Identification and Functional Investigation of Hub Genes Associated with Follicular Lymphoma

Follicular lymphoma (FL), the most common type of indolent lymphoma, originates from germinal center B cells within the lymphoid follicle. However, the underlying mechanisms of this disease remain unclear. This study aimed to identify the potential hub genes for FL and evaluate their functional roles in clinical applications. Microarray data and clinical characteristics of patients with FL were obtained from the Gene Expression Omnibus database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to explore hub genes for FL. Functional enrichment analysis was performed to investigate the potential roles of these hub genes in FL. Mendelian randomization (MR) analysis was performed to verify the causal effect of the top genes on FL risk. In addition, gene set enrichment analysis (GSEA) and immune cell analysis were performed to elucidate the involved mechanisms of the crucial genes in FL. A total of 1363 differentially expressed genes and 157 central genes were identified by differential expression analysis and WGCNA, respectively, resulting in 117 overlapping genes considered as hub genes for FL. Functional enrichment analysis revealed significant correlations between immune-related pathways and FL. MR analysis revealed a significant association only between zeta chain of T-cell receptor-associated protein kinase 70 (ZAP70) and FL risk, with no significance observed for the other top genes. GSEA and immune cell analysis suggested that ZAP70 may be involved in the development and progression of FL through immune-related pathways. By integrating bioinformatics and MR analyses, ZAP70 was successfully identified and validated as a promising FL biomarker. Functional investigations indicated a significant correlation between immune-related pathways and FL. These findings have important implications for the identification of targets for the diagnosis and treatment of FL and provide valuable insights into the molecular mechanisms underlying FL.

Characteristics and Outcomes of Young Patients With ST-Elevation Myocardial Infarction Without Standard Modifiable Risk Factors

Patients with ST-elevation myocardial infarction (STEMI) with no standard modifiable risk factors (SMuRFs: hypertension, diabetes mellitus, hypercholesterolemia, and smoking) have worse short-term mortality than those with SMuRFs. Whether this association extends to younger patients is unclear. A retrospective cohort study was performed of patients aged 18 to 45 years with STEMI at 3 Australian hospitals between 2010 and 2020. Nonatherosclerotic causes of STEMI were excluded. The primary outcome was 30-day all-cause mortality. Secondary outcomes included 1 and 2-year mortality. Cox proportional hazards analysis was used. Of 597 patients, the median age was 42 (interquartile range 38 to 44) years, 85.1% were men and 8.4% were SMuRF-less. Patients who are SMuRF-less were >2 times more likely to have cardiac arrest (28.0% vs 12.6%, p = 0.003); require vasopressors (16.0% vs 6.8%, p = 0.018), mechanical support (10.0% vs 2.3%, p = 0.046), or intensive care admission (20.0% vs 5.7%, p <0.001); and have higher rate of left anterior descending artery infarcts than those with SMuRFs (62.0% vs 47.2%, p = 0.045). No significant differences in thrombolysis or percutaneous intervention were observed. Guideline-directed medical therapy at discharge was high (>90%), and not different in the SMuRF-less. 30-day mortality was almost fivefold higher in the SMuRF-less (hazard ratio 4.70, 95% confidence interval 1.66 to 13.35, p = 0.004), remaining significant at 1 and 2 years. In conclusion, young patients who are SMuRF-less have a higher 30-day mortality after STEMI than their counterparts with SMuRFs. This may be partially mediated by higher rates of cardiac arrest and left anterior descending artery territory events. These findings further highlight the need for improved prevention and management of SMuRF-less STEMI.

Overcoming cohort heterogeneity for the prediction of subclinical cardiovascular disease risk

Cardiovascular disease remains a leading cause of mortality with an estimated half a billion people affected in 2019. However, detecting signals between specific pathophysiology and coronary plaque phenotypes using complex multi-omic discovery datasets remains challenging due to the diversity of individuals and their risk factors. Given the complex cohort heterogeneity present in those with coronary artery disease (CAD), we illustrate several different methods, both knowledge-guided and data-driven approaches, for identifying subcohorts of individuals with subclinical CAD and distinct metabolomic signatures. We then demonstrate that utilizing these subcohorts can improve the prediction of subclinical CAD and can facilitate the discovery of novel biomarkers of subclinical disease. Analyses acknowledging cohort heterogeneity through identifying and utilizing these subcohorts may be able to advance our understanding of CVD and provide more effective preventative treatments to reduce the burden of this disease in individuals and in society as a whole.

Transcriptomic profiling in hypoxia-induced trophoblast cells for preeclampsia

This study aimed to identify the expression profile of mRNAs and analyze the associated pathways in hypoxia-induced trophoblast cells to understand the effect of hypoxia on the pathophysiology of preeclampsia (PE). We downloaded two gene expression datasets (GSE47187 and GSE60432) from the Gene Expression Omnibus (GEO) datasets to identify altered transcriptomes. GEO2R, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) networks were used to reveal the functional roles and regulatory networks of the differentially expressed genes (DEGs). In total, 224 DEGs (91 upregulated and 133 downregulated) were identified, and the "HIF-1 signaling pathway" was activated in placentas from patients with PE. We validated the expression levels of five proteins in the plasma of NP and PE patients during early or late pregnancy using western blotting. In primary trophoblast cells cultured under hypoxic conditions, 754 DEGs were identified, including 362 upregulated and 392 downregulated genes. These DEGs were associated with the "HIF-1signaling pathway," "response to hypoxia," and several glucose metabolism pathways. In addition, a PPI network was constructed, and an important module, including 18 hub genes, was identified. Finally, we validated 18 hub genes using qRT-PCR. Furthermore, we performed microarray profiling of hypoxia-treated HTR8/SVneo cells (immortalized human first-trimester extravillous trophoblast cells) to validate the DEGs and pathways identified in hypoxia-induced primary trophoblast cells. Our results stress the differential expression profiles of mRNAs in hypoxia-induced trophoblast cells, which provide potential pathophysiological mechanisms for preeclampsia.

