Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos

BACKGROUND

Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD.

RESULTS

We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD.

CONCLUSION

In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BACKGROUND

Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.

METHODS

We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.

RESULTS

Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.

CONCLUSIONS

By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

Targeted Metabolomic Profiling of Dapagliflozin in Heart Failure With Preserved Ejection Fraction: The PRESERVED-HF Trial

BACKGROUND

Although sodium glucose co-transporter 2 inhibitors (SGLT2is) improve heart failure (HF)-related symptoms and outcomes in HF with preserved ejection fraction (HFpEF), underlying mechanisms remain unclear. In HF with reduced EF, dapagliflozin altered ketone and fatty acid metabolites vs placebo; however, metabolite signatures of SGLT2is have not been well elucidated in HFpEF.

OBJECTIVES

The goal of this study was to assess whether SGLT2i treatment altered systemic metabolic pathways and their relationship to outcomes in HFpEF.

METHODS

Targeted profiling of 64 metabolites was performed from 293 participants in PRESERVED-HF (Dapagliflozin in PRESERVED Ejection Fraction Heart Failure), a 12-week, placebo-controlled trial of dapagliflozin. Linear regression assessed changes in metabolite factors defined by principal components analysis (PCA) with dapagliflozin vs placebo. The relationship between changes in metabolite factors with changes in study endpoints was also assessed.

RESULTS

The mean age was 70 ± 11 years, 58% were female, and 29% were Black. There were no significant differences in 12 PCA-derived metabolite factors between treatment arms, including metabolites reflecting ketone, fatty acid, or branched-chain amino acid (BCAA) pathways. Combining treatment arms, changes in BCAAs and branched-chain ketoacids were negatively associated with changes in N-terminal pro-B-type natriuretic peptide; changes in medium-/long-chain acylcarnitines were positively associated with changes in N-terminal pro-B-type natriuretic peptide and negatively associated with changes in 6-minute walk test distance; and changes in ketones were negatively associated with changes in weight, without treatment interaction.

CONCLUSIONS

Leveraging targeted metabolomics in a placebo-controlled SGLT2i trial of HFpEF, dapagliflozin did not alter systemic metabolic as reflected by circulating metabolites, in contrast with reported effects in HF with reduced ejection fraction. Metabolite biomarkers reflecting BCAA, ketone, and fatty acid metabolism were associated with markers of disease severity, suggesting a role for potential novel treatment targets. (Dapagliflozin in PRESERVED Ejection Fraction Heart Failure [PRESERVED-HF]; NCT03030235).

Divergent Survival Outcomes Associated with Elevated Branched-Chain Amino Acid Levels among Older Adults with or without Hypertension and Diabetes: A Validated, Prospective, Longitudinal Follow-Up Study

Branched-chain amino acids are critical metabolic intermediates that can indicate increased risk of cardiometabolic disease when levels are elevated or, alternatively, suggest sufficient mitochondrial energy metabolism and reserve in old age. The interpretation of BCAA levels can be context-dependent, and it remains unclear whether abnormal levels can inform prognosis. This prospective longitudinal study aimed to determine the interrelationship between mortality hazard and fasting serum BCAA levels among older men and women aged ≥65 years with or without hypertension and diabetes mellitus. At baseline (0Y), fasting serum BCAA concentration in 2997 community-living older men and women were measured. Approximately 14 years later (14Y), 860 study participants returned for repeat measurements. Deaths were analysed and classified into cardiovascular and non-cardiovascular causes using International Classification of Diseases codes. Survival analysis and multivariable Cox regression were performed. During a median follow-up of 17Y, 971 (78.6%) non-cardiovascular and 263 (21.4%) cardiovascular deaths occurred among 1235 (41.2%) deceased (median age, 85.8 years [IQR 81.7-89.7]). From 0Y to 14Y, BCAA levels declined in both sexes, whereas serum creatinine concentration increased (both p < 0.0001). In older adults without hypertension or diabetes mellitus, the relationship between mortality hazard and BCAA level was linear and above-median BCAA levels were associated with improved survival, whereas in the presence of cardiometabolic disease the relationship was U-shaped. Overall, adjusted Cox regression determined that each 10% increment in BCAA concentration was associated with a 7% (p = 0.0002) and 16% (p = 0.0057) reduction in mortality hazard estimated at 0Y and 14Y, respectively. Our findings suggested that abnormally high or low (dyshomeostatic) BCAA levels among older adults with hypertension and/or diabetes mellitus were associated with increased mortality, whereas in those with neither disease, increased BCAA levels was associated with improved survival, particularly in the oldest-old.

