Reconstruction and analysis of correlation networks based on GC-MS metabolomics data for hypercholesterolemia.

BACKGROUND AND AIMS: Hypercholesterolemia is characterized by the elevation of plasma total cholesterol level, especially low-density lipoprotein (LDL) cholesterol. This disease is usually caused by a mutation in genes such as LDL receptor, apolipoprotein B, or proprotein convertase subtilisin/kexin type 9. However, a considerable number of patients with hypercholesterolemia do not have any mutation in these candidate genes. In this study, we examined the difference in the metabolic level between patients with hypercholesterolemia and healthy subjects, and screened the potential biomarkers for this disease. METHODS: Analysis of plasma metabolomics in hypercholesterolemia patients and healthy controls was performed by gas chromatography-mass spectrometry and metabolic correlation networks were constructed using Gephi-0.9.2. RESULTS: First, metabolic profile analysis confirmed the distinct metabolic footprints between the patients and the healthy ones. The potential biomarkers screened by orthogonal partial least-squares discrimination analysis included l-lactic acid, cholesterol, phosphoric acid, d-glucose, urea, and d-allose (Variable importance in the projection > 1). Second, arginine and methionine metabolism were significantly perturbed in hypercholesterolemia patients. Finally, we identified that l-lactic acid, l-lysine, l-glutamine, and l-cysteine had high scores of centrality parameters in the metabolic correlation network. CONCLUSION: Plasma l-lactic acid could be used as a sensitive biomarker for hypercholesterolemia. In addition, arginine biosynthesis and cysteine and methionine metabolism were profoundly altered in patients with hypercholesterolemia.

Revealing metabolic pathways relevant to prediabetes based on metabolomics profiling analysis.

AIMS: Dahl salt-sensitive (SS) rats develop similar prediabetes lesion characteristics, such as impaired glucose tolerance (IGT), when compared with the salt resistant rat. In this study, we evaluate the risk of high glucose intake during prediabetes and reveal the metabolic pathways relevant to the pathophysiology of prediabetes to diabetes using the SS rat model and compared this with the salt-resistant consomic SS.13BN rat model. METHODS: SS rats were fed with normal chow ±10% glucose solution ad libitum for five weeks. The same experimental treatment was performed on the SS.13BN rats. Metabolites derived from the serum and liver tissue were measured through biochemical and metabolomics analyses. Multivariate, pathway enrichment, and metabolic correlation network analyses were performed based on the metabolomics data. RESULTS: Biochemical analysis revealed that serum triglyceride (TG) significantly increased with a significant decrease in serum total cholesterol (TC) after high glucose intake in the SS rat. Metabolic pathway analysis revealed that high glucose intake interfered with galactose, glyoxylate, and dicarboxylate metabolism, most evidently in the SS rat. Hepatic l-lactic acid content increased in the SS rat after high glucose intake, whereas the opposite was observed in SS.13BN rats. Metabolic correlation network analysis based on serum metabolites revealed that urea and l-valine had higher metabolic centrality in the SS rat. CONCLUSION: Our findings revealed that high glucose intake can significantly stimulate hypertriglyceridemia and reduce serum TC level. The profoundly altered metabolic pathway included galactose, glyoxylate, and dicarboxylate metabolism. l-lactic acid was screened as a biomarker in liver, whereas l-valine and urea were screened as hub metabolites in serum.

Revealing the Pathogenesis of Salt-Sensitive Hypertension in Dahl Salt-Sensitive Rats through Integrated Multi-Omics Analysis.

Salt-induced renal metabolism dysfunction is an important mechanism of salt-sensitive hypertension. Given that the gut-liver axis is the first hit of a high-salt diet (HSD), we aimed to identify the extra-renal mechanism from hepatic metabolism and gut microbiota, and attempted to relieve the salt-induced metabolic dysfunctions by curcumin. Untargeted metabolomics analysis was performed to identify the changes in hepatic metabolic pathways, and integrated analysis was employed to reveal the relationship between hepatic metabolic dysfunction and gut microbial composition. HSD induced significant increase in fumaric acid, l-lactic acid, creatinine, l-alanine, glycine, and l-cysteine levels, and amino acids metabolism pathways associated with glycolysis were significantly altered, including alanine, aspartate, and glutamate metabolism; glycine, serine, and threonine metabolism, which were involved in the regulation of blood pressure. Integrated multi-omics analysis revealed that changes in Paraprevotella, Erysipelotrichaceae, and genera from Clostridiales are associated with metabolic disorders. Gene functional predication analysis based on 16S Ribosomal RNA sequences showed that the dysfunction in hepatic metabolism were correlated with enhanced lipopolysaccharide (LPS) biosynthesis and apoptosis in gut microbes. Curcumin (50 mg/kg/d) might reduce gut microbes-associated LPS biosynthesis and apoptosis, partially reverse metabolic dysfunction, ameliorate renal oxidative stress, and protect against salt-sensitive hypertension.