Elevated Soluble Suppressor of Tumorigenicity 2 Predict Hospital Admissions Due to Major Adverse Cardiovascular Events (MACE)

The role of soluble suppression of tumorigenicity (sST2) as a biomarker in predicting clinical outcomes in patients with cardiovascular diseases (CVD) has not been fully elucidated. In this study, we sought to determine the relationship between sST2 levels and any unplanned hospital readmissions due to a major adverse cardiovascular event (MACE) within 1 year of first admission. Patients (n = 250) admitted to the cardiology unit at John Hunter Hospital were recruited. Occurrences of MACE, defined as the composite of total death, myocardial infarction (MI), stroke, readmissions for heart failure (HF), or coronary revascularization, were recorded after 30, 90, 180, and 365 days of first admission. On univariate analysis, patients with atrial fibrillation (AF) and HF had significantly higher sST2 levels vs. those who did not. Increasing levels of sST2 by quartiles were significantly associated with AF, HF, older age, low hemoglobin, low eGFR, and high CRP levels. On multivariate analysis: high sST2 levels and diabetes remained as risk predictors of any MACE occurrence; an sST2 level in the highest quartile (Q4: >28.4 ng/mL) was independently associated with older age, use of beta-blockers, and number of MACE events within a 1 year period. In this patient cohort, elevated sST2 levels are associated with unplanned hospital admission due to MACE within 1 year, independent of the nature of the index cardiovascular admission.

Association of clinical, laboratory and imaging biomarkers with the occurrence of acute myocardial infarction in patients without standard modifiable risk factors - rationale and design of the "Beyond-SMuRFs Study"

BACKGROUND

Acute myocardial infarction (AMI) remains the leading cause of mortality worldwide. The majority of patients who suffer an AMI have a history of at least one of the standard modifiable risk factors (SMuRFs): smoking, hypertension, dyslipidemia, and diabetes mellitus. However, emerging scientific evidence recognizes a clinically significant and increasing proportion of patients presenting with AMI without any SMuRF (SMuRF-less patients). To date, there are no adequate data to define specific risk factors or biomarkers associated with the development of AMIs in these patients.

METHODS

The ''Beyond-SMuRFs Study'' is a prospective, non-interventional cohort trial designed to enroll patients with AMI and no previous coronary intervention history, who undergo coronary angiography in two academic hospitals in Thessaloniki, Greece. The rationale of the study is to investigate potential relations between SMuRF-less AMIs and the clinical, laboratory and imaging profile of patients, by comparing parameters between patients with and without SMuRFs. Complete demographic and comprehensive clinical data will be recorded, Venous blood samples will be collected before coronary angiography and the following parameters will be measured: total blood count, standard biochemistry parameters, coagulation tests, hormone levels, glycosylated hemoglobin, N- terminal pro-B-type natriuretic peptide and high-sensitivity troponin T levels- as well as serum levels of novel atherosclerosis indicators and pro-inflammatory biomarkers. Furthermore, all participants will undergo a complete and comprehensive transthoracic echocardiographic assessment according to a pre-specified protocol within 24 h from admission. Among others, 2D-speckle-tracking echocardiographic analysis of cardiac chambers and non-invasive calculation of myocardial work indices for the left ventricle will be performed. Moreover, all patients will be assessed for angiographic parameters and the complexity of coronary artery disease using the SYNTAX score. Multivariable linear and logistic regression models will be used to phenotypically characterize SMuRF-less patients and investigate independent clinical, laboratory, echocardiographic and angiographic biomarkers-predictors of SMuRF-less status in AMI.The first patient was enrolled in March 2022 and completion of enrollment is expected until December 2023.

DISCUSSION

The ''Beyond-SmuRFs'' study is an ongoing prospective trial aiming to investigate potential clinical, laboratory and imaging biomarkers associated with the occurrence of AMIs in SMuRF-less patients. The configuration of these patients' profiles could lead to the development of personalized risk-stratification models predicting the occurrence of cardiovascular events in SΜuRF-less individuals.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05535582 / September 10, 2022.

Higher mortality in acute coronary syndrome patients without standard modifiable risk factors: Results from a global meta-analysis of 1,285,722 patients

BACKGROUND

Standard modifiable cardiovascular risk factors (SMuRF), comprising diabetes, hyperlipidemia, hypertension, and smoking, are used for risk stratification in acute coronary syndrome (ACS). Recent studies showed an increasing proportion of SMuRF-less ACS patients.

METHODS

Embase, Medline and Pubmed were searched for studies comparing SMuRF-less and SMuRF patients with first presentation of ACS. We conducted single-arm analyses to determine the proportion of SMuRF-less patients in the ACS cohort, and compared the clinical presentation and outcomes of these patients.

RESULTS

Of 1,285,722 patients from 15 studies, 11.56% were SMuRF-less. A total of 7.44% of non-ST-segment-elevation ACS patients and 12.87% of ST-segment-elevation myocardial infarction (STEMI) patients were SMuRF-less. The proportion of SMuRF-less patients presenting with STEMI (60.71%) tended to be higher than those with SMuRFs (49.21%). Despite lower body mass index and fewer comorbidities such as chronic kidney disease, peripheral arterial disease, stroke and heart failure, SMuRF-less patients had increased in-hospital mortality (RR:1.57, 95%CI:1.38 to 1.80) and cardiogenic shock (RR:1.39, 95%CI:1.18 to 1.65), but lower risk of heart failure (RR:0.91, 95%CI:0.83 to 0.99). On discharge, SMuRF-less patients were prescribed less statins (RR:0.93, 95%CI:0.91 to 0.95), beta-blockers (RR:0.94, 95%CI:0.92 to 0.96), P2Y12 inhibitors (RR: 0.98, 95%CI: 0.96 to 0.99), and angiotensin-converting-enzyme inhibitor or angiotensin-receptor blocker (RR:0.92, 95%CI:0.75 to 0.91).

CONCLUSION

In this study level meta-analysis, SMuRF-less ACS patients demonstrate higher mortality compared with patients with at least one traditional atherosclerotic risk factor. Underuse of guideline-directed medical therapy amongst SMuRF-less patients is concerning. Unraveling novel risk factors amongst SMuRF-less individuals is the next important step.

SUMMARY

Standard modifiable cardiovascular risk factors (SMuRF), comprising diabetes mellitus, hyperlipidemia, hypertension, and smoking, are often used for risk stratification in acute coronary syndrome (ACS). Recent studies showed an increasing proportion of SMuRF-less ACS patients. Of 1,285,722 ACS patients, 11.56% were SMuRF-less. Despite lower body mass index and fewer comorbidities, SMuRF-less patients had increased in-hospital mortality and cardiogenic shock. However, despite worse outcomes, SMuRF-less patients were prescribed less guideline-directed medical therapies on discharge.

