Metabolomics for laboratory diagnostics

Assessment of progression of pulmonary fibrosis based on metabonomics and analysis of intestinal microbiota

The main purpose of this study was to explore the changes of biomarkers in different developmental stages of bleomycin-induced pulmonary fibrosis (PF) in rats via comprehensive pathophysiology, UPLC-QTOF/MS metabonomic technology, and 16S rRNA gene sequencing of intestinal microbiota. The rats were randomly divided into normal control and 1-, 2- and 4-week model group. The rat model of PF was established by one-time intratracheal instillation of bleomycin. The levels of inflammatory and fibrosis-related factors such as hydroxyproline (HYP), type III procollagen (COL-III), type IV collagen (COL-IV), hyaluronidase (HA), laminin (LN), interleukin (IL)-1β, IL-6, malondialdehyde (MDA) increased and superoxide dismutase (SOD) decreased as the PF cycle progressed. In the 1-, 2- and 4-week model group, 2, 19 and 18 potential metabolic biomarkers and 3, 16 and 12 potential microbial biomarkers were detected, respectively, which were significantly correlated. Glycerophospholipid metabolism pathway was observed to be an important pathway affecting PF at 1, 2 and 4 weeks; arginine and proline metabolism pathways significantly affected PF at 2 weeks. Linoleic acid metabolism pathway exhibited clear metabolic abnormalities at 2 and 4 weeks of PF, and alpha-linolenic acid metabolism pathway significantly affected PF at 4 weeks.

Metabolomics: Implication in cardiovascular research and diseases

Cellular metabolism influences all aspects of cellular function and is crucial for overall organismal health. Metabolic disorders related to cardiovascular health can lead to cardiovascular diseases (CVDs). Moreover, associated comorbidities may also damage cardiovascular metabolism, exacerbating CVD and perpetuating a vicious cycle. Given the prominent role of metabolic alterations in CVD, metabolomics has emerged as an imperative technique enabling a comprehensive assessment of metabolites and metabolic architecture within the body. Metabolite profile and metabolic pathways help to deepen and broaden our understanding of complex genomic landscape and pathophysiology of CVD. Here in this review, we aim to overview the experimental and clinical applications of metabolomics in pathogenesis, diagnosis, prognosis, and management of various CVD plus future perspectives and limitations.

ENDOTHELIAL-DEPENDENT VASCULAR REACTIVITY AFTER CARDIOPULMONARY BYPASS IS ASSOCIATED WITH UNIQUE METABOLOMIC SIGNATURES

ABSTRACT

Cardiopulmonary bypass (CPB), an extracorporeal method necessary for the surgical correction of complex congenital heart defects, incites significant inflammation that affects vascular function. These changes are associated with alterations in cellular metabolism that promote energy production to deal with this stress. Utilizing laser Doppler perfusion monitoring coupled with iontophoresis in patients undergoing corrective heart surgery, we hypothesized that temporal, untargeted metabolomics could be performed to assess the link between metabolism and vascular function. Globally, we found 2,404 unique features in the plasma of patients undergoing CPB. Metabolites related to arginine biosynthesis were the most altered by CPB. Correlation of metabolic profiles with endothelial-dependent (acetylcholine [ACh]) or endothelial-independent (sodium nitroprusside [SNP]) vascular reactivity identified purine metabolism being most consistently associated with either vascular response. Concerning ACh-mediated responses, acetylcarnitine levels were most strongly associated, while glutamine levels were associated with both ACh and SNP responsiveness. These data provide insight into the metabolic landscape of children undergoing CPB for corrective heart surgery and provide detail into how these metabolites relate to physiological aberrations in vascular function.

Metabolomics efficiently discriminates monozygotic twins in peripheral blood

Monozygotic (MZ) twins cannot be distinguished using conventional forensic STR typing because they present identical STR genotypings. However, MZ twins do not always live in the same environment and often have different dietary and other lifestyle habits. Metabolic profiles are deyermined by individual characteristics and are also influenced by the environment in which they live. Therefore, they are potential markers capable of identifying MZ twins. Moreover, the production of proteins varies from organism to organism and is influenced by both the physiological state of the body and the external environment. Hence, we used metabolomics and proteomics to identify metabolites and proteins in peripheral blood to discriminate MZ twins. We identified 1749 known metabolites and 622 proteins in proteomic analysis. The metabolic profiles of four pairs of MZ twins revealed minor differences in intra-MZ twins and major differences in inter-MZ twins. Each pair of MZ twins exhibited distinct characteristics, and four metabolites-methyl picolinate, acesulfame, paraxanthine, and phenylbenzimidazole sulfonic acid-were observed in all four MZ twin pairs. These four differential exogenous metabolites conincidently show that the different external environments and life styles can be well distinguished by metabolites, considering that twins do not all have the same eating habits and living environments. Moreover, MZ twins showed different protein profiles in serum but not in whole blood. Thus, our results indicate that differential metabolites provide potential biomarkers for the personal identification of MZ twins in forensic medicine.

Metabolomics in the diagnosis of bacterial infections

One of the essential factors in the appropriate treatment of infections is accurate and timely laboratory diagnosis. The correct diagnosis of infections plays a vital role in determining desirable therapy and controlling the spread of pathogens. Traditional methods of infection diagnosis are limited by several factors such as insufficient sensitivity and specificity, being time-consuming and laborious, having a low ability to distinguish infection from non-infectious inflammatory conditions and a low potential to predict treatment outcomes. Therefore, it is necessary to find innovative strategies for detecting specific biomarkers in order to diagnose infections. The rapid advancement of metabolomics makes it possible to determine the pattern of metabolite changes in the both of pathogen and the host during an infection. Metabolomics is a method used to assess the levels and type of metabolites in an organism. Metabolites are of low-molecular-weight compounds produced as a result of metabolic processes and pathways within cells. Metabolomics provides valuable data to detect accurate biomarkers of specific biochemical features directly related to certain phenotypes or conditions. This study aimed to review the applications and progress of metabolomics as a biomarker for the diagnosis of bacterial infections.

Serum metabolite and metal ions profiles for breast cancer screening

Enhancing early-stage breast cancer detection requires integrating additional screening methods with current diagnostic imaging. Omics screening, using easily collectible serum samples, could serve as an initial step. Alongside biomarker identification capabilities, omics analysis allows for a comprehensive analysis of prevalent histological types-DCIS and IDC. Employing metabolomics, metallomics, and machine learning, could yield accurate screening models with valuable insights into organism responses. Serum samples of confirmed breast cancer patients were utilized to analyze metabolite and metal ion profiles, using two distinct analysis methods, proton NMR for metabolomics and ICP-OES for metallomics. The resulting responses were then subjected to discriminant analysis, progression biomarker exploration, examination of correlations between patients' metabolites and metal ions, and the impact of age and menopause status. Measured NMR spectra and metabolite relative integrals were used to achieve statistically significant discrimination through MVA between breast cancer and control groups. The analysis identified 24 metabolites and 4 metal ions crucial for discrimination. Furthermore, four metabolites were associated with disease progression. Additionally, there were important correlations and relationships between metabolite relative integrals, metal ion concentrations, and age/menopausal status subgroups. Quantified relative integrals allowed for discrimination between studied subgroups, validated with a holdout set. Feature importance and statistical analysis for metabolomics and metallomics extracted a set of common entities which in combination provides valuable insights into ongoing molecular disturbances and disease progression.

Using widely targeted metabolomics profiling to explore differences in constituents of three Bletilla species

Bletilla striata has been used in traditional Chinese medicine for thousands of years to treat a variety of health diseases. Currently, metabolic causes of differences in medicinal values are unknown, due to the lack of a large-scale and comprehensive investigation of metabolites in Bletilla species. In order to gain a better understanding of the major chemical constituents responsible for the medicinal value, this study aimed to explore the metabolomic differences among three Bletilla species (Bletilla striata: Bs, Bletilla ochracea: Bo and Bletilla formosana: Bf). There were 258 different metabolites between 'Bo' and 'Bf', the contents of 109 metabolites had higher abundance, while 149 metabolites showed less accumulation. There were 165 different metabolites between the 'Bs' and 'Bf', content of 72 metabolites was increased and content of 93 metabolites was decreased. There were 239 different metabolites between the 'Bs' and 'Bo', content of 145 metabolites was increased and content of 94 metabolites was decreased. In the Bo_vs_Bf, Bs_vs_Bf and Bs_vs_Bo groups, the major differential categories were flavonoids, phenolic acids, organic acids and alkaloids. Moreover, the differential metabolites were clustered into clear and distinct profiles via K-means analysis. In addition, the major differential categories were flavonoids, phenolic acids, organic acids and alkaloids. The 'Flavonoid biosynthesis' (ko00941) and 'Phenylalanine metabolism' (ko00360) pathways were significantly enriched in Bo_vs_Bf, Bs_vs_Bf and Bs_vs_Bo comparisons. These results clarify the metabolomics in different Bletilla species, as well as providing basis for the phamaceutical value of novel species of Bletilla.

