Metabolic Alterations Associated with Atorvastatin/Fenofibric Acid Combination in Patients with Atherogenic Dyslipidaemia: A Randomized Trial for Comparison with Escalated-Dose Atorvastatin

Neonatal administration of fenofibrate had no developmental programming effect on the lipid profile and relative leucocyte telomere lengths of adolescent rats fed a high-fructose diet postnatally

Telomere length, a marker of ageing, is susceptible to developmental programming that may cause its accelerated attrition. Metabolic syndrome triggers telomere attrition. Fenofibrate, a peroxisome proliferator-activated receptor-alpha agonist, is protective against telomere attrition. We investigated the impact of fenofibrate administered during suckling on the lipid profile and leucocyte telomere lengths of rats fed a high-fructose diet post-weaning. Suckling Sprague-Dawley pups (n = 119) were allocated to four groups and gavaged with either 10 mL·kg-1 body mass 0.5% dimethyl sulfoxide, 100 mg·kg-1 body mass fenofibrate, fructose (20%, w / v), or a combination of fenofibrate and fructose for 15 days. Upon weaning, each of the initial groups was split into two subgroups: one had plain water while the other had fructose solution (20%, w / v) to drink for 6 weeks. Blood was collected for DNA extraction and relative leucocyte telomere length determination by real-time PCR. Plasma triglycerides and cholesterol were also quantified. The treatments had no effect (p > 0.05) on body mass, cholesterol concentration, and relative leucocyte telomere lengths in both sexes. Post-weaning fructose increased triglyceride concentrations (p < 0.05) in female rats. Fenofibrate administered during suckling did not affect ageing nor did it prevent high fructose-induced hypertriglyceridaemia in female rats.

Pharmacometabolomics for the Study of Lipid-Lowering Therapies: Opportunities and Challenges

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Atorvastatin Inhibits High-Fat Diet-Induced Lipid Metabolism Disorders in Rats by Inhibiting Bacteroides Reduction and Improving Metabolism

PURPOSE

The prevalence of hyperlipidemia and related illnesses is on its rise, and atorvastatin is the frequently used hypolipidemic agent. However, there is still uncertainty about the mechanisms, especially the relationship between the lipid-lowering effect, intestinal microbiome, and metabolic profiles. We aim to intensively explain the mechanism of the hypolipidemic effect of atorvastatin through multi-omics perspective of intestinal microbiome and metabolomics.

METHODS

Multi-omics methods play an increasingly important role in the analysis of intestinal triggers and evaluation of metabolic disorders such as obesity, hyperlipidemia, and diabetes. Therefore, we were prompted to explore intestinal triggers, underlying biomarkers, and potential intervention targets of atorvastatin in the treatment of dyslipidemia through multi-omics. To achieve this, SPF Wistar rats were fed a high-fat diet or normal diet for 8 weeks. Atorvastatin was then administered to high-fat diet-fed rats.

RESULTS

By altering intestinal microbiome, a high-fat diet can affect feces and plasma metabolic profiles. Treatment with atorvastatin possibly increases the abundance of Bacteroides, thereby improving "propanoate metabolism" and "glycine, serine and threonine metabolism" in feces and plasma, and contributing to blood lipid reduction.

CONCLUSION

Our study elucidated the intestinal triggers and metabolites of high-fat diet-induced dyslipidemia from the perspective of intestinal microbiome and metabolomics. It equally identified potential intervention targets of atorvastatin. This further explains the mechanism of the hypolipidemic effect of atorvastatin from a multi-omics perspective.

Changes in plasma sphingolipid levels against the background of lipid-lowering therapy in patients with premature atherosclerosis

Lipid-lowering drugs affect standard lipoproteins. However, we have no knowledge of changes in other plasma lipids upon treatment. The study was aimed to assess the dynamic changes in cholesterol, high- and low-density lipoproteins (HDL and LDL), triglycerides, and sphingolipids against the background of lipidlowering therapy in patients with premature coronary artery disease, atherosclerosis and hypercholesterolemia. A total of 18 patients were enrolled (the average age was 53 ± 6.7 years): in group 1, six patients received starting statin doses; group 2 included six patients, who failed to achieve LDL target levels against the background of treatment with starting statin doses, and received escalated statin doses; seven patients in group 3 failed to achieve LDL target levels against the background of treatment with maximum tolerated doses of statins and ezetimibe, and received alirocumab. Sphingolipid levels were assessed by mass spectrometry. In group 1, the decreased levels of ceramide Cer 14:1 (p = 0.046) and sphingomyelins SM 22:1, SM 22:0, SM 24:0 (p = 0.028) were observed. There were no significant changes in the levels of total cholesterol, LDL-C, HDL-C, and triglycerides. In group 2, the significantly decreased levels of total cholesterol (p = 0.028), LDL (p = 0.043), sphingomyelins SM 18:1, SM 24:1 and SM 26:1, and ceramide Cer 16:1 (p = 0.028) were observed. The level of Cer 22:1 significantly increased (p = 0.028). In group 3, total cholesterol decreased by 36.2%, and LDL-C (p = 0.018) decreased by 60.1% compared to baseline (ΔLDL-C = –2.67 ± 3.12); the elevated levels of ceramide Cer 22:1 (p = 0.028) were observed. It has been shown, that decreased sphingomyelin levels are associated with statin therapy and correlate with decreased levels of LDL-C. No significant dynamic changes in ceramides and ceramide risk against the background of statin therapy were observed, however, PCSK9 inhibitor added to therapy reduced the Cer 16:0/24:0 ratio.

Plasma Metabolomics Analysis Identifies Abnormal Energy, Lipid, and Amino Acid Metabolism in Abdominal Aortic Aneurysms

Background

Abdominal aortic aneurysm (AAA) is a complicated aortic dilatation disease. Metabolomics is an emerging system biology method. This aim of this study was to identify abnormal metabolites and metabolic pathways associated with AAA and to discover potential biomarkers that could affect the size of AAAs.

Material/Methods

An untargeted metabolomic method was used to analyze the plasma metabolic profiles of 39 patients with AAAs and 30 controls. Multivariate analysis methods were used to perform differential metabolite screening and metabolic pathway analysis. Cluster analysis and univariate analysis were performed to identify potential metabolites that could affect the size of an AAA.

Results

Forty-five different metabolites were identified with an orthogonal projection to latent squares-discriminant analysis model and the differences between them in the patients with AAAs and the control group were compared. A variable importance in the projection score >1 and P<0.05 were considered statistically significant. In patients with AAAs, the pathways involving metabolism of alanine, aspartate, glutamate, D-glutamine, D-glutamic acid, arginine, and proline; tricarboxylic acid cycling; and biosynthesis of arginine are abnormal. The progression of an AAA may be related to 13 metabolites: citric acid, 2-oxoglutarate, succinic acid, coenzyme Q1, pyruvic acid, sphingosine-1-phosphate, platelet-activating factor, LysoPC (16: 00), lysophosphatidylcholine (18: 2(9Z,12Z)/0: 0), arginine, D-aspartic acid, and L- and D-glutamine.

Conclusions

An untargeted metabolomic analysis using ultraperformance liquid chromatography-tandem mass spectrometry identified metabolites that indicate disordered metabolism of energy, lipids, and amino acids in AAAs.