Blood metabolomic fingerprint is distinct in healthy coronary and in stenosing or microvascular ischemic heart disease

The Associations of Genetically Predicted Plasma Alanine with Coronary Artery Disease and its Risk Factors: A Mendelian Randomization Study

BACKGROUND

Alanine is an amino acid commonly used as a nutritional supplement and plays a key role in the glucose-alanine cycle. Plasma alanine has been associated in observational studies with a higher risk of coronary artery disease (CAD) and unhealthier lipid profiles. However, evidence from large randomized controlled trials is lacking.

OBJECTIVES

Using Mendelian randomization (MR), we assessed the unconfounded associations of plasma alanine with CAD and CAD risk factors.

METHODS

We applied single nucleotide polymorphisms that were strongly (P < 5 ×10-8) associated with plasma alanine as genetic instruments to large genome-wide association studies of CAD (63,108 cases; 296,901 controls), diabetes (90,612 cases; 583,493 controls), glucose (515,538 participants), lipids (low-density lipoprotein [LDL] cholesterol, high-density lipoprotein [HDL] cholesterol, triglycerides, total cholesterol, and apolipoprotein B) (>1.1 million participants), blood pressure (BP) (757,601 participants), and body mass index (682,137 participants). Given the potential sex disparity, we also conducted sex-specific analyses. MR estimates per standard deviation increase in alanine concentrations were obtained using inverse variance weighting followed by sensitivity analyses using weighted median, MR-Egger, MR-Pleiotropy RESidual Sum and Outlier, and MR-Robust Adjusted Profile Score.

RESULTS

Genetically predicted plasma alanine was not associated with CAD but with a higher risk of diabetes (odds ratio [OR]: 1.35; 95% confidence interval [CI]: 1.06, 1.72), higher glucose (β: 0.11; 95% CI: 0.02, 0.19), LDL cholesterol (β: 0.08; 95% CI: 0.04, 0.12), triglycerides (β: 0.25; 95% CI: 0.13, 0.38), total cholesterol (β: 0.14; 95% CI: 0.08, 0.20), apolipoprotein B (β: 0.12; 95% CI: 0.03, 0.21), and BP (β: 1.17; 95% CI: 0.31, 2.04 for systolic BP: β: 0.97; 95% CI: 0.49, 1.45 for diastolic BP) overall. The positive associations of serum alanine with LDL cholesterol and triglycerides were more notable in women than in men.

CONCLUSIONS

Alanine or factors affecting alanine may have causal effects on diabetes, blood glucose, lipid profiles, and BP but not on CAD. Further studies are needed to clarify possible mechanisms.

Causal relationships of circulating amino acids with cardiovascular disease: a trans-ancestry Mendelian randomization analysis

BACKGROUND

Epidemiological studies demonstrated that multiple amino acids (AAs) were associated with cardiovascular diseases (CVDs), but whether these associations were causal remains unclear. This study aims to investigate the causal relationships between circulating levels of 20 AAs and 10 CVDs in European and East Asian populations by Mendelian randomization (MR).

METHODS

This MR study utilized single-nucleotide polymorphisms that were significantly associated with AAs as instrumental variables. Summary-level data for AAs and CVDs were obtained from public genome-wide association studies. The causal effects were primarily estimated by inverse variance weighting with multiplicative random effect method. Sensitivity analyses, including weighted median, weighted mode, and MR Egger regression, were used to test the robustness of our results.

RESULTS

In the European population, alanine and serine were inversely associated with angina pectoris (AP) and chronic heart failure, respectively. With each unit increase of leucine, the risk of ischemic stroke increased by 10%. Moreover, tyrosine was positively associated with AP and deep vein thrombosis. In the East Asian population, each unit increase in glycine was associated with 4.1% and 9.0% decreased risks of coronary artery disease (CAD) and myocardial infarction (MI), respectively. A unit increase in serine was associated with 13.1%, 12.6% and 15.5% decreased risks of AP, CAD and MI, respectively. Sensitivity analyses supported the robustness of our results.

CONCLUSIONS

This MR study demonstrated significant causal effects of circulating levels of AAs on CVDs, indicating the potential use of AAs as biomarkers or as therapeutic targets for CVD in clinical scenarios.