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.

Analyzing how SiMiao Wan regulates ferroptosis to prevent RA-ILD using metabolomics and cyberpharmacology

BACKGROUND

Interstitial lung disease (ILD) is a common complication of rheumatoid arthritis (RA) that plays a significant role in the morbidity and mortality of individuals with this condition. In clinical settings, Si Miao Wan (SMW), a traditional Chinese medicine, is often utilized for the management of RA, as it is believed to possess properties that aid in reducing inflammation, eliminating excess moisture, and alleviating joint pain.

PURPOSE

The primary objective of this investigation was to elucidate the potential mechanism of RA-ILD prevention from the perspective of ferroptosis mediated by SMW.

METHODS

UPLC-Q-TOF/MS and network pharmacology were employed to forecast the potential targets of SMW for the early prevention of RA-ILD. Following this, HE staining, metabolomics, and RT-PCR were utilized to investigate the mechanism by which SMW prevents RA-ILD at an early stage.

RESULTS

Following six weeks of continuous administration of SMW extract at a dosage of 2.16 g/kg/day, it was observed that SMW exhibited early preventive effects against RA-ILD. Metabolomics analysis revealed seven potential biomarkers linked to the pharmacological efficacy of SMW in the early prevention of RA-ILD. Additionally, network pharmacology analysis suggested that SMW may exert its therapeutic effects on RA-ILD by modulating signaling pathways associated with lipid metabolism, atherosclerosis, TNF, and IL-17. Ultimately, through the integration of metabolomics and network pharmacology analysis, along with subsequent verification, it was determined that the early prevention of rheumatoid arthritis-associated interstitial lung disease (RA-ILD) by Shenmai injection (SMW) is associated with the ferroptosis pathway.

CONCLUSION

This research offers preliminary insights into the potential mechanism by which traditional Chinese medicine Shen Mai Wan (SMW) may mitigate the early onset of Rheumatoid Arthritis-Interstitial Lung Disease (RA-ILD) via the process of ferroptosis. Furthermore, it establishes a theoretical framework for the development of innovative SMW-based pharmaceuticals for the management of RA-ILD. The signal proteins implicated in this process are anticipated to emerge as crucial targets for the prevention of RA-ILD.

Non-target metabolomics unravels the effect and mechanism of Lianpu Drink on spleen-stomach damp-heat syndrome

BACKGROUND

Lianpu Drink (LPY) is a classic prescription for treating spleen-stomach damp-heat syndrome (SSDHS), known for its ability to clear heat and eliminate dampness. However, the underlying mechanisms of LPY in treating SSDHS remain unclear.

OBJECTIVES

This study aims to use non-target metabolomics to unravel the effects and mechanisms of LPY on SSDHS.

METHODS

A metabolomics technique based on ultra-high-performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to identify the endogenous small-molecule metabolites in the urine of SSDHS model rats and find the metabolites associated with the LPY treatment of SSDHS. Furthermore, a network pharmacological analysis and molecular docking experiments were used to screen and validate the key metabolic pathways regulated by LPY.

RESULTS

LPY exerted therapeutic effects on SSDHS by increasing the levels of motilin and gastrin, reducing the rectal temperature, alleviating the pathological changes in gastric and colonic tissues, and regulating the metabolic pattern in SSDHS rats. A total of 25 different metabolites, including L-histidine, citric acid and isocitric acid, were identified as the potential biomarkers for SSDHS via metabolomics. Among them, 11 metabolites were substantially reversed by LPY, including L-histidine, citric acid, isocitric acid, pantothenic acid, homovanillic acid sulfate, hippuric acid, indole-3-carboxilic acid-O-sulphate, 6-hydroxy-5-methoxyindole glucuronide, 2-phenylethan-ol glucuronide, 3-hydroxydodecanedioic acid and 3-methoxy-4-hydroxy-phenylethyleneglyclol sulfate. The results of network pharmacological analysis and molecular docking experiments validated that LPY ameliorated SSDHS by regulating the citrate cycle and histidine metabolism.

CONCLUSION

We preliminarily investigated the effects and mechanisms of LPY on SSDHS at the level of endogenous small-molecule metabolites. Furthermore, this study provides a novel perspective for objectively evaluating the therapeutic effects, and exploring the mechanisms of Chinese medicinal formulas on SSDHS.

Integration of proteomics and metabolomics analysis investigate mechanism of As-induced immune injury in rat spleen

Arsenic (As) is a widespread metalloid and human carcinogen found in the natural environment, and multiple toxic effects have been shown to be associated with As exposure. As can be accumulated in the spleen, the largest peripheral lymphatic organ, and long-term exposure to As can lead to splenic injury. In this study, a Sprague-Dawley (SD) rat model of As-poisoned was established, aiming to explore the molecular mechanism of As-induced immune injury through the combined analysis of proteomics and metabolomics of rats' spleen. After feeding the rats with As diet (50 mg/kg) for 90 days, the spleen tissue of the rats in the As-poisoned group was damaged, the level of As was significantly higher than that of the control group (P < 0.001), and the level of inflammatory cytokine interleukin-6 (IL-6) was decreased (P < 0.01). Proteomics and metabolomics results showed that a total of 134 differentially expressed proteins (DEPs) (P < 0.05 and fold change > 1.2) and 182 differentially expressed metabolites (DEMs) (VIP >1 and P < 0.05) were identified in the spleens of the As poisoned group compared to the control group (As/Ctrl). The proteomic results highlight the role of hypoxia-inducible factors (HIF), natural killer cell mediated cytotoxicity, and ribosomes. The major pathways of metabolic disruption included arachidonic acid (AA) metabolism, glycerophospholipid metabolism and folate single-carbon pool. The integrated analysis of these two omics suggested that Hmox1, Stat3, arachidonic acid, phosphatidylcholine and leukotriene B4 may play key roles in the mechanism of immune injury to the spleen by As exposure. The results indicate that As exposure can cause spleen damage in rats. Through proteomic and metabolomic analysis, the key proteins and metabolites and their associated mechanisms were obtained, which provided a basis for further understanding of the molecular mechanism of spleen immune damage caused by As exposure.

Engineered Bimetallic MOF-Crafted Bullet Aids in Penetrating Serum Metabolic Traits of Chronic Obstructive Pulmonary Disease

Metabolomics analysis based on body fluids, combined with high-throughput laser desorption and ionization mass spectrometry (LDI-MS), holds great potential and promising prospects for disease diagnosis and screening. On the other hand, chronic obstructive pulmonary disease (COPD) currently lacks innovative and powerful diagnostic and screening methods. In this work, CoFeNMOF-D, a metal-organic framework (MOF)-derived metal oxide nanomaterial, was synthesized and utilized as a matrix to assist LDI-MS for extracting serum metabolic fingerprints of COPD patients and healthy controls (HC). Through machine learning algorithms, successful discrimination between the COPD and HC was achieved. Furthermore, four potential biomarkers significantly downregulated in COPD were screened out. The disease diagnostic models based on the biomarkers demonstrated excellent diagnostic performance across different algorithms, with area under the curve (AUC) values reaching 0.931 and 0.978 in the training and validation sets, respectively. Finally, the potential metabolic pathways and disease mechanisms associated with the identified markers were explored. This work advances the application of LDI-based molecular diagnostics in clinical settings.

