Increased serum bile acid level is associated with high-risk coronary artery plaques in an asymptomatic population detected by coronary computed tomography angiography

Indoleacetylglutamine Pathway Is a Potential Biomarker for Cardiovascular Diseases

Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality. Metabolomics allows for the identification of important biomarkers for CVDs, essential for early detection and risk assessment. This cross-sectional study aimed to identify novel metabolic biomarkers associated with CVDs using non-targeted metabolomics. We compared the metabolic profiles of 112 patients with confirmed CVDs diagnosis and 112 gender- and age-matched healthy controls from the Qatar Biobank database. Orthogonal partial least square discriminate analysis and linear models were used to analyze differences in the level of metabolites between the two groups. We report here a significant association between the indoleacetylglutamine pathway and cardiovascular diseases, expanding the repertoire of gut microbiota metabolites linked to CVDs. Our findings suggest that alterations in gut microbiota metabolism, potentially resulting in increased production of indoleacetate, indoleacetylglutamine, and related compounds at the expense of the cardioprotective indolepropionate, may contribute to this association. Our findings may pave the way for novel approaches in CVD risk assessment and potential therapeutic interventions targeting the gut-heart axis.

Advanced Machine Learning to Predict Coronary Artery Disease Severity in Patients with Premature Myocardial Infarction

Background

Studies using machine learning to identify the target characteristics and develop predictive models for coronary artery disease severity in patients with premature myocardial infarction (PMI) are limited.

Methods

In this observational study, 1111 PMI patients (≤55 years) at Tianjin Chest Hospital from 2017 to 2022 were selected and divided according to their SYNTAX scores into a low-risk group (≤22) and medium-high-risk group (>22). These groups were further randomly assigned to a training or test set in a ratio of 7:3. Lasso-logistic was initially used to screen out target factors. Subsequently, Lasso-logistic, random forest (RF), k-nearest neighbor (KNN), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost) were used to establish prediction models based on the training set. After comparing prediction performance, the best model was chosen to build a prediction system for coronary artery severity in PMI patients.

Results

Glycosylated hemoglobin (HbA1c), angina, apolipoprotein B (ApoB), total bile acid (TBA), B-type natriuretic peptide (BNP), D-dimer, and fibrinogen (Fg) were associated with the severity of lesions. In the test set, the area under the curve (AUC) of Lasso-logistic, RF, KNN, SVM, and XGBoost were 0.792, 0.775, 0.739, 0.656, and 0.800, respectively. XGBoost showed the best prediction performance according to the AUC, accuracy, F1 score, and Brier score. In addition, we used decision curve analysis (DCA) to assess the clinical validity of the XGBoost prediction model. Finally, an online calculator based on the XGBoost was established to measure the severity of coronary artery lesions in PMI patients.

Conclusions

In summary, we established a novel and convenient prediction system for the severity of lesions in PMI patients. This system can swiftly identify PMI patients who also have severe coronary artery lesions before the coronary intervention, thus offering valuable guidance for clinical decision-making.

Untargeted metabolomics reveals biomarkers for the diagnosis of coronary artery plaques as observed by coronary cardiac computed tomography

Atherosclerosis is a major cause of morbidity and mortality worldwide; in Israel, ischemic heart disease is the second leading cause of death for both genders aged 45 and above. Atherosclerosis involves stiffening of the arteries due to the accumulation of lipids and oxidized lipids on the blood vessel walls, triggering the development of artery plaque. Coronary artery disease (CAD) is the most common manifestation of atherosclerosis. The prevalence of CAD in the general population remains high, despite efforts to improve the identification of risk factors and preventive treatments. The discovery of new biomarkers is vital to improving the diagnosis of CAD and its risk factors. We aimed to identify novel biomarkers that could provide an early diagnosis of coronary artery atherosclerotic plaques, their type, and the percentage of stenosis. We used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive and specific CAD detection. The study consisted of 109 patients who underwent cardiac computed tomography angiography at the Cardiology Department of Ziv Medical Center. Fifty-four patients were diagnosed with coronary atherosclerotic plaques (CAD group), and 55 without plaques used control. Untargeted metabolomics using LC-MS/MS revealed 2560 metabolites in the patients' serum: 106 showed statistically significant upregulation in the serum of the CAD group compared with the healthy control group (p < 0.05). These metabolites belonged to the following chemical families: acyl-carnitines, cyclodipeptides, lysophosphatidylcholine, and primary bile acids. In contrast, 98 metabolites displayed statistically significant downregulation in the serum of the CAD group compared with the control group, belonging to the following chemical families: GABA amino acids and derivatives (inhibitory neurotransmitters), lipids, and secondary bile acids. Our comprehensive untargeted serum metabolomic analysis revealed biomarkers that can be used for the diagnosis of patients with CAD. Further cohort studies with a larger number of participants are needed to validate the detected biomarkers.

