Metabolomics最新文献

Introduction/objectives: Several observational investigations have observed the possible links between Alzheimer's disease (AD) and metabolic dysfunction associated with fatty liver disease (MAFLD), yet the underlying causal relationships remain undetermined. This study aimed to systemically infer the causal associations between AD and MAFLD by employing a bidirectional network two-sample Mendelian randomization (MR) analysis.

Methods: Genome-wide significant (P < 5 × 10^- 8) genetic variants associated with AD and MAFLD were selected as instrumental variables (IVs) from the consortium of FinnGen, MRC-IEU, UK biobank, and genome-wide association studies (GWAS), respectively. The study sample sizes range from 55,134 to 423,738 for AD and from 218,792 to 778,614 for MAFLD. In the forward analysis, AD was set as the exposure factor, and MAFLD was employed as the disease outcome. Causal relationships between AD and MAFLD were evaluated using inverse-variance weighted (IVW), MR Egger regression, the weighted median, and weighted mode. Additionally, the reverse MR analysis was conducted to infer causality between MAFLD and AD. Sensitivity analyses were performed to assess the robustness of causal estimates.

Results: In the forward MR analysis, the genetically determined family history of AD was associated with a lower risk of MAFLD (mother's history: OR_discovery=0.08, 95%CI: 0.03, 0.22, P = 7.91 × 10^- 7; OR_replicate=0.83, 95%CI: 0.74, 0.94, P = 3.68 × 10^- 3; father's history: OR_discovery=0.01, 95%CI: 0.01, 0.08, P = 5.48 × 10^- 5; OR_replicate=0.79, 95%CI: 0.68, 0.93, P = 4.07 × 10^- 3; family history: OR_discovery=0.84, 95%CI: 0.77, 0.91, P = 6.30 × 10^- 5; OR_replicate=0.15, 95%CI: 0.05, 0.41, P = 2.51 × 10^- 4) in the primary MAFLD cohort. Consistent findings were observed in an independent MAFLD cohort (all P < 0.05). However, the reverse MR analysis suggested that genetic susceptibility to MAFLD had no causal effects on developing AD.

Conclusion: Our study demonstrates a causal association between a family history of AD and a lower risk of MAFLD. It suggests that individuals with a history of AD may benefit from tailored metabolic assessments to better understand their risk of MAFLD, and inform the development of preventive strategies targeting high-risk populations.

Introduction: Despite the well-established efficacy of thiazolidinediones (TZDs), including pioglitazone and rosiglitazone, in type II diabetes management, their potential contribution to heart failure risk remains a significant area of uncertainty. This incomplete understanding, which persists despite decades of clinical use of TZDs, has generated ongoing controversy and unanswered questions regarding their safety profiles, ultimately limiting their broader clinical application.

Objective and methods: This study presented a multi-omics approach, integrating toxicoproteomics and toxicometabolomics data with the goal of uncovering novel mechanistic insights into TZD cardiotoxicity and identifying molecular signatures predictive of side effect progression.

Results: Network analysis of proteo-metabolomic data revealed a distinct fingerprint of disrupted biochemical pathways, which were primarily related to energy metabolism. Downregulation of oxidative phosphorylation and fatty acid synthesis was coupled with increased activity in anaerobic glycolysis, the pentose phosphate pathway, and amino acid and purine metabolism. This suggests a potential metabolic shift in AC16 cells from fatty acid oxidation towards anaerobic glycolysis, potentially contributing to observed cardiotoxicity. Additionally, the study identified a marked disruption in the glutathione system, indicating an imbalanced redox state triggered by TZD exposure. Importantly, our analysis identified key molecular signatures across omics datasets, including prominent signatures of amino acids like L-ornithine, L-tyrosine and glutamine, which are evidently associated with heart failure, supporting their potential use for the early prediction of cardiotoxicity progression.

Conclusion: By uncovering a novel mechanistic explanation for TZD cardiotoxicity, this study simultaneously illuminates potential therapeutic interventions, opening avenues for future research to improve the safety profile of TZD agents. (250 words).

Introduction: The knowledge of the mode of action of an antimicrobial is essential for drug development and helps to fight against bacterial resistance. Thus, it is crucial to use analytical techniques to study the mechanism of action of substances that have potential to act as antibacterial agents OBJECTIVE: To use NMR-based metabolomics combined with chemometrics and molecular docking to identify the metabolic responses of Staphylococcus aureus following exposure to commercial antibiotics and some synthesized ω-aminoalkoxylxanthones.

