Tricarboxylic acid cycle related-metabolites and risk of atrial fibrillation and heart failure

Association between sugar-sweetened beverages and pure fruit juice with risk of six cardiovascular diseases: a Mendelian randomization study

BACKGROUND

In observational and prospective cohort studies, intake of sugar-sweetened beverages (SSBs) and pure fruit juice (PFJ) has been associated with cardiovascular disease (CVD). Still, the causality of the connection has not yet been determined. Our objective was to uncover the relationship between SSBs/PFJ and CVD.

METHODS

Genetically predicted causal associations between SSBs/PFJ (obtained in a published genome-wide association study) and six common CVDs (atrial fibrillation (AF), angina, heart failure (HF), acute myocardial infarction, hypertension, and coronary atherosclerosis) were assessed using MR analytic modeling. The primary analysis method utilized was the inverse variance weighted (IVW) method, complemented by additional methods such as the weighted median method, MR Egger regression, Cochran's Q test, MR pleiotropy residual, funnel plot, Bonferroni correction, and others for MR analysis. To ensure the robustness of the findings, F-values were calculated as a complementary test to set looser thresholds for exposing genetic instrumental variables (P < 1e-5).

RESULTS

The results of MR analysis suggested genetically causal associations between SSBs and AF (odds ratio (OR): 1.023; 95% confidence interval (CI) 1.007-1.038; P = 0.0039) as well as between PFJ and angina (OR: 0.968; 95% CI, 0.943-0.993; P = 0.0138) there was genetic causality. However, MR analysis showed no causal association between SSBs/PFJ and other CVD risks.

CONCLUSION

This study suggests that there may be a potential causal relationship between SSBs intake and AF and a causal negative association between PFJ intake and angina.

Integrative analysis of bioinformatics and machine learning to identify cuprotosis-related biomarkers and immunological characteristics in heart failure

Backgrounds

Cuprotosis is a newly discovered programmed cell death by modulating tricarboxylic acid cycle. Emerging evidence showed that cuprotosis-related genes (CRGs) are implicated in the occurrence and progression of multiple diseases. However, the mechanism of cuprotosis in heart failure (HF) has not been investigated yet.

Methods

The HF microarray datasets GSE16499, GSE26887, GSE42955, GSE57338, GSE76701, and GSE79962 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed CRGs between HF patients and nonfailing donors (NFDs). Four machine learning models were used to identify key CRGs features for HF diagnosis. The expression profiles of key CRGs were further validated in a merged GEO external validation dataset and human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, Gene Ontology (GO) function enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and immune infiltration analysis were used to investigate potential biological functions of key CRGs.

Results

We discovered nine differentially expressed CRGs in heart tissues from HF patients and NFDs. With the aid of four machine learning algorithms, we identified three indicators of cuprotosis (DLAT, SLC31A1, and DLST) in HF, which showed good diagnostic properties. In addition, their differential expression between HF patients and NFDs was confirmed through qRT-PCR. Moreover, the results of enrichment analyses and immune infiltration exhibited that these diagnostic markers of CRGs were strongly correlated to energy metabolism and immune activity.

Conclusions

Our study discovered that cuprotosis was strongly related to the pathogenesis of HF, probably by regulating energy metabolism-associated and immune-associated signaling pathways.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Metabolomics of cerebrospinal fluid reveals prognostic biomarkers in pediatric status epilepticus

AIMS

Status epilepticus (SE) is the most common neurological emergency in pediatric patients. This study aimed to screen for prognostic biomarkers of SE in the cerebrospinal fluid (CSF) using metabolomics.

METHODS

Ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC-QTOF-MS) was conducted to identify prognostic biomarkers in CSF metabolomics by comparing the poor outcome group (N = 13) with the good outcome group (N = 15) of children with SE. Differentially expressed metabolites were identified using Mann-Whitney U test corrected by Benjamini-Hochberg and partial least squares discriminant analysis (PLS-DA).

