Liquid Chromatography/Mass Spectrometry based serum metabolomics study on recurrent abortion women with antiphospholipid syndrome

Metabolomics profiling identifies diagnostic metabolic signatures for pregnancy loss: a cross-sectional study from northwestern China

Objective

To identify potential diagnostic metabolic biomarkers for pregnancy loss (PL) by performing untargeted metabolomics analysis.

Methods

The present study performed untargeted metabolomics analysis on plasma samples from PL patients (n=70) and control subjects (n=122) using liquid chromatography‒mass spectrometry (LC‒MS). Metabolic profiles were evaluated using orthogonal partial least squares discriminant analysis (OPLS-DA), and pathway enrichment analysis was conducted via the KEGG database. LASSO regression was employed to identify significant metabolites, and their diagnostic performance was evaluated through receiver operating characteristic (ROC) curves. Pearson correlation analysis was used to explore the relationships between differentially abundant metabolites and clinical parameters.

Results

In total, 359 metabolites were identified, 57 of which were significantly altered between the control and PL group through OPLS-DA. Differential metabolites were significantly enriched in caffeine metabolism, tryptophan metabolism, and riboflavin metabolism pathways. Key metabolites, such as testosterone glucuronide, 6-hydroxymelatonin, and (S)-leucic acid, exhibited strong diagnostic potential, with AUC values of 0.991, 0.936 and 0.952, respectively, and the combined AUC was 0.993. Furthermore, Pearson correlation analysis revealed a significant negative correlation between the waist‒to‒hip ratio (WHR) and the abundance of testosterone glucuronide (r = -0.291, p = 0.0146), and a significant positive correlation between WHR and (S)-leucic acid (r = 0.248, p = 0.0381) in the PL group.

Conclusion

We identified a panel of plasma metabolites with significant diagnostic potential for PL. These biomarkers may facilitate early, noninvasive diagnosis and offer insights into metabolic dysregulation associated with pregnancy loss.

Mapping Thrombosis Serum Markers by 1H-NMR Allied with Machine Learning Tools

Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). 1H-NMR-based metabonomics data of the serum samples of patients with arterial or venous thromboembolism (VTE) without APS (n = 32), thrombotic primary APS patients (APS, n = 32), and healthy controls (HCs) (n = 32) were investigated. Unique metabolic profiles between VTE and HCs, APS and HCs, and between VTE and triple-positive APS groups were indicative of the significant alterations in the metabolic pathways of glycolysis, the TCA cycle, lipid metabolism, and branched-chain amino acid (BCAA) metabolism, and pointed to the complex pathogenesis mechanisms of APS and VTE. Histidine, 3-hydroxybutyrate, and threonine were shown to be the top three metabolites with the most substantial impact on model predictions, suggesting that these metabolites play a pivotal role in distinguishing among APS, VTE, and HCs. These metabolites might be potential biomarkers to differentiate APS and VTE patients.

Metabolomic analysis reveals potential role of immunometabolism dysregulation in recurrent pregnancy loss

Background

Recurrent pregnancy loss (RPL) affects women's reproductive health seriously, with immune dysfunction playing a key role in its cause, yet the exact mechanisms remain elusive. We aim to investigate potential mechanisms and identify biomarkers linked to RPL.

Methods

Immune cytokine testing and metabolomic profiling were conducted on the serum of 34 RPL patients and 30 healthy individuals. The metabolic pathways of the differential metabolites were analyzed, and specific metabolites were validated through targeted profiling. Potential biomarkers were identified, and the relationships between immune cytokines and differential metabolites were explored.