Mortality and Major Adverse Cardiac Events in Patients With Breast Cancer Receiving Radiotherapy: The First Decade

Background Treatment for breast cancer (BC) frequently involves radiotherapy. Guidelines recommend screening for cardiac adverse events starting 10 years after radiotherapy. The rationale for this interval is unclear. Methods and Results We aimed to study cardiovascular event rates in the first decade following curative radiotherapy for BC. We compared mortality and cardiovascular event rates with an age- and risk factor-matched control population. We included 1095 patients with BC (mean age 56±12 years). Two hundred and eighteen (19.9%) women died. Cancer and cardiovascular mortality caused 107 (49.1%) and 22 (10.1%) deaths, respectively. A total of 904 cases were matched to female FLEMENGHO (Flemish Study on Environment, Genes and Health Outcomes) participants. Coronary artery disease incidence was similar (risk ratio [RR], 0.75 [95% CI, 0.48-1.18]), yet heart failure (RR, 1.97 [95% CI, 1.19-3.25]) and atrial fibrillation/flutter (RR, 1.82 [95% CI, 1.07-3.08]) occurred more often in patients with BC. Age (hazard ratio [HR], 1.033 [95% CI, 1.006-1.061], P=0.016), tumor grade (HR, 1.739 [95% CI, 1.166-2.591], P=0.007), and neoadjuvant treatment setting (HR, 2.782 [95% CI, 1.304-5.936], P=0.008) were risk factors for mortality. Risk factors for major adverse cardiac events were age (HR, 1.053 [95% CI, 1.013-1.093]; P=0.008), mean heart dose (HR, 1.093 [95% CI, 1.025-1.167]; P=0.007), history of cardiovascular disease (HR, 2.386 [95% CI, 1.096-6.197]; P=0.029) and Mayo Clinic Cardiotoxicity Risk Score (HR, 2.664 [95% CI, 1.625-4.367]; P<0.001). Conclusions Ten-year mortality following curative treatment for unilateral BC was mainly cancer related, but heart failure and atrial fibrillation/flutter were already common in the first decade following irradiation. Mean heart dose, pre-existing cardiovascular diseases, and Mayo Clinic Cardiotoxicity Risk Score were risk factors for cardiac adverse events. These results suggest a need for early dedicated cardio-oncological follow-up after radiotherapy.

Cardiovascular risk of metabolically healthy obesity in two european populations: Prevention potential from a metabolomic study

BACKGROUND

A new definition of metabolically healthy obesity (MHO) has recently been proposed to stratify the heterogeneous mortality risk of obesity. Metabolomic profiling provides clues to metabolic alterations beyond clinical definition. We aimed to evaluate the association between MHO and cardiovascular events and assess its metabolomic pattern.

METHODS

This prospective study included Europeans from two population-based studies, the FLEMENGHO and the Hortega study. A total of 2339 participants with follow-up were analyzed, including 2218 with metabolomic profiling. Metabolic health was developed from the third National Health and Nutrition Examination Survey and the UK biobank cohorts and defined as systolic blood pressure < 130 mmHg, no antihypertensive drugs, waist-to-hip ratio < 0.95 for women or 1.03 for men, and the absence of diabetes. BMI categories included normal weight, overweight, and obesity (BMI < 25, 25-30, ≥ 30 kg/m²). Participants were classified into six subgroups according to BMI category and metabolic healthy status. Outcomes were fatal and nonfatal composited cardiovascular events.