Integration of Transcriptomics and Metabolomics Reveals the Antitumor Mechanism of Protopanaxadiol Triphenylphosphate Derivative in Non-Small-Cell Lung Cancer

The objective of this study was to enhance the membrane permeability and anticancer effectiveness of (20S)-protopanaxadiol (PPD) by introducing triphenylphosphonium into the OH group at the C-3 site. This study shows that the anti-proliferation activity of CTPPPPD, with an IC50 value of 1.65 ± 0.10 μmol/L, was 33-times better than that of PPD (with an IC50 value of 54.56 ± 4.56 μmol/L) and superior to that of cisplatin (with an IC50 value of 1.82 ± 0.25 μmol/L) against A549 cells. Biological examinations suggested that CTPPPPD treatment reduced the growth rate of A549 cells, increased the permeability of cell membranes, and changed the structure of chromosomal DNA in a concentration-dependent manner. Annexin V/PI assay and flow cytometry were employed to detect the effect of CTPPPPD on the apoptosis of A549 cells. The results showed that CTPPPPD could induce the apoptosis of A549 cells, and the apoptosis rate of A549 cells treated with 0, 1.0, 2.0, and 4.0 μM of CTPPPPD for 24 h was 0%, 4.9%, 12.7%, and 31.0%, respectively. The integration of transcriptomics and metabolomics provided a systematic and detailed perspective on the induced antitumor mechanisms. A combined analysis of DEGs and DAMs suggested that they were primarily involved in the central carbon metabolism pathway in cancer, as well as the metabolism of aminoacyl-tRNA biosynthesis, alanine, aspartate, and glutamate. Central carbon metabolism in cancer-related genes, i.e., SLC16A3, FGFR3, LDHA, PGAM1, and SLC2A1, significantly reduced after treatment with CTPPPPD. In particular, the dominant mechanism responsible for total antitumor activity may be attributed to perturbations in the PI3K-AKT, MAPK, and P53 pathways. The findings derived from transcriptomics and metabolomics were empirically confirmed through q-PCR and molecular docking. Further analyses revealed that CTPPPPD could be a promising lead for the development of protopanaxadiol for non-small-cell lung cancer (NSCLC) drugs.

Plasma metabolites associated with biopsychosocial parameters in overweight/obese women with severe knee osteoarthritis

Introduction

Obesity aligned with quadriceps muscle weakness contributes to the high incidence of knee osteoarthritis (KOA), which is prevalent in women. Although molecular signatures of KOA have been suggested, the association between biopsychosocial responses and the plasma metabolomic profile in overweight/ obese women with KOA remains in its early stages of investigation. This study aims to associate the plasma metabolome with biopsychosocial parameters of overweight/obese women diagnosed with KOA.

Methods

Twenty-eight overweight/obese women (Control-n = 14; KOA-n = 14) underwent two visits to the laboratory. Functional tests and questionnaires assessing biopsychosocial parameters were administered during the first visit. After 48 h, the participants returned to the laboratory for blood collection. Specific to the KOA condition, the Numerical Pain Rating Scale (NPRS), Tampa Scale for Kinesiophobia (TSK), and Knee injury and Osteoarthritis Outcome Score (KOOS) were applied.

Results

Thirteen molecules were different between groups, and four correlated with KOA's biopsychosocial parameters. DG 22:4-2OH and gamma-Glutamylvaline were inversely associated with KOSS leisure and TSK score, respectively. LysoPE 18:0 and LysoPE 20:5 were positively associated with KOSS symptoms and TSK score, respectively.

Discussion

While the correlations of LysoPE 18:0 and gamma-Glutamylvaline are supported by existing literature, this is not the case for DG 22:4-2OH and LysoPE 20:5. Further studies are recommended to better elucidate these correlations before dismissing their potential involvement in the biopsychosocial factors of the disease.

Clinical metabolomics: current state and prospects in Russia

Using analytical technologies it is possible now to measure the entire diversity of molecules even in a small amount of biological samples. Metabolomic technologies simultaneously analyze thousands of low-molecular substances in a single drop of blood. Such analytical performance opens new possibilities for clinical laboratory diagnostics, still relying on the measurement of only a limited number of clinically significant substances. However, there are objective difficulties hampering introduction of metabolomics into clinical practice. The Institute of Biomedical Chemistry (IBMC), consolidating the efforts of leading scientific and medical organizations, has achieved success in this area by developing a clinical blood metabogram (CBM). CBM opens opportunities to obtain overview on the state of the body with the detailed individual metabolic characteristics of the patient. A number of scientific studies have shown that the CBM is an effective tool for monitoring the state of the body, and based on the CBM patterns (signatures), it is possible to diagnose and monitor the treatment of many diseases. Today, the CBM creation determines the current state and prospects of clinical metabolomics in Russia. This article, dedicated to the 80th anniversary of IBMC, is a review of these achievements focused on a discussion of their implementation in clinical practice.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

Volatile organic compounds in exhaled breath of newborns: a pilot study

OBJECTIVE

To assess volatile organic compounds (VOCs) in breath samples collected non-invasively from preterm and full-term infants.

METHODS

This was a pilot study included preterm and full-term infants who were not intubated or suspected or diagnosed with metabolic or gastrointestinal disorders. The samples were analyzed for VOCs using a selected-ion flow-tube mass spectrometer.

RESULTS

Twenty infants were included; ten preterm and ten full-term infants. Twenty-two VOCs were detected and measurable in all samples. There was a significant difference between preterm and full-term infants for the 2-propanol, acetaldehyde, acetone, acetonitrile, benzene, ethanol, isoprene, pentane, 3-methylhexane, 2-nonene, ethane, triethylamine, and trimethylamine compounds.

CONCLUSION

It is feasible to measure VOCs in breath samples of preterm and full-term non-intubated infants. Full-term infants express different concentrations than preterm infants. Further studies are needed to examine the utility and reproducibility of measuring VOCs to identify neonatal diseases and predict outcomes.

Tolerance enhancement of Dendrobium officinale by salicylic acid family-related metabolic pathways under unfavorable temperature

BACKGROUND

Unfavorable temperatures significantly constrain the quality formation of Dendrobium officinale, severely limiting its food demand. Salicylic acid (SA) enhances the resistance of D. officinale to stress and possesses various analogs. The impact and mechanism of the SA family on improving the quality of D. officinale under adverse temperature conditions remains unclear.

RESULTS

Combined with molecular docking analysis, chlorophyll fluorescence and metabolic analysis after treatments with SA analogues or extreme temperatures are performed in this study. The results demonstrate that both heat and cold treatments impede several main parameters of chlorophyll fluorescence of D. officinale, including the ΦPSII parameter, a sensitive growth indicator. However, this inhibition is mitigated by SA or its chemically similar compounds. Comprehensive branch imaging of ΦPSII values revealed position-dependent improvement of tolerance. Molecular docking analysis using a crystal structure model of NPR4 protein reveals that the therapeutic effects of SA analogs are determined by their binding energy and the contact of certain residues. Metabolome analysis identifies 17 compounds are considered participating in the temperature-related SA signaling pathway. Moreover, several natural SA analogs such as 2-hydroxycinnamic acid, benzamide, 2-(formylamino) benzoic acid and 3-o-methylgallic acid, are further found to have high binding ability to NPR4 protein and probably enhance the tolerance of D. officinale against unfavorable temperatures through flavone and guanosine monophosphate degradation pathways.

CONCLUSIONS

These results reveal that the SA family with a high binding capability of NPR4 could improve the tolerance of D. officinale upon extreme temperature challenges. This study also highlights the collaborative role of SA-related natural compounds present in D. officinale in the mechanism of temperature resistance and offers a potential way to develop protective agents for the cultivation of D. officinale.

Combination of Transcriptomics and Metabolomics Analyses Provides Insights into the Mechanisms of Growth Differences in Spotted Seabass (Lateolabrax maculatus) Fed a Low-Phosphorus Diet

To analyze the potential mechanisms of growth differences in spotted seabass (Lateolabrax maculatus) fed a low-phosphorus diet, a total of 150 spotted seabass with an initial body weight of 4.49 ± 0.01 g were used (50 fish per tank) and fed a low-phosphorus diet for eight weeks. At the end of the experiment, five of the heaviest and five of the lightest fish were selected from each tank as fast-growing spotted seabass (FG) and slow-growing spotted seabass (SG), respectively, and their livers were analyzed by metabolomics and transcriptomics. The hepatic antioxidant capacity of the FG fed a low-phosphorus diet was significantly higher than that of the SG. A total of 431 differentially expressed genes (DEGs) were determined in the two groups, and most of the DEGs were involved in metabolism-related pathways such as steroid biosynthesis, glycolysis/gluconeogenesis, and protein digestion and absorption. Substance transport-related regulators and transporters were predominantly up-regulated. Furthermore, a large number of metabolites in the liver of FG were significantly up-regulated, especially amino acids, decanoyl-L-carnitine and dehydroepiandrosterone. The integration analysis of differential metabolites and genes further revealed that the interaction between protein digestion and absorption, as well as phenylalanine metabolism pathways were significantly increased in the liver of FG compared to those of the SG. In general, FG fed a low-phosphorus diet induced an enhancement in hepatic immune response, substance transport, and amino acid metabolism. This study provides new information on genetic mechanisms and regulatory pathways underlying differential growth rate and provides a basis for the foundation of efficient utilization of low-phosphorus diets and selective breeding programs for spotted seabass.

