Metabonomics and diagnostics

Exploration of TCM syndrome types of the material basis and risk prediction of Wilson disease liver fibrosis based on 1H NMR metabolomics

Wilson disease (WD) is an autosomal recessive disorder characterized by abnormal copper metabolism. The accumulation of copper in the liver can progress to liver fibrosis and, ultimately, cirrhosis, which is a primary cause of death in WD patients. Metabonomic technology offers an effective approach to investigate the traditional Chinese medicine (TCM) syndrome types of WD-related liver fibrosis by monitoring the alterations in small molecule metabolites within the body. In this study, we employed 1H-Nuclear Magnetic Resonance (1H NMR) metabonomics to assess the metabolic profiles associated with five TCM syndrome types of WD-related liver fibrosis and analyzed the diagnostic and predictive capabilities of various metabolites. The study found a variety of metabolites, each with varying levels of diagnostic and predictive capabilities. Furthermore, the discerned differential metabolic pathways were primarily associated with various pathways involving carbohydrate metabolism, amino acid metabolism, and lipid metabolism. This study has identified various characteristic metabolic markers and pathways associated with different TCM syndromes of liver fibrosis in WD, providing a substantial foundation for investigating the mechanisms underlying these TCM syndromes.

Metabolomic study combined with the low-level light therapy of Chinese acupuncture points and combined oral contraceptives in treatment of primary dysmenorrhea: A prospective, multicenter, randomized controlled study

Objective

To compare the changes of metabolites between Low-level light therapy (LLLT) and combined oral contraceptive (COC) after treatment of primary dysmenorrhea (PD), and to compare and analyze the biological and biochemical effects of the two treatments by analyzing the differences in metabolite profiles.

Methods

A multicenter, double-blind, prospective, parallel, randomized controlled study was conducted on 69 women aged 16-35 years old with PD who were randomly divided into COC treatment group or LLLT treatment group. Low-level light therapy with light-emitting diodes (LED) was applied on two acupoints named "Guanyuan" (CV4) and "Qihai" (CV6). After 12 weeks of treatment intervention, blood samples were collected before and after treatment for metabolomic analysis. We used UPLC-MS/MS analysis to compare the differences in metabolite changes between LLLT and COC before and after treatment.

Results

76 differential metabolites were detected in the LLLT group, and 92 differential metabolites were detected in the COC group, which were up-regulated or down-regulated (p < 0.001). Prostaglandin D2 (PG D2) was down-regulated and biliverdin was up-regulated after LLLT treatment, 4a-Hydroxytetrahydrobiopterin, Prostaglandin D2, 5-Hydroxy-l-tryptophan, Cholic acid were down-regulated and cortisol was up-regulated after COC treatment, and the differences were statistically significant. Cortisol and testosterone glucuronide in LLLT group were significantly lower than those in COC group. The metabolic pathways affected were glycerophospholipid metabolism, linoleic acid metabolism and arachidonic acid metabolism in the LLLT group, and glycerophospholipid metabolism, folate biosynthesis, arachidonic-acid-metabolism, and tryptophan metabolism in the COC group. The differential metabolic pathway were linoleic acid metabolism, steroid hormone biosynthesis, and alpha-Linolenic acid metabolism after the comparison of LLLT with COC.

Conclusion

LLLT and COC might relieve dysmenorrhea by down-regulating PGD2, and LLLT might also relieve dysmenorrhea by up-regulating biliverdin. The level of cortisol and testosterone glucuronide after LLLT treatment was lower than that after COC treatment, which might lead to the difference in the clinical efficacy of the two treatments for dysmenorrhea.

The Underling Mechanisms Exploration of Rubia cordifolia L. Extract Against Rheumatoid Arthritis by Integrating Network Pharmacology and Metabolomics

Purpose

Rubia cordifolia L. (RC) is a classic herbal medicine for the treatment of rheumatoid arthritis (RA) and has been used since ancient times. The ethanol extract of Rubia cordifolia L. (RCE) showed obvious anti-RA effects in our previous study. However, further potential mechanisms require more exploration. We aimed to investigate the mechanism of RCE for the treatment of RA by integrating metabolomics and network pharmacology in this study.

