Profiles and Predictive Values of Interleukin-6 in Aortic Dissection: a Review

Use of Bacterial DNA Concentration in Ascites as a Marker for Spontaneous Bacterial Peritonitis

Background and aims

Spontaneous bacterial peritonitis (SBP) is a common and serious complication in patients with decompensated cirrhosis. Precise quantification of bacterial DNA (bactDNA) and the related inflammatory response might add further information on the course of disease. The aim of the study was to evaluate the association between bactDNA, cytokine levels and clinical outcome.

Methods

Ascites and serum samples of 98 patients with decompensated liver cirrhosis (42 with SBP and 56 without SBP) as well as serum samples of 21 healthy controls were collected. BactDNA in ascites and serum was detected and quantified by 16S rRNA PCR. Concentrations of IL-1β, TNF-α, IL-6, IL-8 and IL-10 were measured by a LEGENDplexTM multi-analyte flow assay. Clinical data were collected and analyzed retrospectively.

Results

BactDNA was detected more frequently in ascites of patients with SBP (n = 24/42; 57.1%) than in ascites of patients without SBP (n = 5/56; 8.9%; P < 0.001). Additionally, IL-6 levels in both ascites and serum were significantly higher in patients with SBP (ascites P < 0.001, serum P = 0.036). The quantity of bactDNA in ascites was strongly correlated with polymorphonuclear neutrophil count in ascites (r = 0.755; P < 0.001) as well as ascites IL-6 levels (r = 0.399; P < 0.001). Receiver operating characteristic (ROC) curve analysis to diagnose SBP provided an AUC of 0.764 (95% CI: 0.661-0.867) for serum IL-6 levels, an AUC of 0.810 (95% CI: 0.714-0.905) for ascites IL-6 levels, and an AUC of 0.755 (95% CI: 0.651-0.858) for bactDNA levels in ascites.

Conclusions

The correlation between the amount of bactDNA and IL-6 confirms the pathophysiological relevance of bactDNA and IL-6 as potential biomarkers for the diagnosis of SBP.

A comprehensive exploration of novel biomarkers for the early diagnosis of aortic dissection

Aortic dissection (AD) is a catastrophic life-threatening cardiovascular emergency with a 1-2% per hour mortality rate post-diagnosis, characterized physiologically by the separation of aortic wall layers. AD initially presents as intense pain that can then radiate to the back, arms, neck, or jaw along with neurological deficits like difficulty in speaking, and unilateral weakness in some patients. This spectrum of clinical features associated with AD is often confused with acute myocardial infarction, hence leading to a delay in AD diagnosis. Cardiac and vascular biomarkers are structural proteins and microRNAs circulating in the bloodstream that correlate to tissue damage and their levels become detectable even before symptom onset. Timely diagnosis of AD using biomarkers, in combination with advanced imaging diagnostics, will significantly improve prognosis by allowing earlier vascular interventions. This comprehensive review aims to investigate emerging biomarkers in the diagnosis of AD, as well as provide future directives for creating advanced diagnostic tools and imaging techniques.

The diagnostic and prognostic value of SAA1 as a novel biomarker for acute aortic dissection

BACKGROUND AND AIMS

Acute aortic dissection (AAD) is a serious life-threatening cardiovascular condition. It is necessary to find rapid and accurate biomarkers for the diagnosis of AAD. This study aimed to determine the efficacy of serum amyloid A1 (SAA1) in the diagnosis and prediction of long-term adverse events in AAD.

MATERIALS AND METHODS

Four-dimensional label-free quantification (4D-LFQ) technique was used to identify the differentially expressed proteins (DEPs) in aortic tissues of AAD. After comprehensive analysis, SAA1 was identified as a potential biomarker of AAD. ELISA was used to confirm the expression of SAA1 in serum of AAD patients. Moreover, the source of SAA1 in serum was explored by constructing AAD mouse model.

RESULTS

A total of 247 DEPs were identified, of which 139 were upregulated while 108 were downregulated. SAA1 was nearly 6.4-fold and 4.5-fold upregulated in AAD tissue and serum. ROC curve and Kaplan-Meier survival curve confirmed the good efficacy of SAA1 for the diagnosis and prediction of long-term adverse events in AAD. In vivo experiments revealed that SAA1 was mainly derived from the liver when AAD occurred.

CONCLUSION

SAA1 can be used as a potential biomarker for AAD with effective diagnostic and prognostic value.

SIGNIFICANCE

Despite the advances in medical technology in recent years, the mortality rate of acute aortic dissection (AAD) is still high. It is still challenging for clinicians to diagnose AAD patients on time and reduce the mortality rate. In this study, 4D-LFQ technology was used to identify serum amyloid A1 (SAA1) as a potential biomarker of AAD and was verified in subsequent work. The results of this study determined the efficacy of SAA1 in the diagnosis and prediction of long-term adverse events in patients with AAD.

Targeting endothelial tight junctions to predict and protect thoracic aortic aneurysm and dissection

AIMS

Whether changes in endothelial tight junctions (TJs) lead to the formation of thoracic aortic aneurysm and dissection (TAAD) and serve as an early indicator and therapeutic target remains elusive.

