Fecal metabolomics analysis for deciphering the lipid-lowering effect of Qizhi capsule on high-fat feed induced hyperlipidemia

Metabolic profiling of galectin-1 and galectin-3: a cross-sectional, multi-omics, association study

OBJECTIVES

Experimental studies indicate a role for galectin-1 and galectin-3 in metabolic disease, but clinical evidence from larger populations is limited.

METHODS

We measured circulating levels of galectin-1 and galectin-3 in the Prospective investigation of Obesity, Energy and Metabolism (POEM) study, participants (n = 502, all aged 50 years) and characterized the individual association profiles with metabolic markers, including clinical measures, metabolomics, adipose tissue distribution (Imiomics) and proteomics.

RESULTS

Galectin-1 and galectin-3 were associated with fatty acids, lipoproteins and triglycerides including lipid measurements in the metabolomics analysis adjusted for body mass index (BMI). Galectin-1 was associated with several measurements of adiposity, insulin secretion and insulin sensitivity, while galectin-3 was associated with triglyceride-glucose index (TyG) and fasting insulin levels. Both galectins were associated with inflammatory pathways and fatty acid binding protein (FABP)4 and -5-regulated triglyceride metabolic pathways. Galectin-1 was also associated with several proteins related to adipose tissue differentiation.

CONCLUSIONS

The association profiles for galectin-1 and galectin-3 indicate overlapping metabolic effects in humans, while the distinctly different associations seen with fat mass, fat distribution, and adipose tissue differentiation markers may suggest a functional role of galectin-1 in obesity.

Elucidation for the pharmacological effects and mechanism of Shen Bai formula in treating myocardial injury based on energy metabolism and serum metabolomic approaches

ETHNOPHARMACOLOGICAL RELEVANCE

Shen Bai formula (SBF) is a proven effective traditional Chinese medicine for treating viral myocarditis (VMC) sequelae in clinic, and myocardial injury is the pathological basis of VMC sequelae. However, the pharmacological action and mechanism of SBF have not been systematically elucidated.

AIM OF THE STUDY

In present research, the doxorubicin-induced myocardial injury rat model was used to evaluate the efficacy of SBF, and energy metabolism and metabolomics approaches were applied to elucidate the effects of SBF on myocardial injury.

MATERIALS AND METHODS

Through energy metabolism measurement system and UPLC-Q-TOF-MS/MS oriented blood metabolomics, directly reflected the therapeutic effect of SBF at a macro level, and identified biomarkers of myocardial injury in microcosmic, revealing its metabolomic mechanism.

RESULTS

Results showed that SBF significantly improved the electrocardiogram (ECG), heart rate (HR), extent of myocardial tissue lesion, and ratio of heart and spleen. In addition, the serum levels of AST, CK, LDH, α-HBDH, cTnI, BNP, and MDA decreased, whereas SOD and ATP activity and content increased. Moreover, SBF increased locomotor activity and basic daily metabolism in rats with myocardial injury, restoring their usual level of energy metabolism. A total of 45 potential metabolomic biomarkers were identified. Among them, 44 biomarkers were significantly recalled by SBF, including representative biomarkers arachidonic acid (AA), 12-HETE, prostaglandin J2 (PGJ2), 15-deoxy-Δ-12,14-PGJ2, 15-keto-PGE2, 15(S)-HPETE, 15(S)-HETE, 8,11,14-eicosatrienoic acid and 9(S)-HODE, which involved AA metabolism, biosynthesis of unsaturated fatty acids and linoleic acid metabolism.

CONCLUSION

We successfully replicated a myocardial injury rat model with the intraperitoneal injection of doxorubicin, and elucidated the mechanism of SBF in treating myocardial injury. This key mechanism may be achieved by targeting action on COX, Alox, CYP, and 15-PGDH to increase or decrease the level of myocardial injury biomarker, and then emphatically interven in AA metabolism, biosynthesis of unsaturated fatty acids and linoleic acid metabolism, and participate in regulating purine metabolism, sphingolipid metabolism, primary bile acid biosynthesis, and steroid hormone synthesis.

MultiClassMetabo: A Superior Classification Model Constructed Using Metabolic Markers in Multiclass Metabolomics

Multiclass metabolomics has become a popular technique for revealing the mechanisms underlying certain physiological processes, different tumor types, or different therapeutic responses. In multiclass metabolomics, it is highly important to uncover the underlying biological information on biosamples by identifying the metabolic markers with the most associations and classifying the different sample classes. The classification problem of multiclass metabolomics is more difficult than that of the binary problem. To date, various methods exist for constructing classification models and identifying metabolic markers consisting of well-established techniques and newly emerging machine learning algorithms. However, how to construct a superior classification model using these methods remains unclear for a given multiclass metabolomic data set. Herein, MultiClassMetabo has been developed for constructing a superior classification model using metabolic markers identified in multiclass metabolomics. MultiClassMetabo can enable online services, including (a) identifying metabolic markers by marker identification methods, (b) constructing classification models by classification methods, and (c) performing a comprehensive assessment from multiple perspectives to construct a superior classification model for multiclass metabolomics. In summary, MultiClassMetabo is distinguished for its capability to construct a superior classification model using the most appropriate method through a comprehensive assessment, which makes it an important complement to other available tools in multiclass metabolomics. MultiClassMetabo can be accessed at http://idrblab.cn/multiclassmetabo/.

Metabolomics analysis delineates the therapeutic effects of Yinlan Tiaozhi capsule on triton WR-1339 -induced hyperlipidemia in mice

Hyperlipidemia is a disorder of lipid metabolism resulting from abnormal blood lipid metabolism and is one of the most frequent metabolic diseases that endanger people's health. Yinlan Tiaozhi capsule (YL) is a formulated TCM widely used to treat hyperlipidemia. The purpose of this study was to discover biomarkers utilizing untargeted metabolomics techniques, as well as to analyze the mechanisms underlying the changes in metabolic pathways linked to lipid-lowering, anti-inflammation, and regulation of angiogenesis in hyperlipidemia mice. To assess the efficacy of YL, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) levels were measured. Biochemical examinations showed that YL significantly reduced the levels of TC, TG, LDL-c, Il6, Tnf-α, and Vegfa in hyperlipidemia mice (p < 0.01). YL also significantly increased the levels of HDL-c and Alb (p < 0.01). Twenty-seven potential serum biomarkers associated with hyperlipidemia were determined. These differential metabolites were related to the reduction of serum lipid levels in hyperlipidemia mice, probably through metabolic pathways such as linoleic acid metabolism, glycerophospholipid metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and D-glutamine and D-glutamate metabolism. Further correlation analysis showed that the serum lipid reduction through YL was related to the metabolites (amino acid metabolites, phospholipids metabolites, and fatty acids metabolites). The present study reveals that YL has a profound effect on alleviating triton WR-1339-induced hyperlipidemia, inflammation, and angiogenesis and that the positive effects of YL were primarily associated with the correction of metabolic abnormalities and the maintenance of metabolite dynamic balance.