Results

In the RPL group, serum interleukin-6 and interleukin-10 levels were significantly higher, while interleukin-2 and interferon-γ were significantly lower. A total of 296 differential metabolites were detected by untargeted metabolomic profiling between the RPL and control groups, with most linked to amino acid metabolism. Targeted metabolomic profiling of amino acid metabolism revealed upregulation of indole-3-acetic acid, tyrosine, glycine, isoleucine, tryptophan, lysine, aspartic acid, arginine, leucine, threonine, glutamic acid, cystine, and phenylpyruvic acid (PPA) in the RPL group. Moreover, PPA and 5-hydroxy-L-tryptophan showed great potential in predicting RPL in a diagnostic model. Cystine and tyrosine were associated with immune cytokines in correlation analysis.

Conclusion

The study highlights the role of amino acid metabolism in RPL pathogenesis, suggesting that PPA and 5-HTP may be potential predictive indicators, while cystine and tyrosine may potentially regulate immune responses related to RPL. Further investigation into the molecular mechanisms underlying these findings could potentially result in the creation of novel diagnostic and therapeutic approaches for RPL.

Using liquid chromatography and mass spectrometry to predict potential biomarkers for missed miscarriage and its metabolic pathways in a tertiary center: A cross-sectional analytic study

OBJECTIVE

To determine and compare the serum metabolites in missed abortion versus normal early pregnancy using ultra-high-performance liquid chromatography and tandem time-of-flight mass spectrometry, and to determine how these metabolites can be used to predict the potential biomarkers and possible metabolic pathways of a missed abortion.

METHODS

The serum of patients with a missed abortion was used as the experimental group and the serum of patients with an induced abortion during normal early pregnancy was used as the control group. Principal component analysis and orthogonal partial least square discriminant analysis were additionally used to observe the difference in metabolite distribution between the two groups. A variable weight value (variable importance in the projection; VIP) obtained from the orthogonal partial least squares discriminant analysis model more than 1 and P less than 0.05 were taken to indicate significant differences in metabolite screening. After this, enrichment analysis of the metabolic pathways of these metabolites was conducted using Fisher precise test in order to find the metabolic pathway with the highest correlation with the differential metabolites.

RESULTS

In total, 30 patients were included in the experimental group, with 30 patients in the control group. Fifty-five metabolites (VIP > 1, P < 0.05) with significant differences related to missed abortion were selected, among which 35 metabolites increased and 20 decreased in patients with a missed abortion. KEGG pathway enrichment analysis showed that the four metabolic pathways with the highest correlation were cholesterol metabolism, arginine biosynthesis, cell apoptosis, and the FoxO signaling pathway.

CONCLUSION

The missed abortion serum metabolites and changes in related metabolic pathways reported in this study provide a basis for the early prediction and diagnosis of a missed abortion.

Metabolomic markers of biological fluid in women with reproductive failure: a systematic review of current literatures

Understanding metabolic changes in reproductive failure, including early miscarriage (EM), recurrent miscarriage (RM) and repeated implantation failure (RIF), may be beneficial to understand the pathophysiology, thus improving pregnancy outcomes. Nine metabolomic profiling studies in women with reproductive failures (4 for EM, 3 for RM and 2 for RIF) were included for systematic review. In total 78, 75 and 25 significant metabolites were identified and 40, 40 and 34 metabolic pathways were enriched in EM, RM and RIF, respectively. Among them, 7 and 11 metabolites, and 28 and 28 pathways were shared between EM and RM and between RM and RIF, respectively. Notably, histidine metabolism has the highest impact in EM; phenylalanine, tyrosine and tryptophan biosynthesis. Ubiquinone and other terpenoid-quinone biosynthesis metabolism have the highest impact factor in RM; alanine, aspartate and glutamate metabolism have the highest impact factor in RIF. This study not only summarized the common and distinct metabolites and metabolic pathways in different reproductive failures but also summarized limitations of the study designs and methodologies. Hence, further investigations and validations of these metabolites are still urgently needed to understand the underlying metabolic mechanism for the development and treatment of reproductive failures.