Machine learning-based integration develops biomarkers initial the crosstalk between inflammation and immune in acute myocardial infarction patients

Great strides have been made in past years toward revealing the pathogenesis of acute myocardial infarction (AMI). However, the prognosis did not meet satisfactory expectations. Considering the importance of early diagnosis in AMI, biomarkers with high sensitivity and accuracy are urgently needed. On the other hand, the prevalence of AMI worldwide has rapidly increased over the last few years, especially after the outbreak of COVID-19. Thus, in addition to the classical risk factors for AMI, such as overwork, agitation, overeating, cold irritation, constipation, smoking, and alcohol addiction, viral infections triggers have been considered. Immune cells play pivotal roles in the innate immunosurveillance of viral infections. So, immunotherapies might serve as a potential preventive or therapeutic approach, sparking new hope for patients with AMI. An era of artificial intelligence has led to the development of numerous machine learning algorithms. In this study, we integrated multiple machine learning algorithms for the identification of novel diagnostic biomarkers for AMI. Then, the possible association between critical genes and immune cell infiltration status was characterized for improving the diagnosis and treatment of AMI patients.

Identification of key proteins as potential biomarkers associated with post-infarction complications in diabetics

Background: The ability of transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction in diabetic patients remains unknown. The present study was designed to detect possible biomarkers associated with the incidence of post-infarction complications in diabetes to assist thedevelopment of novel treatments for this condition.Methods: Two gene expression datasets, GSE12639 and GSE6880, were downloaded from the Gene Expression Omnibus (GEO) database, and then differentially expressed genes (DEGs) were identified between post-infarction diabetics and healthy samples from the left ventricular wall of rats. These DEGs were then arranged into a protein-protein interaction (PPI) network, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were performed to explore the functional roles of these genes.Results: In total, 30 DEGs (14 upregulated and 16 downregulated) were shared between these two datasets, as identified through Venn diagram analyses. GO analyses revealed these DEGs to be significantly enriched in ovarian steroidogenesis, fatty acid elongation, biosynthesis of unsaturated fatty acids, synthesis and degradation of ketone bodies, and butanoate metabolism. The PPI network of the DEGs had 14 genes and 70 edges. We identified two key proteins, 3-hydroxymethylglutaryl-CoA synthase 2 (Hmgcs2) and Δ3, Δ2-Enoyl-CoA Delta Isomerase 1 (ECI1), and the upregulated gene Hmgcs2 with the highest score in the MCC method. We generated a co-expression network for the hub genes and obtained the top ten medications suggested for infarction with diabetes.Conclusion: Taken together, the findings of these bioinformatics analyses identified key hub genes associated with the development of myocardial infarction in diabetics. These hub genes and potential drugs may become novel biomarkers for prognosis and precision treatment in the future.

Evaluating the association between amino acid and acylcarnitine profiles and different levels of coronary artery disease risk in postmenopausal women using targeted metabolomics technique

OBJECTIVES

Postmenopausal women are at increased risk of developing coronary artery disease (CAD). Metabolomic approaches aim at discovering more helpful biomarkers of CAD to reduce the disease burden in the future. Here, we intend to find potential blood biomarkers, amino acids, and acylcarnitines in postmenopausal women with different severity of CAD by using high-throughput methods.

METHOD

This cross-sectional study was performed on postmenopausal women ( n = 183) who underwent coronary CT scans. Coronary artery calcium scoring (CACS) was assessed to detect plaque burden and degree of coronary artery obstruction. The participants were divided into three groups based on the score as follows (i) "low CACS" ( n = 96); a score of 0 to 10, (ii) "medium CACS" ( n = 35); a score between 11 and 100 and (iii) "high CACS" ( n = 52); a score greater than 100. Metabolites, including amino acids and acylcarnitines, were quantified using a targeted mass spectrometry method in serum samples. The association between metabolites and disease status was evaluated using univariate and multivariate regression analyses with adjustment for confounding factors. Factor analysis was used to deal with multiple comparisons.

RESULTS

Metabolites, including proline, glutamic acid, and phenylalanine, were significantly lower in the high CACS group than the low CACS one. Also, a lower level of lysine and phenylalanine in high CACS compared with medium one was observed. Concerning acylcarnitines, it was found that C4 and C8:1 significantly were higher in women with high CACS. The logistic regression analysis revealed that the circulating levels of these metabolites (except C4) were associated with the presence of coronary artery calcification independently of age, body mass index, and time of menopause. Also, the amino acids were associated independently of medication and diabetes.

CONCLUSIONS

The present study indicated that circulating levels of amino acids and acylcarnitines profile in postmenopausal women are partly associated with the severity of CAD in these participants.

Investigation of the multi-targeted protection potential of tannic acid against doxorubicin-induced kidney damage in rats

Doxorubicin (DOX) is an antitumor drug that is powerful but can cause worse outcomes, including nephrotoxicity, and therefore has limited clinical use. Therefore, it is necessary to identify safer agents that can minimize the damage caused by the drug without shifting the treatment performance, in addition to clarifying the underlying mechanisms of DOX-induced aberrant in vivo renal activation. In this study, we tested the prophylactic capacity and mechanisms of action of tannic acid (TA) against DOX-mediated kidney damage in rats and evaluated the nephrotoxic activity of DOX when used with TA. Rats were treated during the two weeks with cumulative (18 mg/kg with six different injections) DOX, daily TA (50 mg/kg), and the DOX + TA combination. Changes in major metabolites and components involved in antioxidant metabolism were evaluated in the kidney tissues of all animals. Further, the gene expression levels of regulatory factors that have critical importance in cell metabolism, inflammation, and apoptosis were investigated. Both biochemical and molecular examinations showed that TA improved DOX-induced dysregulations at both protein and gene levels in the kidneys. Increased lipid peroxidation and decreased glutathione levels were reversed. Consistent with oxidative stress marker metabolites, suppressed antioxidant enzyme activities and transcript levels of antioxidant system members were restored. Of note, combination treatment with TA could overcome doxorubicin-induced gene expressions markedly altered by DOX, suggesting that nephroprotection conferred by TA involved the remodeling of stress resistance, cell metabolism, inflammation, and apoptosis. Collectively, the present in vivo study suggests that TA could be used as a multitarget and effective agent for the mitigation of doxorubicin-induced nephrotoxicity without changing the therapeutic efficacy of the drug.

Angiographic severity in acute coronary syndrome patients with and without standard modifiable risk factors

Background

Routine coronary artery disease (CAD) secondary prevention strategies target standard modifiable cardiovascular risk factors (SMuRFs), which include: diabetes mellitus, dyslipidemia, hypertension, and smoking. However, a significant proportion of patients with acute coronary syndrome (ACS) present without any SMuRFs. The angiographic severity of disease in this population has not yet been investigated.

Methods

After propensity score matching of patients without SMuRFs and patients with ≥1 SMuRFs (ratio 1:3), we used zero-inflated negative binomial regression modeling to investigate the relationship of SMuRF-less status with the angiographic severity of CAD, as measured by the SYNTAX score. Survival analysis was performed to investigate differences in all-cause mortality at 30 days and at the end of follow-up period.