Plasma proteomics and lipidomics facilitate elucidation of the link between Alzheimer's disease development and vessel wall fragility

Proximity Extension Assay (PEA) and mass spectrometry (MS) methodologies were utilized for the proteomic and lipidomic characterization of plasma specimens from patients who developed Alzheimer's disease. Proteomics was performed by both PEA and Liquid Chromatography (LC)/MS in this study, but all the more because LC/MS generally tends to be biased towards proteins with high expression and high variability, generating hypotheses proved challenging. Consequently, attempt was made to interpret the results from the PEA data. There were 150 significantly variable proteins and 68 lipids among 1000 proteins and 400 lipids. Pathway analysis was performed for both total and variable proteins measured to reduce bias, and it appeared that vascular fragility was related to AD. Furthermore, a multitude of lipid-associated proteins exhibited statistical changes. In certain instances, the function of individual proteins affected the factors associated with them, whereas others demonstrated trends contrary to anticipated outcomes. These trends seem indicative of diverse feedback mechanisms that provide homeostatic equilibrium. The degree of unsaturation of fatty acids, correlated with cardiovascular risk, warrants specific attention. Certain bile acids exhibited the potential to cause vascular endothelial damage. Contemplating these discoveries in tandem with previously documented phenomena, subtle shifts in homeostatic functions seem to be linked to the fragility of vascular endothelial cells. This is evidenced by the slow and chronic evolution of Alzheimer's disease from preclinical stages to its manifestation.

Effect of Bile on Hemodynamics and Blood Micro-Rheological Parameters in Experimental Models of Bilhemia

As a rare complication of liver injury and certain interventions, bile can enter the bloodstream depending on the pressure gradient, resulting in bilhemia. Its micro-rheological and hemodynamic effects are still unclear. We aimed to study these parameters in experimental bilhemia models. Under general anesthesia, via laparotomy, bile was obtained by gallbladder puncture from pigs and by choledochal duct cannulation from rats. In vitro, 1 µL and 5 µL of bile were mixed with 500 µL of anticoagulated autologous blood. The systemic effect was also assessed (i.v. bile, 200 µL/bwkg). Hemodynamic and hematological parameters were monitored, and red blood cell (RBC) deformability and aggregation were determined. RBC deformability significantly decreased with the increasing bile concentration in vitro (1 µL: p = 0.033; 5 µL: p < 0.001) in both species. The RBC aggregation index values were concomitantly worsened (1 µL: p < 0.001; 5 µL: p < 0.001). The mean arterial pressure and heart rate decreased by 15.2 ± 6.9% and 4.6 ± 2.1% in rats (in 10.6 ± 2.6 s) and by 32.1 ± 14% and 25.2 ± 11.63% in pigs (in 48.3 ± 18.9 s). Restoration of the values was observed in 45 ± 9.5 s (rats) and 130 ± 20 s (pigs). Bilhemia directly affected the hemodynamic parameters and caused micro-rheological deterioration. The magnitude and dynamics of the changes were different for the two species.

Serum metabolism characteristics of patients with myocardial injury after noncardiac surgery explored by the untargeted metabolomics approach

BACKGROUND

Myocardial injury after noncardiac surgery (MINS) is one of the most common complications associated with postoperative adverse cardiovascular outcomes and mortality. However, MINS often fails to be timely diagnosed due to the absence of clinical symptoms and limited diagnostic methods. The metabolomic analysis might be an efficient way to discover new biomarkers of MINS. Characterizing the metabolomic features of MINS patients may provide new insight into the diagnosis of MINS.

