Targeted metabolomic analysis of plasma metabolites in patients with coronary heart disease in southern China

Combining the Strengths of the Explainable Boosting Machine and Metabolomics Approaches for Biomarker Discovery in Acute Myocardial Infarction

Acute Myocardial Infarction (AMI), a common disease that can have serious consequences, occurs when myocardial blood flow stops due to occlusion of the coronary artery. Early and accurate prediction of AMI is critical for rapid prognosis and improved patient outcomes. Metabolomics, the study of small molecules within biological systems, is an effective tool used to discover biomarkers associated with many diseases. This study intended to construct a predictive model for AMI utilizing metabolomics data and an explainable machine learning approach called Explainable Boosting Machines (EBM). The EBM model was trained on a dataset of 102 prognostic metabolites gathered from 99 individuals, including 34 healthy controls and 65 AMI patients. After a comprehensive data preprocessing, 21 metabolites were determined as the candidate predictors to predict AMI. The EBM model displayed satisfactory performance in predicting AMI, with various classification performance metrics. The model's predictions were based on the combined effects of individual metabolites and their interactions. In this context, the results obtained in two different EBM modeling, including both only individual metabolite features and their interaction effects, were discussed. The most important predictors included creatinine, nicotinamide, and isocitrate. These metabolites are involved in different biological activities, such as energy metabolism, DNA repair, and cellular signaling. The results demonstrate the potential of the combination of metabolomics and the EBM model in constructing reliable and interpretable prediction outputs for AMI. The discussed metabolite biomarkers may assist in early diagnosis, risk assessment, and personalized treatment methods for AMI patients. This study successfully developed a pipeline incorporating extensive data preprocessing and the EBM model to identify potential metabolite biomarkers for predicting AMI. The EBM model, with its ability to incorporate interaction terms, demonstrated satisfactory classification performance and revealed significant metabolite interactions that could be valuable in assessing AMI risk. However, the results obtained from this study should be validated with studies to be carried out in larger and well-defined samples.

The interactions and biological pathways among metabolomics products of patients with coronary heart disease

BACKGROUND

Through bioinformatics analysis, this study explores the interactions and biological pathways involving metabolomic products in patients diagnosed with coronary heart disease (CHD).

METHODS

A comprehensive search for relevant studies focusing on metabolomics analysis in CHD patients was conducted across databases including CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, Nature, Web of Science, Springer, and Science Direct. Metabolites reported in the literature underwent statistical analysis and summarization, with the identification of differential metabolites. The pathways associated with these metabolites were examined using the Kyoto Encyclopedia of Genes and Genomes (KEGG). Molecular annotation of metabolites and their relationships with enzymes or transporters were elucidated through analysis with the Human Metabolome Database (HMDB). Visual representation of the properties related to these metabolites was achieved using Metabolomics Pathway Analysis (metPA).

RESULTS

A total of 13 literatures satisfying the criteria for enrollment were included. A total of 91 metabolites related to CHD were preliminarily screened, and 87 effective metabolites were obtained after the unrecognized metabolites were excluded. A total of 45 pathways were involved. Through the topology analysis (TPA) of pathways, their influence values were calculated, and 13 major metabolic pathways were selected. The pathways such as Phenylalanine, tyrosine, and tryptophan biosynthesis, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, and Glycine, serine, and threonine metabolism primarily involved the regulation of processes and metabolites related to inflammation, oxidative stress, one-carbon metabolism, energy metabolism, lipid metabolism, immune regulation, and nitric oxide expression.

CONCLUSION

Multiple pathways, including Phenylalanine, tyrosine, and tryptophan biosynthesis, Citrate cycle (TCA cycle), Glyoxylate and dicarboxylate metabolism, and Glycine, serine, and threonine metabolism, were involved in the occurrence of CHD. The occurrence of CHD is primarily associated with the regulation of processes and metabolites related to inflammation, oxidative stress, one-carbon metabolism, energy metabolism, lipid metabolism, immune regulation, and nitric oxide expression.