Methods: Intracellular metabolites of S. aureus were extracted after treatment with four commercial antibiotics and three synthesized ω-aminoalkoxylxanthones. NMR spectra were obtained and ₁H NMR data was analyzed using both unsupervised and supervised algorithms (PCA and PLS-DA, respectively). Docking simulations on DNA topoisomerase IV protein were also performed for the ω-aminoalkoxylxanthones.

Results: Through chemometric analysis, we distinguished between the control group and antibiotics with extracellular (ampicillin) and intracellular targets (kanamycin, tetracycline, and ciprofloxacin). We identified 21 metabolites, including important metabolites that differentiate the groups, such as betaine, acetamide, glutamate, lysine, alanine, isoleucine/leucine, acetate, threonine, proline, and ethanol. Regarding the xanthone-type derivatives (S6, S7 and S8), we observed a greater similarity between S7 and ciprofloxacin, which targets bacterial DNA replication. The molecular docking analysis showed high affinity of the ω-aminoalkoxylxanthones with the topoisomerase IV enzyme, as well as ciprofloxacin.

Conclusion: NMR-based metabolomics has shown to be an effective technique to assess the metabolic profile of S. aureus after treatment with certain antimicrobial compounds, helping the investigation of their mechanism of action.

Introduction: Coronavirus disease 2019 (COVID-19) has widely varying clinical severity. Currently, no single marker or panel of markers is considered standard of care for prediction of COVID-19 disease progression. The goal of this study is to gain mechanistic insights at the molecular level and to discover predictive biomarkers of severity of infection and outcomes among COVID-19 patients.

Method: This cohort study (n = 76) included participants aged 16-78 years who tested positive for SARS-CoV-2 and enrolled in Memphis, TN between August 2020 to July 2022. Clinical outcomes were classified as Non-severe (n = 39) or Severe (n = 37). LC/HRMS-based untargeted metabolomics/lipidomics was conducted to examine the difference in plasma metabolome and lipidome between the two groups.

Results: Metabolomics data indicated that the kynurenine pathway was activated in Severe participants. Significant increases in short chain acylcarnitines, and short and medium chain acylcarnitines containing OH-FA chain in Severe vs. Non-severe group, which indicates that (1) the energy pathway switched to FA β-oxidation to maintain the host energy homeostasis and to provide energy for virus proliferation; (2) ROS status was aggravated in Severe vs. Non-severe group. Based on PLS-DA and correlation analysis to severity score, IL-6, and creatine, a biomarker panel containing glucose (pro-inflammation), ceramide and S1P (inflammation related), 4-hydroxybutyric acid (oxidative stress related), testosterone sulfate (immune related), and creatine (kidney function), was discovered. This novel biomarker panel plus IL-6 with an AUC of 0.945 provides a better indication of COVID-19 clinical outcomes than that of IL-6 alone or the three clinical biomarker panel (IL-6, glucose and creatine) with AUCs of 0.875 or 0.892.

Introduction: Tempeh is an antioxidant-rich soybean fermentation product from Java, Indonesia. Cooking methods have an impact on the nutritional value and bioactivity of food.

Objective: This study aims to investigate how the cooking process affects the metabolites and antioxidant activity in tempeh using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS).

Methods: A nontargeted UHPLC-HRMS metabolomics and chemometric analysis were used to evaluate metabolite profiles and antioxidant activity changes because of food processing in tempeh.

Results: The score plots of tempeh produced by boiling and frying methods displayed a distinct separation from raw tempeh, revealing that the cooking process altered the metabolite composition of tempeh. Due to processing, L-glutamic acid, L-pyroglutamic acid, DL-glutamine, and D-( +)-proline became the most affected metabolites on tempeh. There were 70 metabolites that showed antioxidant activity using the DPPH assay; 23 metabolites significantly differ from DPPH and control for antioxidant activity for all processing tempeh. Metabolites with significantly different antioxidant activity in raw and processed tempeh were dominated by flavonoids, vitamin E, and bioactive lipids.

Conclusion: The DPPH antioxidant assay using UHPLC-HRMS is promising as a fast antioxidant assay by simplifying the conventional DPPH antioxidant assay. Further, it can be used to identify the name of metabolites responsible for its antioxidant activity.

Introduction: Atopic dermatitis (AD) is a common chronic inflammatory dermatosis. However, the exact molecular mechanism underlying the development of AD remain largely unclear.