METHODS

In this study, serum samples from 20 matched patients with or without MINS (n = 10 per group) were subjected to untargeted metabolomics analysis to investigate comprehensive metabolic information. Differential metabolites were identified, and the enriched metabolic pathway was determined based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

RESULTS

A comprehensive analysis revealed 124 distinct metabolites, predominantly encompassing lipids, amino acids and other compounds. The observed modifications in metabolic pathways in patients with or without MINS showed significant clustering in cholesterol metabolism, aldosterone synthesis and secretion, primary bile acid biosynthesis, as well as cysteine and methionine metabolism. Four specific metabolites (taurocholic acid, L-pyroglutamic acid, taurochenodeoxycholic acid, and pyridoxamine) exhibited promising potential as biomarkers for prognosticating MINS.

CONCLUSIONS

This study contributes valuable insights into the metabolomic features of MINS and the discovery of potential biomarkers which may help the early diagnosis of MINS. The identified metabolites and altered pathways offer valuable insights into the molecular underpinnings of MINS, paving the way for improved diagnostic approaches and potential intervention strategies.

A 6-month exercise intervention clinical trial in women: effects of physical activity on multi-omics biomarkers and health during the first wave of COVID-19 in Korea

BACKGROUND

Coronavirus disease 2019 (COVID-19) was first reported in December 2019 and the first case in Korea was confirmed on January 20, 2020. Due to the absence of therapeutic agents and vaccines, the Korean government implemented social distancing on February 29, 2020. This study aimed to examine the effect of physical activity (PA) on health through changes in multi-omics biomarkers with a 6-month of exercise intervention during the first wave of COVID-19 in Korea.

METHODS

Twenty-seven healthy middle-aged women were recruited and 14 subjects completed the exercise intervention. The mean age (± SD) was 46.3 (± 5.33) and the mean BMI (± SD) was 24.9 (± 3.88). A total of three blood and stool samples were collected at enrollment, after period 1, and after period 2 (3-month intervals). The amount of PA was measured with an accelerometer and by questionnaire. Clinical variables were used, including blood pressure, grip strength, flexibility, and blood glucose levels and lipid markers obtained from laboratory tests. The concentration of blood metabolites was measured by targeted metabolomics. Fecal microbiome data were obtained by 16 S rRNA gene amplicon sequencing.

RESULTS

During the second half period (period 2), Coronavirus disease 2019 occurred and spread out in Korea, and PA decreased compared with the first half period (period 1) (185.9 ± 168.73 min/week to 102.5 ± 82.30 min/week; p = 0.0101). Blood pressure, hemoglobin A1c (HbA1c), and low-density lipoprotein cholesterol (LDL-C) decreased in period 1 (p < 0.05) and tended to increase again during period 2 (p < 0.05). Forty metabolites were changed significantly during period 1 (FDR p < 0.05), and we found that 6 of them were correlated with changes in blood pressure, HbA1c, and LDL-C via network analysis.

CONCLUSIONS

Our results may suggest that exercise improves health through changes in biomarkers at multi-omics levels. However, reduced PA due to COVID-19 can adversely affect health, emphasizing the necessity for sustained exercise and support for home-based fitness to maintain health.

TRIAL REGISTRATION

The trial is retrospectively registered on ClinicalTrials.gov (NCT05927675; June 30, 2023).