RESULTS

The PLS-DA model identified and validated significant metabolic differences between the poor and good outcome groups of children with SE (PLS-DA with R2 Y = 0.992 and Q2  = 0.798). A total of 49 prognosis-related metabolites were identified. Of these metabolites, 20 including glutamyl-glutamine, 3-iodothyronamine, and L-fucose had an area under the curve (AUC) ≥ 80% in prognostic prediction of SE. The logistic regression model combining glutamyl-glutamine and 3-iodothyronamine produced an AUC value of 0.976, with a sensitivity of 0.863 and specificity of 0.956. Pathway analysis revealed that dysregulation of the citrate cycle (TCA) and arginine biosynthesis may contribute to poor SE prognosis.

CONCLUSIONS

This study highlighted the prognosis-related metabolomic disturbances in the CSF of children with SE and identified potential prognostic biomarkers. A prognostic prediction model combining glutamyl-glutamine and 3-iodothyronamine with high predictive value was established.

Metabolomics profiling of maternal and umbilical cord blood in normoglycemia macrosomia

Background: Macrosomia is a common disorder that occurs during pregnancy. We investigated the comprehensive metabolite profiles of pregnant maternal and fetal sera in normoglycemic macrosomia in a Chinese population. Methods: Forty pregnant women and their fetuses were included in the study (twenty macrosomia patients and twenty normal-weight controls). Maternal and umbilical cord serum metabolites were identified using ultra-performance liquid chromatography coupled with tandem mass spectrometry. Results: In total, 203 metabolites were identified. Lipids and lipid-like molecules were the predominant metabolites. Fifty-three metabolites with significant differences were obtained in the maternal samples. In the macrosomia group, the levels of docosahexaenoic acid, eicosapentaenoic acid, and arachidonic acid were significantly higher than those in the control group. Umbilical cord serum samples were obtained for 24 different metabolites. The maternal-fetal gradient of polyunsaturated fatty acids was decreased in the macrosomia group. Aconitic acid, citric acid, isocitric acid, 2-methylhexanoic acid, and 12-hydroxystearic acid were the common differential metabolites in the maternal and umbilical cord serum samples. Conclusion: There were obvious metabolic abnormalities in the sera of pregnant women and fetuses with macrosomia. Lipids and lipid-like molecules were the predominant differential metabolites but had different classifications in the maternal and umbilical cord serum. These results may provide new insights into the long-term metabolic disorders associated with macrosomia.

Quantitative profiling and diagnostic potential of one-carbon and central metabolism pools in MODY2 and T1DM

BACKGROUND

Maturity-onset diabetes of the young type 2 (MODY2) is a rare genetic disorder characterized as mild fasting hyperglycemia with low risk of vascular complications caused by glucokinase gene mutation. This study aims to investigate metabolites alteration associated with MODY2, exploring possible mechanism underlying characteristic clinical manifestations and low cardiovascular risks of MODY2 and providing serum metabolite biomarkers to facilitating MODY2 diagnosis.

METHODS

Fasting serum samples from MODY2, type 1 diabetes (T1DM) and healthy individuals were collected. By using targeted metabolomics via liquid chromatography-tandem mass spectrometry platform, we quantified the metabolites involved in tricarboxylic acid (TCA) cycle and one-carbon metabolism.

RESULTS

Metabolomic profiling revealed significant difference of intermediates from central metabolism cycle, methionine cycle and several amino acids between MODY2 and T1DM groups. Among these, serum citrate, α-ketoglutaric acid, serine, glycine, glutamine and homocysteine were significantly elevated in MODY2 patients compared with T1DM patients; and compared with healthy subjects, malate and methionine levels were significantly increased in the two groups of diabetic patients. The correlation analysis with clinical indexes showed that α- ketoglutarate, serine, glycine, and glutamine were negatively correlated with blood glucose indicators including fasting blood glucose, HbA1c, and GA, while citrate was positively correlated with C-peptide. And homocysteine displayed positive correlation with HDL and negative with C-reactive protein, which shed light on the mechanism of mild symptoms and low risk of cardiovascular complications in MODY2 patients. A panel of 4 metabolites differentiated MODY2 from T1DM with AUC of 0.924, and a combination of clinical indices and metabolite also gained good diagnostic value with AUC 0.948.

