Integrative serum metabolomic analysis for preventive effects of Yaobitong capsule in adjuvant-induced rheumatoid arthritis rat based on RP/HILIC-UHPLC-Q-TOF MS

Identification of energy metabolism anomalies and serum biomarkers in the progression of premature ovarian failure via extracellular vesicles' proteomic and metabolomic profiles

BACKGROUND

Premature ovarian failure (POF) is a clinical condition characterized by the cessation of ovarian function, leading to infertility. The underlying molecular mechanisms remain unclear, and no predictable biomarkers have been identified. This study aimed to investigate the protein and metabolite contents of serum extracellular vesicles to investigate underlying molecular mechanisms and explore potential biomarkers.

METHODS

This study was conducted on a cohort consisting of 14 POF patients and 16 healthy controls. The extracellular vesicles extracted from the serum of each group were subjected to label-free proteomic and unbiased metabolomic analysis. Differentially expressed proteins and metabolites were annotated. Pathway network clustering was conducted with further correlation analysis. The biomarkers were confirmed by ROC analysis and random forest machine learning.

RESULTS

The proteomic and metabolomic profiles of POF patients and healthy controls were compared. Two subgroups of POF patients, Pre-POF and Pro-POF, were identified based on the proteomic profile, while all patients displayed a distinguishable metabolomic profile. Proteomic analysis suggested that inflammation serves as an early factor contributing to the infertility of POF patients. For the metabolomic analysis, despite the dysfunction of metabolism, oxidative stress and hormone imbalance were other key factors appearing in POF patients. Signaling pathway clustering of proteomic and metabolomic profiles revealed the progression of dysfunctional energy metabolism during the development of POF. Moreover, correlation analysis identified that differentially expressed proteins and metabolites were highly associated, with six of them being selected as potential biomarkers. ROC curve analysis, together with random forest machine learning, suggested that AFM combined with 2-oxoarginine was the best diagnostic biomarker for POF.

CONCLUSIONS

Omics analysis revealed that inflammation, oxidative stress, and hormone imbalance are factors that damage ovarian tissue, but the progressive dysfunction of energy metabolism might be the critical pathogenic pathway contributing to the development of POF. AFM combined with 2-oxoarginine serves as a precise biomarker for clinical POF diagnosis.

Mechanism of Jinteng Qingbi granules in the treatment of rheumatoid arthritis using metabolomics analysis

This study investigated the differential metabolites after rheumatoid arthritis (RA) rats were treated with Jinteng Qingbi granules. Collagen-induced arthritis rats were divided into three groups, namely normal group, model group, and Jinteng Qingbi granules group. Serum compounds were identified, annotated, and classified using metabolomics to explain the physicochemical properties and biological functions. The metabolites were screened using univariate and multivariate statistical analyses. There were differences in serum metabolites between RA and normal rats; Jinteng Qingbi granules improved RA and recovered the metabolite levels to normal. Compared to the normal group, 51 differential ions were screened, and 108 ions were changed in the Jinteng Qingbi granules group compared to the RA model. Eight metabolites were upregulated in the RA model group compared to the normal group, whereas 10 metabolites were downregulated. Treatment with Jinteng Qingbi granules increased the levels of 12 metabolites such as cinnamate and decreased the levels of 16 metabolites such as allamandin in the RA model. Differential ion enrichment was mainly related to the histidine metabolic pathway in amino acid metabolism. Jinteng Qingbi granules resulted in improvements in the RA model, which were mainly associated with lipids and lipid-like molecules, organic acids, and derivatives, providing a new possibility and basis for screening biomarkers for the diagnosis and treatment of RA.

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Metabolomic insights into the therapeutic mechanisms of costus (Saussurea costus (Falc.) Lipsch.) root extract in propylthiouracil-induced hypothyroidism rat model

ETHNOPHARMACOLOGICAL RELEVANCE

Saussurea costus (Falc.) Lipschitz. is one of the most reputed medicinal plants as a traditional medicine in the Arab and Middle East regions in the treatment of thyroid disorders, however, more investigations are needed to fully understand its effectiveness and mechanism of action.

AIM OF THE STUDY

The primary objective of the study was to assess the impact of Saussurea costus (COST) on the metabolic profiles of propylthiouracil (PTU)-induced hypothyroidism in rats. This involves a comprehensive examination of serum metabolites using UPLC/QqQ-MS analysis aiming to identify differential metabolites, elucidate underlying mechanisms, and evaluate the potential pharmacological effect of COST in restoring metabolic homeostasis.

MATERIALS AND METHODS

Hypothyroidism was induced in female Sprague-Dawley rats by oral administration of propylthiouracil (PTU). UPLC/QqQ MS analysis of serum samples from normal, PTU, and PTU + COST rats was utilized for annotation of intrinsic metabolites with the aid of online Human metabolome database (HMDB) and extensive literature surfing. Multivariate statistical analyses, including orthogonal partial least squares discriminant analysis (OPLS-DA), discerned variations between the different groups. Serum levels of T3, T4 and TSH in addition to arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) levels in thyroid gland tissues; Phospholipase A2 group IIA (PLA2G2A), and lipoprotein lipase (LPL) in liver tissues were assessed by specific ELISA kits. Gene expression for key proteins of the primary evolved pathwayswere quantified by one-step qRT-PCR technique. Histopathological evaluation of thyroid gland tissue was performed by an investigator blinded to the experimental group using light microscope.