Chemical Fingerprint Analysis and Ultra-Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry-Based Metabolomics Study of the Protective Effect of Buxue Yimu Granule in Medical-Induced Incomplete Abortion Rats

Medical abortion is a common method to terminate an early pregnancy and often causes serious complications such as abnormal uterine bleeding and endometritis. Buxue Yimu granule (BYG) is a well-known traditional Chinese medicine prescription composed of five kinds of drugs and is widely used in gynecology and obstetrics. The aim of the present study was to establish the quality standard of BYG and investigate its protective effect on incomplete abortion. The chemical fingerprint of BYG was established by high performance liquid chromatography (HPLC). The major compounds of BYG were determined by ultra-performance liquid chromatography with triple quadrupole mass spectrometry. An incomplete abortion rat model was induced by intragastric administration of mifepristone (8.3 mg·kg^-1) combined with misoprostol (100.0 μg·kg^-1) during early pregnancy. The serum levels of human chorionic gonadotrophin (HCG), estradiol (E₂), and progesterone (PG) were determined. The serum endogenous metabolites were analyzed by ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). Multivariate analysis, including partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), was employed to analyze the metabolic profiles, and MetaboAnalyst was used to investigate the metabolic pathways. Furthermore, hematoxylin-eosin staining (HE) was used to evaluate the histopathological changes in uterine tissue. The expression levels of VEGFA and NF-κB were detected by immunohistochemistry. The results indicated that HPLC fingerprint analysis can be successfully used to assess the quality of BYG. The medical-induced incomplete abortion rats were clearly separated from control rats, and the biochemical changes were gradually restored to normal after administration of BYG. Moreover, 19 potential biomarkers, including N-lactoylleucine, 2-piperidinone, isobutyryl-l-carnitine, eicosapentaenoylcholine, LysoPC(14:0), LysoPC(20:5), physagulin C, LysoPC(18:3), leukotriene D5, deoxycholic acid 3-glucuronide, glycine, pregnanediol 3-O-glucuronide, LysoPC(18:2), LysoPC(17:0/0:0), N-acetyl-leukotriene E4, LysoPC(18:0), platelet-activating factor, LysoPA(24:1), and LysoPC(18:1), which were mainly related to the amino acids metabolism, lipids metabolism, and bile acid biosynthesis, were identified. Consequently, BYG exerts a potential protective role in the intervention of incomplete abortion by anti-inflammatory, promote endometrial repair, and regulate the metabolic disorders.

UPLC/MS/MS-Based Metabolomics Study of the Hepatotoxicity and Nephrotoxicity in Rats Induced by Polygonum multiflorum Thunb

Polygonum multiflorum Thunb. (PM) is one of the most frequently used natural products in China. Its hepatotoxicity has been proven and reported. However, chronic PM toxicity is a dynamic process, and a few studies have reported the long-term hepatotoxic mechanism of PM or its nephrotoxicity. To elucidate the mechanism of hepatotoxicity and nephrotoxicity induced by PM after different administration times, different samples from rats were systematically investigated by traditional biochemical analysis, histopathological observation, and nontargeted metabolomics. The concentrations of direct bilirubin (DBIL) at 4 weeks and total bile acid, DBIL, uric acid, and blood urea nitrogen at 8 weeks were significantly increased in the treatment group compared with those in the control group. Approximately, 12 metabolites and 24 proteins were considered as unique toxic biomarkers and targets. Metabolic pathway analysis showed that the primary pathways disrupted by PM were phenylalanine and tyrosine metabolism, which resulted in liver injury, accompanied by chronic kidney injury. As the administration time increased, the toxicity of PM gradually affected vitamin B6, bile acid, and bilirubin metabolism, leading to aggravated liver injury, abnormal biochemical indicators, and marked nephrotoxicity. Our results suggest that the hepatotoxicity and nephrotoxicity caused by PM are both dynamic processes that affect different metabolic pathways at different administration times, which indicated that PM-induced liver and kidney injury should be treated differently in the clinic according to the degree of injury.