CONCLUSION

In this research, we characterized the metabolite profiles of TCA cycle and one-carbon metabolism in MODY2 and T1DM and identified promising diagnostic biomarkers for MODY2. This study may provide novel insights into the pathogenesis and clinical manifestations of MODY2.

Genome-wide analysis revealed the dysregulation of RNA binding protein-correlated alternative splicing events in myocardial ischemia reperfusion injury

BACKGROUND

Myocardial ischemia reperfusion injury (MIRI), the tissue damage which is caused by the returning of blood supply to tissue after a period of ischemia, greatly reduces the therapeutic effect of treatment of myocardial infarction. But the underlying functional mechanisms of MIRI are still unclear.

METHODS

We constructed mouse models of MIRI, extracted injured and healthy myocardial tissues, and performed transcriptome sequencing experiments (RNA-seq) to systematically investigate the dysregulated transcriptome of MIRI, especially the alternative splicing (AS) regulation and RNA binding proteins (RBPs). Selected RBPs and MIRI-associated AS events were then validated by RT-qPCR experiments.

RESULTS

The differentially expressed gene (DEG) analyses indicated that transcriptome profiles were changed by MIRI and that DEGs' enriched functions were consistent with MIRI's dysregulated pathways. Furthermore, the AS profile was synergistically regulated and showed clear differences between the mouse model and the healthy samples. The exon skipping events significantly increased in MIRI model samples, while the opposite cassette exon events significantly decreased. According to the functional analysis, regulated alternative splicing genes (RASGs) were enriched in protein transport, cell division /cell cycle, RNA splicing, and endocytosis pathways, which were associated with the development of MIRI. Meanwhile, 493 differentially expressed RBPs (DE RBPs) were detected, most of which were correlated with the changed ratios of AS events. In addition, nine DE RBP genes were validated, including Eif5, Pdia6, Tagln2, Vasp, Zfp36l2, Grsf1, Idh2, Ndrg2, and Uqcrc1. These nine DE RBPs were correlated with RASGs enriched in translation process, cell growth and division, and endocytosis pathways, highly consistent with the functions of all RASGs. Finally, we validated the AS ratio changes of five regulated alternative splicing events (RASEs) derived from important regulatory genes, including Mtmr3, Cdc42, Cd47, Fbln2, Vegfa, and Fhl2.

CONCLUSION

Our study emphasized the critical roles of the dysregulated AS profiles in MIRI development, investigated the potential functions of MIRI-associated RASGs, and identified regulatory RBPs involved in AS regulation. We propose that the identified RASEs and RBPs could serve as important regulators and potential therapeutic targets in MIRI treatment in the future.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

Elevated Plasma Levels of Ketone Bodies Are Associated With All-Cause Mortality and Incidence of Heart Failure in Older Adults: The CHS

Background Chronic disease, such as heart failure, influences cellular metabolism and shapes circulating metabolites. The relationships between key energy metabolites and chronic diseases in aging are not well understood. This study aims to determine the relationship between main components of energy metabolism with all-cause mortality and incident heart failure. Methods and Results We analyzed the association between plasma metabolite levels with all-cause mortality and incident heart failure among US older adults in the CHS (Cardiovascular Health Study). We followed 1758 participants without heart failure at baseline with hazard ratios (HRs) of analyte levels and metabolic profiles characterized by high levels of ketone bodies for all-cause mortality and incident heart failure. Multivariable Cox analyses revealed a dose-response relationship of 50% increase in all-cause mortality between lowest and highest quintiles of ketone body concentrations (HR, 1.5 [95% CI, 1.0-1.9]; P=0.007). Ketone body levels remained associated with incident heart failure after adjusting for cardiovascular disease confounders (HR, 1.2 [95% CI, 1.0-1.3]; P=0.02). Using K-means cluster analysis, we identified a cluster with higher levels of ketone bodies, citrate, interleukin-6, and B-type natriuretic peptide but lower levels of pyruvate, body mass index, and estimated glomerular filtration rate. The cluster with elevated ketone body levels was associated with higher all-cause mortality (HR, 1.7 [95% CI, 1.1-2.7]; P=0.01). Conclusions Higher concentrations of ketone bodies predict incident heart failure and all-cause mortality in an older US population, independent of metabolic and cardiovascular confounders. This association suggests a potentially important relationship between ketone body metabolism and aging.