Interstage Single Ventricle Heart Disease Infants Show Dysregulation in Multiple Metabolic Pathways: Targeted Metabolomics Analysis

BACKGROUND

Infants with SVHD experience morbidity related to pulmonary vascular inadequacy. Metabolomic analysis involves a systems biology approach to identifying novel biomarkers and pathways in complex diseases. The metabolome of infants with SVHD is not well understood and no prior study has evaluated the relationship between serum metabolite patterns and pulmonary vascular readiness for staged SVHD palliation.

OBJECTIVES

The purpose of this study was to evaluate the circulating metabolome of interstage infants with single ventricle heart disease (SVHD) and determine whether metabolite levels were associated with pulmonary vascular inadequacy.

METHODS

This was a prospective cohort study of 52 infants with SVHD undergoing Stage 2 palliation and 48 healthy infants. Targeted metabolomic phenotyping (175 metabolites) was performed by tandem mass spectrometry on SVHD pre-Stage 2, post-Stage 2, and control serum samples. Clinical variables were extracted from the medical record.

RESULTS

Random forest analysis readily distinguished between cases and controls and preoperative and postoperative samples. Seventy-four of 175 metabolites differed between SVHD and controls. Twenty-seven of 39 metabolic pathways were altered including pentose phosphate and arginine metabolism. Seventy-one metabolites differed in SVHD patients between timepoints. Thirty-three of 39 pathways were altered postoperatively including arginine and tryptophan metabolism. We found trends toward increased preoperative methionine metabolites in patients with higher pulmonary vascular resistance and higher postoperative tryptophan metabolites in patients with greater postoperative hypoxemia.

CONCLUSIONS

The circulating metabolome of interstage SVHD infants differs significantly from controls and is further disrupted after Stage 2. Several metabolites showed trends toward association with adverse outcomes. Metabolic dysregulation may be an important factor in early SVHD pathobiology.

Understanding How Heart Metabolic Derangement Shows Differential Stage Specificity for Heart Failure with Preserved and Reduced Ejection Fraction

Heart failure (HF) is a clinical condition defined by structural and functional abnormalities in the heart that gradually result in reduced cardiac output (HFrEF) and/or increased cardiac pressures at rest and under stress (HFpEF). The presence of asymptomatic individuals hampers HF identification, resulting in delays in recognizing patients until heart dysfunction is manifested, thus increasing the chance of poor prognosis. Given the recent advances in metabolomics, in this review we dissect the main alterations occurring in the metabolic pathways behind the decrease in cardiac function caused by HF. Indeed, relevant preclinical and clinical research has been conducted on the metabolite connections and differences between HFpEF and HFrEF. Despite these promising results, it is crucial to note that, in addition to identifying single markers and reliable threshold levels within the healthy population, the introduction of composite panels would strongly help in the identification of those individuals with an increased HF risk. That said, additional research in the field is required to overcome the current drawbacks and shed light on the pathophysiological changes that lead to HF. Finally, greater collaborative data sharing, as well as standardization of procedures and approaches, would enhance this research field to fulfil its potential.

Why Do High-Risk Patients Develop or Not Develop Coronary Artery Disease? Metabolic Insights from the CAPIRE Study

Traditional cardiovascular (CV) risk factors (RFs) and coronary artery disease (CAD) do not always show a direct correlation. We investigated the metabolic differences in a cohort of patients with a high CV risk profile who developed, or did not develop, among those enrolled in the Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation (CAPIRE) study. We studied 112 subjects with a high CV risk profile, subdividing them according to the presence (CAD/High-RFs) or absence of CAD (No-CAD/High-RFs), assessed by computed tomography angiography. The metabolic differences between the two groups were identified by gas chromatography-mass spectrometry. Characteristic patterns and specific metabolites emerged for each of the two phenotypic groups: high concentrations of pyruvic acid, pipecolic acid, p-cresol, 3-aminoisobutyric acid, isoleucine, glyceric acid, lactic acid, sucrose, phosphoric acid, trimethylamine-N-oxide, 3-hydroxy-3-methylglutaric acid, erythritol, 3-hydroxybutyric acid, glucose, leucine, and glutamic acid; and low concentrations of cholesterol, hypoxanthine, glycerol-3-P, and cysteine in the CAD/High-RFs group vs the No-CAD/High-RFs group. Our results show the existence of different metabolic profiles between patients who develop CAD and those who do not, despite comparable high CV risk profiles. A specific cluster of metabolites, rather than a single marker, appears to be able to identify novel predisposing or protective mechanisms towards CAD beyond classic CVRFs.