RESULTS

Of 2339 participants, the mean age was 51 years, 1161 (49.6%) were women, 434 (18.6%) had obesity, 117 (5.0%) were classified as MHO, and both cohorts had similar characteristics. Over a median of 9.2-year (3.7-13.0) follow-up, 245 cardiovascular events occurred. Compared to those with metabolically healthy normal weight, individuals with metabolic unhealthy status had a higher risk of cardiovascular events, regardless of BMI category (adjusted HR: 3.30 [95% CI: 1.73-6.28] for normal weight, 2.50 [95% CI: 1.34-4.66] for overweight, and 3.42 [95% CI: 1.81-6.44] for obesity), whereas those with MHO were not at increased risk of cardiovascular events (HR: 1.11 [95% CI: 0.36-3.45]). Factor analysis identified a metabolomic factor mainly associated with glucose regulation, which was associated with cardiovascular events (HR: 1.22 [95% CI: 1.10-1.36]). Individuals with MHO tended to present a higher metabolomic factor score than those with metabolically healthy normal weight (0.175 vs. -0.057, P = 0.019), and the score was comparable to metabolically unhealthy obesity (0.175 vs. -0.080, P = 0.91).

CONCLUSIONS

Individuals with MHO may not present higher short-term cardiovascular risk but tend to have a metabolomic pattern associated with higher cardiovascular risk, emphasizing a need for early intervention.

Branched-chain amino acids in cardiovascular disease

Research conducted in the past 15 years has yielded crucial insights that are reshaping our understanding of the systems physiology of branched-chain amino acid (BCAA) metabolism and the molecular mechanisms underlying the close relationship between BCAA homeostasis and cardiovascular health. The rapidly evolving literature paints a complex picture, in which numerous tissue-specific and disease-specific modes of BCAA regulation initiate a diverse set of molecular mechanisms that connect changes in BCAA homeostasis to the pathogenesis of cardiovascular diseases, including myocardial infarction, ischaemia-reperfusion injury, atherosclerosis, hypertension and heart failure. In this Review, we outline the current understanding of the major factors regulating BCAA abundance and metabolic fate, highlight molecular mechanisms connecting impaired BCAA homeostasis to cardiovascular disease, discuss the epidemiological evidence connecting BCAAs with various cardiovascular disease states and identify current knowledge gaps requiring further investigation.

Association between Excessive Dietary Branched-Chain Amino Acids Intake and Hypertension Risk in Chinese Population

The dietary intake of branched-chain amino acids (BCAAs) has been reported to be associated with both elevated blood pressure (BP) and hypertension risk, while published findings were inconsistent, and the causality has never been well disclosed. We performed this prospective study aiming to find out the relationship between dietary BCAAs intake and hypertension risk in the Chinese population. A total of 8491 participants (40,285 person-years) were selected. The levels of dietary BCAAs intake were estimated using the 24-h Food Frequency Questionnaire. Associations of both BP values and hypertension risk with per standard deviation increase of BCAAs were estimated using linear and COX regression analysis, respectively. The hazard ratios and 95% confidence interval were given. Restricted cubic spline analysis (RCS) was used to estimate the nonlinearity. Both systolic and diastolic BP values at the end points of follow-up were positively associated with dietary BCAAs intake. Positive associations between BCAAs intake and hypertension risk were shown in both men and women. By performing a RCS analysis, the nonlinear relationship between BCAAs intake and hypertension was shown. As the intake levels of Ile, Leu, and Val, respectively, exceeded 2.49 g/day, 4.91 g/day, and 2.88 g/day in men (2.16 g/day, 3.84 g/day, and 2.56 g/day in women), the hypertension risk increased. Our findings could provide some concrete evidence in the primary prevention of hypertension based on dietary interventions.