Improving the Data Quality of Untargeted Metabolomics through a Targeted Data-Dependent Acquisition Based on an Inclusion List of Differential and Preidentified Ions

Metabolomics based on high-resolution mass spectrometry has become a powerful technique in biomedical research. The development of various analytical tools and online libraries has promoted the identification of biomarkers. However, how to make mass spectrometry collect more data information is an important but underestimated research topic. Herein, we combined full-scan and data-dependent acquisition (DDA) modes to develop a new targeted DDA based on the inclusion list of differential and preidentified ions (dpDDA). In this workflow, the MS1 datasets for statistical analysis and metabolite preidentification were first obtained using full-scan, and then, the MS/MS datasets for metabolite identification were obtained using targeted DDA of quality control samples based on the inclusion list. Compared with the current methods (DDA, data-independent acquisition, targeted DDA with time-staggered precursor ion list, and iterative exclusion DDA), dpDDA showed better stability, higher characteristic ion coverage, higher differential metabolites' MS/MS coverage, and higher quality MS/MS spectra. Moreover, the same trend was verified in the analysis of large-scale clinical samples. More surprisingly, dpDDA can distinguish patients with different severities of coronary heart disease (CHD) based on the Canadian Cardiovascular Society angina classification, which we cannot distinguish through conventional metabolomics data collection. Finally, dpDDA was employed to differentiate CHD from healthy control, and targeted metabolomics confirmed that dpDDA could identify a more complete metabolic pathway network. At the same time, four unreported potential CHD biomarkers were identified, and the area under the receiver operating characteristic curve was greater than 0.85. These results showed that dpDDA would expand the discovery of biomarkers based on metabolomics, more comprehensively explore the key metabolites and their association with diseases, and promote the development of precision medicine.

Targeting metabolism in aortic aneurysm and dissection: from basic research to clinical applications

Aortic aneurysm and dissection (AAD) are a group of insidious and lethal cardiovascular diseases that characterized by seriously threatening the life and health of people, but lack effective nonsurgical interventions. Alterations in metabolites are increasingly recognized as universal features of AAD because metabolic abnormalities have been identified not only in arterial tissue but also in blood and vascular cells from both patients and animal models with this disease. Over the past few decades, studies have further supported this notion by linking AAD to various types of metabolites such as those derived from gut microbiota or involved in TCA cycle or lipid metabolism. Many of these altered metabolites may contribute to the pathogenesis of AAD. This review aims to illustrate the close association between body metabolism and the occurrence and development of AAD, as well as summarize the significance of metabolites correlated with the pathological process of AAD. This provides valuable insight for developing new therapeutic agents for AAD. Therefore, we present a brief overview of metabolism in AAD biology, including signaling pathways involved in these processes and current clinical studies targeting AAD metabolisms. It is necessary to understand the metabolic mechanisms underlying AAD to provides significant knowledge for AAD diagnosis and new therapeutics for treatment.

The causal effects of genetically determined human blood metabolites on the risk of atrial fibrillation

Background

Blood metabolites have been found related to atrial fibrillation (AF), but the causal role is still unclear. Mendel randomization (MR) can give information about the causality between blood metabolites and AF.

Methods

Two-sample MR analysis was used to evaluate the causality between 486 blood metabolites and AF. Firstly, the genome-wide association study (GWAS) data for AF (from Nielsen et al.) was analyzed and some metabolites were identified. Then another GWAS data for AF (from Roselli et al.) was repeatedly analyzed to verify the results. Inverse variance weighted method was mainly used to determine the causality, and MR-egger, Weighted Median, and MR-PRESSO models were used as supplements of MR. Cochran's Q test was used to assess heterogeneity. And MR-Egger intercept and MR-PRESSO global test were performed to measure pleiotropy.