Metabolic profiling links cardiovascular risk and vascular end organ damage

BACKGROUND AND AIMS

An untargeted metabolomics approach allows for a better understanding and identification of new candidate metabolites involved in the etiology of vascular disease. We aimed to investigate the associations of cardiovascular (CV) risk factors with the metabolic fingerprint and macro- and microvascular health in an untargeted metabolomic approach in predefined CV risk groups of aged individuals.

METHODS

The metabolic fingerprint and the macro- and microvascular health from 155 well-characterized aged (50-80 years) individuals, based on the EXAMIN AGE study, were analysed. Nuclear magnetic resonance spectroscopy was used to analyse the metabolic fingerprint. Carotid-femoral pulse wave velocity and retinal vessel diameters were assessed to quantify macro- and microvascular health.

RESULTS

The metabolic fingerprint became more heterogeneous with an increasing number of risk factors. There was strong evidence for higher levels of glutamine [estimate (95% CI): -14.54 (-17.81 to -11.27), p < 0.001], glycine [-5.84 (-7.88 to -3.79), p < 0.001], histidine [-0.73 (-0.96 to -0.50), p < 0.001], and acetate [-1.68 (-2.91 to -0.46), p = 0.007] to be associated with a lower CV risk profile. Tryptophan, however, was positively associated with higher CV risk [0.31 (0.06-0.56), p = 0.015]. The combination of a priori defined CV risk factors explained up to 45.4% of the metabolic variation. The metabolic fingerprint explained 20% of macro- and 23% of microvascular variation.

CONCLUSIONS

Metabolic profiling has the potential to improve CV risk stratification by identifying new underlying metabolic pathways associated with atherosclerotic disease development, from cardiovascular risk to metabolites, to vascular end organ damage.

Metabolomic correlates of coronary atherosclerosis, cardiovascular risk, both or neither. Results of the 2 × 2 phenotypic CAPIRE study

BACKGROUND

Traditional cardiovascular risk factors (RFs) and coronary artery disease (CAD) do not always run parallel. We investigated functional-metabolic correlations of CAD, RFs, or neither in the CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation) 2 × 2 phenotypic observational study.

METHODS

Two hundred and fortyone subjects were included based on RF burden, presence/absence of CAD (assessed by computed tomography angiography), age and sex. Participants displayed one of four phenotypes: CAD with ≥3 RFs, no-CAD with ≥3 RFs, CAD with ≤1 RF and no-CAD with ≤1 RF. Metabolites were identified by gas chromatography-mass spectrometry and pathways by metabolite set enrichment analysis.

RESULTS

Characteristic patterns and specific pathways emerged for each phenotypic group: amino sugars for CAD/high-RF; urea cycle for no-CAD/high-RF; glutathione for CAD/low-RF; glycine and serine for no-CAD/low-RF. Presence of CAD correlated with ammonia recycling; absence of CAD with the transfer of acetyl groups into mitochondria; high-risk profile with alanine metabolism (all p < 0.05). The comparative case-control analyses showed a statistically significant difference for the two pathways of phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism in the CAD/Low-RF vs NoCAD/Low-RF comparison.

CONCLUSIONS

The present 2 × 2 observational study identified specific metabolic pathways for each of the four phenotypes, providing novel functional insights, particularly on CAD with low RF profiles and on the absence of CAD despite high-risk factor profiles.

Comparing Levels of Metabolic Predictors of Coronary Heart Disease between Healthy Lean and Overweight Females

Screening for the metabolomic signature of coronary heart disease (CHD) before disease onset could help in early diagnosis and potentially disease prevention. In this study, the levels of 17 CHD metabolic biomarkers in apparently healthy overweight females were compared to lean counterparts, and their associations with conventional clinical risk factors were determined. Clinical and metabolic data from 200 apparently healthy non-obese Qatari females were collected from Qatar Biobank (discovery cohort). Logistic regression was used to assess the association between body mass index (BMI) groups and 17 CHD metabolic biomarkers, and receiver operating characteristic (ROC) analysis was used to evaluate the prognostic value of CHD metabolic biomarkers in overweight. Stepwise linear regression was performed to identify the classical risk factors associated with CHD metabolites differentiating the two BMI groups. Validation of the association of CHD metabolic biomarkers with BMI groups was performed in 107 subjects (replication cohort). Out of the tested CHD metabolic biomarkers, five were significantly different between lean and overweight females in the discovery cohort (AUC = 0.73). Among these, the association of mannose, asparagine, and linoleate with BMI groups was confirmed in the replication cohort (AUC = 0.97). Significant correlations between predictors of CHD in overweight healthy women and classical risk factors were observed, including serum levels of cholesterol, testosterone, triiodothyronine, thyroxine, creatinine, albumin, bilirubin, glucose, c-peptide, uric acid, calcium and chloride. Apparently, healthy overweight females exhibit significantly different levels of specific CHD metabolites compared to their lean counterparts, offering a prognostic potential with preventative value.