Buyang Huanwu Decoction Alleviates Atherosclerosis by Regulating gut Microbiome and Metabolites in Apolipoprotein E-deficient Mice fed with High-fat Diet

ABSTRACT

The traditional Chinese herbal prescription Buyang Huanwu decoction (BHD), effectively treats atherosclerosis. However, the mechanism of BHD in atherosclerosis remains unclear. We aimed to determine whether BHD could alleviate atherosclerosis by altering the microbiome-associated metabolic changes in atherosclerotic mice. An atherosclerotic model was established in apolipoprotein E-deficient mice fed high-fat diet, and BHD was administered through gavage for 12 weeks at 8.4 g/kg/d and 16.8 g/kg/d. The atherosclerotic plaque size, composition, serum lipid profile, and inflammatory cytokines, were assessed. Mechanistically, metabolomic and microbiota profiles were analyzed by liquid chromatography-mass spectrometry and 16S rRNA gene sequencing, respectively. Furthermore, intestinal microbiota and atherosclerosis-related metabolic parameters were correlated using Spearman analysis. Atherosclerotic mice treated with BHD exhibited reduced plaque area, aortic lumen occlusion, and lipid accumulation in the aortic root. Nine perturbed serum metabolites were significantly restored along with the relative abundance of microbiota at the family and genus levels but not at the phylum level. Gut microbiome improvement was strongly negatively correlated with improved metabolite levels. BHD treatment effectively slows the progression of atherosclerosis by regulating altered intestinal microbiota and perturbed metabolites.

Blood-Derived Lipid and Metabolite Biomarkers in Cardiovascular Research from Clinical Studies: A Recent Update

The primary prevention, early detection, and treatment of cardiovascular disease (CVD) have been long-standing scientific research goals worldwide. In the past decades, traditional blood lipid profiles have been routinely used in clinical practice to estimate the risk of CVDs such as atherosclerotic cardiovascular disease (ASCVD) and as treatment targets for the primary prevention of adverse cardiac events. These blood lipid panel tests often fail to fully predict all CVD risks and thus need to be improved. A comprehensive analysis of molecular species of lipids and metabolites (defined as lipidomics and metabolomics, respectively) can provide molecular insights into the pathophysiology of the disease and could serve as diagnostic and prognostic indicators of disease. Mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based lipidomics and metabolomics analysis have been increasingly used to study the metabolic changes that occur during CVD pathogenesis. In this review, we provide an overview of various MS-based platforms and approaches that are commonly used in lipidomics and metabolomics workflows. This review summarizes the lipids and metabolites in human plasma/serum that have recently (from 2018 to December 2022) been identified as promising CVD biomarkers. In addition, this review describes the potential pathophysiological mechanisms associated with candidate CVD biomarkers. Future studies focused on these potential biomarkers and pathways will provide mechanistic clues of CVD pathogenesis and thus help with the risk assessment, diagnosis, and treatment of CVD.

Serum trimethylamine N-oxide levels among coronary artery disease and acute coronary syndrome patients: a systematic review and meta-analysis

Background and Aim

Recent studies have linked trimethylamine N-oxide (TMAO) to cardiovascular diseases; our study aimed to analyze the association between coronary artery disease (CAD), acute coronary syndrome (ACS), and TMAO.

Methods

PubMed, Scopus, Embase, and Web of Science were searched using terms such as 'CAD' and 'TMAO'. Only observational controlled studies were included. RevMan software version 5.4 was used for the analysis.

Results

A significant association was found between the CAD group and increased serum TMAO levels compared with the control group (MD=1.16, 95% CI=0.54-1.78, P=0.0003). This association remained significant among acute coronary syndrome patients (MD=0.98, 95% CI=0.73-1.23, P<0.00001) and was also detected among young and old CAD patients (MD=0.35, 95% CI=0.06-0.64, P=0.02 and MD=1.36, 95% CI=0.71-2.01, P<0.0001, respectively). On further analysis of intestinal metabolites, the authors detected an insignificant association between choline, betaine, carnitine, and CAD. According to our sensitivity analysis, TMAO is an acceptable diagnostic marker for CAD (0.721, SE was 0.0816, 95% CI: 0.561-0.881).

Conclusion

TMAO is an acceptable diagnostic marker for CAD, with significantly higher levels among these patients regardless of their age. Other metabolites did not show such an association. The role of serum level TMAO in the early diagnosis of CAD should be further explored.