Urinary peptidomic profiles to address age-related disabilities: a prospective population study

BACKGROUND

The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 called for innovation in addressing age-related disabilities. Our study aimed to identify and validate a urinary peptidomic profile (UPP) differentiating healthy from unhealthy ageing in the general population, to test the UPP predictor in independent patient cohorts, and to search for targetable molecular pathways underlying age-related chronic diseases.

METHODS

In this prospective population study, we used data from participants in the Flemish Study on Environment, Genes and Health Outcomes (FLEMENGHO), done in northern Belgium from 1985 to 2019, and invited participants to a follow-up examination in 2005-10. Participants were eligible if their address was within 15 km of the examination centre and if they had not withdrawn consent in any of the previous examination cycles (1985-2004). All participants (2005-10) were also invited to an additional follow-up examination in 2009-13. Participants who took part in both the 2005-10 follow-up examination and in the additional 2009-13 follow-up visit constituted the derivation dataset, which included their 2005-10 data, and the time-shifted internal validation dataset, which included their 2009-13 data. The remaining participants who only had 2005-10 data constituted the synchronous internal validation dataset. Participants were excluded from analyses if they were incapacitated, had not undergone UPP, or had either missing or outlying (three SDs greater than the mean of all consenting participants) values of body-mass index, plasma glucose, or serum creatinine. The UPP was assessed by capillary electrophoresis coupled with mass spectrometry. The multidimensional UPP signature reflecting ageing was generated from the derivation dataset and validated in the time-shifted internal validation dataset and the synchronous validation dataset. It was further validated in patients with diabetes, COVID-19, or chronic kidney disease (CKD). In FLEMENGHO, the mortality endpoints were all-cause, cardiovascular, and non-cardiovascular mortality; other endpoints were fatal or non-fatal cancer and musculoskeletal disorders. Molecular pathway exploration was done using the Reactome and Kyoto Encyclopedia of Genes and Genomes databases.

FINDINGS

778 individuals (395 [51%] women and 383 [49%] men; aged 16·2-82·1 years; mean age 50·9 years [SD 15·8]) from the FLEMENGHO cohort had a follow-up examination between 2005 and 2010, of whom 559 participants had a further follow-up from Oct 28, 2009, to March 19, 2013, and made up the derivation (2005-10) and time-shifted internal validation (2009-13) datasets. 219 were examined once and constituted the synchronous internal validation dataset (2005-10). With correction for multiple testing and multivariable adjustment, chronological age was associated with 210 sequenced peptides mainly showing downregulation of collagen fragments. The trained model relating chronological age to UPP, derived by elastic net regression, included 54 peptides from 17 proteins. The UPP-age prediction model explained 76·3% (r=0·87) of chronological age in the derivation dataset, 54·4% (r=0·74) in the time-shifted validation dataset, and 65·3% (r=0·81) in the synchronous internal validation dataset. Compared with chronological age, the predicted UPP-age was greater in patients with diabetes (chronological age 50·8 years [SE 0·37] vs UPP-age 56·9 years [0·30]), COVID‑19 (53·2 years [1·80] vs 58·5 years [1·67]), or CKD (54·6 years [0·97] vs 62·3 years [0·85]; all p<0·0001). In the FLEMENGHO cohort, independent of chronological age, UPP-age was significantly associated with various risk markers related to cardiovascular, metabolic, and renal disease, inflammation, and medication use. Over a median of 12·4 years (IQR 10·8-13·2), total mortality, cardiovascular mortality, and osteoporosis in the population was associated with UPP-age independent of chronological age, with hazard ratios per 10 year increase in UPP-age of 1·54 (95% CI 1·22-1·95) for total mortality, 1·72 (1·20-2·47) for cardiovascular mortality, and 1·40 (1·06-1·85) for osteoporosis and fractures. The most relevant molecular pathways informed by the proteins involved deregulation of collagen biology and extracellular matrix maintenance.