Methods

An adjuvant-induced arthritis (AIA) rat model was established, and we evaluated the therapeutic effects of RCE. Metabolomics of serum and urine was used to identify the differential metabolites. Network pharmacology was applied to determine the key metabolites and potential targets. Finally, the potential targets and compounds of RCE were verified by molecular docking.

Results

The results indicated that RCE suppressed foot swelling and alleviated joint damage and also had anti-inflammatory properties by inhibiting the expressions of tumor necrosis factor (TNF)-α, Interleukin (IL)-1β, prostaglandin E2 (PGE2), and P65. Ten and seven differential metabolites were found in the serum and urine, respectively, of rats. Six key targets, ie, phospholipase A2 group IIA (PLA2G2A), phospholipase A2 group X (PLA2G10), cytidine deaminase (CDA), uridine-cytidine kinase 2 (UCK2), charcot-leyden crystal galectin (CLC), and 5',3'-nucleotidase, mitochondrial (NT5M), were discovered by network pharmacology and metabolite analysis and were found to be related to glycerophospholipid metabolism and pyrimidine metabolism. Molecular docking confirmed that the favorable compounds showed affinities with the key targets, including alizarin, 6-hydroxyrubiadin, ruberythric acid, and munjistin.

Conclusion

This study revealed the underlying mechanisms of RCE and provided evidence that will allow researchers to further investigate the functions and components of RCE against RA.

LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study

Today’s high-resolution mass spectrometers (HRMS) allow bioanalysts to perform untargeted/global determinations that can reveal unexpected compounds or concentrations in a patient’s sample. This could be performed for preliminary diagnosis attempts when usual diagnostic processes and targeted determinations fail. We have evaluated an untargeted diagnostic screening (UDS) procedure. UDS is a metabolome analysis that compares one sample (e.g., a patient) with control samples (a healthy population). Using liquid chromatography (LC)-HRMS full-scan analysis of human serum extracts and unsupervised data treatment, we have compared individual samples that were spiked with one xenobiotic or a higher level of one endogenous compound with control samples. After the use of different filters that drastically reduced the number of metabolites detected, the spiked compound was eventually revealed in each test sample and ranked. The proposed UDS procedure appears feasible and reliable to reveal unexpected xenobiotics (toxicology) or higher concentrations of endogenous metabolites. HRMS-based untargeted approaches could be useful as preliminary diagnostic screening when canonical processes do not reveal disease etiology nor establish a clear diagnosis and could reduce misdiagnosis. On the other hand, the risk of overdiagnosis of this approach should be reduced with mandatory biomedical interpretation of the patient’s UDS results and with confirmatory targeted and quantitative determinations.

Liver tissue metabolic profiling and pathways of non-alcoholic steatohepatitis in rats

AIM

The mechanisms of non-alcoholic steatohepatitis (NASH) in hepatocytes are unknown. Our aim is to study the tissue metabolic profiling and pathways of NASH.

METHODS

We built rat models for simple steatosis and NASH and analyzed the liver extract using a liquid chromatograph-mass spectrometer. The acquired data were processed by multivariate principal component analysis and partial least squares discriminant analysis (PLS-DA) to obtain metabolic profiling. Orthogonal projections to latent structures DA was used to obtain metabolites capable of distinguishing NASH and steatosis. The total differences in the metabolites between groups were analyzed to determine their metabolic pathways.

RESULTS

Principal component analysis showed that the metabolic profiles of NASH and steatosis are different. The PLS-DA modeling revealed a clear separation between two groups with parameters R² Y and Q² Y all greater than 0.7. The orthogonal projections to latent structures DA model identified 171 metabolites capable of distinguishing NASH from steatosis. The identified metabolites are involved in fatty acid metabolism, tryptophan metabolism, the urea cycle, and the citric acid cycle in hepatocytes.

CONCLUSIONS

These metabolic profiles and pathways in rat hepatocytes will offer useful information when studying metabolic disorders in patients with NASH.