Effect of Qishen granules on isoproterenol-induced chronic heart failure in rats evaluated by comprehensive metabolomics

Qishen granules (QSG), a Chinese herbal formula, has been widely used in the treatment of myocardial ischemic chronic heart failure (CHF) for many years, but its mechanism of action is still unclear. In this study, comprehensive metabolomics was used to investigate the underlying protective mechanisms of QSG in an isoproterenol-induced CHF rat model. A total of 14 biomarkers were identified in serum and 34 biomarkers in urine, which were mainly related to fatty acid metabolism, bile acid metabolism, amino acid metabolism, purine metabolism, vitamin metabolism, and inflammation. Finally, 22 markers were selected for quantitative analysis of serum, urine, and fecal samples to verify the reliability of the results of untargeted metabolomics, and the results were similar to those of untargeted metabolomics. The correlation analysis showed that the targeted quantitative endogenous metabolites and CHF-related indexes were closely related. QSG might alleviate myocardial inflammatory response, oxidative stress, and amino acid metabolism disorder in CHF by regulating the level of endogenous metabolites. This study revealed QSG could regulate potential biomarkers and correlated metabolic pathway, which provided support for the further application of QSG.

Positive Association of Plasma Trimethylamine-N-Oxide and Atherosclerosis in Patient with Acute Coronary Syndrome

Aim. Atherosclerosis is the major cause of acute coronary syndrome (ACS) which is a significant contributor to both morbidity and mortality in the world. The microbiome-derived metabolite trimethylamine-N-oxide (TMAO) has aroused great interest and controversy as a risk factor of atherosclerosis. Therefore, in this study, we aimed at investigating whether plasma TMAO can be a risk factor of atherosclerosis in coronary artery of patients with ACS and how this relates to lipids and proinflammatory cytokines in plasma. Methods. We enrolled consecutive patients with ACS who underwent percutaneous coronary intervention (PCI). Gensini scoring was used to evaluate angiographic atherosclerosis in the coronary artery of the patients. 13 patients were divided into low ( $\text{Gensini}\text{score}<25$ ), 33 into intermediate (Gensini score 25-50), and 81 into severe atherosclerosis (Gensini score ≥50). Plasma TMAO, vasculitis factors, and cardiovascular biomarkers were measured by clinical biochemistry, intima-media thickness (IMT) of carotid artery was determined by the Color Doppler ultrasound, and the atherosclerotic lesion in coronary artery was assessed in PCI. Results. Plasma TMAO concentrations were positively associated with Gensini score ( $\text{OR}=0.629$ , $p<0.001$ ) and Gensini subgroup ( $\text{R}=0.604$ , $p<0.0$ 01). Plasma TMAO concentrations in patients with severe coronary atherosclerosis were higher than those of patients with moderate coronary atherosclerosis, and the plasma TMAO concentrations of patients with moderate coronary atherosclerosis were higher than those of patients with mild coronary atherosclerosis, the difference was statistically significant [4.73 (3.13, 4.62) versus 1.13 (0.63, 3.34) versus 0.79 (0.20, 1.29), $p<0.001$ ], respectively. Furthermore, ROC analysis showed that plasma TMAO could identify the severity of atherosclerosis ( $p<0.001$ ). The AUC of TMAO for severe atherosclerosis was 0.852 ( $95\%\text{CI}=0.779-0.925$ ). The sensitivity and specificity of TMAO for identifying severe atherosclerosis are 96.3% and 63.0% when the cut-off value of TMAO was set at 1.2715 pg/ml. Furthermore, logistic regression analysis showed plasma TMAO concentrations were positively associated with severity of atherosclerosis in coronary artery ( $\text{OR}=1.934$ , $95\%\text{CI}=1.522-2.459$ , $p<0.001$ ). For all that, negatively association was observed between TMAO and age ( $\text{OR}=-0.224$ , $p<0.05$ ), B-type natriuretic peptide (BNP) ( $\text{OR}=-0.175$ , $p<0.05$ ), and interleukin-8 (IL-8) ( $\text{OR}=-0.324$ , $p<0.001$ ), while positive association was observed between TMAO and nitric oxide (NO) ( $\text{OR}=0.234$ , $p<0.01$ ). However, there is no obvious association was observed between Gensini score and cardiovascular biomarkers, vasculitis factors, and carotid IMT, respectively. Conclusion. Our cross-sectional observation suggested that plasma TMAO concentrations positively associated with coronary atherosclerosis in ACS patients and serve as a risk factor for severe atherosclerosis. Plasma TMAO also correlated with age, BNP, IL-8, and NO. However, no obvious association was found between atherosclerosis with vasculitis factors and cardiovascular biomarkers in this study, and there was no conclusive evidence showing TMAO enhance atherosclerosis via regulation of inflammation or lipid.