INTERPRETATION

The UPP signature indicative of ageing reflects fibrosis and extracellular matrix remodelling and was associated with risk factors and adverse health outcomes in the population and with accelerated ageing in patients. Innovation in addressing disability should shift focus from the ontology of diseases to shared disease mechanisms, in particular ageing-related fibrotic degeneration.

FUNDING

European Research Council, Ministry of the Flemish Community, OMRON Healthcare.

Serum metabolites of hypertension among Chinese adolescents aged 12-17 years

The regulatory mechanisms of hypertension in youth are incompletely understood. We aimed to identify potential serum metabolic alterations associated with hypertension in adolescents. A 1:1 age- and sex-matched case-control study including 30 hypertensive adolescents aged 12-17 years and 30 normotensive adolescents for the training set and 14 hypertensive adolescents and 14 normotensive adolescents for the test set was performed, which came from one cross-sectional study in Ningxia, China. Hypertension was defined based on blood pressure (BP) values measured on three different occasions according to the BP reference of Chinese children and adolescents. Untargeted ultra-high-performance liquid tandem chromatography quadrupole time of flight mass spectrometry was used to identify differential metabolites between hypertensive and normotensive adolescents. A total of 77 metabolites in positive mode and 101 in negative mode were identified (VIP > 1.0 and P < 0.05). After adjustment for the false discovery rate, 4 differential metabolites in positive mode and 10 in negative mode were found (Q value < 0.05). The logistic regression model adjusted for body mass index and lipid profile selected four significant metabolites (4-hydroxybutanoic acid, L-serine, acetone, and pterostilbene). The main metabolic pathways of amino acid metabolism, pantothenate and CoA biosynthesis, glyoxylate and dicarboxylate metabolism, fructose and mannose metabolism, and linoleic acid metabolism may contribute to the development of hypertension in Chinese adolescents. Based on the receiver operating characteristic plot, 4-hydroxybutanoic acid, L-serine, acetone, and pterostilbene may preliminarily help distinguish hypertension from normal BP in adolescents, with AUC values of 0.857 in the training set and 0.934 in the test set. The identified metabolites and pathways may foster a better understanding of hypertension pathogenesis in Chinese adolescents.

Sex differences in the longitudinal relationship of low-grade inflammation and echocardiographic measures in the Hoorn and FLEMENGHO Study

Background

This study aimed to determine the within-person and between-persons associations of low-grade inflammation (LGI) and endothelial dysfunction (ED) with echocardiographic measures related to diastolic dysfunction (DD) in two general populations and whether these associations differed by sex.

Methods

Biomarkers and echocardiographic measures were measured at both baseline and follow-up in the Hoorn Study (n = 383) and FLEMENGHO (n = 491). Individual biomarker levels were combined into either a Z-score of LGI (CRP, SAA, IL-6, IL-8, TNF-α and sICAM-1) or ED (sICAM-1, sVCAM-1, sE-selectin and sTM). Mixed models were used to determine within-person and between-persons associations of biomarker Z-scores with left ventricular ejection fraction (LVEF), left ventricular mass index (LVMI) and left atrial volume index (LAVI). These associations were adjusted for a-priori selected confounders.

Results

Overall Z-scores for LGI or ED were not associated with echocardiographic measures. Effect modification by sex was apparent for ED with LVEF in both cohorts (P-for interaction = 0.08 and 0.06), but stratified results were not consistent. Effect modification by sex was apparent for TNF-α in the Hoorn Study and E-selectin in FLEMENGHO with LVEF (P-for interaction≤0.05). In the Hoorn Study, women whose TNF-α levels increased with 1-SD over time had a decrease in LVEF of 2.2 (-4.5;0.01) %. In FLEMENGHO, men whose E-selectin levels increased with 1-SD over time had a decrease in LVEF of 1.6 (-2.7;-0.5) %.