Results

We analyzed 534 patients presenting with ACS who underwent coronary angiography. Of them, 56 (10.5%) presented without any SMuRF. After propensity score matching, the median SYNTAX score was 13.8 (IQR 0–22.1) in 56 SMuRF-less patients and 14 (IQR 5–25) in 166 patients with ≥1 SMuRFs. SMuRF-less status was associated with increased odds of zero SYNTAX score [zero-part model: odds ratio = 2.11, 95% confidence interval (CI): 1.03–4.33], but not with decreased SYNTAX score among patients with non-zero SYNTAX score (count-part model: incidence rate ratio = 0.99, 95% CI: 0.79–1.24); the overall distribution of the SYNTAX score was similar between the two groups (p = 0.26). The 30-day risk for all-cause mortality was higher for SMuRF-less patients compared to patients with ≥1 SMuRFs [hazard ratio (HR) = 3.58, 95% CI: 1.30–9.88]; however, the all-cause mortality risk was not different between the two groups over a median 1.7-year follow-up (HR = 1.72, 95% CI: 0.83–3.57).

Conclusion

Among patients with ACS, the absence of SMuRFs is associated with increased odds for non-obstructive CAD and with increased short-term mortality rates.

Mortality and Cardiovascular Outcomes in Patients Presenting With Non-ST Elevation Myocardial Infarction Despite No Standard Modifiable Risk Factors: Results From the SWEDEHEART Registry

Background A significant proportion of patients with ST-segment-elevation myocardial infarction (MI) have no standard modifiable cardiovascular risk factors (SMuRFs) and have unexpected worse 30-day outcomes compared with those with SMuRFs. The aim of this article is to examine outcomes of patients with non-ST-segment-elevation MI in the absence of SMuRFs. Methods and Results Presenting features, management, and outcomes of patients with non-ST-segment-elevation MI without SmuRFs (hypertension, diabetes, hypercholesterolemia, smoking) were compared with those with SmuRFs in the Swedish MI registry SWEDEHEART (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies; 2005-2018). Cox proportional hazard models were used. Out of 99 718 patients with non-ST-segment-elevation MI, 11 131 (11.2%) had no SMuRFs. Patients without SMuRFs had higher all-cause and cardiovascular mortality at 30 days (hazard ratio [HR], 1.20 [95% CI, 1.10-1.30], P<0.0001; and HR, 1.25 [95% CI, 1.13-1.38]), a difference that remained after adjustment for age and sex. SMuRF-less patients were less likely to receive secondary prevention statins (76% versus 82%); angiotensin-converting enzyme inhibitors/angiotensin receptor blockade (54% versus 72%); or β-blockers (81% versus 87%, P for all <0.0001), with lowest rates observed in women without SMuRFs. In patients who survived to 30 days, rates of all-cause and cardiovascular death were lower in patients without SMuRFs compared with those with risk factors, over 12 years. Conclusions One in 10 patients presenting with non-ST-segment-elevation MI present without traditional risk factors. The excess 30-day mortality rate in this group emphasizes the need for both improved population-based strategies for prevention of MI, as well as the need for equitable evidence-based treatment at the time of an MI.

Human Plasma Transcriptome Implicates Dysregulated S100A12 Expression: A Strong, Early-Stage Prognostic Factor in ST-Segment Elevated Myocardial Infarction: Bioinformatics Analysis and Experimental Verification

The ability of blood transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction remains unknown. Two gene expression datasets (GSE60993 and GSE61144) were downloaded from Gene Expression Omnibus (GEO) Datasets to identify altered plasma transcriptomes in patients with ST-segment elevated myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. GEO2R, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotations, protein–protein interaction analysis, etc., were adopted to determine functional roles and regulatory networks of differentially expressed genes (DEGs). Dysregulated expressomes were verified at transcriptional and translational levels by analyzing the GSE49925 dataset and our own samples, respectively. A total of 91 DEGs were identified in the discovery phase, consisting of 15 downregulated genes and 76 upregulated genes. Two hub modules consisting of 12 hub genes were identified. In the verification phase, six of the 12 hub genes exhibited the same variation patterns at the transcriptional level in the GSE49925 dataset. Among them, S100A12 was shown to have the best discriminative performance for predicting in-hospital mortality and to be the only independent predictor of death during follow-up. Validation of 223 samples from our center showed that S100A12 protein level in plasma was significantly lower among patients who survived to discharge, but it was not an independent predictor of survival to discharge or recurrent major adverse cardiovascular events after discharge. In conclusion, the dysregulated expression of plasma S100A12 at the transcriptional level is a robust early prognostic factor in patients with STEMI, while the discrimination power of the protein level in plasma needs to be further verified by large-scale, prospective, international, multicenter studies.

Antibody response to oral biofilm is a biomarker for acute coronary syndrome in periodontal disease

Cumulative evidence over the last decades have supported the role of gum infections as a risk for future major cardiovascular events. The precise mechanism connecting coronary artery disease (CAD) with periodontal findings has remained elusive. Here, we employ next generation phage display mimotope-variation analysis (MVA) to identify the features of dysfunctional immune system that associate CAD with periodontitis. We identify a fine molecular description of the antigenic epitope repertoires of CAD and its most severe form - acute coronary syndrome (ACS) by profiling the antibody reactivity in a patient cohort with invasive heart examination and complete clinical oral assessment. Specifically, we identify a strong immune response to an EBV VP26 epitope mimicking multiple antigens of oral biofilm as a biomarker for the no-CAD group. With a 2-step biomarker test, we stratify subjects with periodontitis from healthy controls (balanced accuracy 84%), and then assess the risk for ACS with sensitivity 71-89% and specificity 67-100%, depending on the oral health status. Our findings highlight the importance of resolving the immune mechanisms related to severe heart conditions such as ACS in the background of oral health. Prospective validation of these findings will support incorporation of these non-invasive biomarkers into clinical practice.