Predictive value of serum TBA for 2-year MACEs in ACS patients undergoing PCI: a prospective cohort study

Bile acids play important roles in lipid metabolism and glucose homeostasis. Limited research exist on the association between serum total bile acid (TBA) levels and major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS), particularly those with comorbid type 2 diabetes mellitus (T2DM). This study was conducted to examine the relationship between baseline serum TBA level and T2DM status in patients with ACS after percutaneous coronary intervention (PCI) and to identify the predictive value of TBA levels for a 2-year risk of MACEs. 425 ACS patients underwent PCI were recruited and divided into three groups based on baseline serum TBA concentration. An analysis of the association between the T2DM status and baseline serum TBA levels was conducted using univariate linear regression and multivariate linear regression. The predictive relevance of serum TBA levels was evaluated using the receiver operating characteristic (ROC) curve and Cox regression. Kaplan-Meier curves were employed to analyze the differences among groups in predicting MACEs over a 2-year follow-up period. Baseline serum TBA levels were higher in ACS patients who were diagnosed with T2DM (the median 3.6 µmol/L) than those without T2DM (the median 3.0 µmol/L). T2DM status in ACS patients was positively correlated with baseline serum TBA concentrations (β: 1.7, 95% confidence interval [CI] 0.3-3.0), particularly in the male (β: 2.0, 95% CI 0.3-3.6) and 50-69-year-old (β: 2.5, 95% CI 0.6-4.4) populations. The areas under the ROC curve of baseline serum TBA levels predicted MACEs in ACS and ACS-T2DM patients following PCI were 0.649 (95% CI 0.595-0.703) and 0.783 (95% CI 0.685-0.881), respectively. Furthermore, Cox regression analysis showed that baseline serum TBA level was associated with the occurrence of MACEs in patients with ACS after PCI over a 2-year follow-up period, especially in those diagnosed with T2DM, whose baseline TBA concentration was lower than 10.0 µmol/L. ACS Patients with T2DM had higher serum TBA levels. TBA level at baseline was an independent predictor of MACEs in ACS patients who underwent PCI, especially with comorbid T2DM.

Gut microbiota and metabolomics profiles in patients with chronic stable angina and acute coronary syndrome

Cardiovascular disease (CVD) is the leading cause of death worldwide. The gut microbiota and its associated metabolites may be involved in the development and progression of CVD, although the mechanisms and impact on clinical outcomes are not fully understood. This study investigated the gut microbiome profile and associated metabolites in patients with chronic stable angina (CSA) and acute coronary syndrome (ACS) compared with healthy controls. Bacterial alpha diversity in stool from patients with ACS or CSA was comparable to healthy controls at both baseline and follow-up visits. Differential abundance analysis identified operational taxonomic units (OTUs) assigned to commensal taxa differentiating patients with ACS from healthy controls at both baseline and follow-up. Patients with CSA and ACS had significantly higher levels of trimethylamine N-oxide compared with healthy controls (CSA: 0.032 ± 0.023 mmol/L, P < 0.01 vs. healthy, and ACS: 0.032 ± 0.023 mmol/L, P = 0.02 vs. healthy, respectively). Patients with ACS had reduced levels of propionate and butyrate (119 ± 4 vs. 139 ± 5.1 µM, P = 0.001, and 14 ± 4.3 vs. 23.5 ± 8.1 µM, P < 0.001, respectively), as well as elevated serum sCD14 (2245 ± 75.1 vs. 1834 ± 45.8 ng/mL, P < 0.0001) and sCD163 levels (457.3 ± 31.8 vs. 326.8 ± 20.7 ng/mL, P = 0.001), compared with healthy controls at baseline. Furthermore, a modified small molecule metabolomic and lipidomic signature was observed in patients with CSA and ACS compared with healthy controls. These findings provide evidence of a link between gut microbiome composition and gut bacterial metabolites with CVD. Future time course studies in patients to observe temporal changes and subsequent associations with gut microbiome composition are required to provide insight into how these are affected by transient changes following an acute coronary event.NEW & NOTEWORTHY The study found discriminative microorganisms differentiating patients with acute coronary syndrome (ACS) from healthy controls. In addition, reduced levels of certain bacterial metabolites and elevated sCD14 and sCD163 were observed in patients with ACS compared with healthy controls. Furthermore, modified small molecule metabolomic and lipidomic signatures were found in both patient groups. Although it is not known whether these differences in profiles are associated with disease development and/or progression, the findings provide exciting options for potential new disease-related mechanism(s) and associated therapeutic target(s).

