Relationship between low levels of circulating TRAIL and atheromatosis progression in patients with chronic kidney disease

TRAIL and its receptors in cardiac diseases

Cardiovascular disease is a leading cause of death worldwide. Loss of cardiomyocytes that occurs during many types of damage to the heart such as ischemic injury and stress caused by pressure overload, diminishes cardiac function due to their limited regenerative capacity and promotes remodeling, which further damages the heart. Cardiomyocyte death occurs through two primary mechanisms, necrosis and apoptosis. Apoptosis is a highly regulated form of cell death that can occur through intrinsic (mitochondrial) or extrinsic (receptor mediated) pathways. Extrinsic apoptosis occurs through a subset of Tumor Necrosis Receptor (TNF) family receptors termed "Death Receptors." While some ligands for death receptors have been extensively studied in the heart, such as TNF-α, others have been virtually unstudied. One poorly characterized cardiac TNF related ligand is TNF-Related Apoptosis Inducing Ligand (TRAIL). TRAIL binds to two apoptosis-inducing receptors, Death Receptor (DR) 4 and DR5. There are also three decoy TRAIL receptors, Decoy Receptor (DcR) 1, DcR2 and osteoprotegerin (OPG). While TRAIL has been extensively studied in the cancer field due to its ability to selectively induce apoptosis in transformed cell types, emerging clinical evidence points towards a role for TRAIL and its receptors in cardiac pathology. This article will highlight our current understanding of TRAIL and its receptors in normal and pathological conditions in the heart.

TRAIL or TRAIL-R2 as a Predictive Biomarker for Mortality or Cardiovascular Events: A Systematic Review and Meta-analysis

ABSTRACT

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and TRAIL-receptor-2 (TRAIL-R2) are associated with atherosclerosis. This meta-analysis aimed to investigate the potential association between TRAIL/TRAIL-R2 with mortality or cardiovascular (CV) events. PubMed, Embase, and Cochrane Library were searched for reports published up to May 2021. Reports were included when the association between TRAIL or TRAIL-R2 and mortality or CV events was reported. Considering the heterogeneity between studies, we used the random-effects model for all analyses. Ultimately, the meta-analysis included 18 studies (16,295 patients). The average follow-up ranged from 0.25 to 10 years. Decreased TRAIL levels were negatively associated with all-cause mortality [rank variable, hazard ratio (HR), 95% CI, 2.93, 1.94-4.42; I2 = 0.0%, Pheterogeneity = 0.835]. Increased TRAIL-R2 levels were positively associated with all-cause mortality (continuous variable, HR, 95% CI, 1.43, 1.23-1.65; I2 = 0.0%, Pheterogeneity = 0.548; rank variable, HR, 95% CI, 7.08, 2.70-18.56; I2 = 46.5%, Pheterogeneity = 0.154), CV mortality (continuous variable, HR, 95% CI, 1.33, 1.14-1.57; I2 = 0.0%, Pheterogeneity = 0.435), myocardial infarction (continuous variable, HR, 95% CI, 1.23, 1.02-1.49; rank variable, HR, 95% CI, 1.49, 1.26-1.76; I2 = 0.7%, Pheterogeneity = 0.402), and new-onset heart failure (rank variable, HR, 95% CI, 3.23, 1.32-7.87; I2 = 83.0%, Pheterogeneity = 0.003). In conclusion, decreased TRAIL was negatively associated with all-cause mortality, and increased TRAIL-R2 was positively associated with all-cause mortality, CV mortality, myocardial infarction, and heart failure.

Diagnostic model constructed by nine inflammation-related genes for diagnosing ischemic stroke and reflecting the condition of immune-related cells

Background

Ischemic cerebral infarction is the most common type of stroke with high rates of mortality, disability, and recurrence. However, the known diagnostic biomarkers and therapeutic targets for ischemic stroke (IS) are limited. In the current study, we aimed to identify novel inflammation-related biomarkers for IS using machine learning analysis and to explore their relationship with the levels of immune-related cells in whole blood samples.

