Metabolomics reveal dynamic changes in eicosanoid profile in patients with ST-elevation myocardial infarction after percutaneous coronary intervention

Genetic Evidence for Causal Relationships between Plasma Eicosanoid Levels and Cardiovascular Disease

Cardiovascular diseases are the most common causes of mortality and disability worldwide. Eicosanoids are a group of bioactive metabolites that are mainly oxidized by arachidonic acid. Eicosanoids play a diverse role in cardiovascular diseases, with some exerting beneficial effects while others have detrimental consequences. However, a causal relationship between eicosanoid levels and cardiovascular disease remains unclear. Six single nucleotide polymorphisms (SNPs) with strong associations with plasma eicosanoid levels were selected. Summary-level data for cardiovascular disease were obtained from publicly available genome-wide association studies. A two-sample MR analysis identified that plasma eicosanoid levels were inversely correlated with unstable angina pectoris (OR 1.06; 95% CI 1-1.12; p = 0.04), myocardial infarction (OR 1.05; 95% CI 1.02-1.09; p = 0.005), ischemia stroke (OR 1.05; 95% CI 1-1.11; p = 0.047), transient ischemic attack (OR 1.03; 95% CI 1-1.07; p = 0.042), heart failure (OR 1.03; 95% CI 1.01-1.05; p = 0.011), and pulmonary embolism (OR 1.08; 95% CI 1.02-1.14; p = 1.69 × 10-6). In conclusion, our data strongly suggest a genetic causal link between high plasma eicosanoid levels and an increased cardiovascular disease risk. This study provides genetic evidence for treating cardiovascular diseases.

Dynamic molecular signatures of acute myocardial infarction based on transcriptomics and metabolomics

Acute myocardial infarction (AMI) commonly precedes ventricular remodeling, heart failure. Few dynamic molecular signatures have gained widespread acceptance in mainstream clinical testing despite the discovery of many potential candidates. These unmet needs with respect to biomarker and drug discovery of AMI necessitate a prioritization. We enrolled patients with AMI aged between 30 and 70. RNA-seq analysis was performed on the peripheral blood mononuclear cells collected from the patients at three time points: 1 day, 7 days, and 3 months after AMI. PLC/LC-MS analysis was conducted on the peripheral blood plasma collected from these patients at the same three time points. Differential genes and metabolites between groups were screened by bio-informatics methods to understand the dynamic changes of AMI in different periods. We obtained 15 transcriptional and 95 metabolite expression profiles at three time points after AMI through high-throughput sequencing. AMI-1d: enrichment analysis revealed the biological features of 1 day after AMI primarily included acute inflammatory response, elevated glycerophospholipid metabolism, and decreased protein synthesis capacity. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) might stand promising biomarkers to differentiate post-AMI stage. Anti-inflammatory therapy during the acute phase is an important direction for preventing related pathology. AMI-7d: the biological features of this stage primarily involved the initiation of cardiac fibrosis response and activation of platelet adhesion pathways. Accompanied by upregulated TGF-beta signaling pathway and ECM receptor interaction, GP5 help assess platelet activation, a potential therapeutic target to improve haemostasis. AMI-3m: the biological features of 3 months after AMI primarily showed a vascular regeneration response with VEGF signaling pathway, NOS3 and SHC2 widely activated, which holds promise for providing new therapeutic approaches for AMI. Our analysis highlights transcriptional and metabolomics signatures at different time points after MI, which deepens our understanding of the dynamic biological responses and associated molecular mechanisms that occur during cardiac repair.

Myocardial infarction complexity: A multi-omics approach

Myocardial infarction (MI), a prevalent cardiovascular disease, is fundamentally precipitated by thrombus formation in the coronary arteries, which subsequently decreases myocardial perfusion and leads to cellular necrosis. The intricacy of MI pathogenesis necessitates extensive research to elucidate the disease's root cause, thereby addressing the limitations present in its diagnosis and prognosis. With the continuous advancement of genomics technology, genomics, proteomics, metabolomics and transcriptomics are widely used in the study of MI, which provides an excellent way to identify new biomarkers that elucidate the complex mechanisms of MI. This paper provides a detailed review of various genomics studies of MI, including genomics, proteomics, transcriptomics, metabolomics and multi-omics studies. The metabolites and proteins involved in the pathogenesis of MI are investigated through integrated protein-protein interactions and multi-omics analysis by STRING and Metascape platforms. In conclusion, the future of omics research in myocardial infarction offers significant promise.

Effect of Short-Chain Fatty Acids and Polyunsaturated Fatty Acids on Metabolites in H460 Lung Cancer Cells

Lung cancer is the most common primary malignant lung tumor. However, the etiology of lung cancer is still unclear. Fatty acids include short-chain fatty acids (SCFAs) and polyunsaturated fatty acids (PUFAs) as essential components of lipids. SCFAs can enter the nucleus of cancer cells, inhibit histone deacetylase activity, and upregulate histone acetylation and crotonylation. Meanwhile, PUFAs can inhibit lung cancer cells. Moreover, they also play an essential role in inhibiting migration and invasion. However, the mechanisms and different effects of SCFAs and PUFAs on lung cancer remain unclear. Sodium acetate, butyrate, linoleic acid, and linolenic acid were selected to treat H460 lung cancer cells. Through untargeted metabonomics, it was observed that the differential metabolites were concentrated in energy metabolites, phospholipids, and bile acids. Then, targeted metabonomics was conducted for these three target types. Three LC-MS/MS methods were established for 71 compounds, including energy metabolites, phospholipids, and bile acids. The subsequent methodology validation results were used to verify the validity of the method. The targeted metabonomics results show that, in H460 lung cancer cells incubated with linolenic acid and linoleic acid, while the content of PCs increased significantly, the content of Lyso PCs decreased significantly. This demonstrates that there are significant changes in LCAT content before and after administration. Through subsequent WB and RT-PCR experiments, the result was verified. We demonstrated a substantial metabolic disparity between the dosing and control groups, further verifying the reliability of the method.

Defining Acute Coronary Syndrome through Metabolomics

As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.