Metabolite Profiling of Osteoporosis and Atherosclerosis in Postmenopausal Women: A Cross-Sectional Study

Purpose

Atherosclerosis (AS) and osteoporosis (OP) are common causes of morbidity and mortality in postmenopausal women and are connected via an unknown mechanistic link. Metabolite profiling of blood samples may allow the identification of new biomarkers and pathways for this enigmatic association.

Patients and Methods

We studied the difference in 148 metabolite levels from serum samples in postmenopausal women with AS and OP compared with those in healthy participants in this cross-sectional study. Quantitative AS was assessed by carotid artery intima-media thickness (cIMT) and carotid artery calcifications (CACs) by ultrasound, as well as OP by femoral neck (FN) bone mineral density (BMD) and 148 metabolic measures with high-throughput proton (¹H) nuclear magnetic resonance (NMR) in serum samples from 280 postmenopausal (PM) women. Subjects were a randomly selected subsample from the population-based Kuopio Osteoporosis Risk Factor and Prevention (OSTPRE) study. The final study population included the following groups: OP with CAC (n=16, group I), non-OP with no CAC (n=59, group II), high cIMT tertile with OP (n=11, group III) and low cIMT tertile without OP (n=48, group IV).

Results

There were differences in several metabolite levels between groups I and II. The acetate level was lower in group I compared to that in group II (group I mean ± SD: 0.033 ± 0.0070; group II: 0.041 ± 0.014, CI95%: 0.018‒0.15, p=0.014). The result was similar with diacylglycerol (p=0.002), leucine (p=0.031), valine (p=0.022) and several very low-density lipoprotein (VLDL) metabolite levels, which were lower in group I compared to those in group II. However, no associations were found in adjusted analyses with total body (TB) fat mass (FM), age and statin use (p>0.05).

Conclusion

Our novel study found differences in the metabolite profiling of altered amino acid and lipoprotein metabolism in participants with OP and AS compared with those in healthy women. The causative mechanisms remain unknown and further studies are needed.

Urinary metabolic signatures reflect cardiovascular risk in the young, middle-aged, and elderly populations

The predictive value of traditional cardiovascular risk estimators is limited, and young and elderly populations are particularly underrepresented. We aimed to investigate the urine metabolome and its association with cardiovascular risk to identify novel markers that might complement current estimators based on age. Urine samples were collected from 234 subjects categorized into three age-grouped cohorts: 30-50 years (cohort I, young), 50-70 years (cohort II, middle-aged), and > 70 years (cohort III, elderly). Each cohort was further classified into three groups: (a) control, (b) individuals with cardiovascular risk factors, and (c) those who had a previous cardiovascular event. Novel urinary metabolites linked to cardiovascular risk were identified by nuclear magnetic resonance in cohort I and then evaluated by target mass spectrometry quantification in all cohorts. A previously identified metabolic fingerprint associated with atherosclerosis was also analyzed and its potential risk estimation investigated in the three aged cohorts. Three different metabolic signatures were identified according to age: 2-hydroxybutyrate, gamma-aminobutyric acid, hypoxanthine, guanidoacetate, oxaloacetate, and serine in young adults; citrate, cyclohexanol, glutamine, lysine, pantothenate, pipecolate, threonine, and tyramine shared by middle-aged and elderly adults; and trimethylamine N-oxide and glucuronate associated with cardiovascular risk in all three cohorts. The urinary metabolome contains a metabolic signature of cardiovascular risk that differs across age groups. These signatures might serve to complement existing algorithms and improve the accuracy of cardiovascular risk prediction for personalized prevention. KEY MESSAGES: • Cardiovascular risk in the young and elderly is underestimated. • The urinary metabolome reflects cardiovascular risk across all age groups. • Six metabolites constitute a metabolic signature of cardiovascular risk in young adults. • Middle-aged and elderly adults share a cardiovascular risk metabolic signature. • TMAO and glucuronate levels reflect cardiovascular risk across all age groups.