Patient Endothelial Colony-Forming Cells to Model Coronary Artery Disease Susceptibility and Unravel the Role of Dysregulated Mitochondrial Redox Signalling

Mechanisms involved in the individual susceptibility to atherosclerotic coronary artery disease (CAD) beyond traditional risk factors are poorly understood. Here, we describe the utility of cultured patient-derived endothelial colony-forming cells (ECFCs) in examining novel mechanisms of CAD susceptibility, particularly the role of dysregulated redox signalling. ECFCs were selectively cultured from peripheral blood mononuclear cells from 828 patients from the BioHEART-CT cohort, each with corresponding demographic, clinical and CT coronary angiographic imaging data. Spontaneous growth occurred in 178 (21.5%) patients and was more common in patients with hypertension (OR 1.45 (95% CI 1.03-2.02), p = 0.031), and less likely in patients with obesity (OR 0.62 [95% CI 0.40-0.95], p = 0.027) or obstructive CAD (stenosis > 50%) (OR 0.60 [95% CI 0.38-0.95], p = 0.027). ECFCs from patients with CAD had higher mitochondrial production of superoxide (O₂^--MitoSOX assay). The latter was strongly correlated with the severity of CAD as measured by either coronary artery calcium score (R² = 0.46; p = 0.0051) or Gensini Score (R² = 0.67; p = 0.0002). Patient-derived ECFCs were successfully cultured in 3D culture pulsatile mini-vessels. Patient-derived ECFCs can provide a novel resource for discovering mechanisms of CAD disease susceptibility, particularly in relation to mitochondrial redox signalling.

Classifiers for Predicting Coronary Artery Disease Based on Gene Expression Profiles in Peripheral Blood Mononuclear Cells

Objective

Coronary artery disease (CAD) is a serious global health concern. Current diagnostic methods for CAD involve risk to the patient and are costly, so better diagnostic tools are needed. We defined four classifiers based on gene expression profiles in peripheral blood mononuclear cells and determined their potential for CAD detection.

Methods

We downloaded a CAD-related data set (GSE113079) from the Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in peripheral blood mononuclear cells between CAD samples and healthy controls. DEGs were analyzed for functional enrichment. To create a robust CAD classifier, DEGs were identified by feature selection using the principal component analysis. Then, least absolute shrinkage and selection operator (LASSO) logistic regression, random forest, and support vector machine (SVM) models were created. Gene set variation analysis (GSVA) score and gene set enrichment analysis (GSEA) were also conducted. The performance of the models was evaluated in terms of the area under receiver operating characteristic curves (AUC).

Results

In the training set, we found 135 up-regulated genes and 104 down-regulated genes in CAD patients compared with controls. The DEGs were involved in some pathways associated with CAD, such as pathways involving calcium and interleukin-17 signaling. Twenty genes were identified as optimal features and used to generate the logistic classifier based on LASSO. The AUC for the classifier was 1.00 in the training set and 0.997 in the test set. Using the 20 DEGs, SVM and random forest classifiers were also generated and showed high diagnostic efficacy, with respective AUCs of 0.997 and 1.00 against the training set. A GSVA score was also established using the top 20 significant DEGs, which showed an AUC of 0.971 in the training set and 0.989 in the test set. Furthermore, GSEA showed autophagy and the proteasome to be major pathways involving the DEGs.

Conclusion

We identified a set of genes specific for CAD whose expression can be measured non-invasively. Using these genes, we defined four diagnostic classifiers using multiple methods.

Examining the Potential for Coronary Artery Calcium (CAC) Scoring for Individuals at Low Cardiovascular Risk

Atherosclerosis is the commonest cause of death in Australia. Cardiovascular (CV) risk calculators have an important role in preventative cardiology, although they are are strongly age-dependent and designed to identify individuals at high risk of an imminent event. The imprecision around "intermediate" or "low" risk generates therapeutic uncertainty, and a significant proportion of patients presenting with myocardial infarction come from these groups, often with no warning. This highlights a conundrum: "Low" risk does not mean "no" risk. A fresh approach may be required to address the clinical conundrum around CV preventative approaches in non-high-risk individuals. While probabilistic calculators do not measure atherosclerosis, calculation of Coronary Artery Calcium (CAC) scores by low-dose computed tomography (CT) can provide a snapshot of atherosclerotic burden. In intermediate-risk individuals, CAC is well-established as an aid to CV risk prediction. Although CAC scoring in low-risk asymptomatic people may be considered controversial, CAC has emerged as the single best predictor of CV events in asymptomatic individuals, independent of traditional risk factor calculators. Therefore, apart from the contribution of age and sex, the somewhat arbitrary distinction between "intermediate" and "low" CV risk using probabilistic calculators may need to be reconsidered. A zero CAC score has a very low future event rate and non-zero CAC scores are associated with a progressive, graded increase in risk as the CAC score rises. In this review, we examine the evidence for CAC screening in low-risk individuals, and propose more widespread use of CAC using simple new model intended to enhance established CV risk prediction equations.

A Call to Action for New Global Approaches to Cardiovascular Disease Drug Solutions

While we continue to wrestle with the immense challenge of implementing equitable access to established evidence-based treatments, substantial gaps remain in our pharmacotherapy armament for common forms of cardiovascular disease including coronary and peripheral arterial disease, heart failure, hypertension, and arrhythmia. We need to continue to invest in the development of new approaches for the discovery, rigorous assessment, and implementation of new therapies. Currently, the time and cost to progress from lead compound/product identification to the clinic, and the success rate in getting there reduces the incentive for industry to invest, despite the enormous burden of disease and potential size of market. There are tremendous opportunities with improved phenotyping of patients currently batched together in syndromic "buckets." Use of advanced imaging and molecular markers may allow stratification of patients in a manner more aligned to biological mechanisms that can, in turn, be targeted by specific approaches developed using high-throughput molecular technologies. Unbiased "omic" approaches enhance the possibility of discovering completely new mechanisms in such groups. Furthermore, advances in drug discovery platforms, and models to study efficacy and toxicity more relevant to the human disease, are valuable. Re-imagining the relationships among discovery, translation, evaluation, and implementation will help reverse the trend away from investment in the cardiovascular space, establishing innovative platforms and approaches across the full spectrum of therapeutic development.

Identification of Cysteine Protease Inhibitor CST2 as a Potential Biomarker for Colorectal Cancer

Additional biomarkers for the development and progression of colorectal cancer (CRC) remain to be identified. Hence, the current study aimed to identify potential diagnostic markers for CRC. Analyses of cysteine protease inhibitor [cystatins (CSTs)] expression in CRC samples and its correlation with cancer stage or survival in patients with CRC demonstrated that CRC tissues had greater CST1 and CST2 mRNA expression compared to noncancerous adjacent tissues, while higher CST2 mRNA expression in CRC tissues was correlated with advanced stages and disease-free survival in patients with CRC, encouraging further exploration on the role of CST2 in CRC. Through an online database search and tissue microarray (TMA), we confirmed that CRC samples had higher CST2 expression compared to noncancerous adjacent tissue or normal colorectal tissues at both the mRNA and protein levels. TMA also revealed that colorectal adenoma, CRC, and metastatic CRC tissues exhibited a significantly increased CST2 protein expression. Accordingly, survival analysis demonstrated that the increase in CST2 protein expression was correlated with shorter overall survival of patients with CRC. Moreover, our results found a significant upregulation of CST2 in multiple cancer tissues. Taken together, these findings suggest the potential role of CST2 as a diagnostic and prognostic biomarker for CRC.