Neuroprotective Mechanism of MOTS-c in TBI Mice: Insights from Integrated Transcriptomic and Metabolomic Analyses

Background

Traumatic brain injury (TBI) is a condition characterized by structural and physiological disruptions in brain function caused by external forces. However, as the highly complex and heterogenous nature of TBI, effective treatments are currently lacking. Mitochondrial open reading frame of the 12S rRNA-c (MOTS-c) has shown notable antinociceptive and anti-inflammatory effects, yet its detailed neuroprotective effects and mode of action remain incompletely understood. This study investigated the neuroprotective effects and the underlying mechanisms of MOTS-c.

Methods

Adult male C57BL/6 mice were randomly divided into three groups: control (CON) group, MOTS-c group and TBI group. Enzyme-linked immunosorbent assay (ELISA) kit method was used to measure the expression levels of MOTS-c in different groups. Behavioral tests were conducted to assess the effects of MOTS-c. Then, transcriptomics and metabolomics were performed to search Differentially Expressed Genes (DEGs) and Differentially Expressed Metabolites (DEMs), respectively. Moreover, the integrated transcriptomics and metabolomics analysis were employed using R packages and online Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Results

ELISA kit method showed that TBI resulted in a decrease in the expression of MOTS-c. and peripheral administration of MOTS-c could enter the brain tissue after TBI. Behavioral tests revealed that MOTS-c improved memory, learning, and motor function impairments in TBI mice. Additionally, transcriptomic analysis screened 159 differentially expressed genes. Metabolomic analysis identified 491 metabolites with significant differences. Integrated analysis found 14 KEGG pathways, primarily related to metabolic pathways. Besides, several signaling pathways were enriched, including neuroactive ligand-receptor interaction and retrograde endocannabinoid signaling.

Conclusion

TBI reduced the expression of MOTS-c. MOTS-c reduced inflammatory responses, molecular damage, and cell death by down-regulating macrophage migration inhibitory factor (MIF) expression and activating the retrograde endocannabinoid signaling pathway. In addition, MOTS-c alleviated the response to hypoxic stress and enhanced lipid β-oxidation to provide energy for the body following TBI. Overall, our study offered new insights into the neuroprotective mechanisms of MOTS-c in TBI mice.

Navigating Challenges and Opportunities in Multi-Omics Integration for Personalized Healthcare

The field of multi-omics has witnessed unprecedented growth, converging multiple scientific disciplines and technological advances. This surge is evidenced by a more than doubling in multi-omics scientific publications within just two years (2022-2023) since its first referenced mention in 2002, as indexed by the National Library of Medicine. This emerging field has demonstrated its capability to provide comprehensive insights into complex biological systems, representing a transformative force in health diagnostics and therapeutic strategies. However, several challenges are evident when merging varied omics data sets and methodologies, interpreting vast data dimensions, streamlining longitudinal sampling and analysis, and addressing the ethical implications of managing sensitive health information. This review evaluates these challenges while spotlighting pivotal milestones: the development of targeted sampling methods, the use of artificial intelligence in formulating health indices, the integration of sophisticated n-of-1 statistical models such as digital twins, and the incorporation of blockchain technology for heightened data security. For multi-omics to truly revolutionize healthcare, it demands rigorous validation, tangible real-world applications, and smooth integration into existing healthcare infrastructures. It is imperative to address ethical dilemmas, paving the way for the realization of a future steered by omics-informed personalized medicine.

Machine Learning-Driven SERS Nanoendoscopy and Optophysiology

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic efficacy, and fundamental biochemical function of the host. Following the completion of the Human Genome Project, current research aims to link genes to functions of an organism and investigate how the environment modulates functional properties of organisms. New analytical methods have been developed to detect chemical changes with high spatial and temporal resolution, including minimally invasive surface-enhanced Raman scattering (SERS) nanofibers using the principles of endoscopy (SERS nanoendoscopy) or optical physiology (SERS optophysiology). Given the large spectral data sets generated from these experiments, SERS nanoendoscopy and optophysiology benefit from advances in data science and machine learning to extract chemical information from complex vibrational spectra measured by SERS. This review highlights new opportunities for intracellular, extracellular, and in vivo chemical measurements arising from the combination of SERS nanosensing and machine learning.

Genetics, transcriptomics, metagenomics, and metabolomics in the pathogenesis and prediction of atrial fibrillation

The primary cellular substrates of atrial fibrillation (AF) and the mechanisms underlying AF onset remain poorly characterized and therefore, its risk assessment lacks precision. While the use of omics may enable discovery of novel AF risk factors and narrow down the cellular pathways involved in AF pathogenesis, the work is far from complete. Large-scale genome-wide association studies and transcriptomic analyses that allow an unbiased, non-candidate-gene-based delineation of molecular changes associated with AF in humans have identified at least 150 genetic loci associated with AF. However, only few of these loci have been thoroughly mechanistically dissected, indicating that much remains to be discovered for targeted diagnostics and therapeutics. Metabolomics and metagenomics, on the other hand, add to the understanding of AF downstream of the primary substrate and integrate the signalling of environmental and host factors, respectively. These two rapidly developing fields have already provided several correlates of prevalent and incident AF that require additional validation in external cohorts and experimental studies. In this review, we take a look at the recent developments in genetics, transcriptomics, metagenomics, and metabolomics and how they may aid in improving the discovery of AF risk factors and shed light into the molecular mechanisms leading to AF onset.

Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

[Characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome]

OBJECTIVES

To study the characteristics and clinical value of intestinal metabolites in children aged 4-6 years with obstructive sleep apnea-hypopnea syndrome (OSAHS).

METHODS

A total of 31 children aged 4-6 years with OSAHS were prospectively enrolled as the test group, and 24 healthy children aged 4-6 years were included as the control group. Relevant clinical indicators were recorded. Fecal samples were collected, and non-targeted metabolomics analysis using liquid chromatography-mass spectrometry was performed to detect all metabolites.

RESULTS

A total of 206 metabolites were detected, mainly amino acids and their derivatives. There was a significant difference in the overall composition of intestinal metabolites between the test and control groups (P<0.05). Eighteen different metabolites were selected, among which six (N-acetylmethionine, L-methionine, L-lysine, DL-phenylalanine, L-tyrosine, and L-isoleucine) had receiver operating characteristic curve areas greater than 0.7 for diagnosing OSAHS. Among them, N-acetylmethionine had the largest area under the curve, which was 0.807, with a sensitivity of 70.83% and a specificity of 80.65%. Correlation analysis between different metabolites and clinical indicators showed that there were positive correlations between the degree of tonsil enlargement and enterolactone, between uric acid and phenylacetaldehyde, between blood glucose and acetylmethionine, and between cholesterol and 9-bromodiphenyl and procaine (P<0.05). There were negative correlations between the degree of tonsil enlargement and N-methyltyramine, aspartate aminotransferase and indolepropionic acid and L-isoleucine, between alanine aminotransferase and DL-phenylalanine, between indolepropionic acid and L-isoleucine, between uric acid and hydroxyquinoline, and between urea nitrogen and N,N-dicyclohexylurea (P<0.05). The metabolic functional pathways affected by differential metabolites mainly included riboflavin metabolism, arginine and proline metabolism, pantothenic acid and coenzyme A biosynthesis, cysteine and methionine metabolism, lysine degradation and glutathione metabolism.

CONCLUSIONS

Intestinal metabolites and metabolic functions are altered in children aged 4-6 years with OSAHS, primarily involving amino acid metabolism disorders. The screened differential intestinal metabolites have potential screening and diagnostic value as biomarkers for OSAHS.