Results

The study used Bonferroni's corrected P value (P < 1.03 × 10-4) as the significance threshold. After MR analysis and replication analysis, we found two overlapped metabolites. Among which tryptophan betaine was the most significant causal metabolite in both AF GWAS data (from Nielsen et al.) (odds ratio (OR) = 0.83, 95% confidence interval (CI) = 0.76-0.90, P = 9.37 × 10-6) and AF GWAS data (from Roselli et al.) (OR = 0.82, 95% CI = 0.76-0.88, P = 2.00 × 10-7), while uridine was nominally significant metabolites in both AF GWAS data (from Nielsen et al.) (OR = 0.58, 95% CI = 0.40-0.84, P = 0.004) and AF GWAS data (from Roselli et al.) (OR = 0.56, 95% CI = 0.35-0.88, P = 0.01). And the results of sensitivity analysis showed that none of them had obvious heterogeneity or pleiotropy.

Conclusion

The study identified several blood metabolites that were causally related to AF, which may provide new perspectives on the pathogenesis of AF.

TCA cycle metabolites associated with adverse outcomes after acute coronary syndrome: mediating effect of renal function

Aims

To examine relationships of tricarboxylic acid (TCA) cycle metabolites with risk of cardiovascular events and mortality after acute coronary syndrome (ACS), and evaluate the mediating role of renal function in these associations.

Methods

This is a prospective study performed among 309 ACS patients who were followed for a mean of 6.7 years. During this period 131 patients developed major adverse cardiovascular events (MACE), defined as the composite of myocardial infarction, hospitalization for heart failure, and all-cause mortality, and 90 deaths were recorded. Plasma concentrations of citrate, aconitate, isocitrate, succinate, malate, fumarate, α-ketoglutarate and d/l-2-hydroxyglutarate were quantified using LC-tandem MS. Multivariable Cox regression models were used to estimate hazard ratios, and a counterfactual-based mediation analysis was performed to test the mediating role of estimated glomerular filtration rate (eGFR).

Results

After adjustment for traditional cardiovascular risk factors and medications, positive associations were found between isocitrate and MACE (HR per 1 SD, 1.25; 95% CI: 1.03, 1.50), and between aconitate, isocitrate, d/l-2-hydroxyglutarate and all-cause mortality (HR per 1 SD, 1.41; 95% CI: 1.07, 1.84; 1.58; 95% CI: 1.23, 2.02; 1.38; 95% CI: 1.14, 1.68). However, these associations were no longer significant after additional adjustment for eGFR. Mediation analyses demonstrated that eGFR is a strong mediator of these associations.

Conclusion

These findings underscore the importance of TCA metabolites and renal function as conjunctive targets in the prevention of ACS complications.

Microbial metabolites in chronic heart failure and its common comorbidities

This study aimed to identify microbial signatures that contribute to the shared etiologies between chronic heart failure (CHF), type 2 diabetes, and chronic kidney disease. The serum levels of 151 microbial metabolites were measured in 260 individuals from the Risk Evaluation and Management of heart failure cohort, and it was found that those metabolites varied by an order of 10⁵ fold. Out of 96 metabolites associated with the three cardiometabolic diseases, most were validated in two geographically independent cohorts. In all three cohorts, 16 metabolites including imidazole propionate (ImP) consistently showed significant differences. Notably, baseline ImP levels were three times higher in the Chinese compared with the Swedish cohorts and increased by 1.1-1.6 fold with each additional CHF comorbidity in the Chinese population. Cellular experiments further supported a causal link between ImP and distinct CHF relevant phenotypes. Additionally, key microbial metabolite-based risk scores were superior in CHF prognosis than the traditional Framingham or Get with the Guidelines-Heart Failure risk scores. Interactive visualization of these specific metabolite-disease links is available on our omics data server (https://omicsdata.org/Apps/REM-HF/).

Circulating citric acid cycle metabolites and risk of cardiovascular disease in the PREDIMED study

BACKGROUND AND AIM

Plasma citric acid cycle (CAC) metabolites might be likely related to cardiovascular disease (CVD). However, studies assessing the longitudinal associations between circulating CAC-related metabolites and CVD risk are lacking. The aim of this study was to evaluate the association of baseline and 1-year levels of plasma CAC-related metabolites with CVD incidence (a composite of myocardial infarction, stroke or cardiovascular death), and their interaction with Mediterranean diet interventions.