Exploring the protective effects of schizandrol A in acute myocardial ischemia mice by comprehensive metabolomics profiling integrated with molecular mechanism studies

Schizandrol A (SA) is an bioactive component isolated from the Schisandra chinensis (Turcz.) Baill., which has been used as a remedy to prevent oxidative injury. However, whether the cardioprotective effect of SA is associated with regulating endogenous metabolites remains unclear, thus we performed comprehensive metabolomics profiling in acute myocardial ischemia (AMI) mice following SA treatment. AMI was induced in ICR mice by coronary artery ligation, then SA (6 mg·kg⁻¹·d⁻¹, ip) was administered. SA treatment significantly decreased the infarct size, preserved the cardiac function, and improved the biochemical indicators and cardiac pathological alterations. Moreover, SA (10, 100 M) significantly decreased the apoptotic index in OGD-treated H8c2 cardiomycytes in vitro. By using HPLC-Q-TOF/MS, we conducted metabonomics analysis to screen the significantly changed endogenous metabolites and construct the network in both serum and urine. The results revealed that SA regulated the pathways of glycine, serine and threonine metabolism, lysine biosynthesis, pyrimidine metabolism, arginine and proline metabolism, cysteine and methionine metabolism, valine, leucine and isoleucine biosynthesis under the pathological conditions of AMI. Furthermore, we selected the regulatory enzymes related to heart disease, including ecto-5’-nucleotidase (NT5E), guanidinoacetate N-methyltransferase (GAMT), platelet-derived endothelial cell growth factor (PD-ECGF) and methionine synthase (MTR), for validation. In addition, SA was found to facilitate PI3K/Akt activation and inhibit the expression of NOX2 in AMI mice and OGD-treated H9c2 cells. In conclusion, we have elucidated SA-regulated endogenous metabolic pathways and constructed a regulatory metabolic network map. Furthermore, we have validated the new potential therapeutic targets and underlying molecular mechanisms of SA against AMI, which might provide a reference for its future application in cardiovascular diseases.

Metabolomic Profile in HFpEF vs HFrEF Patients

BACKGROUND

Heart failure with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF) are associated with metabolic derangements, which may have different pathophysiological implications.

METHODS AND RESULTS

In new-onset HFpEF (EF of ≥50%, n = 46) and HFrEF (EF of <40%, n = 75) patients, 109 endogenous plasma metabolites including amino acids, phospholipids and acylcarnitines were assessed using targeted metabolomics. Differentially altered metabolites and associations with clinical characteristics were explored. Patients with HFpEF were older, more often female with hypertension, atrial fibrillation, and diabetes compared with patients with HFrEF. Patients with HFpEF displayed higher levels of hydroxyproline and symmetric dimethyl arginine, alanine, cystine, and kynurenine reflecting fibrosis, inflammation and oxidative stress. Serine, cGMP, cAMP, l-carnitine, lysophophatidylcholine (18:2), lactate, and arginine were lower compared with patients with HFrEF. In patients with HFpEF with diabetes, kynurenine was higher (P = .014) and arginine lower (P = .014) vs patients with no diabetes, but did not differ with diabetes status in HFrEF. Decreasing kynurenine was associated with higher eGFR only in HFpEF (P_interaction = .020).

CONCLUSIONS

Patients with new-onset HFpEF compared with patients with new-onset HFrEF display a different metabolic profile associated with comorbidities, such as diabetes and kidney dysfunction. HFpEF is associated with indices of increased inflammation and oxidative stress, impaired lipid metabolism, increased collagen synthesis, and downregulated nitric oxide signaling. Together, these findings suggest a more predominant systemic microvascular endothelial dysfunction and inflammation linked to increased fibrosis in HFpEF compared with HFrEF.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT03671122 https://clinicaltrials.gov.

Metabolomics and its application in the treatment of coronary heart disease with traditional Chinese medicine

Traditional Chinese Medicine (TCM) is the treasure of Chinese Nation and gained the gradual acceptance of the international community. However, the methods and theories of TCM understanding of diseases are lack of appropriate modern scientific characterization systems. Moreover, traditional risk factors cannot promote to detection and prevent those patients with coronary artery disease (CAD) who have not developed acute myocardial infarction (MI) in time. To sum up, there is still no objective systematic evaluation system for the therapeutic mechanism of TCM in the prevention and cure of cardiovascular disease. Thus, new ideas and technologies are needed. The development of omics technology, especially metabolomics, can be used to predict the level of metabolites in vivo and diagnose the physiological state of the body in time to guide the corresponding intervention. In particular, metabolomics is also a very powerful tool to promote the modernization of TCM and the development of TCM in personalized medicine. This article summarized the application of metabolomics in the early diagnosis, the discovery of biomarkers and the treatment of TCM in CAD.