Bile acid metabolism and signaling: Emerging pharmacological targets of dietary polyphenols

Beyond their role as emulsifiers of lipophilic compounds, bile acids (BAs) are signaling endocrine molecules that show differential affinity and specificity for a variety of canonical and non-canonical BA receptors. Primary BAs (PBAs) are synthesized in the liver while secondary BAs (SBAs) are gut microbial metabolites of PBA species. PBAs and SBAs signal to BA receptors that regulate downstream pathways of inflammation and energy metabolism. Dysregulation of BA metabolism or signaling has emerged as a feature of chronic disease. Dietary polyphenols are non-nutritive plant-derived compounds associated with decreased risk of metabolic syndrome, type-2 diabetes, hepatobiliary and cardiovascular disease. Evidence suggests that the health promoting effects of dietary polyphenols are linked to their ability to alter the gut microbial community, the BA pool, and BA signaling. In this review we provide an overview of BA metabolism and summarize studies that link the cardiometabolic improvements of dietary polyphenols to their modulation of BA metabolism and signaling pathways, and the gut microbiota. Finally, we discuss approaches and challenges in deciphering cause-effect relationships between dietary polyphenols, BAs, and gut microbes.

Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia

Acute myocardial ischemia (AMI) remains the leading cause of death worldwide, and the post-mortem diagnosis of AMI represents a current challenge for both clinical and forensic pathologists. In the present study, the untargeted metabolomics based on ultra-performance liquid chromatography combined with high-resolution mass spectrometry was applied to analyze serum metabolic signatures from AMI in a rat model (n = 10 per group). A total of 28 endogenous metabolites in serum were significantly altered in AMI group relative to control and sham groups. A set of machine learning algorithms, namely gradient tree boosting (GTB), support vector machine (SVM), random forest (RF), logistic regression (LR), and multilayer perceptron (MLP) models, was used to screen the more valuable metabolites from 28 metabolites to optimize the biomarker panel. The results showed that classification accuracy and performance of MLP model were better than other algorithms when the metabolites consisting of L-threonic acid, N-acetyl-L-cysteine, CMPF, glycocholic acid, L-tyrosine, cholic acid, and glycoursodeoxycholic acid. Finally, 17 blood samples from autopsy cases were applied to validate the classification model's value in human samples. The MLP model constructed based on rat dataset achieved accuracy of 88.23%, and ROC of 0.89 for predicting AMI type II in autopsy cases of sudden cardiac death. The results demonstrated that MLP model based on 7 molecular biomarkers had a good diagnostic performance for both AMI rats and autopsy-based blood samples. Thus, the combination of metabolomics and machine learning algorithms provides a novel strategy for AMI diagnosis.

Role of gut microbe-derived metabolites in cardiometabolic diseases: Systems based approach

BACKGROUND

The gut microbiome influences host physiology and cardiometabolic diseases by interacting directly with intestinal cells or by producing molecules that enter the host circulation. Given the large number of microbial species present in the gut and the numerous factors that influence gut bacterial composition, it has been challenging to understand the underlying biological mechanisms that modulate risk of cardiometabolic disease.

SCOPE OF THE REVIEW

Here we discuss a systems-based approach that involves simultaneously examining individuals in populations for gut microbiome composition, molecular traits using "omics" technologies, such as circulating metabolites quantified by mass spectrometry, and clinical traits. We summarize findings from landmark studies using this approach and discuss future applications.

MAJOR CONCLUSIONS

Population-based integrative approaches have identified a large number of microbe-derived or microbe-modified metabolites that are associated with cardiometabolic traits. The knowledge gained from these studies provide new opportunities for understanding the mechanisms involved in gut microbiome-host interactions and may have potentially important implications for developing novel therapeutic approaches.

