IL-2Rβγ signalling in lymphocytes promotes systemic inflammation and reduces plasma cholesterol in atherosclerotic mice

Systemic immune inflammation index is associated with in-stent neoatherosclerosis and plaque vulnerability: An optical coherence tomography study

Background

In-stent neoatherosclerosis (ISNA) is identified as the primary cause of in-stent restenosis (ISR). The systemic immune inflammation index (SII), shows promise for predicting post-percutaneous coronary intervention (PCI) adverse cardiovascular events and is associated with coronary stenosis severity; however, its specific relationship with ISNA remains unclear. This study aimed to investigate the association between the SII and ISNA after drug-eluting stent (DES) implantation.

Methods

This cross-sectional study included 195 participants with 195 ISR lesions who underwent optical coherence tomography (OCT)-guided PCI between August 2018 and October 2022. Participants were categorized based on the SII levels into Tertile 1 (SII <432.37, n = 65), Tertile 2 (432.37 ≤ SII ≤751.94, n = 65), and Tertile 3 (SII >751.94, n = 65). Baseline Clinical, angiographic, and OCT characteristics were analyzed. The association of the SII with ISNA and thin-fibroatheroma (TCFA) was investigated using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of the SII in detecting ISNA and TCFA.

Results

Patients in Tertile 3 had a significantly higher incidences of ISNA and TCFA than did those in Tertile 1. Logistic regression analysis revealed the SII is an independent indicator of ISNA and TCFA in ISR lesions (P = 0.045 and P = 0.002, respectively). The areas under the ROC curves for ISNA and TCFA were 0.611 and 0.671, respectively.

Conclusion

The SII is associated with ISNA and TCFA and may serve as an independent indicator in patients with ISR.

CXCL9, IL2RB, and SPP1, potential diagnostic biomarkers in the co-morbidity pattern of atherosclerosis and non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) is a hepatocyte inflammation based on hepatocellular steatosis, yet there is no effective drug treatment. Atherosclerosis (AS) is caused by lipid deposition in the endothelium, which can lead to various cardiovascular diseases. NASH and AS share common risk factors, and NASH can also elevate the risk of AS, causing a higher morbidity and mortality rate for atherosclerotic heart disease. Therefore, timely detection and diagnosis of NASH and AS are particularly important. In this study, differential gene expression analysis and weighted gene co-expression network analysis were performed on the AS (GSE100927) and NASH (GSE89632) datasets to obtain common crosstalk genes, respectively. Then, candidate Hub genes were screened using four topological algorithms and externally validated in the GSE43292 and GSE63067 datasets to obtain Hub genes. Furthermore, immune infiltration analysis and gene set variation analysis were performed on the Hub genes to explore the underlying mechanisms. The DGIbd database was used to screen candidate drugs for AS and NASH. Finally, a NASH model was constructed using free fatty acid-induced human L02 cells, an AS model was constructed using lipopolysaccharide-induced HUVECs, and a co-morbidity model was constructed using L02 cells and HUVECs to verify Hub gene expression. The result showed that a total of 113 genes common to both AS and NASH were identified as crosstalk genes, and enrichment analysis indicated that these genes were mainly involved in the regulation of immune and metabolism-related pathways. 28 candidate Hub genes were screened according to four topological algorithms, and CXCL9, IL2RB, and SPP1 were identified as Hub genes after in vitro experiments and external dataset validation. The ROC curves and SVM modeling demonstrated the good diagnostic efficacy of these three Hub genes. In addition, the Hub genes are strongly associated with immune cell infiltration, especially macrophages and γ-δ T cell infiltration. Finally, five potential therapeutic drugs were identified. has-miR-185 and hsa-miR-335 were closely related to AS and NASH. This study demonstrates that CXCL9, IL2RB, and SPP1 may serve as potential biomarkers for the diagnosis of the co-morbidity patterns of AS and NASH and as potential targets for drug therapy.

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

Aging is a strong risk factor for atherosclerosis and induces accumulation of memory CD8+ T cells in mice and humans. Biological changes that occur with aging lead to enhanced atherosclerosis, yet the role of aging on CD8+ T cells during atherogenesis is unclear. In this study, using femle mice, we found that depletion of CD8+ T cells attenuated atherogenesis in aged, but not young, animals. Furthermore, adoptive transfer of splenic CD8+ T cells from aged wild-type, but not young wild-type, donor mice significantly enhanced atherosclerosis in recipient mice lacking CD8+ T cells. We also characterized T cells in healthy and atherosclerotic young and aged mice by single-cell RNA sequencing. We found specific subsets of age-associated CD8+ T cells, including a Granzyme K+ effector memory subset, that accumulated and was clonally expanded within atherosclerotic plaques. These had transcriptomic signatures of T cell activation, migration, cytotoxicity and exhaustion. Overall, our study identified memory CD8+ T cells as therapeutic targets for atherosclerosis in aging.