The application of proteomics and metabolomics to reveal the molecular mechanism of Nutmeg-5 in ameliorating cardiac fibrosis following myocardial infarction

BACKGROUND

Nutmeg-5, an ancient and classic formula in traditional Mongolian medicine comprising five kinds of traditional Chinese medicine, is widely used in the treatment of myocardial infarction (MI, called heart "Heyi" disease in Mongolian medicine). Cardiac fibrosis plays a critical role in the development and progression of heart failure after MI. However, the material basis and pharmacological mechanisms of the effect of Nutmeg-5 on cardiac fibrosis after MI remain unclear.

OBJECTIVE

The aim of this study was to first explore the potential material basis and molecular mechanism of action of Nutmeg-5 in improving cardiac fibrosis after MI via a multiomics approach.

METHODS

The constituents in Nutmeg-5 were identified by ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). High-performance liquid chromatography (HPLC) and gas chromatography (GC)-based fingerprints of Nutmeg-5 were analysed, and characteristic peaks were identified by comparison to standard samples. A rat MI model was created by permanent ligation of the left anterior descending artery. The protective effect of Nutmeg-5 on cardiac fibrosis after MI was evaluated by tissue histology and measurement of the serum biomarkers of myocardial injury. Cardiac fibrosis levels were evaluated by Sirius red staining. Differentially expressed proteins in the myocardium and metabolites in the serum were explored by proteomic and untargeted metabolome analyses, respectively. Pearson correlation analysis was performed to explore the association between serum metabolites and myocardial proteins.

RESULTS

A total of 67 constituents were identified in Nutmeg-5 by UPLC-MS/MS. Sixteen components were identified in the fingerprint of Nutmeg-5 by comparison with a standard sample. Six lactones were isolated from Nutmeg-5 and quantified by HPLC and GC. MI was significantly alleviated in Nutmeg-5-treated rats compared to MI rats, as demonstrated by their decreased mortality, improved cardiac function, and attenuated cardiac fibrosis and myocardial injury. A total of 252 significant differential metabolites were identified in plasma between model and Nutmeg-5-treated rats by untargeted metabolome analysis. Among these, 36 critical metabolites were associated with Nutmeg-5 activity. Proteomic analysis identified 338 differentially expressed proteins in the rat myocardium between MI and Nutmeg-5-treated rats, including 204 upregulated and 134 downregulated proteins. Protein set enrichment analysis revealed that Nutmeg-5 treatment significantly inhibited the extracellular matrix (ECM)-receptor interaction pathway, which was activated in the myocardium of MI rats. A significant decrease in collagen and alpha smooth muscle actin expression levels was found in the myocardium of Nutmeg-5-treated rats compared to MI rats. These results illustrated that Nutmeg-5 had a significant protective effect on cardiac fibrosis after MI. A significant correlation was found between the ECM-receptor interaction pathway in the myocardium and critical metabolites in the serum. In addition, there were positive correlations between the levels of critical metabolites and the expression levels of transforming growth factor (TGF)-β1 and Smad2 in the rat myocardium.

CONCLUSIONS

Nutmeg-5 alleviated cardiac fibrosis after MI in rats by inhibiting the myocardial ECM-receptor interaction pathway and TGF-β1/Smad2 signalling, which was achieved by regulating plasma metabolites.

Plasma Quantitative Lipid Profiles: Identification of CarnitineC18:1-OH, CarnitineC18:2-OH and FFA (20:1) as Novel Biomarkers for Pre-warning and Prognosis in Acute Myocardial Infarction

This study was aimed to determine the association between potential plasma lipid biomarkers and early screening and prognosis of Acute myocardial infarction (AMI). In the present study, a total of 795 differentially expressed lipid metabolites were detected based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Out of these metabolites, 25 lipid metabolites were identified which showed specifical expression in the AMI group compared with the healthy control (HC) group and unstable angina (UA) group. Then, we applied the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) methods to obtain three lipid molecules, including CarnitineC18:1-OH, CarnitineC18:2-OH and FFA (20:1). The three lipid metabolites and the diagnostic model exhibited well predictive ability in discriminating between AMI patients and UA patients in both the discovery and validation sets with an area under the curve (AUC) of 0.9. Univariate and multivariate logistic regression analyses indicated that the three lipid metabolites may serve as potential biomarkers for diagnosing AMI. A subsequent 1-year follow-up analysis indicated that the three lipid biomarkers also had prominent performance in predicting re-admission of patients with AMI due to cardiovascular events. In summary, we used quantitative lipid technology to delineate the characteristics of lipid metabolism in patients with AMI, and identified potential early diagnosis biomarkers of AMI via machine learning approach.

Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach

This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p < 0.05). Also, a combination of eicosanoids from the arachidonic acid pathway, mainly prostaglandin F2α, prostaglandin A2, 16,16-dimethyl prostaglandin E2, and 5-hydroxyeicosatetraenoic acid were collectively up-regulated as a group in keratoconus patients (p < 0.05). On the other hand, glycerophospholipid PS(17:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)) was found to be significantly upregulated in the metabolomics profiles of control subjects (p < 0.05). The differently regulated metabolites provide insights into the pathophysiology of keratoconus and could potentially be used as biomarkers for keratoconus to aid in screening for individuals at risk hence, enabling early diagnosis and timely monitoring of disease.

Serum Metabolomic Analysis of Coronary Heart Disease Patients with Stable Angina Pectoris Subtyped by Traditional Chinese Medicine Diagnostics Reveals Biomarkers Relevant to Personalized Treatments

To improve the treatment of patients with coronary heart disease (CHD), personalized treatments based on potential biomarkers could make a difference. To investigate if such potential biomarkers could be found for CHD inhomogeneous, we combined traditional Chinese medicine based diagnosis with untargeted and targeted metabolomics analyses. Shi and Xu patient subtype groups of CHD with angina pectoris were identified. Different metabolites including lipids, fatty acids and amino acids were further analyzed with targeted metabolomics and mapped to disease-related pathways. The long-chain unsaturated lipids ceramides metabolism, bile acid metabolism were differentially affected in the Xu subtype groups. While, Shi-subtype patients seemed to show inflammation, anomalous levels of bioactive phospholipids and antioxidant molecules. Furthermore, variations in the endothelial damage response and energy metabolism found based on ELISA analysis are the key divergence points between different CHD subtypes. The results showed Xu subtype patients might benefit from long-chain unsaturated lipids ceramides as therapeutic targets. Shi subtype patients might benefit more from levels of polyunsaturated fatty acid consumption and treatments that help in restoring energy balance. Metabolic differences can be essential for treatment protocols. Thus, patient group specific differences can serve as important information to refine current treatment approaches in a personalized manner.

The Association between Trimethylamine N-Oxide and Its Predecessors Choline, L-Carnitine, and Betaine with Coronary Artery Disease and Artery Stenosis

Background

Trimethylamine N-oxide (TMAO) and its predecessor products, choline, L-carnitine, and betaine, were reported to be associated with cardiovascular events risk. However, the association of TMAO and its predecessors with extent of artery stenosis in coronary artery disease (CAD) and in different gender is still unknown. Our aim is to investigate the association of plasma TMAO and its predecessors in CAD and extent of artery lesion in different gender.

Methods

94 CAD patients and 75 healthy controls (CON) were enrolled. Fasting plasma TMAO, choline, L-carnitine, and betaine were detected using liquid chromatography-tandem mass spectrometry.

Results

Elevated plasma TMAO but not choline, L-carnitine, or betaine was observed in CAD (1.46(0.8–2.32) μM) and severe artery stenosis patients (S) (1.62(0.91–2.81) μM) compared with controls and mild artery stenosis (M) (1.18(0.67–1.7) μM in CON; 1.27(0.77–1.82) μM in M, p < 0.05). TMAO was an independent risk factor of CAD and severe artery stenosis (CAD : OR = 1.81, 95%CI: 1.07–3.09, p=0.03; S : OR = 1.36, 95%CI: 1.01–1.84, p=0.04). TMAO was more sensitive in diagnosing CAD and severe artery stenosis from controls in men rather than in women by ROC analysis (AUC for men and women in CAD: 0.64 versus 0.57; AUC for men and women in S: 0.64 versus 0.58), while the combined four metabolites greatly improved diagnostic accuracy in women with CAD and severe artery stenosis (AUC in CAD: 0.64, AUC in S: 0.68).

Conclusion

The associations of TMAO with CAD and severe artery stenosis were sex-related. TMAO alone was more powerful in determining CAD and artery stenosis in men than women, while a combination of TMAO, choline, L-carnitine, and betaine could be potential biomarkers for diagnosing CAD and artery stenosis in both men and women.

Reconstructing the blood metabolome and genotype using long-range chromatin interactions

BACKGROUND

-Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome.

OBJECTIVE

-We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs.

METHOD

-We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs.

FINDINGS

-We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites.

CONCLUSIONS

-The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels.