Conclusion

Our study did not show consistent associations of LGI and ED with echocardiographic measures. Some evidence of effect modification by sex was present for ED and specific biomarkers.

Metabolomic Analysis of the Ameliorative Effect of Enhanced Proline Metabolism on Hypoxia-Induced Injury in Cardiomyocytes

Background

Coronary heart disease is currently the leading cause of death in humans. Its poor prognosis and high mortality are associated with myocardial ischemia, which leads to metabolic disorder-related cardiomyocyte apoptosis and reactive oxygen species (ROS) production. Previous cardiovascular metabolomics studies in humans and mice have shown that proline metabolism is severely altered after cardiomyocyte hypoxia. Proline dehydrogenase (PRODH) is located on the inner mitochondrial membrane and is an enzyme that catalyzes the first step of proline catabolism, which plays an important role in improving the cellular redox state. In vitro oxygen-glucose deprivation can mimic in vivo myocardial ischemic injury. This study is aimed at investigating whether enhancing proline metabolism by overexpressing PRODH can ameliorate hypoxia-induced injury in cardiomyocytes and to reveal the related altered metabolites and mechanistic pathway via untargeted metabolomics analysis.

Methods and Results

First, through public database analysis and RT-qPCR and western blot analyses in a cardiomyocyte hypoxia model, we found that the expression of the proline-degrading enzyme PRODH was downregulated after myocardial infarction and hypoxia exposure. Second, LDH assays, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL), DHE staining, flow cytometric apoptosis analysis with DCFH and Annexin V-FITC/PI, and western blot analysis were used to assess the injury level in cardiomyocytes. Enhanced proline metabolism induced by PRODH overexpression reduced the levels of reactive oxidative stress and apoptosis, whereas PRODH knockdown had the opposite effects. Third, untargeted metabolomics analysis revealed that the protective effect was associated with significant changes in metabolism linked to sphingolipid signaling pathways, unsaturated fatty acid biosynthesis, phosphocreatine, glutathione disulfide, aminoacyl-tRNA biosynthesis, and ABC transporters.

Conclusions

Our study demonstrated a protective effect of enhanced proline metabolism in cardiomyocytes under hypoxia, providing a novel strategy for exploring new treatments for coronary heart disease.

Exploring the mechanism underlying the cardioprotective effect of shexiang baoxin pill on acute myocardial infarction rats by comprehensive metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Shexiang Baoxin Pill (SBP) is a commercial Chinese medicine included in the Chinese Pharmacopoeia with well-established cardiovascular protect effect in clinic. However, the mechanism of SBP underlying protective effect on cardiovascular disease has not been clearly elucidated yet.

AIM OF THE STUDY

We aimed to investigate the underlying protective mechanisms of SBP on an acute myocardial infarction (AMI) rat model by using comprehensive metabolomics.

MATERIALS AND METHODS

The rat model of AMI was generated by ligating the left anterior descending coronary artery. After two weeks of treatment with SBP, comprehensive metabolomics and echocardiography index was performed for a therapeutic evaluation. The wiff data were processed using Progenesis QI and metabolites were identified based on the database of HMDB and LIPIDMAPS. Meanwhile, the untargeted metabolomics data from LC-MS combined with correlation analysis to characterize the metabolic alterations.

RESULTS

The metabolomics profiles of different groups in different biological samples (heart, serum, urine and feces) were significantly different, in which a total of 217 metabolites were identified. AMI caused comprehensive metabolic changes in amino acid metabolism, glycerophospholipid metabolism and pyrimidine metabolism, while SBP reversed more than half of the differential metabolic changes, mainly affecting amino acid metabolism, butanoate metabolism and glycerophospholipid metabolism. Correlation analysis found that SBP could significantly alter the metabolic activity of six key metabolites (5-hydroxyindoleacetic acid, glycerophosphocholine, PS (20:4/0:0), xanthosine, adenosine and L-phenylalanine) related to AMI. The key role of these metabolites was further validated with correlation analysis with echocardiography indexes.