RESULTS

Distinct clustering in multivariate statistical analysis models indicated significant variations in serum chemical profiles among normal, disease, and treated groups. VIP values guided the selection of differential metabolites, revealing significant changes in metabolite concentrations. Subsequent to COST treatment, 43 differential intrinsic metabolites exhibited a notable tendency to revert towards normal levels. Annotated metabolites, such as lysophosphatidylcholine (LPC), L-acetylcarnitine, gamma-glutamylserine, and others, showed differential regulation in response to PTU and subsequent S. costus treatment. Notably, 21 metabolites were associated with polyunsaturated fatty acids (PUFAs) biosynthesis, arachidonic acid (ARA) metabolism, and glycerophospholipid metabolism exhibited significant changes on conducting metabolic pathway analysis.

CONCLUSIONS

COST improves PTU-induced hypothyroidism by regulating biosynthesis of PUFAs signified by n-3/n-6, ARA and glycerophospholipid metabolism. The study provides us a novel mechanism to explain the improvement of hypothyroidism and associated dyslipidemia by COST, depicts a metabolic profile of hypothyroidism, and gives us another point cut for further exploring the biomarkers and pathogenesis of hypothyroidism.

A liquid chromatography-mass spectrometry untargeted urinary metabonomics combined with quantitative analysis of seven amino acids biomarkers on yaobitong capsule in the intervention of rheumatoid arthritis rats

Yaobitong capsule is a compound preparation of traditional Chinese medicine that has been widely applied in disease treatment. To insight into the therapeutic effects of the yaobitong capsule on rheumatoid arthritis and its mechanisms, a liquid chromatography-mass spectrometry untargeted urine metabolomics method was established and validated, combined with the quantitative analysis of seven potential amino acid biomarkers in rat urine. The results showed that 35 potential biomarkers were found in untargeted metabonomics, which was related to amino acid metabolism, lipid metabolism, energy metabolism, and purine metabolism. Moreover, seven amino acid biomarkers, including proline, methionine, glutamic acid, histidine, lysine, cysteine, and glutamine, were further separated and quantified in multiple-reaction monitoring with a positive ionization mode. Then the linearity, standard curves, accuracy, precision, limit of quantitation, recovery, stability, carryover, and matrix effect of the quantitative method were examined. Finally, the validated method was successfully applied to investigate the urine samples of the control group, adjuvant-induced rheumatoid arthritis model group, yaobitong capsule-treatment group, and positive control group in rats. The contents of seven amino acids in different groups showed significant differences. Consequently, our findings revealed that the yaobitong capsule exerted therapeutic effects on rheumatoid arthritis rats by maintaining amino acid homeostasis.

Metabolomics in rheumatoid arthritis: Advances and review

Rheumatoid arthritis (RA) is an autoimmune disease accompanied by metabolic alterations. The metabolic profiles of patients with RA can be determined using targeted and non-targeted metabolomics technology. Metabolic changes in glucose, lipid, and amino acid levels are involved in glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway, the arachidonic acid metabolic pathway, and amino acid metabolism. These alterations in metabolic pathways and metabolites can fulfill bio-energetic requirements, promote cell proliferation, drive inflammatory mediator secretion, mediate leukocyte infiltration, induce joint destruction and muscle atrophy, and regulate cell proliferation, which may reflect the etiologies of RA. Differential metabolites can be used as biomarkers for the diagnosis, prognosis, and risk prediction, improving the specificity and accuracy of diagnostics and prognosis prediction. Additionally, metabolic changes associated with therapeutic responses can improve the understanding of drug mechanism. Metabolic homeostasis and regulation are new therapeutic strategies for RA. In this review, we provide a comprehensive overview of advances in metabolomics for RA.

Quercetin ameliorated cardiac injury via reducing inflammatory actions and the glycerophospholipid metabolism dysregulation in a diabetic cardiomyopathy mouse model

Quercetin has multiple protective effects against cardiometabolic diseases, but the biological mechanisms underlying the benefits in diabetic cardiomyopathy (DCM) are unclear. A mouse DCM model was established by high-fat diet...

Amino Acids and Lipids Associated with Long-Term and Short-Term Red Meat Consumption in the Chinese Population: An Untargeted Metabolomics Study

Red meat (RM) consumption is correlated with multiple health outcomes. This study aims to identify potential biomarkers of RM consumption in the Chinese population and evaluate their predictive ability. We selected 500 adults who participated in the 2015 China Health and Nutrition Survey and examined their overall metabolome differences by RM consumption by using elastic-net regression, then evaluate the predictivity of a combination of filtered metabolites; 1108 metabolites were detected. In the long-term RM consumption analysis 12,13-DiHOME, androstenediol (3α, 17α) monosulfate 2, and gamma-Glutamyl-2-aminobutyrate were positively associated, 2-naphthol sulfate and S-methylcysteine were negatively associated with long-term high RM consumption, the combination of metabolites prediction model evaluated by area under the receiver operating characteristic curve (AUC) was 70.4% (95% CI: 59.9–80.9%). In the short-term RM consumption analysis, asparagine, 4-hydroxyproline, and 3-hydroxyisobutyrate were positively associated, behenoyl sphingomyelin (d18:1/22:0) was negatively associated with short-term high RM consumption. Combination prediction model AUC was 75.6% (95% CI: 65.5–85.6%). We identified 10 and 11 serum metabolites that differed according to LT and ST RM consumption which mainly involved branch-chained amino acids, arginine and proline, urea cycle and polyunsaturated fatty acid metabolism. These metabolites may become a mediator of some chronic diseases among high RM consumers and provide new evidence for RM biomarkers.