 B); Compared to cell cluster 5, the remaining cell clusters all exhibited a consistent cytotoxic CD8+ T cell transcription profile, possessing effector characteristics (CD44+SELL-CCR7-) (see Figure 13 C); and highly expresses toxicity and cytokine-related genes (NKG7, GZMK, and CCL5), while also expressing some exhaustion genes (see C). Figure 13 D). The above results indicate that a subset of CD8+ T cells with high Tcf7 expression exists in late-stage human carotid atherosclerotic plaques, but the dominant expression is still cytotoxic Tcf7. lo The majority of cells are CD8+ T cells.

[0051] Furthermore, the transcriptional profile of CD8+ T cell subsets was also validated in the GEO dataset (GSE196943) of coronary atherosclerotic plaques (see [link to dataset]). Figure 14 A), all samples were from 12 heart transplant recipients (mean age 59 years). Results showed that CD8+ cells in the coronary arteries exhibited a significant effector phenotype of Tcf7 expressing GZMK and GZMB. lo The predominance of CD8+ T cells, with no significant expression of TCF7-based memory CD8+ T cells, suggests that the majority of CD8+ T cells in the coronary arteries of these patients are in the late differentiation stage. Due to the limited coronary plaque data included, more datasets are needed to validate this result (see [link to relevant documentation]). Figure 14 B).

[0052] In addition, the expression level of Tcf7 in CD8+ T cells in peripheral blood of patients with hypercholesterolemia was analyzed. Familial hypercholesterolemia (FH) is an autosomal dominant inherited disease characterized by LDL-C. Specifically, peripheral blood samples were collected from 12 heterozygous FH patients receiving lipid-lowering therapy (LLT) and 8 patients not receiving cholesterol-lowering therapy (NoLLT), as well as 19 age-matched healthy subjects for flow cytometry analysis. Compared with healthy subjects and LLT-FH patients, NoLLT-FH patients had significantly higher plasma cholesterol levels (Table 1). Compared with healthy subjects, the proportion of CD8+ T cells in peripheral blood of NoLLT-FH patients was significantly increased (34.59% vs. 47.05%, p < 0.01). Figure 15 (A and B), while the proportion of Tcf7+CD8+ T cells decreased significantly (92.39% vs. 85.57%, p<0.05). Figure 15 C).

[0053] Table 1 Baseline characteristics of FH patients

[0054] Furthermore, further detection via flow cytometry (gating strategies such as...) Figure 15 (As shown in D) The proportions of different types of CD8+ T cells, including Naive T (CD45RA+CCR7+), TCM (CD45RA-CCR7+), TEM (CD45RA-CCR7-), and TEMRA (effective memory T cells expressing CD45RA, CD45RA+CCR7-) cells, and the distribution of Tcf7 in these CD8 T cells were analyzed in the healthy group and the no-LLT-FH group. Compared with the healthy group, the number of Naive CD8+ T cells was significantly decreased in the no-LLT-FH group (36.01% vs. 18.43%, p < 0.001), while the number of CD8+ TEM cells was significantly increased (29.02% vs. 41.92%, p < 0.001). Figure 15 E). Tcf7 was highly expressed in all types of CD8+ T cells. Compared to the healthy group, the expression of Tcf7 in NaiveCD8+ T, CD8+TCM, and CD8+TEM cells was significantly decreased in the no-LLT FH group (see [link to original text]). Figure 15 F).

[0055] In addition, the expression levels of IFNG in TCF7+CD8+ T cells in different groups were further evaluated (gating strategies such as...). Figure 15As shown in G), the results showed that the noLLT-FH group had a higher IFNG expression level than the healthy group (4.34% vs. 7.51%, p < 0.01). The relationship between blood lipid levels and the proportion of Tcf7+CD8+ T cells was also assessed. The results showed that plasma total cholesterol (TC) levels (r = -0.5609, P < 0.001) and LDL-C levels (r = -0.5392, p < 0.001) were negatively correlated with the proportion of Tcf7+CD8+ T cells in all subjects. These results indicate that circulating Tcf7+CD8+ T cells with a memory phenotype in humans conform to stem cell characteristics and may drive circulating inflammation under the induction of high LDL-C (see G). Figure 15 H and 15I).

[0056] Example 3 Thirty-six samples were selected according to the above requirements, including 10 healthy samples and 26 samples from patients with atherosclerosis. The samples were analyzed using the Tcf7 assay method described above. hi Using CD8+T as a characteristic, ROC curves were constructed using the Xsmart Analysis platform (https: / / www.xsmartanalysis.com / ), and related indicators such as sensitivity were analyzed. The ROC curves are shown below. Figure 16 As shown in Table 2 below, the results of the analysis indicators are presented.

[0057] Table 2. Relevant Indicators for ROC Curve Analysis

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. Tcf7 hi Use of a CD8+ T cell detection reagent in the manufacture of a product for diagnosing atherosclerosis or assessing progression of atherosclerosis.

