Study on Proteomics-Based Aortic Dissection Molecular Markers Using iTRAQ Combined With Label Free Techniques

Platelet factors ameliorate thoracic aortic aneurysm and dissection by inhibiting the FGF-FGFR cascade activation in aortic-endothelial cell

Thoracic aortic aneurysm and dissection (TAAD) is closely associated with vascular endothelial dysfunction. Platelet factor 4 (PF4) is crucial for maintaining vascular endothelial cell homeostasis. However, whether PF4 can influence the progression of TAAD remains unknown. In the present study, we constructed a liposome-encapsulated PF4 nanomedicine and verified its effect on BAPN-induced TAAD in vivo. We found that liposome PF4 nanoparticles (Lipo-PF4), more effectively than PF4 alone, inhibited the formation of TAAD. In vitro, PF4 improved endothelial cell function under pathological conditions by inhibiting migratory and angiogenic abilities of human aortic endothelial cells (HAECs). Mechanically, PF4 inhibited the development of TAAD and improved HAECs function by combining with heparin sulfate and blocking fibroblast growth factor-fibroblast growth factor receptor (FGF-FGFR) signaling. Taken together, we developed a nano-drug (Lipo-PF4) that effectively ameliorates the progression of TAAD by improving endothelial function. Lipo-PF4 is expected to be a therapeutic option for TAAD in the future.

The combined use of serum Raman spectroscopy and D dimer testing for the early diagnosis of acute aortic dissection

Objectives

Acute aortic dissection (AAD) is an extremely life-threatening medical emergency, often misdiagnosed in its early stages, resulting in prolonged wait times for rescue. This study aims to identify potential serum biomarkers that can assist in the accurate diagnosis of AAD and effectively differentiate it from other conditions causing severe chest pain.

Methods

A total of 122 patients with AAD and 129 patients with other severe chest pain disorders were included in the study. Serum samples were analyzed by measuring the peak intensities of Raman spectra. For each measurement, the Raman spectrum was accumulated by two accumulations (3 s per acquisition). Logistic regression and nomogram models were developed using these peak intensities as well as D-dimer levels to predict the occurrence of AAD. The clinical utilities of these models were assessed through receiver operating characteristics (ROC) curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) in both training and internal test cohorts.

Results

The D-dimer levels of AAD patients were significantly increased, as well as higher intensities at specific Raman peaks, including 505 cm-1, 842 cm-1, 947 cm-1, 1254 cm-1, 1448 cm-1, and 1655 cm-1 when compared to non-AAD patients. Conversely, decreased intensities were observed at Raman peaks such as 750 cm-1, 1004 cm-1, 1153 cm-1, 1208 cm-1, and 1514 cm-1 in AAD patients. Least absolute shrinkage and selection operator regression analysis on the training cohort identified eight potential predictors: D-dimer along with intensity measurements at peaks such as 505 cm-1, 750 cm-1, 1153 cm-1, 1208 cm-1, 1254 cm-1, 1448 cm-1, and 1655 cm-1. The combination of these eight potential predictors demonstrated a good discriminatory performance, with an area under the curve (AUC) value of 0.928 in the training cohort and an AUC of 0.936 in the internal test cohort, outperforming the use of D-dimer alone. Furthermore, DCA curve analysis revealed that leveraging this combination of eight potential predictors would provide substantial net benefits for clinical application. Moreover, this combination significantly augmented discrimination power, as evidenced by a continuous NRI of 39.8 % and IDI of 9.95 % in the training cohort, as well as a continuous NRI of 27.1 % and IDI of 9.95 % in the internal test cohort.

Conclusions

The employment of this combination of eight potential predictors effectively rules out AAD to a greater extent. This study presents a promising diagnostic strategy for early detection using optical diagnostic techniques such as Raman spectroscopy.