METHODS AND RESULTS

Case-cohort study from the PREDIMED trial involving participants aged 55-80 years at high cardiovascular risk, allocated to MedDiets or control diet. A subcohort of 791 participants was selected at baseline, and a total of 231 cases were identified after a median follow-up of 4.8 years. Nine plasma CAC-related metabolites (pyruvate, lactate, citrate, aconitate, isocitrate, 2-hydroxyglutarate, fumarate, malate and succinate) were measured using liquid chromatography-tandem mass spectrometry. Weighted Cox multiple regression was used to calculate hazard ratios (HRs). Baseline fasting plasma levels of 3 metabolites were associated with higher CVD risk, with HRs (for each standard deviation, 1-SD) of 1.46 (95%CI:1.20-1.78) for 2-hydroxyglutarate, 1.33 (95%CI:1.12-1.58) for fumarate and 1.47 (95%CI:1.21-1.78) for malate (p of linear trend <0.001 for all). A higher risk of CVD was also found for a 1-SD increment of a combined score of these 3 metabolites (HR = 1.60; 95%CI: 1.32-1.94, p trend <0.001). This result was replicated using plasma measurements after one-year. No interactions were detected with the nutritional intervention.

CONCLUSION

Plasma 2-hydroxyglutarate, fumarate and malate levels were prospectively associated with increased cardiovascular risk.

CLINICAL TRIAL NUMBER

ISRCTN35739639.

Ginsenoside Rc ameliorated atherosclerosis via regulating gut microbiota and fecal metabolites

Atherosclerosis (AS) and the accompanied cardiovascular diseases (CVDs) were the leading cause of death worldwide. Recently, the association between CVDs, gut microbiota, and metabolites had aroused increasing attention. In the study, we headed our investigation into the underlying mechanism of ginsenoside Rc (GRc), an active ingredient of ginsenosides used for the treatment of CVDs, in apolipoprotein E-deficient (ApoE^−/−) mice with high-fat diet (HFD). Seven-week-old male ApoE^−/− mice were randomly divided into four groups: the normal control (NC) group, the HFD group, the GRc group (40 mg/kg/d), and the atorvastatin (Ato) group (10 mg/kg/d). Atherosclerotic injury was evaluated by aortic lesions, serum lipid levels, and inflammatory factors. The composition of gut microbiota and fecal metabolite profile were analyzed using 16S rRNA sequence and untargeted metabolomics, respectively. The results showed that GRc significantly alleviated HFD-induced aortic lesions, reduced serum levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), tumor necrosis factor-α (TNF-α), and interleukin (IL)-6 and IL-1β, and increased high-density lipoprotein cholesterol (HFD-C) level, as well as the alteration of gut microbiota composition, function, and metabolite profile. GRc also reversed HFD change of Bacteroidetes and Firmicutes at the phylum level, Muribaculaceae, Lactobacillus, Ileibacterium, Bifidobacterium, Faecalibaculum, Oscillibacter, Blautia, and Eubacterium_coprostanoligenes_group at the genus level, and 23 key metabolites involved in taurine and hypotaurine metabolism, arginine biosynthesis, ATP-binding cassette (ABC) transporters, primary bile acid biosynthesis, purine metabolism, tricarboxylic acid (TCA) cycle, and glucagon signaling pathways. Additionally, eight differential intestinal floras at the genus level were associated with 23 key differential metabolites involving atherosclerotic injury. In conclusion, our results demonstrated that GRc ameliorated atherosclerotic injury, regulated microbial and metabolomic changes in HFD-induced ApoE^−/− mice, and suggested a potential correlation among gut microbiota, metabolites, and atherosclerotic injury regarding the mechanisms of GRc against AS.