Lipid Metabolic Disorder Induced by Pyrethroids in Nonalcoholic Fatty Liver Disease of Xenopus laevis

Pyrethroids, an effective and widely used class of pesticides, have attracted considerable concerns considering their frequent detection in environmental matrices. However, their potential health risks to amphibians remain unclear. In our study, female Xenopus laevis were exposed to 0, 0.06, and 0.3 μg/L typical pyrethroid, cis-bifenthrin (cis-BF), for 3 months. Elevated activities of both aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were observed, indicating an ongoing liver injury. Furthermore, exposure to cis-BF led to hyperlipidemia and lipid accumulation in the liver of Xenopus. The targeted lipidomic analysis further revealed that treatment with cis-BF perturbed liver steroid homeostasis, as evidenced by the enriched lipids in the steroid biosynthesis pathway. Consistent with the targeted lipidomic result, treatment with cis-BF changed the liver transcriptome profile with induction of 808 and 1230 differentially expressed genes. Kyoto Encyclopedia of Genes and Genomes analysis underlined the adverse effects of cis-BF exposure on steroid biosynthesis, primary bile acid biosynthesis, and the PPAR signaling pathway in the Xenopus liver. Taken together, our study revealed that exposure to cis-BF at environmentally relevant concentrations resulted in lipid metabolic disorder associated with nonalcoholic fatty liver disease of X. laevis, and our results provided new insight into the potential long-term hazards of pyrethroids.

Serum Metabolomics Reveals Distinct Profiles during Ischemia and Reperfusion in a Porcine Model of Myocardial Ischemia-Reperfusion

Acute myocardial infarction (MI) is one of the leading causes of death worldwide. Early identification of ischemia and establishing reperfusion remain cornerstones in the treatment of MI, as mortality and morbidity can be significantly reduced by establishing reperfusion to the affected areas. The aim of the current study was to investigate the metabolomic changes in the serum in a swine model of MI induced by ischemia and reperfusion (I/R) injury, and to identify circulating metabolomic biomarkers for myocardial injury at different phases. Female Yucatan minipigs were subjected to 60 min of ischemia followed by reperfusion, and serum samples were collected at baseline, 60 min of ischemia, 4 h of reperfusion, and 24 h of reperfusion. Circulating metabolites were analyzed using an untargeted metabolomic approach. A bioinformatic approach revealed that serum metabolites show distinct profiles during ischemia and during early and late reperfusion. Some notable changes during ischemia include accumulation of metabolites that indicate impaired mitochondrial function and N-terminally modified amino acids. Changes in branched-chain amino-acid metabolites were noted during early reperfusion, while bile acid pathway derivatives and intermediates predominated in the late reperfusion phases. This indicates a potential for such an approach toward identification of the distinct phases of ischemia and reperfusion in clinical situations.

Antihypertensive effect and underlying mechanism of tripeptide NCW on spontaneously hypertensive rats using metabolomics analysis

Tripeptide NCW identified in our previous study displayed a strong ACE inhibitory activity, but whether it has any antihypertensive effect in vivo remains unknown. Thus, in this study, we aimed to investigate the protective effects of tripeptide NCW in spontaneously hypertensive rats (SHRs) and to further figure out the serum metabolic profiling variations due to its oral administration via UPLC-Q-TOF-MS/MS-based metabolomics analysis to clarify the underlying hypotensive mechanism. After three weeks of oral administration, the tripeptide NCW-treated group (NCW/SHR group, 80 mg per kg BW per d) showed significantly reduced systolic and diastolic blood pressure by 48.08 ± 3.84 mmHg and 48.92 ± 5.77 mmHg, respectively. Additionally, a total of 25 blood pressure-related metabolites were identified as being significantly changed in SHRs given tripeptide NCW after three weeks. These 25 metabolites might be biomarkers that indicated that the tripeptide NCW exhibits antihypertensive activity via regulating bile acid metabolism, lipid metabolism, amino acid metabolism, purinergic signaling, pantothenate and CoA biosynthesis, and the citrate cycle. Collectively, tripeptide NCW has a protective effect on SHRs associated with serum metabolite abnormalities.

Current Knowledge of MicroRNAs (miRNAs) in Acute Coronary Syndrome (ACS): ST-Elevation Myocardial Infarction (STEMI)

Regardless of the newly diagnostic and therapeutic advances, coronary artery disease (CAD) and more explicitly, ST-elevation myocardial infarction (STEMI), remains one of the leading causes of morbidity and mortality worldwide. Thus, early and prompt diagnosis of cardiac dysfunction is pivotal in STEMI patients for a better prognosis and outcome. In recent years, microRNAs (miRNAs) gained attention as potential biomarkers in myocardial infarction (MI) and acute coronary syndromes (ACS), as they have key roles in heart development, various cardiac processes, and act as indicators of cardiac damage. In this review, we describe the current available knowledge about cardiac miRNAs and their functions, and focus mainly on their potential use as novel circulating diagnostic and prognostic biomarkers in STEMI.

