Mediators of Inflammation

Background. Systemic inflammation with elevated inflammatory cytokines is a hallmark in patients with cirrhosis and the main driver of decompensation. There is insufficient data on whether inflammatory cytokine levels differ between hepatic and jugular veins, which may have implications for further immunological studies. Methods. Blood from the hepatic and jugular veins of 40 patients with cirrhosis was collected during hepatic venous pressure gradient (HVPG) measurements. Serum levels of 13 inflammatory cytokines (IL-1β, Int-α2, Int-γ, TNF-α, MCP-1, IL-6, IL-8, IL-10, IL-12p70, IL-17A, IL-18, IL-23, and IL-33) were quantified by cytometric bead array. Results. Cytokine levels of IFN-α2, IFN-γ, TNF-α, IL-6, IL-8, IL-10, IL-17A, IL-18, IL-23, and IL-33 were significantly elevated in patients with decompensated cirrhosis compared to patients with compensated cirrhosis. When comparing patients with clinically significant portal hypertension (CSPH, HVPG ≥ 10 mmHg) to patients without CSPH, there were significantly enhanced serum levels of IL-6 and IL-18 in the former group. There was no significant difference between cytokine serum levels between blood obtained from the jugular versus hepatic veins. Even in subgroup analyses stratified for an early cirrhosis stage (Child-Pugh (CP) A) or more decompensated stages (CP B/C), cytokine levels were similar. Conclusion. Cytokine levels increase with decompensation and increasing portal hypertension in patients with cirrhosis. There is no relevant difference in cytokine levels between hepatic and jugular blood in patients with cirrhosis.

Background. Abdominal aortic occlusion (AAO) occurs frequently and causes ischemia/reperfusion (I/R) injury to distant organs. In this study, we aimed to investigate whether AAO induced I/R injury and subsequent damage in cardiac and neurologic tissue. We also aimed to investigate the how length of ischemic time in AAO influences reactive oxygen species (ROS) production and inflammatory marker levels in the heart, brain, and serum. Methods. Sixty male C57BL/6 mice were used in this study. The mice were randomly divided into either sham group or AAO group. The AAO group was further subdivided into 1–4 hr groups of aortic occlusion times. The infrarenal abdominal aorta was clamped for 1–4 hr depending on the AAO group and was then reperfused for 24 hr after clamp removal. Serum, hippocampus, and left ventricle tissue samples were then subjected to biochemical and histopathological analyses. Results. AAO-induced I/R injury had no effect on cell necrosis, cell apoptosis, or ROS production. However, serum and hippocampus levels of malondialdehyde (MDA) and lactate dehydrogenase (LDH) increased in AAO groups when compared to sham group. Superoxide dismutase and total antioxidant capacity decreased in the serum, hippocampus, and left ventricle. In the serum, AAO increased the level of inducible nitric oxide synthase (iNOS) and decreased the levels of anti-inflammatory factors (such as arginase-1), transforming growth factor- β1 (TGF-β1), interleukin 4 (IL-4), and interleukin 10 (IL-10). In the hippocampus, AAO increased the levels of tumor necrosis factor (TNF-α), interleukin 1β (IL-1β), interleukin 6 (IL-6), IL-4, and IL-6, and decreased the level of TGF-β1. In the left ventricle, AAO increased the level of iNOS and decreased the levels of TGF-β1, IL-4, and IL-10. Conclusions. AAO did not induce cell necrosis or apoptosis in cardiac or neurologic tissue, but it can cause inflammation in the serum, brain, and heart.

Background. Literature and data mining found abnormal induction of chemokine (C-X-C motif) ligand 1 (CXCL1) and CXCL8 and down-regulation of CXCL2 in inflammatory liver diseases. This study was performed to understand the glucocorticoid receptor’s (GR’s) effects on chemokine and acute-phase protein expression in human liver, in settings of bacterial infection (modeled using LPS) or inflammation (modeled using TNFα). Methods. Primary human hepatocytes (PHH) were treated with combinations of tumor necrosis factor alpha (TNFα), lipopolysaccharide (LPS), and dexamethasone (DEX) for 24 h, following which chemokine mRNA and protein expression were analyzed using qPCR and enzyme-linked immunosorbent assay assays. Dual luciferase assays were performed on transfected cell lines. Mutant CXCL2 promoters were used in dual luciferase assays to identify specific regions of the CXCL2 promoter affected by GR, TNFα, or hepatocyte nuclear factor 4α (HNF4α, a liver-enriched transcription factor). Results. In PHH from donor 1, GR strongly inhibited LPS-induced CXCL1 and CXCL8 translation and transcription, whereas CXCL2 transcription tended to increase with DEX treatment. In PHH from donor 2, DEX treatment inhibited protein expression and secretion of CXCL1 and CXCL8 induced by TNFα and/or LPS, whereas CXCL2 upregulation was largely unaffected by DEX treatment. In nonliver HEK293T cells GR activity inhibited CXCL2 promoter activity. However, in liver-derived HEPG2 cells, GR induced CXCL2 promoter activity. A 407-base pair region upstream of CXCL2 promoter is necessary for full GR functionality in HEPG2 cells. TNFα synergized with HNF4α in inducing CXCL2 promoter activity in HEPG2 cells. Conclusions. GR’s effects on chemokine expression are cell-type specific and chemokine specific. GR down-regulated CXCL1 and CXCL8 in different cell types, whereas the specific activation of CXCL2 in hepatocytes and down-regulation of CXCL2 in nonhepatocytes by GR appears due to cell-specific utilization of CXCL2 promoter. By specifically increasing GR activity in the liver, we may normalize chemokine imbalances and prevent sepsis in inflammatory liver diseases.