Methods

Gene expression profiles of healthy controls and patients with IS were download from the Gene Expression Omnibus. Analysis of differentially expressed genes (DEGs) was performed in healthy controls and patients with IS. Single-sample gene set enrichment analysis was performed to calculate inflammation scores, and weighted gene co-expression network analysis was used to analyze genes in significant modules associated with inflammation scores. Key DEGs in significant modules were then analyzed using LASSO regression analysis for constructing a diagnostic model. The effectiveness and specificity of the diagnostic model was verified in healthy controls and patients with IS and with cerebral hemorrhage (CH) using qRT-PCR. The relationship between diagnostic score and the levels of immune-related cells in whole blood were analyzed using Pearson correlations.

Results

A total of 831 DEGs were identified. Both chronic and acute inflammation scores were higher in patients with IS, while 54 DEGs were also clustered in the gene modules associated with chronic and acute inflammation scores. Among them, a total of 9 genes were selected to construct a diagnostic model. Interestingly, RT-qPCR showed that the diagnostic model had better diagnostic value for IS but not for CH. The levels of lymphocytes were lower in blood of patients with IS, while the levels of monocytes and neutrophils were increased. The diagnostic score of the model was negatively associated with the levels of lymphocytes and positively associated with levels of monocytes and neutrophils.

Conclusions

Taken together, the diagnostic model constructed using the inflammation-related genes TNFSF10, ID1, PAQR8, OSR2, PDK4, PEX11B, TNIP1, FFAR2, and JUN exhibited high and specific diagnostic value for IS and reflected the condition of lymphocytes, monocytes, and neutrophils in the blood. The diagnostic model may contribute to the diagnosis of IS.

Identification of Biomarkers of Autophagy-Related Genes Between Early and Advanced Carotid Atherosclerosis

Background

Accumulating evidence demonstrates that autophagy is important in inhibiting inflammation and cholesterol efflux. It suggested the autophagy may be a treatment of atherosclerosis. Thus, we screened autophagy-related mRNA to explore their mechanism of scientific basis for early diagnosis and therapy of atherosclerosis.

Methods

The GSE28829 datasets were assessed to analyze differentially expressed genes by GEO2R. And autophagy-related hub genes were identified by HADb. The biological function of autophagy-related DEmRNAs was examined by Metascape. The construction of a protein–protein network was explored by String. Cytohubba was utilized to screen hub genes. Analysis of DEmiRNA-mRNA pairs was executed by DIANA microT-CDS database. Finally, correlation analysis was carried out to identify the relationship between DEARGs and clinical and prognostic factors.

Results

A number of 1087 DEGs and 19 autophagy-related DEmRNAs were identified in advanced carotid atherosclerotic plaque compared with the early. The biological function containing development and growth was enriched. Moreover, we screened the top hub nodes with the highest degrees. MicroRNAs (miRNAs) are confirmed to participate in genesis and progression of atherosclerosis, so we further analyzed the miRNA–mRNA regulatory network genes with four hub genes to explore their potential mechanism in atherosclerosis. Then, we revealed co-expression of four key genes CTSB, ITGB1, CXCR4, TNFSF10 and autophagy-related genes. As for the clinical factors, hypertension factor showed higher expression of ITGB1. The probability of coronary heart disease factor was significantly increased with high expression of CTSB and CXCR4, as well as low expression of ITGB1 and TNFSF10. Diabetes factor tended to express distinguished levels of CTSB and ITGB1. TNFSF10 was highly expressed in both hyperlipidemia and ischemic stroke factor.

Conclusion

CTSB, ITGB1, CXCR4 and TNFSF10 may be critical in atherosclerosis development and were thought to be potential diagnostic biomarkers for atherosclerosis.

Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand (TRAIL) in Patients after Acute Stroke: Relation to Stroke Severity, Myocardial Injury, and Impact on Prognosis

Background: Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is known to be associated with poor prognosis after cardiovascular events. We aimed to assess the dynamic changes in TRAIL levels and the relation of TRAIL level to stroke severity, its impact on the short-term outcomes, and its association with markers of cardiac injury in patients after acute stroke. Methods: Between August 2020 and August 2021, 120 consecutive patients, 104 after acute ischemic stroke (AIS), 76 receiving reperfusion therapy, and 16 patients after intracerebral hemorrhage (ICH) were enrolled in our study. Blood samples were obtained from patients at the time of admission, 24 h later, and 48 h later to determine the plasma level of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and high-sensitive Troponin I (hs-TnI). Twelve-lead ECGs were obtained at the time of admission, 24 h later, 48 h later, and at the release of the patients. Evaluations were performed using the National Institutes of Health Stroke Scale (NIHSS) at the time of admission and using the modified Rankin Scale (mRS) 90 days following the patient’s discharge from the hospital. Results: We observed a connection between lower TRAIL levels and stroke severity evaluated using the NIHSS (p = 0.044) on the first day. Lower TRAIL showed an association with severe disability and death as evaluated using the mRS at 90 days, both after 24 (p = 0.0022) and 48 h (p = 0.044) of hospitalization. Moreover, we observed an association between lower TRAIL and NT-proBNP elevation at the time of admission (p = 0.039), after 24 (p = 0.043), and after 48 h (p = 0.023) of hospitalization. In the ECG analysis, lower TRAIL levels were associated with the occurrence of premature ventricular extrasystoles (p = 0.043), and there was an association with prolonged QTc interval (p = 0.052). Conclusions: The results show that lower TRAIL is associated with stroke severity, unfavorable functional outcome, and short-term mortality in patients after acute ischemic stroke. Moreover, we described the association with markers of cardiac injury and ECG changes.

Osteoprotegerin and RANKL-RANK-OPG-TRAIL signalling axis in heart failure and other cardiovascular diseases

Osteoprotegerin (OPG) is a glycoprotein involved in the regulation of bone remodelling. OPG regulates osteoclast activity by blocking the interaction between the receptor activator of nuclear factor kappa B (RANK) and its ligand (RANKL). More and more studies confirm the relationship between OPG and cardiovascular diseases. Numerous studies have confirmed that a high plasma concentration of OPG and a low concentration of tumour necrosis factor–related apoptosis inducing ligand (TRAIL) together with a high OPG/TRAIL ratio are predictors of poor prognosis in patients with myocardial infarction. A high plasma OPG concentration and a high ratio of OPG/TRAIL in the acute myocardial infarction are a prognostic indicator of adverse left ventricular remodelling and of the development of heart failure. Ever more data indicates the participation of OPG in the regulation of the function of vascular endothelial cells and the initiation of the atherosclerotic process in the arteries. Additionally, it has been shown that TRAIL has a protective effect on blood vessels and exerts an anti-atherosclerotic effect. The mechanisms of action of both OPG and TRAIL within the cells of the vascular wall are complex and remain largely unclear. However, these mechanisms of action as well as their interaction in the local vascular environment are of great interest to researchers. This article presents the current state of knowledge on the mechanisms of action of OPG and TRAIL in the circulatory system and their role in cardiovascular diseases. Understanding these mechanisms may allow their use as a therapeutic target in cardiovascular diseases in the future.

Plasma Protein Profile of Incident Myocardial Infarction, Ischemic Stroke, and Heart Failure in 2 Cohorts

Background The aim is to study common etiological pathways for 3 major cardiovascular diseases (CVD), as reflected in multiple proteins. Methods and Results Eighty-four proteins were measured using the proximity extension technique in 870 participants in the PIVUS (Prospective Investigation of Uppsala Seniors Study) cohort on 3 occasions (age 70, 75, and 80 years). The sample was followed for incident myocardial infarction, ischemic stroke or heart failure. The same proteins were measured in an independent validation sample, the ULSAM (Uppsala Longitudinal Study of Adult Men) cohort in 595 participants at age 77. During a follow-up of up to 15 years in PIVUS and 9 years in ULSAM, 222 and 167 individuals experienced a CVD. Examining associations with the 3 outcomes separately in a meta-analysis of the 2 cohorts, 6 proteins were related to incident myocardial infarction, 25 to heart failure, and 8 proteins to ischemic stroke following adjustment for traditional risk factors. Growth differentiation factor 15 and tumor necrosis factor-related apoptosis-inducing ligand receptor 2 were related to all 3 CVDs. Including estimated glomerular filtration rate in the models attenuated some of these relationships. Fifteen proteins were related to a composite of all 3 CVDs using a discovery/validation approach when adjusting for traditional risk factors. A selection of 7 proteins by lasso in PIVUS improved discrimination of incident CVD by 7.3% compared with traditional risk factors in ULSAM. Conclusions We discovered and validated associations of multiple proteins with incident CVD. Only a few proteins were associated with all 3 diseases: myocardial infarction, ischemic stroke, and heart failure.

