Orbitrap-MS-based untargeted metabolomics study on the therapeutic effect of colchicine on myocardial infarction

Integration of metabolomics and network pharmacology to reveal the protective mechanism underlying Wogonoside in acute myocardial ischemia rats

ETHNOPHARMACOLOGICAL RELEVANCE

In traditional medicine, both Scutellaria baicalensis Georgi (SBG) and the traditional formulas composed of it have been used to treat a wide range of diseases, including cancer and cardiovascular. Wogonoside (Wog) is the biologically active flavonoid compound extracted from the root of SBG, with potential cardiovascular protective effects. However, the mechanisms underlying the protective effect of Wog on acute myocardial ischemia (AMI) have not yet been clearly elucidated.

AIM OF THE STUDY

To explore the protective mechanism of Wog on AMI rats by comprehensively integrating traditional pharmacodynamics, metabolomics, and network pharmacology.

METHODS

The rat was pretreatment with Wog at a dose of 20 mg/kg/d and 40 mg/kg/d once daily for 10 days and then ligated the left anterior descending coronary artery of rats to establish the AMI rat model. Electrocardiogram (ECG), cardiac enzyme levels, heart weight index (HWI), Triphenyltetrazolium chloride (TTC) staining, and histopathological analyses were adopted to evaluate the protective effect of Wog on AMI rats. Moreover, a serum metabolomic-based UHPLC-Q-Orbitrap MS approach was performed to find metabolic biomarkers and metabolic pathways, and network pharmacology analysis was applied to predict targets and pathways of Wog in treating AMI. Then, the network pharmacology and metabolomic results were integrated to elucidate the mechanism of Wog in treating AMI. Finally, RT- PCR was used to detect the mRNA expression levels of PTGS1, PTGS2, ALOX5, and ALOX15 to validate the result of integrated metabolomics and network analysis.

RESULTS

Pharmacodynamic studies suggest that Wog could effectively prevent the ST-segment of electrocardiogram elevation, reduce the myocardial infarct size, heart weight index, and cardiac enzyme levels, and alleviate cardiac histological damage in AMI rats. Metabolomics analysis showed that the disturbances of metabolic profile in AMI rats were partly corrected by Wog and the cardio-protection effects on AMI rats involved 32 differential metabolic biomarkers and 4 metabolic pathways. In addition, the integrated analysis of network pharmacology and metabolomics showed that 7 metabolic biomarkers, 6 targets, and 6 crucial pathways were the main mechanism for the therapeutic application of Wog for AMI. Moreover, the results of RT-PCR showed that PTGS1, PTGS2, ALOX5, and ALOX15 mRNA expression levels were reduced after treatment with Wog.

CONCLUSION

Wog exerts cardio-protection effects on AMI rats via the regulation of multiple metabolic biomarkers, multiple targets, and multiple pathways, our current study will provide strong scientific evidence supporting the therapeutic application of Wog for AMI.

From multi-omics approaches to personalized medicine in myocardial infarction

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.

The involvement of gut microbiota in the anti-tumor effect of carnosic acid via IL-17 suppression in colorectal cancer

Colorectal cancer (CRC) is a malignant tumor that threatens human health worldwide. Disturbance of the gut microbiota caused by various external factors is one of the leading causes. Carnosic acid (CA) is a phenolic diterpene compound, mainly isolated from rosemary plants, with anti-inflammatory and anti-tumor properties. In this study, we aimed to investigate the role of CA in CRC development and its underlying mechanisms in B6/JGpt-Apc^em1Cin(min)/Gpt (Apc^Min/+) mice based on the analysis of gut microbiota, serum metabolomics, and tumor proteomics. Enzyme-linked immunosorbent assay (ELISA) and Western blot were performed to confirm the changes in cytokine and protein levels related to inflammation after CA administration. CA regulated the abundance of the gut microbiota, which further caused changes in the production of dl-lactic acid. CA suppressed the inflammatory response by reducing the levels of IL-1β, -6, and -17A. Overall, CA showed anti-CRC properties via modulation of gut microbiota and serum metabolites through NF-κB/STAT3 signaling to inhibit IL-17 expression in Apc^Min/+ mice. These results provide experimental evidence for the future treatment of CRC with CA.

Cross-comparative metabolomics reveal sex-age specific metabolic fingerprints and metabolic interactions in acute myocardial infarction

The elucidation of metabolic perturbations and gender-age-specific metabolic characteristics associated with acute myocardial infarction (AMI) is essential for clinical risk stratification and disease management. A comprehensive cross-comparative metabolomics analysis was performed on the sera from 445 healthy controls, 347 AMI patients without cardiovascular disease (CVD), 79 AMI with CVD (AMICVD) patients including 27 deaths. Machine-learning-based integrated biomarker profiling and global network analysis were used to create a multi-biomarker for distinguishing the different AMI outcomes. The changes of most metabolites were dependent on AMI, but gender and age also give additional contributions to the changes of histidine, malonate, O-acetyl-glycoprotein and trimethylamine N-oxide. The altered metabolic pathways included gut dysbiosis, increased amino acid metabolism, glucose metabolism and ketone metabolism, and inactivation of tricarboxylic acid cycle. Enhanced histidine metabolism and microbiota dysbiosis may be one of the key factors during the developing of AMI into AMICVD. For the differential diagnosis of AMI events, three sets of specific multi-biomarkers provided relatively high accuracy with the areas under the curve more than 0.8 and hazard ratio more than 1 in the discovery set, and the results were reproduced and confirmed by the validation set. First use of cross-comparative metabolomics and machine-learning-based integrated biomarker analysis gives great capability to discriminate the different AMI outcomes. Also, the multi-biomarkers seem to be a valid and accurate auxiliary diagnosis biomarker in addition to standard stratification based on clinical parameters.