Background. The systemic immune-inflammation index (SII) is used as an indicator of prognosis for a wide range of diseases. Thyroid function has been found to be strongly associated with inflammation. The purpose of this investigation was to analyze the correlation between SII and various thyroid functions. Methods. This study utilized data from the National Health and Nutrition Examination Survey (NHANES) 2007–2012. The association between SII and thyroid function was analyzed using weighted univariate and multivariate linear regression analyses. Subgroup analyses, interaction tests, and weighted restricted cubic spline (RCS) regression analyses were also employed to test this correlation. Results. Of the 6,875 participants (age ≥ 20 years), the mean age was 46.87 ± 0.40 years. The adjusted model showed that lnSII was negatively correlated with FT3 (β = −0.0559, 95% CI −0.1060 to −0.0059,) and FT3/FT4 (β = −0.0920, 95% CI −0.1667 to −0.0173,). There was a positive correlation between lnSII and TT4 (β = 0.1499, 95% CI 0.0722–0.2276,). In subgroup analyses, lnSII still independently affected a wide range of thyroid functions. Weighted RCS analysis showed a nonlinear relationship between FT3 and lnSII. Conclusion. Close relationships exist between SII and a variety of thyroid functions. SII can be used as an indicator to predict thyroid dysfunction. Control of inflammatory activity may be a protective measure against thyroid dysfunction. More large-scale prospective studies are necessary to further explore the correlation between SII and thyroid function and the role of obesity in this.

Kawasaki disease (KD) is an immune-response disorder with unknown etiology. KD is an acute systemic immune vasculitis caused by infectious factors that can be complicated by coronary artery lesions. Innate immune cells are closely associated with KD onset, but we know little regarding the expression of immunity-related genes (IRGs) and the possible immune regulatory mechanisms involved in KD. In this study, we analyzed public single-cell RNA sequencing (scRNA-seq) and microarray data of peripheral blood mononuclear cells from normal controls and KD patients. The results of scRNA-seq revealed myeloid cells, T cells, B cells, NK cells, erythrocytes, platelets, plasma cells, hematopoietic stem cells, and progenitor cells in the peripheral blood of patients with KD. In particular, myeloid cells were expanded and heterogeneous. Further analysis of the myeloid cell population revealed that monocytes in KD exhibited higher expression of the inflammatory genes S100A8, S100A9, and S100A12; furthermore, CD14+CD16+ monocyte clusters were associated with inflammatory responses. Microarray data revealed that activation of the innate immune response contributed to KD development and progression. Differential expression and weighted gene coexpression network analysis identified 48 differentially expressed IRGs associated with response to intravenous immunoglobulin, currently the most effective treatment of KD, although numerous patients are resistant. Protein–protein interaction analysis identified ten hub genes (IL1R1, SOCS3, IL1R2, TLR8, IL1RN, CCR1, IL1B, IL4R, IL10RB, and IFNGR1) among the IRGs. In addition, the expressions of IL1R1, SOCS3, CCR1, IL1B, and IL10RB were validated in Chinese KD patients using the real-time reverse transcriptase-polymerase chain reaction. Finally, we found that the neutrophil/lymphocyte ratio could be used as a biomarker to predict responsiveness to intravenous immunoglobulin in KD. In conclusion, our data highlight the importance of innate immunity in KD pathogenesis and its potential in predicting treatment response.

Background. 5-Methylcytosine (m5C) RNA modification is closely implicated in the occurrence of a variety of cancers. Here, we established a novel prognostic signature for ovarian cancer (OC) patients based on m5C RNA modification-related genes and explored the correlation between these genes with the tumor immune microenvironment. Methods. Methylated-RNA immunoprecipitation sequencing helped us to identify candidate genes related to m5C RNA modification at first. Based on TCGA database, we screened the differentially expressed candidate genes related to the prognosis and constructed a prognostic model using LASSO Cox regression analyses. Notably, the accuracy of the model was evaluated by Kaplan–Meier analysis and receiver operator characteristic curves. Independent prognostic risk factors were investigated by Cox proportional hazard model. Furthermore, we also analyzed the biological functions and pathways involved in the signature. Finally, the immune response of the model was visualized in great detail. Results. Totally, 2,493 candidate genes proved to be involved in m5C modification of RNA for OC. We developed a signature with prognostic value consisting of six m5C RNA modification-related genes. Specially, samples have been split into two cohorts with low- and high-risk scores according to the model, in which the low-risk OC patients exhibited dramatically better overall survival time than those with high-risk scores. Besides, not only was this model a prognostic factor independent of other clinical characteristics but it predicted the intensity of the immune response in OC. Significantly, the accuracy and availability of the signature were verified by ICGC database. Conclusions. Our study bridged the gap between m5C RNA modification and the prognosis of OC and was expected to provide an effective breakthrough for immunotherapy in OC patients.