Circulating metabolites and molecular lipid species are associated with future cardiovascular morbidity and mortality in type 1 diabetes

Background

Cardiovascular disease remains the leading cause of mortality in individuals with diabetes and improved understanding of its pathophysiology is needed. We investigated the association of a large panel of metabolites and molecular lipid species with future cardiovascular events in type 1 diabetes.

Methods

The study included 669 individuals with type 1 diabetes. Non-targeted serum metabolomics and lipidomics analyses were performed using mass spectrometry. Data on cardiovascular events (cardiovascular mortality, coronary artery disease, stroke, and peripheral arterial interventions) were obtained from Danish Health registries and analyzed by Cox hazards models. Metabolites and molecular lipid species were analyzed in univariate models adjusted for false discovery rate (FDR). Metabolites and molecular lipid species fulfilling a p_FDR < 0.05 were subsequently analyzed in adjusted models including age, sex, hemoglobin A_1c, mean arterial pressure, smoking, body mass index, low-density lipoprotein cholesterol, estimated glomerular filtration rate, urinary albumin excretion rate and previous cardiovascular disease. Analyses of molecular lipid species were further adjusted for triglycerides and statin use.

Results

Of the included participants, 55% were male and mean age was 55 ± 13 years. Higher 4-hydroxyphenylacetic acid (HR 1.35, CI [1.01–1.80], p = 0.04) and lower threonine (HR 0.81, CI [0.67–0.98] p = 0.03) were associated with development of cardiovascular events (n = 95). In lipidomics analysis, higher levels of three different species, diacyl-phosphatidylcholines (PC)(36:2) (HR 0.82, CI [0.70–0.98], p = 0.02), alkyl-acyl-phosphatidylcholines (PC-O)(34:2) (HR 0.76, CI [0.59–0.98], p = 0.03) and (PC-O)(34:3) (HR 0.75, CI [0.58–0.97], p = 0.03), correlated with lower risk of cardiovascular events, whereas higher sphingomyelin (SM)(34:1) (HR 1.32, CI [1.04–1.68], p = 0.02), was associated with an increased risk.

Conclusions

Circulating metabolites and molecular lipid species were associated with future cardiovascular events in type 1 diabetes. While the causal effect of these biomolecules on the cardiovascular system remains unknown, our findings support that omics-based technologies, although still in an early phase, may have the potential to unravel new pathways and biomarkers in the field of cardiovascular disease in type 1 diabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01568-8.

Chronic Hyperglycaemia Inhibits Tricarboxylic Acid Cycle in Rat Cardiomyoblasts Overexpressing Glucose Transporter Type 4

An oversupply of nutrients with a loss of metabolic flexibility and subsequent cardiac dysfunction are hallmarks of diabetic cardiomyopathy. Even if excess substrate is offered, the heart suffers energy depletion as metabolic fluxes are diminished. To study the effects of a high glucose supply, a stably glucose transporter type 4 (GLUT4)-overexpressing cell line presenting an onset of diabetic cardiomyopathy-like phenotype was established. Long-term hyperglycaemia effects were analysed. Rat cardiomyoblasts overexpressing GLUT4 (H9C2KE2) were cultured under normo- and hyperglycaemic conditions for long-term. Expression profiles of several proteins were compared to non-transfected H9C2 cells (H9C2) using RT-qPCR, proteomics-based analysis, or Western blotting. GLUT4 surface analysis, glucose uptake, and cell morphology changes as well as apoptosis/necrosis measurements were performed using flow cytometry. Additionally, brain natriuretic peptide (BNP) levels, reactive oxygen species (ROS) formation, glucose consumption, and lactate production were quantified. Long-term hyperglycaemia in H9C2KE2 cells induced increased GLUT4 presence on the cell surface and was associated with exaggerated glucose influx and lactate production. On the metabolic level, hyperglycaemia affected the tricarboxylic acid (TCA) cycle with accumulation of fumarate. This was associated with increased BNP-levels, oxidative stress, and lower antioxidant response, resulting in pronounced apoptosis and necrosis. Chronic glucose overload in cardiomyoblasts induced by GLUT4 overexpression and hyperglycaemia resulted in metabolically stimulated proteome profile changes and metabolic alterations on the TCA level.