Potential clinical value of fibrinogen-like protein 1 as a serum biomarker for the identification of diabetic cardiomyopathy

Diabetic individuals with diabetic cardiomyopathy (DbCM) present with abnormal myocardial structure and function. DbCM cannot be accurately diagnosed due to the lack of suitable diagnostic biomarkers. In this study, 171 eligible participants were divided into a healthy control (HC), type 2 diabetes mellitus (T2DM) patients without DbCM (T2DM), or DbCM group. Serum fibrinogen-like protein 1 (FGL-1) and other biochemical parameters were determined for all participants. Serum FGL-1 levels were significantly higher in patients with DbCM compared with those in the T2DM group and HCs. Serum FGL-1 levels were negatively correlated with left ventricular fractional shortening and left ventricular ejection fraction (LVEF) and positively correlated with left ventricular mass index in patients with DbCM after adjusting for age, sex and body mass index. Interaction of serum FGL-1 and triglyceride levels on LVEF was noted in patients with DbCM. A composite marker including serum FGL-1 and triglycerides could differentiate patients with DbCM from those with T2DM and HCs with an area under the curve of 0.773 and 0.789, respectively. Composite marker levels were negatively correlated with N-terminal B-type natriuretic peptide levels in patients with DbCM. Circulating FGL-1 may therefore be a valuable index reflecting cardiac functions in DbCM and to diagnose DbCM.

Lumican, a Multifunctional Cell Instructive Biomarker Proteoglycan Has Novel Roles as a Marker of the Hypercoagulative State of Long Covid Disease

This study has reviewed the many roles of lumican as a biomarker of tissue pathology in health and disease. Lumican is a structure regulatory proteoglycan of collagen-rich tissues, with cell instructive properties through interactions with a number of cell surface receptors in tissue repair, thereby regulating cell proliferation, differentiation, inflammation and the innate and humoral immune systems to combat infection. The exponential increase in publications in the last decade dealing with lumican testify to its role as a pleiotropic biomarker regulatory protein. Recent findings show lumican has novel roles as a biomarker of the hypercoagulative state that occurs in SARS CoV-2 infections; thus, it may also prove useful in the delineation of the complex tissue changes that characterize COVID-19 disease. Lumican may be useful as a prognostic and diagnostic biomarker of long COVID disease and its sequelae.

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.

Physical Training vs. Perindopril Treatment on Arterial Stiffening of Spontaneously Hypertensive Rats: A Proteomic Analysis and Possible Mechanisms

(1) Background: Arterial stiffness is an important predictor of cardiovascular events. Perindopril and physical exercise are important in controlling hypertension and arterial stiffness, but the mechanisms are unclear. (2) Methods: Thirty-two spontaneously hypertensive rats (SHR) were evaluated for eight weeks: SHR_C (sedentary); SHR_P (sedentary treated with perindopril-3 mg/kg) and SHR_T (trained). Pulse wave velocity (PWV) analysis was performed, and the aorta was collected for proteomic analysis. (3) Results: Both treatments determined a similar reduction in PWV (-33% for SHR_P and -23% for SHR_T) vs. SHR_C, as well as in BP. Among the altered proteins, the proteomic analysis identified an upregulation of the EH domain-containing 2 (EHD2) protein in the SHR_P group, required for nitric oxide-dependent vessel relaxation. The SHR_T group showed downregulation of collagen-1 (COL1). Accordingly, SHR_P showed an increase (+69%) in the e-NOS protein level and SHR_T showed a lower COL1 protein level (-46%) compared with SHR_C. (4) Conclusions: Both perindopril and aerobic training reduced arterial stiffness in SHR; however, the results suggest that the mechanisms can be distinct. While treatment with perindopril increased EHD2, a protein involved in vessel relaxation, aerobic training decreased COL1 protein level, an important protein of the extracellular matrix (ECM) that normally enhances vessel rigidity.

Applying multi-omics techniques to the discovery of biomarkers for acute aortic dissection

Acute aortic dissection (AAD) is a cardiovascular disease that manifests suddenly and fatally. Due to the lack of specific early symptoms, many patients with AAD are often overlooked or misdiagnosed, which is undoubtedly catastrophic for patients. The particular pathogenic mechanism of AAD is yet unknown, which makes clinical pharmacological therapy extremely difficult. Therefore, it is necessary and crucial to find and employ unique biomarkers for Acute aortic dissection (AAD) as soon as possible in clinical practice and research. This will aid in the early detection of AAD and give clear guidelines for the creation of focused treatment agents. This goal has been made attainable over the past 20 years by the quick advancement of omics technologies and the development of high-throughput tissue specimen biomarker screening. The primary histology data support and add to one another to create a more thorough and three-dimensional picture of the disease. Based on the introduction of the main histology technologies, in this review, we summarize the current situation and most recent developments in the application of multi-omics technologies to AAD biomarker discovery and emphasize the significance of concentrating on integration concepts for integrating multi-omics data. In this context, we seek to offer fresh concepts and recommendations for fundamental investigation, perspective innovation, and therapeutic development in AAD.