CONCLUSION

This study demonstrated that SBP was effective for protecting cardiac dysfunction by regulating amino acid, lipid and energy metabolisms. The results also suggested that the modulation on gut microbiota might be involved the cardioprotective effect of SBP.

Novel Findings From a Metabolomics Study of Left Ventricular Diastolic Function: The Bogalusa Heart Study

Background

Diastolic dysfunction is one important causal factor for heart failure with preserved ejection fraction, yet the metabolic signature associated with this subclinical phenotype remains unknown.

Methods and Results

Ultra‐high‐performance liquid chromatography–tandem mass spectroscopy was used to conduct untargeted metabolomic analysis of fasting serum samples in 1050 white and black participants of the BHS (Bogalusa Heart Study). After quality control, 1202 metabolites were individually tested for association with 5 echocardiographic measures of left ventricular diastolic function using multivariable‐adjusted linear regression. Measures of left ventricular diastolic function included the ratio of peak early filling velocity to peak late filling velocity, ratio of peak early filling velocity to mitral annular velocity, deceleration time, isovolumic relaxation time, and left atrial maximum volume index (LAVI). Analyses adjusted for multiple cardiovascular disease risk factors and used Bonferroni‐corrected alpha thresholds. Eight metabolites robustly associated with left ventricular diastolic function in the overall population and demonstrated consistent associations in white and black study participants. N‐formylmethionine (B=0.05; P=1.50×10⁻⁷); 1‐methylhistidine (B=0.05; P=1.60×10⁻⁷); formiminoglutamate (B=0.07; P=5.60×10⁻⁷); N2, N5‐diacetylornithine (B=0.05; P=1.30×10⁻⁷); N‐trimethyl 5‐aminovalerate (B=0.04; P=5.10×10⁻⁶); 5‐methylthioadenosine (B=0.04; P=1.40×10⁻⁵); and methionine sulfoxide (B=0.04; P=3.80×10⁻⁶) were significantly associated with the natural log of the ratio of peak early filling velocity to mitral annular velocity. Butyrylcarnitine (B=3.18; P=2.10×10⁻⁶) was significantly associated with isovolumic relaxation time.

Conclusions

The current study identified novel findings of metabolite associations with left ventricular diastolic function, suggesting that the serum metabolome, and its underlying biological pathways, may be implicated in heart failure with preserved ejection fraction pathogenesis.

Integrated Metabolomics-DNA Methylation Analysis Reveals Significant Long-Term Tissue-Dependent Directional Alterations in Aminoacyl-tRNA Biosynthesis in the Left Ventricle of the Heart and Hippocampus Following Proton Irradiation

In this study, an untargeted metabolomics approach was used to assess the effects of proton irradiation (1 Gy of 150 MeV) on the metabolome and DNA methylation pattern in the murine hippocampus and left ventricle of the heart 22 weeks following exposure using an integrated metabolomics-DNA methylation analysis. The integrated metabolomics-DNA methylation analysis in both tissues revealed significant alterations in aminoacyl-tRNA biosynthesis, but the direction of change was tissue-dependent. Individual and total amino acid synthesis were downregulated in the left ventricle of proton-irradiated mice but were upregulated in the hippocampus of proton-irradiated mice. Amino acid tRNA synthetase methylation was mostly downregulated in the hippocampus of proton-irradiated mice, whereas no consistent methylation pattern was observed for amino acid tRNA synthetases in the left ventricle of proton-irradiated mice. Thus, proton irradiation causes long-term changes in the left ventricle and hippocampus in part through methylation-based epigenetic modifications. Integrated analysis of metabolomics and DNA methylation is a powerful approach to obtain converging evidence of pathways significantly affected. This in turn might identify biomarkers of the radiation response, help identify therapeutic targets, and assess the efficacy of mitigators directed at those targets to minimize, or even prevent detrimental long-term effects of proton irradiation on the heart and the brain.