Identification and Validation of Plasma Metabolomics Reveal Potential Biomarkers for Coronary Heart Disease

Coronary heart disease (CHD) is a prevalent and chronic life-threatening disease. However, there is no reliable way for early diagnosis and prevention of CHD so far. The precise molecular pathological mechanism of CHD remains obscure. Therefore, developing novel biomarkers is urgently needed.In order to evaluate the potential of untargeted plasma metabolomics in biomarker discovery for characterizing CHD, plasma metabolites from patients newly diagnosed with CHD and controls were profiled using liquid chromatography quadrupole time-of-flight mass spectrometry. Differential metabolites were identified using both univariate and multivariate statistical analyses. Metabolites with significant changes were subjected to binary logistic regression analysis, and a CHD prediction model was established. A total of 28 differential plasma metabolites were identified, of which the concentrations of 11 increased significantly and those of 17 decreased significantly in patients with CHD compared with controls. The altered metabolic pathways included reduced phospholipid metabolism, increased monoglyceride metabolism, and abnormal fatty acid metabolism. Furthermore, binary logistic regression showed that nine metabolites could be used as potential plasma biomarkers for the diagnosis of CHD. The prediction model based on these nine metabolites was then tested with an independent cohort of samples (area under the curve = 0.929).Our plasma metabolomics study not only yielded fundamental insights into dysregulated metabolism in CHD but also presented a combinatorial biomarker that might support the clinical diagnosis of CHD.

Application of NMR metabolomics to search for human disease biomarkers in blood

Recently, nuclear magnetic resonance spectroscopy (NMR)-based metabolomics analysis and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The purpose of these efforts is to identify unique metabolite biomarkers in a specific human disease so as to (1) accurately predict and diagnose diseases, including separating distinct disease stages; (2) provide insights into underlying pathways in the pathogenesis and progression of the malady and (3) aid in disease treatment and evaluate the efficacy of drugs. In this review we discuss recent developments in the application of NMR-based metabolomics in searching disease biomarkers in human blood samples in the last 5 years.

Aryl hydrocarbon receptor activation mediates kidney disease and renal cell carcinoma

The aryl hydrocarbon receptor (AhR) is a well-known ligand-activated cytoplasmic transcription factor that contributes to cellular responses against environmental toxins and carcinogens. AhR is activated by a range of structurally diverse compounds from the environment, microbiome, natural products, and host metabolism, suggesting that AhR possesses a rather promiscuous ligand binding site. Increasing studies have indicated that AhR can be activated by a variety of endogenous ligands and induce the expression of a battery of genes. AhR regulates a variety of physiopathological events, including cell proliferation, differentiation, apoptosis, adhesion and migration. These new roles have expanded our understanding of the AhR signalling pathways and endogenous metabolites interacting with AhR under homeostatic and pathological conditions. Recent studies have demonstrated that AhR is linked to cardiovascular disease (CVD), chronic kidney disease (CKD) and renal cell carcinoma (RCC). In this review, we summarize gut microbiota-derived ligands inducing AhR activity in patients with CKD, CVD, diabetic nephropathy and RCC that may provide a new diagnostic and prognostic approach for complex renal damage. We further highlight polyphenols from natural products as AhR agonists or antagonists that regulate AhR activity. A better understanding of structurally diverse polyphenols and AhR biological activities would allow us to illuminate their molecular mechanism and discover potential therapeutic strategies targeting AhR activation.

Metabolomic fingerprint of coronary blood in STEMI patients depends on the ischemic time and inflammatory state

In this study we investigated whether the metabolomic analysis could identify a specific fingerprint of coronary blood collected during primary PCI in STEMI patients. Fifteen samples was subjected to metabolomic analysis. Subsequently, the study population was divided into two groups according to the peripheral blood neutrophil-to-lymphocyte ratio (NLR), a marker of the systemic inflammatory response. Regression analysis was then applied separately to the two NLR groups. A partial least square (PLS) regression identified the most significant involved metabolites and the PLS-class analysis revealed a significant correlation between the metabolic profile and the total ischemic time only in patients with an NLR > 5.77.