Bench-to-Bedside in Vascular Medicine: Optimizing the Translational Pipeline for Patients With Peripheral Artery Disease

Peripheral arterial disease is a growing worldwide problem with a wide spectrum of clinical severity and is projected to consume >$21 billion per year in the United States alone. While vascular researchers have brought several therapies to the clinic in recent years, few of these approaches have leveraged advances in high-throughput discovery screens, novel translational models, or innovative trial designs. In the following review, we discuss recent advances in unbiased genomics and broader omics technology platforms, along with preclinical vascular models designed to enhance our understanding of disease pathobiology and prioritize targets for additional investigation. Furthermore, we summarize novel approaches to clinical studies in subjects with claudication and ischemic ulceration, with an emphasis on streamlining and accelerating bench-to-bedside translation. By providing a framework designed to enhance each aspect of future clinical development programs, we hope to enrich the pipeline of therapies that may prevent loss of life and limb for those with peripheral arterial disease.

A Versatile Big Data Health System for Australia: Driving Improvements in Cardiovascular Health

Cardiovascular diseases (CVD) are leading causes of death and morbidity in Australia and worldwide. Despite improvements in treatment, there remain large gaps in our understanding to prevent, treat and manage CVD events and associated morbidities. This article lays out a vision for enhancing CVD research in Australia through the development of a Big Data system, bringing together the multitude of rich administrative and health datasets available. The article describes the different types of Big Data available for CVD research in Australia and presents an overview of the potential benefits of a Big Data system for CVD research and some of the major challenges in establishing the system for Australia. The steps for progressing this vision are outlined.

Coronary artery disease burden in women poorly explained by traditional risk factors: Sex disaggregated analyses from the BioHEART-CT study

BACKGROUND AND AIMS

Targeting the modifiable risk factors for coronary artery disease (CAD) has substantial impact at the community level. However, it is not uncommon for individuals to present with atherosclerosis related events without identified risk factors. We examined sex differences in the association of risk factors and atherosclerotic burden assessed by CT coronary angiography (CTCA).

METHODS

We analysed clinical and imaging data in 1002 individuals in the BioHEART cohort.

RESULTS

45% were female, 35% had no CAD identified. Median coronary calcium score was 9.9 Agatston units (IQR: 0-146), and median Gensini Score was 3.5 (IQR: 0-11.5). 26% had a calcified plaque predominant phenotype, and 18% had a non-calcified plaque predominant phenotype. There were no sex differences in the prevalence of risk factors. However, there were notable sex differences in the adjusted associations of risk factors with CAD. Age and hypercholesterolaemia (OR 1.56, 95% CI 1.03-2.36, p = 0.04 in males, and OR 1.75, 95% CI 1.09-2.78, p = 0.02 in females) were associated with the presence of CAD in both genders (p < 0.05). Diabetes and smoking were associated with presence of CAD, calcified CAD, and non-calcified plaque in males (p < 0.05) but not females. In women, none of the standard modifiable risk factors were associated with the amount of plaque present when adjusted for age, BMI, and family history of premature CAD.

CONCLUSIONS

CTCA provides an important opportunity for improving the stratification of cohorts to assess underlying biology and risk. We demonstrate sex-specific differences in associations of risk factors with atherosclerosis burden.

Metabolic Signatures in Coronary Artery Disease: Results from the BioHEART-CT Study

Despite effective prevention programs targeting cardiovascular risk factors, coronary artery disease (CAD) remains the leading cause of death. Novel biomarkers are needed for improved risk stratification and primary prevention. To assess for independent associations between plasma metabolites and specific CAD plaque phenotypes we performed liquid chromatography mass-spectrometry on plasma from 1002 patients in the BioHEART-CT study. Four metabolites were examined as candidate biomarkers. Dimethylguanidino valerate (DMGV) was associated with presence and amount of CAD (OR) 1.41 (95% Confidence Interval [CI] 1.12-1.79, p = 0.004), calcified plaque, and obstructive CAD (p < 0.05 for both). The association with amount of plaque remained after adjustment for traditional risk factors, ß-coefficient 0.17 (95% CI 0.02-0.32, p = 0.026). Glutamate was associated with the presence of non-calcified plaque, OR 1.48 (95% CI 1.09-2.01, p = 0.011). Phenylalanine was associated with amount of CAD, ß-coefficient 0.33 (95% CI 0.04-0.62, p = 0.025), amount of calcified plaque, (ß-coefficient 0.88, 95% CI 0.23-1.53, p = 0.008), and obstructive CAD, OR 1.84 (95% CI 1.01-3.31, p = 0.046). Trimethylamine N-oxide was negatively associated non-calcified plaque OR 0.72 (95% CI 0.53-0.97, p = 0.029) and the association remained when adjusted for traditional risk factors. In targeted metabolomic analyses including 53 known metabolites and controlling for a 5% false discovery rate, DMGV was strongly associated with the presence of calcified plaque, OR 1.59 (95% CI 1.26-2.01, p = 0.006), obstructive CAD, OR 2.33 (95% CI 1.59-3.43, p = 0.0009), and amount of CAD, ß-coefficient 0.3 (95% CI 0.14-0.45, p = 0.014). In multivariate analyses the lipid and nucleotide metabolic pathways were both associated with the presence of CAD, after adjustment for traditional risk factors. We report novel associations between CAD plaque phenotypes and four metabolites previously associated with CAD. We also identified two metabolic pathways strongly associated with CAD, independent of traditional risk factors. These pathways warrant further investigation at both a biomarker and mechanistic level.

A call to action for new global approaches to cardiovascular disease drug solutions

Whilst we continue to wrestle with the immense challenge of implementing equitable access to established evidence-based treatments, substantial gaps remain in our pharmacotherapy armament for common forms of cardiovascular disease including coronary and peripheral arterial disease, heart failure, hypertension, and arrhythmia. We need to continue to invest in the development of new approaches for the discovery, rigorous assessment, and implementation of new therapies. Currently, the time and cost to progress from lead compound/product identification to the clinic, and the success rate in getting there reduces the incentive for industry to invest, despite the enormous burden of disease and potential size of market. There are tremendous opportunities with improved phenotyping of patients currently batched together in syndromic 'buckets'. Use of advanced imaging and molecular markers may allow stratification of patients in a manner more aligned to biological mechanisms that can, in turn, be targeted by specific approaches developed using high-throughput molecular technologies. Unbiased 'omic' approaches enhance the possibility of discovering completely new mechanisms in such groups. Furthermore, advances in drug discovery platforms, and models to study efficacy and toxicity more relevant to the human disease, are valuable. Re-imagining the relationships among discovery, translation, evaluation, and implementation will help reverse the trend away from investment in the cardiovascular space, establishing innovative platforms and approaches across the full spectrum of therapeutic development.