Stereoselective Amine-omics Using Heavy Atom Isotope Labeled l- and d-Marfey's Reagents

Biological amines and amino acids play essential roles in many biochemical processes. The chemical complexity of biological samples is challenging, and the selective identification and quantification of amines and amino acid stereoisomers would be very useful for amine-focused "amino-omics" studies. Many amines and amino acids are chiral, and their stereoisomers cannot be resolved on achiral media without chiral derivatization. In prior studies, we demonstrated the use of Marfey's reagent─a chiral derivatization reagent for amines and phenolic OH groups─for the LC-MS/MS resolution and quantification of amines and amino acid stereoisomers. In this study, a heavy atom isotope labeled Marfey's reagent approach for the stereoselective detection and quantification of amines and amino acids was developed. Heavy (13C2) l-Marfey's (Hl-Mar) and heavy (2H3) d-Marfey's (Hd-Mar) were synthesized from 13C2-l-Ala and 2H3-d-Ala, respectively. Both light and heavy Marfey's reagents were used to derivatize standard amine mixtures, which were analyzed by LC-QToF-HRMS. Aligned peak lists were comparatively analyzed by light vs heavy Mar mass differences to identify mono-, di-, and tri-Marfey's adducts and then by the retention time difference between l- and d-Mar derivatives to identify stereoisomers. This approach was then applied to identify achiral and chiral amine and amino acid components in a methicillin-resistant Staphylococcus aureus (MRSA) extract. This approach shows high analytical selectivity and reproducibility.

Metabolic profiling during COVID-19 infection in humans: Identification of potential biomarkers for occurrence, severity and outcomes using machine learning

BACKGROUND

After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity.

METHODS

Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models.

RESULTS

The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness.

CONCLUSIONS

Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites.

Development and trends in metabolomics studies in psoriasis: A bibliometric analysis of related research from 2011 to 2024

Background

Psoriasis is a chronic, inflammatory skin disease with autoimmune characteristics. Recent research has made significant progress in the field of psoriasis metabolomics. However, there is a lack of bibliometric analysis on metabolomics of psoriasis. The objective of this study is to utilize bibliometrics to present a comprehensive understanding of the knowledge structure and research hotspots in psoriasis within the field of metabolomics.

Methods

We conducted a bibliometric analysis by searching the Web of Science Core Collection database for publications on metabolomics in psoriasis from 2011 to 2024. To perform this analysis, we utilized tools such as VOSviewers, CiteSpace, and the R package "bibliometrix".

Results

A total of 307 articles from 47 countries, with the United States and China leading the way, were included in the analysis. The publications focusing on metabolomics in psoriasis have shown a steady year-on-year growth. The Medical University of Bialystok is the main research institution. The International Journal of Molecular Sciences emerges as the prominent journal in the field, while the Journal of Investigative Dermatology stands out as the highly co-cited publication. A total of 2029 authors contributed to these publications, with Skrzydlewska Elzbieta, Baran Anna, Flisiak Iwona, Murakami Makoto being the most prolific contributors. Notably, Armstrong April W. received the highest co-citation. Investigating the mechanisms of metabolomics in the onset and progression of psoriasis, as well as exploring therapeutic strategies, represents the primary focus of this research area. Emerging research hotspots encompass inflammation, lipid metabolism, biomarker, metabolic syndrome, obesity, and arthritis.

Conclusion

The results of this study indicate that metabolism-related research is thriving in psoriasis, with a focus on the investigation of metabolic targets and interventions within the metabolic processes. Metabolism is expected to be a hot topic in future psoriasis research.

Biomarkers of bipolar disorder based on metabolomics: A systematic review

Bipolar disorder (BD) is a severe affective disorder characterized by recurrent episodes of depression or mania/hypomania, which significantly impair cognitive function, life skills, and social abilities of patients. There is little understanding of the neurobiological mechanisms of BD. The diagnosis of BD is primarily based on clinical assessment and psychiatric examination, highlighting the urgent need for objective markers to facilitate the diagnosis of BD. Metabolomics can be used as a diagnostic tool for disease identification and evaluation. This study summarized the altered metabolites in BD and analyzed aberrant metabolic pathways, which might contribute to the diagnosis of BD. Search of PubMed and Web of science for human BD studies related to metabolism to identify articles published up to November 19, 2022 yielded 987 articles. After screening and applying the inclusion and exclusion criteria, 16 untargeted and 11 targeted metabolomics studies were included. Pathway analysis of the potential differential biometabolic markers was performed using the Kyoto encyclopedia of genes and genomes (KEGG). There were 72 upregulated and 134 downregulated biomarkers in the untargeted metabolomics studies using blood samples. Untargeted metabolomics studies utilizing urine specimens revealed the presence of 78 upregulated and 54 downregulated metabolites. The targeted metabolomics studies revealed abnormalities in the metabolism of glutamate and tryptophan. Enrichment analysis revealed that the differential metabolic pathways were mainly involved in the metabolism of glucose, amino acid and fatty acid. These findings suggested that certain metabolic biomarkers or metabolic biomarker panels might serve as a reference for the diagnosis of BD.

Metabolomics for the diagnosis of bladder cancer: A systematic review

Objective

Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.

Methods

A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.

Results

The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.

Conclusion

The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.

Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

Gentiopicroside improves non-alcoholic steatohepatitis by activating PPARα and suppressing HIF1

Gentiopicroside (GPS) is a highly water-soluble small-molecule drug and the main bioactive secoiridoid glycoside of Gentiana scabra that has been shown to have hepatoprotective effects against non-alcoholic steatohepatitis (NASH), a form of non-alcoholic fatty liver disease (NAFLD) that can progress to cirrhosis and hepatocellular carcinoma. However, the effects of GPS on NASH and the underlying mechanisms remain obscure. Firstly, a high-fat, high-cholesterol (HFHC) diet and a high-sugar solution containing d-fructose and d-glucose were used to establish a non-alcoholic steatohepatitis (NASH) mice model. Secondly, we confirmed GPS supplementation improve metabolic abnormalities and reduce inflammation in NASH mice induced by HFHC and high-sugar solution. Then we used metabolomics to investigate the mechanisms of GPS in NASH mice. Metabolomics analysis showed GPS may work through the Peroxisome Proliferator-Activated Receptor (PPAR) signaling pathway and glycine, serine, and threonine metabolism. Functional metabolites restored by GPS included serine, glycine, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Western blot and qRT-PCR analysis confirmed GPS improve NASH by regulating PPARα and Hypoxia-Inducible Factor-1α (HIF-1α) signaling pathways. In vitro, studies further demonstrated EPA and DHA enhance fatty acid oxidation through the PPARα pathway, while serine and glycine inhibit oxidative stress through the HIF-1α pathway in palmitic acid-stimulated HepG2 cells. Our results suggest GPS's anti-inflammatory and anti-steatosis effects in NASH progression are related to the suppression of HIF-1α through the restoration of L-serine and glycine and the activation of PPARα through increased EPA and DHA.

Profiling canine mammary tumors: A potential model for studying human breast cancer

Despite all clinical progress recorded in the last decades, human breast cancer (HBC) remains a major challenge worldwide both in terms of its incidence and its management. Canine mammary tumors (CMTs) share similarities with HBC and represent an alternative model for HBC. The utility of the canine model in studying HBC relies on their common features, include spontaneous development, subtype classification, mutational profile, alterations in gene expression profile, and incidence/prevalence. This review describes the similarities between CMTs and HBC regarding genomic landscape, microRNA expression alteration, methylation, and metabolomic changes occurring during mammary gland carcinogenesis. The primary purpose of this review is to highlight the advantages of using the canine model as a translational animal model for HBC research and to investigate the challenges and limitations of this approach.

Determining predictive metabolomic biomarkers of meniscal injury in dogs with cranial cruciate ligament rupture

OBJECTIVES

This study used hydrogen nuclear magnetic resonance spectroscopy for the first time to examine differences in the metabolomic profile of stifle joint synovial fluid from dogs with cranial cruciate ligament rupture with and without meniscal injuries, in order to identify biomarkers of meniscal injury. Identifying a biomarker of meniscal injury could then ultimately be used to design a minimally invasive diagnostic test for meniscal injuries in dogs.

MATERIALS AND METHODS

Stifle joint synovial fluid was collected from dogs undergoing stifle joint surgery or arthrocentesis for lameness investigations. We used multi-variate statistical analysis using principal component analysis and univariate statistical analysis using one-way analysis of variance and analysis of co-variance to identify differences in the metabolomic profile between dogs with cranial cruciate ligament rupture and meniscal injury, cranial cruciate ligament rupture without meniscal injury, and neither cranial cruciate ligament rupture nor meniscal injury, taking into consideration clinical variables.