Association between systemic immune-inflammatory markers and the risk of moyamoya disease: a case-control study

Background:Systemic immune-inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic immune-inflammatory index (SII) are associated with the prognosis of many cardiovascular and neoplastic diseases. Moyamoya disease (MMD) is associated with inflammation, but the relationship between systemic immune-inflammatory markers between MMD is unclear. The aim of our study was to analyse the association between systemic immune-inflammatory markers and the risk of MMD and its subtypes.Methods:We consecutively recruited 360 patients with MMD and 89 healthy control subjects in a case-control study to calculate and analyse the association of systemic immune-inflammatory markers with the risk of MMD and its subtypes.Results:The risk of MMD increased with higher levels of NLR (OR 1.237, 95% CI [1.008, 1.520], p = .042). When NLR and SII were assessed as quartile-spaced subgroups, the third quartile grouping of NLR and SII had a higher risk of MMD than the first quartile grouping (NLR: OR 3.206, 95% CI [1.271, 8.088], p = .014; SII: OR 3.074,95% CI [1.232,7.672], p = .016). When NLR was combined with SII, the highest subgroup had a higher risk of MMD than the lowest subgroup (OR2.643, 95% CI [1.340, 5.212], p = .005). The risk of subtypes also increased with higher levels of NLR and SII. The association between the levels of NLR and SII with the staging of the Suzuki stage follows an inverted U-shape. The highest levels of NLR and SII were found in patients with MMD at Suzuki stages 3-4.Conclusion:The risk of MMD increases with elevated systemic immune-inflammatory markers. This study analysed the association of systemic immune-inflammatory markers with the risk of developing MMD and its subtypes, and identified novel inflammatory markers for MMD.

Associations between systemic immune-inflammation index and abdominal aortic calcification: Results of a nationwide survey

BACKGROUND AND AIM

The Systemic Immune-Inflammation Index (SII) is a novel index of inflammation assessment that appears to be superior to the common single blood index in the assessment of cardiovascular disease. The purpose of this study was to investigate the association between SII and abdominal aortic calcification (AAC) in adults.

METHODS AND RESULTS

Multivariate logistic regression, sensitivity analysis, and smoothing curve fitting were used to investigate the relationship between SII and AAC based on data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014. Subgroup analysis and interaction tests were used to investigate whether this association was stable across populations. There was a positive association between SII and ACC in 3036 participants >40 years of age. In the fully adjusted model, each 100-unit increase in SII was associated with a 4% increase in the risk of developing severe AAC [1.04 (1.02, 1.07)]. Participants in the highest quartile of SII had a 47% higher risk of developing severe AAC than those in the lowest quartile [1.47 (1.10, 1.99)]. This positive association was more pronounced in older adults >60 years of age.

CONCLUSIONS

SII is positively associated with AAC in US adults. Our findings imply that SII has the potential to improve AAC prevention in the general population.

Systemic immune-inflammation index as a potential biomarker of cardiovascular diseases: A systematic review and meta-analysis

Background

Several studies have investigated the value of the systemic immune-inflammation index (SII) for predicting cardiovascular disease (CVD), but the results were inconsistent. Therefore, a meta-analysis and systematic review were conducted to assess the correlation between SII and risk of CVD.

Materials and methods

Two investigators systematically searched PubMed, Embase, Web of Science, Cochrane library, and CINAHL databases to identify all studies that examined the association between SII levels and CVD. The risk estimates of CVD for people with high SII compared to those with low SII levels and the weighted mean difference (WMD) between the CVD and control groups were pooled using fixed- or random-effects models based on the heterogeneity test. We used the Newcastle-Ottawa Scale to assess the risk of bias in eligible studies, and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was applied to rate the certainty of evidence.

Results

A total of 13 studies with 152,996 participants were included for analysis. The overall pooled results showed that higher SII was significantly associated with an increased risk of CVD (HR = 1.39, 95%CI: 1.20–1.61, P < 0.001). This increased risk could be observed in almost all CVD subtypes, including ischemic stroke (HR = 1.31, 95%CI: 1.06–1.63, P = 0.013), hemorrhagic stroke (HR = 1.22, 95%CI: 1.10–1.37, P < 0.001), myocardial infarction (HR = 1.11, 95%CI: 1.01–1.23, P = 0.027), and peripheral arterial disease (HR = 1.51, 95%CI: 1.18–1.93, P = 0.001). There were no significant but still similar trends in venous thrombosis (HR = 4.65, 95%CI: 0.66–32.71, P = 0.122), cerebral small vessel disease (HR = 1.09, 95%CI: 0.95–1.25, P = 0.233), and acute coronary syndrome (HR = 1.08, 95%CI: 0.96–1.22, P = 0.200). Furthermore, the pooled results showed that SII levels at the onset of CVD were significantly higher than that in the general population (WMD = 355.2, 95%CI: 234.8–475.6, P < 0.001), which was consistent across different CVD subtypes. The GRADE assessment suggested that the quality of current evidence from observational studies was low or very low.

Conclusion

This study indicated that SII may be a potential biomarker for CVD development and elevated SII is associated with an increased risk of CVD. However, the quality of evidence is generally low. Additional well-designed studies are necessary to determine the optimal cutoff value and to characterize the benefited population.