Mortality in STEMI patients without standard modifiable risk factors: a sex-disaggregated analysis of SWEDEHEART registry data

BACKGROUND

In cardiovascular disease, prevention strategies targeting standard modifiable cardiovascular risk factors (SMuRFs; hypertension, diabetes, hypercholesterolaemia, and smoking) are crucial; however, myocardial infarction in the absence of SMuRFs is not infrequent. The outcomes of individuals without SMuRFs are not well known.

METHODS

We retrospectively analysed adult patients with first-presentation ST-elevation myocardial infarction (STEMI) using data from the Swedish myocardial infarction registry SWEDEHEART. Clinical characteristics and outcomes of adult patients (age ≥18 years) with and without SMuRFs were examined overall and by sex. Patients with a known history of coronary artery disease were excluded. The primary outcome was all-cause mortality at 30 days after STEMI presentation. Secondary outcomes included cardiovascular mortality, heart failure, and myocardial infarction at30 days. Endpoints were also examined up to discharge, and to the end of a 12-year follow-up. Multivariable logistic regression models were used to compare in-hospital mortality, and Cox-proportional hazard models and Kaplan-Meier analysis for long-term outcomes.

FINDINGS

Between Jan 1, 2005, and May 25, 2018, 9228 (14·9%) of 62 048 patients with STEMI had no SMuRFs reaching diagnostic thresholds. Median age was similar between patients with SMuRFs and patients without SMuRFs (68 years [IQR 59-78]) vs 69 years [60-78], p<0·0001). SMuRF-less patients had a similar rate of percutaneous coronary intervention to those with at least one modifiable risk factor, but were significantly less likely to receive statins, angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockade (ARB), or β-blockers at discharge. By 30 days after presentation, all-cause mortality was significantly higher in SMuRF-less patients (hazard ratio 1·47 [95% CI 1·37-1·57], p<0·0001). SMuRF-less women had the highest 30-day mortality (381 [17·6%] of 2164), followed by women with SMuRFs (2032 [11·1%] of 18 220), SMuRF-less men (660 [9·3%] of 7064), and men with SMuRFs (2117 [6·1%] of 34 600). The increased risk of 30-day all-cause mortality in SMuRF-less patients remained significant after adjusting for age, sex, left ventricular ejection fraction, creatinine, and blood pressure, but was attenuated on inclusion of pharmacotherapy prescription (ACEI or ARB, β-blocker, or statin) at discharge. Additionally, SMuRF-less patients had a significantly higher rate of in-hospital all-cause mortality than patients with one or more SMuRF (883 [9·6%] vs 3411 [6·5%], p<0·0001). Myocardial infarction and heart failure at 30 days were lower in SMuRF-less patients. All-cause mortality remained increased in the SMuRF-less group for more than 8 years in men and up to the 12-year endpoint in women.

INTERPRETATION

Individuals who present with STEMI in the absence of SMuRFs have a significantly increased risk of all-cause mortality, compared with those with at least one SMuRF, which was particularly evident in women. The increased early mortality rates are attenuated after adjustment for use of guideline-indicated treatments, highlighting the need for evidence-based pharmacotherapy during the immediate post-infarct period irrespective of perceived low risk.

FUNDING

Swedish Heart and Lung Foundation, National Health and Medical Research Council (Australia).

Analysis of genes and underlying mechanisms involved in foam cells formation and atherosclerosis development

Background

Foam cells (FCs) play crucial roles in the process of all stages of atherosclerosis. Smooth muscle cells (SMCs) and macrophages are the major sources of FCs. This study aimed to identify the common molecular mechanism in these two types of FCs.

Methods

GSE28829, GSE43292, GSE68021, and GSE54666 were included to identify the differentially expressed genes (DEGs) associated with FCs derived from SMCs and macrophages. Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by using the DAVID database. The co-regulated genes associated with the two origins of FCs were validated (GSE9874), and their expression in vulnerable atherosclerosis plaques (GSE120521 and GSE41571) was assessed.

Results

A total of 432 genes associated with FCs derived from SMCs (SMC-FCs) and 81 genes associated with FCs derived from macrophages (M-FCs) were identified, and they were mainly involved in lipid metabolism, inflammation, cell cycle/apoptosis. Furthermore, three co-regulated genes associated with FCs were identified: GLRX, RNF13, and ABCA1. These three common genes showed an increased tendency in unstable or ruptured plaques, although in some cases, no statistically significant difference was found.

Conclusions

DEGs related to FCs derived from SMCs and macrophages have contributed to the understanding of the molecular mechanism underlying the formation of FCs and atherosclerosis. GLRX, RNF13, and ABCA1 might be potential targets for atherosclerosis treatment.

Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis

Background

Familial hypercholesterolemia (FH) is one of the commonest inherited metabolic disorders. Abnormally high level of low-density lipoprotein cholesterol (LDL-C) in blood leads to premature atherosclerosis onset and a high risk of cardiovascular disease (CVD). However, the specific mechanisms of the progression process are still unclear. Our study aimed to investigate the potential differently expressed genes (DEGs) and mechanism of FH using various bioinformatic tools.

Methods

GSE13985 and GSE6054 were downloaded from the Gene Expression Omnibus (GEO) database for bioinformatic analysis in this study. First, limma package of R was used to identify DEGs between blood samples of patients with FH and those from healthy individuals. Then, the functional annotation of DEGs was carried out by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Ontology (GO) analysis. Based on Search Tool for the Retrieval of Interacting Genes (STRING) tool, we constructed the Protein-Protein Interactions (PPIs) network among DEGs and mined the core genes as well.

Results

A total of 102 communal DEGs (49 up-regulated and 53 down-regulated) are identified in FH samples compared with control samples. The functional changes of DEGs are mainly associated with the focal adhere and glucagon signaling pathway. Ten genes (ITGAL, TLN1, POLR2A, CD69, GZMA, VASP, HNRNPUL1, SF1, SRRM2, ITGAV) were identified as core genes. Bioinformatic analysis showed that the core genes are mainly enriched in numerous processes related to cell adhesion, integrin-mediated signaling pathway and cell-matrix adhesion. In the transcription factor (TF) target regulating network, 219 nodes were detected, including 214 DEGs and 5 TFs (SP1, EGR3, CREB, SEF1, HOX13). In conclusion, the DEGs and hub genes identified in this study may help us understand the potential etiology of the occurrence and development of AS.