RESULTS

A total of 154 samples of canine synovial fluid were included in the study. Sixty-four metabolites were annotated to the hydrogen nuclear magnetic resonance spectroscopy spectra. Six spectral regions were found to be significantly altered (false discovery rate adjusted P-value <0.05) between groups with cranial cruciate ligament rupture with and without meniscal injury, including three attributed to nuclear magnetic resonance mobile lipids [mobile lipid -CH3 (P=0.016), mobile lipid -n(CH3 )3 (P=0.017), mobile unsaturated lipid (P=0.031)].

CLINICAL SIGNIFICANCE

We identified an increase in nuclear magnetic resonance mobile lipids in the synovial fluid of dogs with meniscal injury which are of interest as potential biomarkers of meniscal injury.

Exploiting volatile fingerprints for bladder cancer diagnosis: A scoping review of metabolomics and sensor-based approaches

Bladder cancer (BC) represents a significant global health concern, for which early detection is essential to improve patient outcomes. This review evaluates the potential of the urinary volatile organic compounds (VOCs) as biomarkers for detecting and staging BC. The methods used include gas chromatography-mass spectrometry (GC-MS)-based metabolomics and electronic-nose (e-nose) sensors. The GC-MS studies that have been published reveal diverse results in terms of diagnostic performance. The sensitivities range from 27 % to an impressive 97 %, while specificities vary between 43 % and 94 %. Furthermore, the accuracies reported in these studies range from 80 to 89 %. In the urine of BC patients, a total of 80 VOCs were discovered to be significantly altered when compared to controls. These VOCs encompassed a variety of chemical classes such as alcohols, aldehydes, alkanes, aromatic compounds, fatty acids, ketones, and terpenoids, among others. Conversely, e-nose-based studies displayed sensitivities from 60 to 100 %, specificities from 53 to 96 %, and accuracies from 65 to 97 %. Interestingly, conductive polymer-based sensors performed better, followed by metal oxide semiconductor and optical sensors. GC-MS studies have shown improved performance in detecting early stages and low-grade tumors, providing valuable insights into staging. Based on these findings, VOC-based diagnostic tools hold great promise for early BC detection and staging. Further studies are needed to validate biomarkers and their classification performance. In the future, advancements in VOC profiling technologies may significantly contribute to improving the overall survival and quality of life for BC patients.

The regulatory effect of Angelicae Sinensis Radix on neuroendocrine-immune network and sphingolipid metabolism in CUMS-induced model of depression

ETHNOPHARMACOLOGICAL RELEVANCE

Conventional antidepressants therapy remains unsatisfactory due to the disadvantages of delayed clinical onset of action and side effects. Traditional Chinese Medicine (TCM) with good efficacy and higher safety have received much attention. Angelicae Sinensis Radix (AS), a well-known TCM, has been proved to exhibit the efficacy of antidepression recently.

AIM OF THE STUDY

The purpose of this study was to investigate the potential anti-depressant mechanisms of AS based on chronic unpredictable mild stress (CUMS) rat model.

MATERIALS AND METHODS

In this study, behavioral experiments, molecular biology techniques, and ultra performance liquid chromatography-triple-time of flight mass spectrometer (UPLC-Triple-TOF/MS) were combined to explore the potential antidepressant mechanisms of AS based on CUMS rat model.

RESULTS

The results demonstrated that AS could reduce the contents of serum hypothalamic-pituitary-adrenal (HPA) axis hormones in CUMS rats, including corticotropin-releasing hormone (CRH), adrenocorticotropic hormone (ACTH) and cortisol (CORT). In addition, AS regulated the percentage of CD4+ T lymphocytes, the ratio of CD4+/CD8+, and the levels of serum cytokines such as IL-1β, IL-4, IL-6, and TNF-α in CUMS rats. Lipidomics showed that 31 lipids were related to depression and AS could regulate the lipid metabolism alteration induced by CUMS, particularly sphingolipid metabolism. Finally, the key proteins in sphingolipid metabolic pathways in hippocampus of CUMS rats could be back-regulated by AS, including serine palmitoyl transferase (SPTLC2), ceramide synthase (CerS2), sphingomyelinase (SPHK1), and neutral sphingomyelinase (nSMase).

CONCLUSION

AS could alleviate NEI network disorder and restore the levels of sphingolipid metabolites and key proteins in CUMS rats. The underlying mechanism by which AS relieved depression-like behavior in CUMS rats may be through modulation of NEI and disturbances in sphingolipid metabolism.

Discovery of potential biomarkers for osteoporosis using LC/GC-MS metabolomic methods

Purpose

For early diagnosis of osteoporosis (OP), plasma metabolomics of OP was studied by untargeted LC/GC-MS in a Chinese elderly population to find possible diagnostic biomarkers.

Methods

A total of 379 Chinese community-dwelling older adults aged ≥65 years were recruited for this study. The BMD of the calcaneus was measured using quantitative ultrasound (QUS), and a T value ≤-2.5 was defined as OP. Twenty-nine men and 47 women with OP were screened, and 29 men and 36 women were matched according to age and BMI as normal controls using propensity matching. Plasma from these participants was first analyzed by untargeted LC/GC-MS, followed by FC and P values to screen for differential metabolites and heatmaps and box plots to differentiate metabolites between groups. Finally, metabolic pathway enrichment analysis of differential metabolites was performed based on KEGG, and pathways with P ≤ 0.05 were selected as enrichment pathways.

Results

We screened metabolites with FC>1.2 or FC<1/1.2 and P<0.05 and found 33 differential metabolites in elderly men and 30 differential metabolites in elderly women that could be potential biomarkers for OP. 2-Aminomuconic acid semialdehyde (AUC=0.72, 95% CI 0.582-0.857, P=0.004) is highly likely to be a biomarker for screening OP in older men. Tetradecanedioic acid (AUC=0.70, 95% CI 0.575-0.818, P=0.004) is highly likely to be a biomarker for screening OP in older women.

Conclusion

These findings can be applied to clinical work through further validation studies. This study also shows that metabolomic analysis has great potential for application in the early diagnosis and recurrence monitoring of OP in elderly individuals.

Huangqi Guizhi Wuwu Decoction Improves Inflammatory Factor Levels in Chemotherapy-induced Peripheral Neuropathy by Regulating the Arachidonic Acid Metabolic Pathway

BACKGROUND

Chemotherapy-induced Peripheral Neuropathy (CIPN) is a common complication that arises from the use of anticancer drugs. Huangqi Guizhi Wuwu Decoction (HGWWD) is an effective classic prescription for treating CIPN; however, the mechanism of the activity is not entirely understood.

OBJECTIVE

This study aimed to investigate the remedial effects and mechanisms of HGWWD on CIPN.

METHODS

Changes in behavioral, biochemical, histopathological, and biomarker indices were used to evaluate the efficacy of HGWWD treatment. Ultra-high-performance liquid chromatography/mass spectrometry combined with the pattern recognition method was used to screen biomarkers and metabolic pathways related to CIPN. The results of pathway analyses were verified by protein blotting experiments.

RESULTS

A total of 29 potential biomarkers were identified and 13 metabolic pathways were found to be involved in CIPN. In addition HGWWD reversed the levels of 19 biomarkers. Prostaglandin H2 and 17α,21-dihydroxypregnenolone were targeted as core biomarkers.

CONCLUSION

This study provides scientific evidence to support the finding that HGWWD mainly inhibits the inflammatory response during CIPN by regulating arachidonic acid metabolism.

Untargeted Metabolomic Analyses of Body Fluids to Differentiate TBI DOC and NTBI DOC

OBJECTIVE

To investigate the metabolomic differences between Traumatic brain injury (TBI) disorder of consciousness (DOC) patients and non-traumatic brain injury (NTBI) DOC patients by using cerebrospinal fluid (CSF), serum and urine samples beneficial to understand the pathological mechanism differences between the two etiologies, provide potential clues for the subsequent treatment and prognosis, and investigate the metabolome differences and similarities between TBI and NTBI among three different body fluids.

METHODS

In total, 24 TBI DOC subjects and 29 NTBI DOC subjects were enrolled. CSF, serum and urine samples from TBI DOC and NTBI DOC patients were collected and analyzed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarkers and altered metabolic functions.