METHODS AND RESULTS

Single-cell RNA sequencing analysis showed aberrant endothelial TJ expressions in the thoracic aortas of patients with TAAD. In a β-aminopropionitrile (BAPN)-induced TAAD mouse model, endothelial TJ function was disrupted in the thoracic aortas at an early stage (5 and 10 days) as observed by a vascular permeability assay, while the intercellular distribution of crucial TJ components was significantly decreased by en face staining. For the non-invasive detection of endothelial TJ function, two dextrans of molecular weights 4 and 70 kDa were conjugated with the magnetic resonance imaging (MRI) contrast agent Gd-DOTA to synthesize FITC-dextran-DOTA-Gd and rhodamine B-dextran-DOTA-Gd. MRI images showed that both probes accumulated in the thoracic aortas of the BAPN-fed mice. Particularly, the mice with increased accumulated signals from 5 to 10 days developed TAAD at 14 days, whereas the mice with similar signals between the two time points did not. Furthermore, the protease-activated receptor 2 inhibitor AT-1001, which seals TJs, alleviated the BAPN-induced impairment of endothelial TJ function and expression and subsequently reduced TAAD incidence. Notably, endothelial-targeted ZO-1 conditional knockout increased TAAD incidence. Mechanistically, vascular inflammation and edema were observed in the thoracic aortas of the BAPN-fed mice, whereas these phenomena were attenuated by AT-1001.

CONCLUSION

The disruption of endothelial TJ function is an early event prior to TAAD formation, herein serving as a potential indicator and a promising target for TAAD.

Serum Oxylipin Profiles Identify Potential Biomarkers in Patients with Acute Aortic Dissection

Aortic dissection (AD) is a life-threatening cardiovascular disease with a dismal prognosis. Inflammation plays an important role in AD. Oxylipins are bioactive lipids involved in the modulation of inflammation and may be involved in the pathogenesis and progression of AD. This study aims to identify possible metabolites related to AD. A total of 10 type A Aortic dissection (TAAD) patients, 10 type B Aortic dissection (TBAD) patients and 10 healthy controls were included in this study. Over 100 oxylipin species were identified and quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis. Our investigation demonstrated substantial alterations in 91 oxylipins between AD and healthy individuals. Patients with TAAD had 89 entries accessible compared to healthy controls. According to orthogonal partial least squares discriminant analysis (OPLS-DA), fitness (R²X = 0.362 and R²Y = 0.807, p = 0.03) and predictability (Q² = 0.517, p = 0.005) are the validation parameters between the two groups. Using multivariate logistic regression, 13-HOTrE and 16(17)-EpDPE were the risk factors in the aortic patients group compared to healthy people (OR = 2.467, 95%CI:1.256–7.245, p = 0.035; OR = 0.015, 95%CI:0.0002–0.3240, p = 0.016, respectively). In KEGG enrichment of differential metabolites, the arachidonic acid metabolism pathway has the most metabolites involved. We established a diagnostic model in distinguishing between AD and healthy people. The AUC was 0.905. Oxylipins were significantly altered in AD patients, suggesting oxylipin profile is expected to exploit a novel, non-invasive, objective diagnosis for AD.

Prediction model for postoperative severe acute lung injury in patients undergoing acute type A aortic dissection surgery

OBJECTIVE

This study aimed to establish a risk assessment model to predict postoperative severe acute lung injury (ALI) risk in patients with acute type A aortic dissection (ATAAD).

METHODS

Consecutive patients with ATAAD admitted to our hospital were included in this retrospective assessment and placed in the postoperative severe ALI and nonsevere ALI groups based on the presence or absence of ALI within 72 h postoperatively (oxygen index [OI] ≤ 100 mmHg). Patients were then randomly divided into training and validation groups in a ratio of 8:2. Univariate and multivariate stepwise forward logistic regression analyses were used to statistically assess data and establish the prediction model. The prediction model's effectiveness was evaluated via 10-fold cross-validation of the validation group to facilitate the construction of a nomogram.

RESULTS

After the screening, 479 patients were included in the study: 132 (27.6%) in the postoperative severe ALI group and 347 (72.4%) in the postoperative nonsevere ALI group. Based on multivariate logistics regression analyses, the following variables were included in the model: coronary heart disease, cardiopulmonary bypass (CPB) ≥ 257.5 min, left atrium diameter ≥ 35.5 mm, hemoglobin ≤ 139.5 g/L, preCPB OI ≤ 100 mmHg, intensive care unit OI ≤ 100 mmHg, left ventricular posterior wall thickness ≥ 10.5 mm, and neutrophilic granulocyte percentage ≥ 0.824. The area under the receiver operating characteristic (ROC) curve of the modeling group was 0.805 and differences between observed and predicted values were not deemed statistically significant via the Hosmer-Lemeshow test (χ²  = 6.037, df = 8, p = .643). For the validation group, the area under the ROC curve was 0.778, and observed and predicted value differences were insignificant when assessed using the Hosmer-Lemeshow test (χ²  = 3.3782, df = 7; p = .848). The average 10-fold cross-validation score was 0.756.

CONCLUSIONS

This study established a prediction model and developed a nomogram to determine the risk of postoperative severe ALI after ATAAD. Variables used in the model were easy to obtain clinically and the effectiveness of the model was good.