Conclusion

Up-regulated ITGAL, TLN1, POLR2A, VASP, HNRNPUL1, SF1, SRRM2, and down-regulated CD69, GZMA and ITGAV performed important promotional effects for the formation of atherosclerotic plaques those suffering from FH. Moreover, SP1, EGR3, CREB, SEF1 and HOX13 were the potential transcription factors for DEGs and could serve as underlying targets for AS rupture prevention. These findings provide a theoretical basis for us to understand the potential etiology of the occurrence and development of AS in FH patients and we may be able to find potential diagnostic and therapeutic targets.

Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine

Artificial Intelligence (AI) is a broad term that combines computation with sophisticated mathematical models and in turn allows the development of complex algorithms which are capable to simulate human intelligence such as problem solving and learning. It is devised to promote a significant paradigm shift in the most diverse areas of medical knowledge. On the other hand, Cardiology is a vast field dealing with diseases relating to the heart, the circulatory system, and includes coronary heart disease, cerebrovascular disease, rheumatic heart disease and other conditions. AI has emerged as a promising tool in cardiovascular medicine which is aimed in augmenting the effectiveness of the cardiologist and to extend better quality to patients. It has the ability to support decision‑making and improve diagnostic and prognostic performance. Attempt has also been made to explore novel genotypes and phenotypes in existing cardiovascular diseases, improve the quality of patient care, to enablecost-effectiveness with reducereadmissionand mortality rates. Our review addresses the integration of AI and laboratory medicine as an accelerator of personalization care associated with the precision and the need of value creation services in cardiovascular medicine.

ST-Segment-Elevation Myocardial Infarction (STEMI) Patients Without Standard Modifiable Cardiovascular Risk Factors-How Common Are They, and What Are Their Outcomes?

Background

Programs targeting the standard modifiable cardiovascular risk factors (SMuRFs: hypertension, diabetes mellitus, hypercholesterolemia, smoking) are critical to tackling coronary heart disease at a community level. However, myocardial infarction in SMuRF‐less individuals is not uncommon. This study uses 2 sequential large, multicenter registries to examine the proportion and outcomes of SMuRF‐less ST‐segment–elevation myocardial infarction (STEMI) patients.

Methods and Results

We identified 3081 STEMI patients without a prior history of cardiovascular disease in the Australian GRACE (Global Registry of Acute Coronary Events) and CONCORDANCE (Cooperative National Registry of Acute Coronary Syndrome Care) registries, encompassing 42 hospitals, between 1999 and 2017. We examined the proportion that were SMuRF‐less as well as outcomes. The primary outcome was in‐hospital mortality, and the secondary outcome was major adverse cardiovascular events (death, myocardial infarction, or heart failure, during the index admission). Multivariate regression models were used to identify predictors of major adverse cardiovascular events. Of STEMI patients without a prior history of cardiovascular disease 19% also had no history of SMuRFs. This proportion increased from 14% to 23% during the study period (P=0.0067). SMuRF‐less individuals had a higher in‐hospital mortality rate than individuals with 1 or more SMuRFs. There were no clinically significant differences in major adverse cardiovascular events at 6 months between the 2 groups.

Conclusions

A substantial and increasing proportion of STEMI presentations occur independently of SMuRFs. Discovery of new markers and mechanisms of disease beyond standard risk factors may facilitate novel preventative strategies. Studies to assess longer‐term outcomes of SMuRF‐less STEMI patients are warranted.

Biobanking for discovery of novel cardiovascular biomarkers using imaging-quantified disease burden: protocol for the longitudinal, prospective, BioHEART-CT cohort study

INTRODUCTION

Coronary artery disease (CAD) persists as a major cause of morbidity and mortality worldwide despite intensive identification and treatment of traditional risk factors. Data emerging over the past decade show a quarter of patients have disease in the absence of any known risk factor, and half have only one risk factor. Improvements in quantification and characterisation of coronary atherosclerosis by CT coronary angiography (CTCA) can provide quantitative measures of subclinical atherosclerosis-enhancing the power of unbiased 'omics' studies to unravel the missing biology of personal susceptibility, identify new biomarkers for early diagnosis and to suggest new targeted therapeutics.

METHODS AND ANALYSIS

BioHEART-CT is a longitudinal, prospective cohort study, aiming to recruit 5000 adult patients undergoing clinically indicated CTCA. After informed consent, patient data, blood samples and CTCA imaging data are recorded. Follow-up for all patients is conducted 1 month after recruitment, and then annually for the life of the study. CTCA data provide volumetric quantification of total calcified and non-calcified plaque, which will be assessed using established and novel scoring systems. Comprehensive molecular phenotyping will be performed using state-of-the-art genomics, metabolomics, proteomics and immunophenotyping. Complex network and machine learning approaches will be applied to biological and clinical datasets to identify novel pathophysiological pathways and to prioritise new biomarkers. Discovery analysis will be performed in the first 1000 patients of BioHEART-CT, with validation analysis in the following 4000 patients. Outcome data will be used to build improved risk models for CAD.

ETHICS AND DISSEMINATION

The study protocol has been approved by the human research ethics committee of North Shore Local Health District in Sydney, Australia. All findings will be published in peer-reviewed journals or at scientific conferences.

TRIAL REGISTRATION NUMBER

ACTRN12618001322224.

Systems biology identifies cytosolic PLA2 as a target in vascular calcification treatment

Although cardiovascular disease (CVD) is the leading cause of morbimortality worldwide, promising new drug candidates are lacking. We compared the arterial high-resolution proteome of patients with advanced versus early-stage CVD to predict, from a library of small bioactive molecules, drug candidates able to reverse this disease signature. Of the approximately 4000 identified proteins, 100 proteins were upregulated and 52 were downregulated in advanced-stage CVD. Arachidonyl trifluoromethyl ketone (AACOCF3), a cytosolic phospholipase A2 (cPLA2) inhibitor was predicted as the top drug able to reverse the advanced-stage CVD signature. Vascular cPLA2 expression was increased in patients with advanced-stage CVD. Treatment with AACOCF3 significantly reduced vascular calcification in a cholecalciferol-overload mouse model and inhibited osteoinductive signaling in vivo and in vitro in human aortic smooth muscle cells. In conclusion, using a systems biology approach, we have identified a potentially new compound that prevented typical vascular calcification in CVD in vivo. Apart from the clear effect of this approach in CVD, such strategy should also be able to generate novel drug candidates in other complex diseases.