RESULTS

When comparing TBI DOC and NTBI DOC, 36, 31 and 52 differential metabolites were obtained in CSF, serum and urine, respectively. The functional analysis of differential metabolites obtained in CSF, serum and urine were all related to amino acid metabolism. Except for amino acid metabolism, metabolic biomarkers in CSF, serum and urine mainly focus on central function, cognitive function, necrosis and apoptosis and neurological function, respectively. In CSF, the highest AUC was 0.864 (Isoproturon) and 0.816 (Proline betaine). Then, the AUC of NFurfurylformamide in serum was 0.941, while the AUC of Dihydronepetalactone and Doxepin N-oxide glucuronide were 1.0 in urine.

CONCLUSION

CSF, serum and urine metabolomic analyses could differentiate TBI DOC from NTBI DOC and functional analyses showed a metabolic change difference between TBI DOC and NTBI DOC.

Metabolic Patterns of High-Invasive and Low-Invasive Oral Squamous Cell Carcinoma Cells Using Quantitative Metabolomics and 13C-Glucose Tracing

Most current metabolomics studies of oral squamous cell carcinoma (OSCC) are mainly focused on identifying potential biomarkers for early screening and diagnosis, while few studies have investigated the metabolic profiles promoting metastasis. In this study, we aimed to explore the altered metabolic pathways associated with metastasis of OSCC. Here, we identified four OSCC cell models (CAL27, HN6, HSC-3, SAS) that possess different invasive heterogeneity via the transwell invasion assay and divided them into high-invasive (HN6, SAS) and low-invasive (CAL27, HSC-3) cells. Quantitative analysis and stable isotope tracing using [U-13C6] glucose were performed to detect the altered metabolites in high-invasive OSCC cells, low-invasive OSCC cells and normal human oral keratinocytes (HOK). The metabolic changes in the high-invasive and low-invasive cells included elevated glycolysis, increased fatty acid metabolism and an impaired TCA cycle compared with HOK. Moreover, pathway analysis demonstrated significant differences in fatty acid biosynthesis; arachidonic acid (AA) metabolism; and glycine, serine and threonine metabolism between the high-invasive and low-invasive cells. Furthermore, the high-invasive cells displayed a significant increase in the percentages of 13C-glycine, 13C-palmitate, 13C-stearic acid, 13C-oleic acid, 13C-AA and estimated FADS1/2 activities compared with the low-invasive cells. Overall, this exploratory study suggested that the metabolic differences related to the metastatic phenotypes of OSCC cells were concentrated in glycine metabolism, de novo fatty acid synthesis and polyunsaturated fatty acid (PUFA) metabolism, providing a comprehensive understanding of the metabolic alterations and a basis for studying related molecular mechanisms in metastatic OSCC cells.

Serum metabolic alterations in peritoneal dialysis patients with excessive daytime sleepiness

Excessive daytime sleepiness (EDS) is associated with quality of life and all-cause mortality in the end-stage renal disease population. This study aims to identify biomarkers and reveal the underlying mechanisms of EDS in peritoneal dialysis (PD) patients. A total of 48 nondiabetic continuous ambulatory peritoneal dialysis patients were assigned to the EDS group and the non-EDS group according to the Epworth Sleepiness Scale (ESS). Ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) was used to identify the differential metabolites. Twenty-seven (male/female, 15/12; age, 60.1 ± 16.2 years) PD patients with ESS ≥ 10 were assigned to the EDS group, while twenty-one (male/female, 13/8; age, 57.9 ± 10.1 years) PD patients with ESS < 10 were defined as the non-EDS group. With UHPLC-Q-TOF/MS, 39 metabolites with significant differences between the two groups were found, 9 of which had good correlations with disease severity and were further classified into amino acid, lipid and organic acid metabolism. A total of 103 overlapping target proteins of the differential metabolites and EDS were found. Then, the EDS-metabolite-target network and the protein-protein interaction network were constructed. The metabolomics approach integrated with network pharmacology provides new insights into the early diagnosis and mechanisms of EDS in PD patients.

The Integration of the Metabolome and Transcriptome for Dendrobium nobile Lindl. in Response to Methyl Jasmonate

Dendrobium nobile Lindl., as an endangered medicinal plant within the genus Dendrobium, is widely distributed in southwestern China and has important ecological and economic value. There are a variety of metabolites with pharmacological activity in D. nobile. The alkaloids and polysaccharides contained within D. nobile are very important active components, which mainly have antiviral, anti-tumor, and immunity improvement effects. However, the changes in the compounds and functional genes of D. nobile induced by methyl jasmonate (MeJA) are not clearly understood. In this study, the metabolome and transcriptome of D. nobile were analyzed after exposure to MeJA. A total of 377 differential metabolites were obtained through data analysis, of which 15 were related to polysaccharide pathways and 35 were related to terpenoids and alkaloids pathways. Additionally, the transcriptome sequencing results identified 3256 differentially expressed genes that were discovered in 11 groups. Compared with the control group, 1346 unigenes were differentially expressed in the samples treated with MeJA for 14 days (TF14). Moreover, the expression levels of differentially expressed genes were also significant at different growth and development stages. According to GO and KEGG annotations, 189 and 99 candidate genes were identified as being involved in terpenoid biosynthesis and polysaccharide biosynthesis, respectively. In addition, the co-expression analysis indicated that 238 and 313 transcription factors (TFs) may contribute to the regulation of terpenoid and polysaccharide biosynthesis, respectively. Through a heat map analysis, fourteen terpenoid synthetase genes, twenty-three cytochrome P450 oxidase genes, eight methyltransferase genes, and six aminotransferase genes were identified that may be related to dendrobine biosynthesis. Among them, one sesquiterpene synthase gene was found to be highly expressed after the treatment with MeJA and was positively correlated with the content of dendrobine. This study provides important and valuable metabolomics and transcriptomic information for the further understanding of D. nobile at the metabolic and molecular levels and provides candidate genes and possible intermediate compounds for the dendrobine biosynthesis pathway, which lays a certain foundation for further research on and application of Dendrobium.

Lung proteomics combined with metabolomics reveals molecular characteristics of inflammation-related lung tumorigenesis induced by B(a)P and LPS

Inflammatory microenvironment may take a promoting role in lung tumorigenesis. However, the molecular characteristics underlying inflammation-related lung cancer remains unknown. In this work, the inflammation-related lung tumorigenesis mouse model was established by treated with B(a)P (1 mg/mouse, once a week for 4 weeks), followed by LPS (2.5 μg/mouse, once every 3 weeks for five times), the mice were sacrificed 30 weeks after exposure. TMT-labeled quantitative proteomics and untargeted metabolomics were used to interrogate differentially expressed proteins and metabolites in different mouse cancer tissues, followed by integrated crosstalk between proteomics and metabolomics through Spearman's correlation analysis. The result showed that compared with the control group, 103 proteins and 37 metabolites in B(a)P/LPS group were identified as significantly altered. By searching KEGG pathway database, proteomics pathways such as Leishmaniasis, Asthma and Intestinal immune network for IgA production, metabolomics pathways such as Vascular smooth muscle contraction, Linoleic acid metabolism and cGMP-PKG signaling pathway were enriched. A total of 22 pathways were enriched after conjoint analysis of the proteomic and metabolomics, and purine metabolism pathway, the unique metabolism-related pathway, which included significantly altered protein (adenylate cyclase 4, ADCY4) and metabolites (L-Glutamine, guanosine monophosphate (GMP), adenosine and guanosine) was found. Results suggested purine metabolism may contribute to the inflammation-related lung tumorigenesis, which may provide novel clues for the therapeutic strategies of inflammation-related lung cancer.

The Kynurenine/Tryptophan Ratio as a Promising Metabolomic Biomarker for Diagnosing the Spectrum of Tuberculosis Infection and Disease

The metabolic system and immunology used to be seen as distinct fields of study. Recent developments in our understanding of how the immune system operates in health and disease have connected these fields to complex systems. An effective technique for identifying probable abnormalities of metabolic homeostasis brought on by disease is metabolomics, which is defined as the thorough study of small molecule metabolic intermediates within a biological system that collectively make up the metabolome. A prognostic metabolic biomarker with adequate prognostic accuracy for tuberculosis progression has recently been created. The rate-limiting host enzyme for the conversion of tryptophan to kynurenine, indoleamine 2,3-dioxygenase (IDO), is greatly elevated in the lungs of tuberculosis disease patients. Targeted study on tryptophan in tuberculosis disease indicates that such decreases may also resembled this upregulation. Although tuberculosis diagnosis has improved with the use of interferon release assay and tuberculosis nucleic acid amplification, tuberculosis control is made difficult by the lack of a biomarker to diagnose active tuberculosis disease. We hope that the reader of this work can develop an understanding of the advantages of metabolomics testing, particularly as a sort of testing that can be used for both diagnosing and monitoring a patient's response to treatment for tuberculosis.

