[The role of lipid metabolism in the prevention of coronary heart disease]

Exploring biological basis of Syndrome differentiation in coronary heart disease patients with two distinct Syndromes by integrated multi-omics and network pharmacology strategy

Background

Traditional Chinese Medicine (TCM) is distinguished by Syndrome differentiation, which prescribes various formulae for different Syndromes of same disease. This study aims to investigate the underlying mechanism.

Methods

Using a strategy which integrated proteomics, metabolomics study for clinic samples and network pharmacology for six classic TCM formulae, we systemically explored the biological basis of TCM Syndrome differentiation for two typical Syndromes of CHD: Cold Congealing and Qi Stagnation (CCQS), and Qi Stagnation and Blood Stasis (QSBS).

Results

Our study revealed that CHD patients with CCQS Syndrome were characterized with alteration in pantothenate and CoA biosynthesis, while more extensively altered pathways including D-glutamine and D-glutamate metabolism; alanine, aspartate and glutamate metabolism, and glyoxylate and dicarboxylate metabolism, were present in QSBS patients. Furthermore, our results suggested that the down-expressed PON1 and ADIPOQ might be potential biomarkers for CCQS Syndrome, while the down-expressed APOE and APOA1 for QSBS Syndrome in CHD patients. In addition, network pharmacology and integrated analysis indicated possible comorbidity differences between the two Syndromes, that is, CCQS or QSBS Syndrome was strongly linked to diabetes or ischemic stroke, respectively, which is consistent with the complication disparity between the enrolled patients with two different Syndromes. These results confirmed our assumption that the molecules and biological processes regulated by the Syndrome-specific formulae could be associated with dysfunctional objects caused by the Syndrome of the disease.

Conclusion

This study provided evidence-based strategy for exploring the biological basis of Syndrome differentiation in TCM, which sheds light on the translation of TCM theory in the practice of precision medicine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00521-3.

1. Our work was based on clinical samples rather than pure data analysis or animal models.

2. We conducted multiple omics studies. Especially, as for metabolomics study, we performed both untargeted and targeted metabolomics experiments.

3. We performed network pharmacological study to cross-validated the results of multi-omics study. Although the data sources of network pharmacology were completely unrelated with our omics data, they came to the same conclusion about the difference of the two Syndromes.

4. In the network pharmacological study, we made efforts to collect and screen high-quality data. We collected data from multiple TCM databases and conducted drug likeness screening. Especially, we added quality markers of each herb, whose pharmacological relevance had been validated. To enhance the reliability of targets, for each Syndrome, we only studied common targets of 3 different TCM formulae prescribed for this Syndrome.

Quantitative determination of EPA and DHA in fish oil capsules for cardiovascular disease therapy in Indonesia by GC-MS

BACKGROUND

The consumption of EPA (Eicosapentaenoic acid), and DHA (docosahexaenoic acid), from fish oil, in the long run, has been observed to have a positive impact on patients with coronary heart disease. Fish oil products, with so much EPA and DHA content are available, and have very variable prices. Therefore, as a therapy to be used for long-term treatment, the cost factor is to be considered.

DESIGN AND METHODS

This study analyzed the content of EPA and DHA, using GC-MS. The sample to be analyzed was the fish oil that has the lowest price (Product A1), and that of the highest (Product A2). Furthermore, the macroscopic analysis was performed, by observing the physical form including organoleptic and qualitative tests, by reading the fragments identified by EPA and DHA.

RESULTS

Clinical trials were conducted on patients (about 46 people), with risk factors and dyslipidemia. Product A1 showed EPA at tR= 15.574 min (relative%= 88.49%, similarity= 95%), and DHA at tR= 21.714 min (relative%= 88.92%, similarity= 93%). Product A2 showed EPA at tR= 28.719 min (relative%= 22.58%, similarity= 89%), and DHA at tR= 32.327 min (relative%= 22.87%, similarity= 90%), which meant that both had EPA and DHA contents, in accordance with their labels. Both products were confirmed to reduce total cholesterol in 4weeks (p=0.000, p= 0.000), with no significant difference in their effectiveness (p=0.652).

CONCLUSION

The results showed that both the A1 and A2 products, had the EPA and DHA contents in accordance with their respective labels. However, with the A2 product having a percentage relatively higher than that of the A1 brand, both are equally very effective.