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BACKGROUND: Ceramides have recently been identified as novel biomarkers associated with diabetes mellitus (DM) and major adverse cardiac and cerebrovascular events (MACCE). This study aims to explore their utility in diagnosing microvascular disease. METHODS: This study prospectively enrolled 309 patients from 2018 to 2020 into three groups: healthy controls (Group 1, N = 51), DM patients without acute myocardial infarction (AMI) (Group 2, N = 150), and DM patients with AMI (Group 3, N = 108). We assessed outcomes using stress perfusion cardiac magnetic resonance (CMR) imaging for coronary microvascular disease (CMD) (Outcome 1), retinography for retinal microvascular disease (RMD) (Outcome 2), both CMD and RMD (Outcome 3), and absence of microvascular disease (w/o MD) (outcome 4). We evaluated the classification performance of ceramides using receiver operating characteristic (ROC) analysis and multiple logistic regression. 11-ceramide panel previously identified by our research group as related to macrovascular disease were used. RESULTS: Average glycated hemoglobin (HbA1c) values were 5.1% in Group 1, 8.3% in Group 2, and 7.6% in Group 3. Within the cohort, CMD was present in 59.5% of patients, RMD in 25.8%, both CMD and RMD in 18.8%, and w/o MD in 38.5%. The AUC values for the reference ceramide ratios were as follows: CMD at 0.66 (p = 0.012), RMD at 0.61 (p = 0.248), CMD & RMD at 0.64 (p = 0.282), and w/o MD at 0.67 (p = 0.010). In contrast, the AUC values using 11-ceramide panel showed significant improvement in the outcomes prediction: CMD at 0.81 (p = 0.001), RMD at 0.73 (p = 0.010), CMD & RMD at 0.73 (p = 0.04), and w/o MD at 0.83 (p = 0.010). Additionally, the plasma concentration of C14.0 was notably higher in the w/o MD group (p < 0.001). CONCLUSIONS: Plasma ceramides serve as potential predictors for health status and microvascular disease phenotypes in diabetic patients.

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O infarto agudo do miocárdio (IAM) é a maior causa de mortalidade no mundo. A oclusão coronária determina a necrose completa de cardiomiócitos (células musculares cardíacas) durante as primeiras horas do IAM. Porém, mesmo após a perda de massa de miocárdio viável cessar, a região infartada pode se expandir ou contrair no decorrer das primeiras semanas, afetando o prognóstico dos pacientes. Alguns tratamentos podem auxiliar na recuperação e melhoria do prognóstico desses pacientes, como o uso de estatinas e antiplaquetários, que quando utilizados em conjunto, proporcionam efeitos sinérgicos. O presente estudo investigou e comparou, através da óptica da metabolômica global multiplataforma, tratamentos concomitantes de estatinas (sinvastatina ou rosuvastatina) e antiplaquetários bloqueadores do receptor de ADP (clopidogrel ou ticagrelor), em pacientes que sofreram IAM. Foram coletadas amostras de plasma e urina de cerca 40 pacientes tratados com clopidrogrel e sinvastatina ou ticagrelor e rosuvastatina no Hospital São Paulo em diferentes períodos (basal, 1 mês e 6 meses após IAM). Amostras de plasma (basal e 1 mês) foram analisadas por RPLC-MS nos modos de ionização positivo e negativo, GC-MS e CEMS. Amostras de urina (basal, 1 mês e 6 meses) foram analisadas por RPLC-MS no modo de ionização positivo e HILIC-MS nos modos de ionização positivo e negativo. A abordagem metabolomica global multiplataforma evidenciou alterações no metabolismo de diferentes vias pelos dois tratamentos. Os dois tratamentos proporcionaram um efeito pronunciado no metabolismo de diferentes lipídios, como glicerolipídios, esfingolipídios, glicerofosfolipídios e ácidos graxos, sendo que a combinação rosuvastatina e ticagrelor resultou num efeito mais acentuado. Já o tratamento com clopidogrel e sinvastatina alterou de maneira mais pronunciada o metabolismo de aminoácidos ramificados e de acilcarnitinas de cadeia curta. Observou-se ainda a alteração de possíveis biomarcadores relatados na literatura como associados a problemas cardiovasculares, como hipoxantina, ácido 2-hidroxibutírico, algumas espécies de ceramidas, fosfatidilcolinas e acilcarnitinas de cadeia curta