Metabolomics insights into the effects of pre-pregnancy lead exposure on bone metabolism in pregnant rats

Today's women of childbearing age with a history of high lead (Pb) exposure in childhood have large Pb body burdens, which increases Pb release during pregnancy by promoting bone Pb mobilisation. The purpose of this study was to investigate the metabolic mechanisms underlying bone Pb mobilisation and explore the bone metabolism-related pathways during pregnancy. Drinking water containing 0.05% sodium acetate or Pb acetate was provided to weaned female rats for 4 weeks followed by a 4-week washout period, and then rats were co-caged with healthy males of the same age until pregnancy. Blood and bone tissues of the female rats were collected at gestational day (GD) 3 (early pregnancy), GD 10 (middle pregnancy), and GD 17 (late pregnancy), respectively. Pb and calcium concentrations, biomarkers for bone turnover, bone microstructure, serum metabolomics, and metabolic indicators were intensively analyzed. The results demonstrated that pre-pregnancy Pb exposure elevated blood lead levels (BLLs) at GD17, accompanied by a negative correlation between BLLs and trabecular bone Pb levels. Meanwhile, Pb-exposed rats had low bone mass and aberrant bone architecture with a larger number of mature osteoclasts (OCs) compared to the control group. Moreover, the metabolomics uncovered that Pb exposure caused mitochondrial dysfunction, such as enhanced oxidative stress and inflammatory response, and suppressed energy metabolism. Additionally, the levels of ROS, MDA, IL-1β, and IL-18 involved in redox and inflammatory pathways of bone tissues were significantly increased in the Pb-exposed group, while antioxidant SOD and energy metabolism-related indicators including ATP levels, Na+-K+-ATPase, and Ca2+-Mg2+-ATPase activities were significantly decreased. In conclusion, pre-pregnancy Pb exposure promotes bone Pb mobilisation and affects bone microstructure in the third trimester of pregnancy, which may be attributed to OC activation and mitochondrial dysfunction.

Recent omics advances in hair aging biology and hair biomarkers analysis

Aging is a complex natural process that leads to a decline in physiological functions, which is visible in signs such as hair graying, thinning, and loss. Although hair graying is characterized by a loss of pigment in the hair shaft, the underlying mechanism of age-associated hair graying is not fully understood. Hair graying and loss can have a significant impact on an individual's self-esteem and self-confidence, potentially leading to mental health problems such as depression and anxiety. Omics technologies, which have applications beyond clinical medicine, have led to the discovery of candidate hair biomarkers and may provide insight into the complex biology of hair aging and identify targets for effective therapies. This review provides an up-to-date overview of recent omics discoveries, including age-associated alterations of proteins and metabolites in the hair shaft and follicle, and highlights the significance of hair aging and graying biomarker discoveries. The decline in hair follicle stem cell activity with aging decreased the regeneration capacity of hair follicles. Cellular senescence, oxidative damage and altered extracellular matrix of hair follicle constituents characterized hair follicle and hair shaft aging and graying. The review attempts to correlate the impact of endogenous and exogenous factors on hair aging. We close by discussing the main challenges and limitations of the field, defining major open questions and offering an outlook for future research.

The role of the host-microbiome and metabolomics in sarcoidosis

Sarcoidosis is a complex inflammatory fibrotic disease that affects multiple organ systems. It is characterized by the infiltration of lymphocytes and mononuclear phagocytes, which form non-caseating granulomas in affected organs. The lungs and intrathoracic lymph nodes are the most commonly affected organs. The underlying cause of sarcoidosis is unknown, but it is believed to occur in genetically predisposed individuals who are exposed to pathogenic organisms, environmental contaminants, or self and non-self-antigens. Recent research has suggested that the microbiome may play a role in the development of respiratory conditions, including sarcoidosis. Additionally, metabolomic studies have identified potential biomarkers for monitoring sarcoidosis progression. This review will focus on recent microbiome and metabolomic findings in sarcoidosis, with the goal of shedding light on the pathogenesis and possible diagnostic and therapeutic approaches.

Polyphenols Cause Structure Dependent Effects on the Metabolic Profile of Human Hepatocarcinogenic Cells

SCOPE

Although many beneficial health effects are attributed to polyphenols their influence on the human metabolome has not been elucidated yet. The ubiquitous occurrence of polyphenols in the human diet demands comprehensive knowledge about physiological and toxicological effects of these compounds on human cells.

METHODS AND RESULTS

The human hepatocarcinogenic cell line HepG2 is used to elucidate the effects of 13 polyphenols and three respective phenolic degradation products on the human metabolome using HPLC-MS/MS. To investigate structure-activity-relationships, structurally related examples of polyphenols from different compound classes are selected. The analysis of catechins points toward a relation between the degree of hydroxylation and the extent of metabolic effects particularly on the urea cycle and the pentose phosphate pathway (PPP). A correlation between the modulation of the PPP and the stability of the compounds is demonstrated, which may be caused by reactive oxygen species (ROS). The incubation of flavones and alkenylbenzenes demonstrates reduced activity of methoxylated compounds and no impact of the B-ring position.

CONCLUSION

In general, polyphenols induce a multitude of metabolic effects, for example, on energy metabolism, PPP, and urea cycle. These metabolic alterations may be related to the widely reported bioactivity of these compounds such as the anticarcinogenic effects.

Metabolomic analysis for asymptomatic hyperuricemia and gout based on a combination of dried blood spot sampling and mass spectrometry technology

BACKGROUND

Gout is the most common inflammatory arthritis and closely related to metabolic syndrome, leading to excruciating pain and the decline in quality of patients' life. However, the pathogenesis of gout is still unclear, and novel biomarkers are demanded for the early prediction and diagnosis of gout.

OBJECTIVE

This study aimed at profiling the dysregulated metabolic pathways in asymptomatic hyperuricemia (AHU) and gout and elucidating the associations between AHU, gout and metabolomics, which may aid in performing gout screening.

METHODS

A total of 300 participants, including 114 healthy controls, 92 patients with AHU, and 94 patients with gout, were analyzed by using a combination of dried blood spot (DBS) sampling and mass spectrometry (MS) technology. Multiple algorithms were applied to characterize altered metabolic profiles in AHU and gout. The mainly altered metabolites were identified by random forest analysis.

RESULTS

There were significant differences in AHU and gout compared with control group. The altered metabolites were involved in oxidation of fatty acids, carnitine synthesis, urea cycle, and amino acid metabolism in AHU and gout. Random forest classification of 16 metabolites yielded 3 important features to distinguish gout from AHU.

CONCLUSIONS

Distinct metabolomic signatures were observed in AHU and gout. The selected metabolites may have the potential to improve the early detection of gout.

Gas Chromatography-Mass Spectrometry Reveals Stage-Specific Metabolic Signatures of Ankylosing Spondylitis

Ankylosing spondylitis (AS) is a type of chronic rheumatic immune disease, and the crucial point of AS treatment is identifying the correct stage of the disease. However, there is a lack of effective diagnostic methods for AS staging. The primary objective of this study was to perform an untargeted metabolomic approach in AS patients in an effort to reveal metabolic differences between patients in remission and acute stages. Serum samples from 40 controls and 57 AS patients were analyzed via gas chromatography-mass spectrometry (GC-MS). Twenty-four kinds of differential metabolites were identified between the healthy controls and AS patients, mainly involving valine/leucine/isoleucine biosynthesis and degradation, phenylalanine/tyrosine/tryptophan biosynthesis, glutathione metabolism, etc. Furthermore, the levels of fatty acids (linoleate, dodecanoate, hexadecanoate, and octadecanoate), amino acids (serine and pyroglutamate), 2-hydroxybutanoate, glucose, etc., were lower in patients in the acute stage than those in the remission stage, which may be associated with the aggravated inflammatory response and elevated oxidative stress in the acute stage. Multiple stage-specific metabolites were significantly correlated with inflammatory indicators (CRP and ESR). In addition, the combination of serum 2-hydroxybutanoate and hexadecanoate plays a significant role in the diagnosis of AS stages. These metabolomics-based findings provide new perspectives for AS staging, treatment, and pathogenesis studies.