2. Use according to claim 1, characterized in that, The application comprises: diagnosing or evaluating the progression of atherosclerosis by detecting one or more indicators of the proportion of Tcf7hiCD8+ T cells, the expression level of the Tcf7 gene, the proliferation marker Mki67, the pro-inflammatory cytokine IFNG, or the expression level of the exhaustion marker PD-L1 in a biological sample.

3. Use according to claim 1, characterized in that, The biological sample is selected from the group consisting of arterial tissue, perivascular adipose tissue (PVAT), or peripheral blood.

4. Use according to claim 3, characterized in that The application comprises: When the biological sample is peripheral blood, the proportion of Tcf7hiCD8+ T cells in CD8+ T cells in the peripheral blood is detected, combined with the total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) levels in the plasma to diagnose or evaluate the condition of AS; when the proportion of Tcf7hiCD8+ T cells in the peripheral blood is less than 85% (with the average proportion of Tcf7hiCD8+ T cells in the peripheral blood of healthy people being 92.39% as a reference), and TC≥7.10mmol / L and LDL-C≥4.57mmol / L, it indicates that the patient has a high risk of AS or the condition is progressing; and / or When the biological sample is atherosclerotic plaque tissue, the proportion of Tcf7hiCD8+ T cells and Tcf7loCD8+ T cells in the plaque tissue is detected to evaluate the condition; the Tcf7loCD8+ T cells are a CD8+ T cell subpopulation that expresses low levels of the Tcf7 gene and high levels of cytotoxic genes (Nkg7, Gzmb, Ctsw) and chemokines (Ccl5, Ccl4, Cxcr6); when the proportion of Tcf7hiCD8+ T cells in CD8+ T cells in the plaque tissue is less than 35.7%, and the proportion of Tcf7loCD8+ T cells is more than 60%, it indicates that the patient is in the late stage of AS.

5. A reagent / kit for diagnosing atherosclerosis or assessing the progression of the disease, characterized in that, The reagent / kit comprises a detection reagent that specifically recognizes a marker of Tcf7hiCD8+ T cells.

6. The reagent / kit for diagnosing atherosclerosis or evaluating progression of atherosclerosis according to claim 4, wherein The detection reagent that specifically recognizes a marker of Tcf7hiCD8+ T cells is a reagent for detecting the expression level of one or more of the proliferation marker Mki67, the pro-inflammatory cytokine IFNG, or the exhaustion marker PD-L1 in Tcf7hiCD8+ T cells.

7. The reagent / kit for diagnosing atherosclerosis or evaluating progression of atherosclerosis according to claim 6, wherein The detection reagent that specifically recognizes a marker of Tcf7hiCD8+ T cells is one or more of an antibody, a nucleic acid probe, or a primer.

8. The reagent / kit for diagnosing atherosclerosis or evaluating progression of atherosclerosis according to claim 7, wherein The detection reagent is a fluorescently labeled antibody, and the fluorescently labeled antibody comprises at least three of an anti-Tcf7 fluorescent antibody, an anti-SELL fluorescent antibody, an anti-CCR7 fluorescent antibody, and an anti-Cd44 fluorescent antibody; the reagent / kit further comprises buffers, fixing solutions, and membrane-breaking solutions required for flow cytometry detection, and is accompanied by a flow cytometry detection parameter setting instruction that clearly defines the fluorescence signal threshold for distinguishing Tcf7hiCD8+ T cells from other CD8+ T cell subpopulations.

9. The reagent / kit for diagnosing atherosclerosis or evaluating progression of atherosclerosis according to claim 7, wherein The detection reagent is a nucleic acid detection reagent, which comprises a specific primer pair for the Tcf7 gene, and the sequence design of the primer pair is based on the conserved region of the Tcf7 gene; the nucleic acid detection reagent further comprises specific primer pairs for SELL, CCR7 and Cd44 genes, which are used to detect the expression levels of the above-mentioned genes by real-time fluorescent quantitative PCR (qPCR) or reverse transcription PCR (RT-PCR) to determine the number of Tcf7hiCD8+T cells.

10. A method for screening a drug for treating atherosclerosis, characterized by, The method comprises: determining Tcf7 hi The change in the function or quantity of CD8+ T cells is a screening index; Tcf7 hi The CD8+ T cells are a CD8+ T cell subpopulation with high expression of the Tcf7 gene, and simultaneously with expression characteristics of memory cell markers SELL+, CCR7+ and Il7r+ and effector cell markers Cd44+ and Nkg7+; the screening index comprises: changes in the proportion of Tcf7hiCD8+ T cells in the biological sample and changes in the expression level of the Tcf7 gene, or changes in the expression level of a proliferation marker (Mki67), a pro-inflammatory cytokine (IFNG) and a exhaustion marker (PD-L1) in the cells after the candidate drug acts; if the candidate drug can increase the proportion of Tcf7hiCD8+ T cells, up-regulate the expression of Tcf7, or reduce the expression of the exhaustion marker (PD-L1), while maintaining or enhancing the normal functional expression of the proliferation marker (Mki67) and the pro-inflammatory cytokine (IFNG), it is determined as a potential AS treatment drug; the biological sample is at least one of an artery tissue, a perivascular adipose tissue (PVAT) and peripheral blood.

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