Plasma Protein Profile of Carotid Artery Atherosclerosis and Atherosclerotic Outcomes: Meta-Analyses and Mendelian Randomization Analyses

[Figure: see text].

TRAIL and Cardiovascular Disease-A Risk Factor or Risk Marker: A Systematic Review

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a pro-apoptotic protein showing broad biological functions. Data from animal studies indicate that TRAIL may possibly contribute to the pathophysiology of cardiomyopathy, atherosclerosis, ischemic stroke and abdominal aortic aneurysm. It has been also suggested that TRAIL might be useful in cardiovascular risk stratification. This systematic review aimed to evaluate whether TRAIL is a risk factor or risk marker in cardiovascular diseases (CVDs) focusing on major adverse cardiovascular events. Two databases (PubMed and Cochrane Library) were searched until December 2020 without a year limit in accordance to the PRISMA guidelines. A total of 63 eligible original studies were identified and included in our systematic review. Studies suggest an important role of TRAIL in disorders such as heart failure, myocardial infarction, atrial fibrillation, ischemic stroke, peripheral artery disease, and pulmonary and gestational hypertension. Most evidence associates reduced TRAIL levels and increased TRAIL-R2 concentration with all-cause mortality in patients with CVDs. It is, however, unclear whether low TRAIL levels should be considered as a risk factor rather than a risk marker of CVDs. Further studies are needed to better define the association of TRAIL with cardiovascular diseases.

Use of proteomics to identify biomarkers associated with chronic kidney disease and long-term outcomes in patients with myocardial infarction

BACKGROUND

Patients with chronic kidney disease (CKD) have poor outcomes following myocardial infarction (MI). We performed an untargeted examination of 175 biomarkers to identify those with the strongest association with CKD and to examine the association of those biomarkers with long-term outcomes.

METHODS

A total of 175 different biomarkers from MI patients enrolled in the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry were analysed either by a multiple reaction monitoring mass spectrometry assay or by a multiplex assay (proximity extension assay). Random forests statistical models were used to assess the predictor importance of biomarkers, CKD and outcomes.

RESULTS

A total of 1098 MI patients with a median estimated glomerular filtration rate of 85 mL min^-1 /1.73 m² were followed for a median of 3.2 years. The random forests analyses, without and with adjustment for differences in demography, comorbidities and severity of disease, identified six biomarkers (adrenomedullin, TNF receptor-1, adipocyte fatty acid-binding protein-4, TNF-related apoptosis-inducing ligand receptor 2, growth differentiation factor-15 and TNF receptor-2) to be strongly associated with CKD. All six biomarkers were also amongst the 15 strongest predictors for death, and four of them were amongst the strongest predictors of subsequent MI and heart failure hospitalization.

CONCLUSION

In patients with MI, a proteomic approach could identify six biomarkers that best predicted CKD. These biomarkers were also amongst the most important predictors of long-term outcomes. Thus, these biomarkers indicate underlying mechanisms that may contribute to the poor prognosis seen in patients with MI and CKD.