Myocardial Infarction and Coronary Artery Disease in Menopausal Women With Type 2 Diabetes Mellitus Negatively Correlate With Total Serum Bile Acids

Background

As metabolic molecules, bile acids (BAs) not only promote the absorption of fat-soluble nutrients, but they also regulate many metabolic processes, including the homeostasis of glucose and lipids. Although total serum BA (TBA) measurement is a readily available clinical test related to coronary artery disease (CAD), myocardial infarction (MI), and type 2 diabetes mellitus (T2DM), the relationship between TBA and these pathological conditions remain unclear, and research on this topic is inconclusive.

Methods

This study enrolled 20,255 menopausal women aged over 50 years, including 6,421 T2DM patients. The study population was divided into different groups according to the median TBA level in order to explore the clinical characteristics of menopausal women with different TBA levels. Spline analyses, generalized additive model (GAM) model and regression analyses based on TBA level were used to explore the relationship between TBA and different diseases independently, including CAD and MI, or in combination with T2DM.

Results

Both in the general population and in the T2DM subgroup, the TBA level was significantly lower in CAD patients than in non-CAD patients. Spline analyses indicated that within normal clinical range of TBA concentration (0-10 µmol/L), the presence of CAD and MI showed similar trends in total and T2DM population. Similarly, the GAM model indicated that within the 0-10 μmol/L clinical range, the predicted probability for CAD and MI alone and in combination with T2DM was negatively correlated with TBA concentration. Multivariate regression analysis suggested that low TBA level was positively associated with the occurrence of CAD combined with T2DM (OR: 1.451; 95%CI: 1.141-1.847).

Conclusions

In menopausal women, TBA may represent a valuable clinical serum marker with negative correlation for CAD and MI in patients with T2DM.

RNA-seq identifies circulating miRNAs as potential biomarkers for plaque rupture in patients with ST-segment elevation myocardial infarction

BACKGROUND

Plaque rupture (PR) and plaque erosion (PE) are the two major pathological phenotypes in acute coronary syndrome. Since microRNAs have been found to be involved in the mechanisms of PR and PE, we investigated the diagnostic utility of microRNAs in differentiating between patients with PR and patients with PE.

METHODS

MicroRNA sequencing was performed on plasma from 21 patients with PR, 20 patients with PE and 17 healthy control subjects (HCs). 24 miRNAs were selected for validation in 20 PR patients and 20 PE patients and 8 miRNAs were further validated in an independent replication cohort (82 patients with PR, 84 patients with PE and 59 HCs) by applying quantitative real-time polymerase chain reaction. Then we analyzed pathways associated with significant miRNAs in PR.

RESULTS

MiR-744-3p, miR-324-3p and miR-330-3p were significantly upregulated in the PR group compared with the PE group (Log₁₀miR-744-3p: 0.26[--0.28-1.57] versus -0.41[-0.83--0.03], p_adj < 0.001; Log₁₀miR-324-3p: 0.40[-0.09-0.84] versus -0.12[-0.53-0.29], p_adj < 0.001; Log₁₀miR-330-3p: 0.34[0.08-0.93] versus -0.07[-0.65-0.22], p_adj < 0.001), The area under the receiver operating characteristic curve for the combination of these three miRNAs in distinguishing between PR from PE in training and test set was 0.764 (0.679-0.850, sensitivity = 86.2%, specificity = 54.4%, P < 0.001) and 0.768 (0.637-0.898, sensitivity,65.4%, specificity:80.0%, P = 0.001), respectively.

CONCLUSION

A set of circulating microRNAs (miR-744-3p, miR-330-3p, and miR-324-3p) is associated with PR and has clinical utility as a diagnostic marker for distinguishing the plaque phenotype in STEMI patients.