cute myocardium infarction (AMI) is the main mortality cause in the world. The coronary occlusion determines the complete necrosis of cardiomyocytes (cardiac muscle cells) during the first hours of AMI. However, even after the loss of viable myocardial mass ceases, the infarcted area may still expand or contract during the first weeks after AMI, affecting the patient prognosis. Some treatments may assist patient recovery and improve prognostic, such as statins and antiplatelets which, when combined, provide synergic effects. This study investigated and compared, by untargeted multiplatform metabolomics, simultaneous treatments of statins (simvastatin or rosuvastatin) and ADP receptor antagonist antiplatelets (clopidogrel or ticagrelor) in patients that suffered AMI. Plasma and urine samples from around 40 patients treated with clopidogrel and simvastatin or ticagrelor and rosuvastatin were collected in Hospital Sao Paulo at different time points (basal, 1 month, 6 months after AMI). Plasma samples (basal and 1 month) were analyzed by RPLC-MS in positive and negative ionization modes, GC-MS and CE-MS. Urine samples (basal, 1 month, 6 months) were analyzed by RPLC-MS in positive ionization mode and by HILIC-MS in positive and negative ionization modes. The untargeted multiplatform metabolomics approach has shown that different metabolic pathways have been altered by the two treatments. Both treatments had a profound impact on the metabolism of different lipids, such as glycerolipids, sphingolipids, glycerophospholipids, and fatty acids. However, the combined treatment using rosuvastatin and ticagrelor impacted the most the lipid pathways. On the other hand, clopidogrel and simvastatin treatment affected more intensily the branched chain amino acids and short chain acylcarnitines metabolisms. Reported biomarkers in the literature related to cardiovascular diseases were also observed in this study, such as hypoxanthine, 2-hydroxybutyric acid, some species of ceramides, phosphatidylcholines and short chain acylcarnitines

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For cardiovascular disease prevention, statins alone or combined with ezetimibe have been recommended to achieve low-density lipoprotein cholesterol targets, but their effects on other lipids are less reported. This study was designed to examine lipid changes in subjects with ST-segment elevation myocardial infarction (STEMI) after two highly effective lipid-lowering therapies. Twenty patients with STEMI were randomized to be treated with rosuvastatin 20 mg QD or simvastatin 40 mg combined with ezetimibe 10 mg QD for 30 days. Fasting blood samples were collected on the first day (D1) and after 30 days (D30). Lipidomic analysis was performed using the Lipidyzer platform. Similar classic lipid profile was obtained in both groups of lipid-lowering therapies. However, differences with the lipidomic analysis were observed between D30 and D1 for most of the analyzed classes. Differences were noted with lipid-lowering therapies for lipids such as FA, LPC, PC, PE, CE, Cer, and SM, notably in patients treated with rosuvastatin. Correlation studies between classic lipid profiles and lipidomic results showed different information. These findings seem relevant, due to the involvement of these lipid classes in crucial mechanisms of atherosclerosis, and may account for residual cardiovascular risk.Randomized clinical trial: ClinicalTrials.gov, NCT02428374, registered on 28/09/2014.

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Altered cell metabolism is a hallmark of cancer and critical for its development. Particularly, activation of one-carbon metabolism in tumor cells can sustain oncogenesis while contributing to epigenetic changes and metabolic adaptation during tumor progression. We assessed whether increased one-carbon metabolism activity is a metabolic feature of invasive ductal carcinoma (IDC). Differences in the metabolic profile between biopsies from IDC (n = 47) and its adjacent tissue (n = 43) and between biopsies from different breast cancer subtypes were assessed by gas spectrometry in targeted (Biocrates Life Science ® ) and untargeted approaches, respectively. The metabolomics data were statistically treated using MetaboAnalyst 4.0, SIMCA P+ (version 12.01), Statistica 10 software and t test with p < 0.05. The Cancer Genome Atlas breast cancer dataset was also assessed to validate the metabolomic profile of IDC. Our targeted metabolomics analysis showed distinct metabolomics profiles between IDC and adjacent tissue, where IDC displayed a comparative enrichment of metabolites involved in one-carbon metabolism (serine, glycine, threonine, and methionine) and a predicted increase in the activity of pathways that receive and donate carbon units (i.e., folate, methionine, and homocysteine). In addition, the targeted and untargeted metabolomics analyses showed similar metabolomics profiles between breast cancer subtypes. The gene set enrichment analysis identified different transcription-related functions between IDC and non-tumor tissues that involved one-carbon metabolism. Our data suggest that one-carbon metabolism may be a central pathway in IDC and even in general breast tumors, representing a potential target for its treatment and prevention.

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Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

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