Single-cell analyses identify dysfunctional CD16+ CD8 T cells in smokers

Tobacco smoke exposure contributes to the global burden of communicable and chronic diseases. To identify the immune cells affected by smoking, we use single-cell RNA sequencing on peripheral blood from smokers and nonsmokers. Transcriptomes reveal a subpopulation of FCGR3A (CD16)-expressing natural killer (NK)-like CD8 T lymphocytes that increase in smokers. Mass cytometry confirms elevated CD16⁺ CD8 T cells in smokers. Inferred as highly differentiated by pseudotime analysis, NK-like CD8 T cells express markers that are characteristic of effector memory re-expressing CD45RA T (T_EMRA) cells. Indicative of immune aging, smokers’ CD8 T cells are biased toward differentiated cells, and smokers have fewer naive cells than nonsmokers. DNA methylation-based models show that smoking dose is associated with accelerated aging and decreased telomere length, a biomarker of T cell senescence. Immune aging accompanies T cell senescence, which can ultimately lead to impaired immune function. This suggests a role for smoking-induced, senescence-associated immune dysregulation in smoking-mediated pathologies.

Smoking shifts the composition of CD8 T cells from naive to differentiated states

NK-like CD16⁺ CD8 T_EMRA cells are elevated in smokers and express GZMB and PRF1

DNA methylation links smoking dose with age acceleration and shortened telomeres

CD8 T, CD4 T, NKT, NK, and monocytes express senescence-linked genes in smokers

Atherosclerosis in Chronic Kidney Disease: More, Less, or Just Different?

Patients with chronic kidney disease (CKD) are at an increased risk of premature mortality, mainly from cardiovascular causes. The association between CKD on hemodialysis and accelerated atherosclerosis was described >40 years ago. However, more recently, it has been suggested that the increase in atherosclerosis risk is actually observed in early CKD stages, remaining stable thereafter. In this regard, interventions targeting the pathogenesis of atherosclerosis, such as statins, successful in the general population, have failed to benefit patients with very advanced CKD. This raises the issue of the relative contribution of atherosclerosis versus other forms of cardiovascular injury such as arteriosclerosis or myocardial injury to the increased cardiovascular risk in CKD. In this review, the pathophysiogical contributors to atherosclerosis in CKD that are shared with the general population, or specific to CKD, are discussed. The NEFRONA study (Observatorio Nacional de Atherosclerosis en NEFrologia) prospectively assessed the prevalence and progression of subclinical atherosclerosis (plaque in vascular ultrasound), confirming an increased prevalence of atherosclerosis in patients with moderate CKD. However, the adjusted odds ratio for subclinical atherosclerosis increased with CKD stage, suggesting a contribution of CKD itself to subclinical atherosclerosis. Progression of atherosclerosis was closely related to CKD progression as well as to the baseline presence of atheroma plaque, and to higher phosphate, uric acid, and ferritin and lower 25(OH) vitamin D levels. These insights may help design future clinical trials of stratified personalized medicine targeting atherosclerosis in patients with CKD. Future primary prevention trials should enroll patients with evidence of subclinical atherosclerosis and should provide a comprehensive control of all known risk factors in addition to testing any additional intervention or placebo.

TRAIL, OPG, and TWEAK in kidney disease: biomarkers or therapeutic targets?

Ligands and receptors of the tumor necrosis factor (TNF) superfamily regulate immune responses and homeostatic functions with potential diagnostic and therapeutic implications. Kidney disease represents a global public health problem, whose prevalence is rising worldwide, due to the aging of the population and the increasing prevalence of diabetes, hypertension, obesity, and immune disorders. In addition, chronic kidney disease is an independent risk factor for the development of cardiovascular disease, which further increases kidney-related morbidity and mortality. Recently, it has been shown that some TNF superfamily members are actively implicated in renal pathophysiology. These members include TNF-related apoptosis-inducing ligand (TRAIL), its decoy receptor osteoprotegerin (OPG), and TNF-like weaker inducer of apoptosis (TWEAK). All of them have shown the ability to activate crucial pathways involved in kidney disease development and progression (e.g. canonical and non-canonical pathways of the transcription factor nuclear factor-kappa B), as well as the ability to regulate cell proliferation, differentiation, apoptosis, necrosis, inflammation, angiogenesis, and fibrosis with double-edged effects depending on the type and stage of kidney injury. Here we will review the actions of TRAIL, OPG, and TWEAK on diabetic and non-diabetic kidney disease, in order to provide insights into their full clinical potential as biomarkers and/or therapeutic options against kidney disease.