Plasma Choline as a Diagnostic Biomarker in Slow Coronary Flow

Aim

The slow coronary flow (SCF) phenomenon was characterized by delayed perfusion of epicardial arteries, and no obvious coronary artery lesion in coronary angiography. The prognosis of patients with slow coronary flow was poor. However, there is lack of rapid, simple, and accurate method for SCF diagnosis. This study aimed to explore the utility of plasma choline as a diagnostic biomarker for SCF.

Methods

Patients with coronary artery stenosis <40% evaluated by the coronary angiogram method were recruited in this study and were grouped into normal coronary flow (NCF) and SCF by thrombolysis in myocardial infarction frame count (TFC). Plasma choline concentrations of patients with NCF and SCF were quantified by Ultra Performance Liquid Chromatography Tandem Mass Spectrometry. Correlation analysis was performed between plasma choline concentration and TFC. Receiver operating characteristic (ROC) curve analysis with or without confounding factor adjustment was applied to predict the diagnostic power of plasma choline in SCF.

Results

Forty-four patients with SCF and 21 patients with NCF were included in this study. TFC in LAD, LCX, and RCA and mean TFC were significantly higher in patients with SCF in comparison with patients with NCF (32.67 ± 8.37 vs. 20.66 ± 3.41, P  <  0.01). Plasma choline level was obviously higher in patients with SCF when compared with patients with NCF (754.65 ± 238.18 vs. 635.79 ± 108.25, P=0.007). Plasma choline level had significantly positive correlation with Mean TFC (r = 0.364, P=0.002). Receiver operating characteristic (ROC) analysis showed that choline with or without confounding factor adjustment had an AUC score of 0.65 and 0.77, respectively.

Conclusions

TFC were closely related with plasma choline level, and plasma choline can be a suitable and stable diagnostic biomarker for SCF.

Mass Spectrometric Analysis of L-carnitine and its Esters: Potential Biomarkers of Disturbances in Carnitine Homeostasis

PURPOSE

After a golden age of classic carnitine research three decades ago, the spread of mass spectrometry opened new perspectives and a much better understanding of the carnitine system is available nowadays. In the classic period, several human and animal studies were focused on various distinct physiological functions of this molecule and these revealed different aspects of carnitine homeostasis in normal and pathological conditions. Initially, the laboratory analyses were based on the classic or radioenzymatic assays, enabling only the determination of free and total carnitine levels and calculation of total carnitine esters' amount without any information on the composition of the acyl groups. The introduction of mass spectrometry allowed the measurement of free carnitine along with the specific and sensitive determination of different carnitine esters. Beyond basic research, mass spectrometry study of carnitine esters was introduced into the newborn screening program because of being capable to detect more than 30 metabolic disorders simultaneously. Furthermore, mass spectrometry measurements were performed to investigate different disease states affecting carnitine homeostasis, such as diabetes, chronic renal failure, celiac disease, cardiovascular diseases, autism spectrum disorder or inflammatory bowel diseases.

RESULTS

This article will review the recent advances in the field of carnitine research with respect to mass spectrometric analyses of acyl-carnitines in normal and various pathological states.

CONCLUSION

The growing number of publications using mass spectrometry as a tool to investigate normal physiological conditions or reveal potential biomarkers of primary and secondary carnitine deficiencies shows that this tool brought a new perspective to carnitine research.

Gut Microbiota-Dependent Marker TMAO in Promoting Cardiovascular Disease: Inflammation Mechanism, Clinical Prognostic, and Potential as a Therapeutic Target

Cardiovascular disease (CVD) is the leading cause of death worldwide, especially in developed countries, and atherosclerosis (AS) is the common pathological basis of many cardiovascular diseases (CVDs) such as coronary heart disease (CHD). The role of the gut microbiota in AS has begun to be appreciated in recent years. Trimethylamine N-oxide (TMAO), an important gut microbe-dependent metabolite, is generated from dietary choline, betaine, and L-carnitine. Multiple studies have suggested a correlation between plasma TMAO levels and the risk of AS. However, the mechanism underlying this relationship is still unclear. In this review, we discuss the TMAO-involved mechanisms of atherosclerotic CVD from the perspective of inflammation, inflammation-related immunity, cholesterol metabolism, and atherothrombosis. We also summarize available clinical studies on the role of TMAO in predicting prognostic outcomes, including major adverse cardiovascular events (MACE), in patients presenting with AS. Finally, since TMAO may be a novel therapeutic target for AS, several therapeutic strategies including drugs, dietary, etc. to lower TMAO levels that are currently being explored are also discussed.