Objective: To investigate comprehensive metabolomic alterations in serum and skin tissue between 2,4-dinitrofluorobenzene (DNFB)-induced AD-like mice and healthy controls, aiming to identify the potential disease biomarkers and explore the molecular mechanisms of AD.

Methods: In this study, Untargeted metabolomics analysis was used to investigate both skin and serum metabolic abnormalities of 2,4-dinitrofluorobenzene (DNFB)-induced AD-like mice. Then, the metabolic differences among the groups were determined through the application of multivariate analysis. Additionally, the selection of predictive biomarkers was accomplished using the receiver operating characteristic (ROC) module.

Results: Our findings showed that levels of 220 metabolites in the skin and 94 metabolites in the serum were different in AD-like mice that were treated with DNFB compared to control mice. Uracil, N-Acetyl-L-methionine, deoxyadenosine monophoosphate, 2-acetyl-l-alkyl-sn-glycero-3-phosphcholine, and prostaglandin D2 are considered potential biomarkers of AD as obtained by integrating skin and serum differential metabolite results. Metabolomic data analysis showed that the metabolic pathways in which skin and serum are involved together include histidine metabolism, pyrimidine metabolism, alanine, aspartate, and glutamate metabolism.

Conclusion: Our research explained the possible molecular mechanism of AD at the metabolite level and provided potential targets for the development of clinical drugs for AD.

Introduction: A better understanding of the physiological response of silage maize to a mild reduction in nitrogen (N) fertilization and the identification of predictive biochemical markers of N utilization efficiency could contribute to limit the detrimental effect of the overuse of N inputs.

Objectives: We integrated phenotypic and biochemical data to interpret the physiology of maize in response to a mild reduction in N fertilization under agronomic conditions and identify predictive leaf metabolic and proteic markers that could be used to pilot and rationalize N fertilization.

Methods: Eco-physiological, developmental and yield-related traits were measured and complemented with metabolomic and proteomic approaches performed on young leaves of a core panel of 29 European genetically diverse dent hybrids cultivated in the field under non-limiting and reduced N fertilization conditions.

Results: Metabolome and proteome data were analyzed either individually or in an integrated manner together with eco-physiological, developmental, phenotypic and yield-related traits. They allowed to identify (i) common N-responsive metabolites and proteins that could be used as predictive markers to monitor N fertilization, (ii) silage maize hybrids that exhibit improved agronomic performance when N fertilization is reduced.

Conclusions: Among the N-responsive metabolites and proteins identified, a cytosolic NADP-dependent malic enzyme and four metabolite signatures stand out as promising markers that could be used for both breeding and agronomic purposes.

Objectives: While some metals have been reported as carcinogens or potential carcinogens, only few modern-standard datasets including a large number of elements are available. The present analysis established a first trace elements spectrum by relating the concentration of metals and trace elements in the serum of sarcoma patients with survival data.

Methods: Patients with sarcoma and controls were retrospectively selected from the International Sarcoma Kindred Study database (ISKS). As part of the ISKS study, blood samples were prospectively collected at the Leon Bérard Cancer Center from February 2012 to July 2019. Stable specimens and copper isotopes (⁶⁵Cu/⁶³Cu) were analyzed using Triple Quadrupole Inductively Coupled Plasma Mass Spectrometer (ICP-MS) and the Multicollector MC-ICP-MS Nu Plasma HR 500. Wilcoxon rank sum test, log-rank test, and multivariate Cox regression models were used for statistics.

Results: In total, 151 patients and 59 healthy controls were included. At the time of blood sample collection, 62% of patients had locally advanced or metastatic disease. Copper (Cu), copper/zinc (Cu/Zn) and potassium/rubidium (K/Rb) ratio were significantly higher in patients compared to controls and were also significantly higher in patients with advanced compared to early-stage sarcoma. Whereas S and Se were significantly correlated in patients, no correlation was observed in controls. Importantly, levels of K, Rb, Se, Fe, P, Si, S, δ⁶⁵Cu, Cu, S/Se and Cu/Zn ratio were independently associated with overall survival.

Conclusions: These results depict the metallomic spectrum in sarcoma and highlight substantial variation associated with survival, enhancing our understanding of sarcoma's biology.

Background: Pulmonary tuberculosis (PTB) exacerbation can lead to respiratory failure, multi-organ failure, and symptoms related to central nervous system diseases. The purpose of this study is to screen biomarkers and metabolic pathways that can predict the progression of PTB, and to verify the role of the metabolic enzyme xanthine oxidase (XO) in the progression of PTB.

Methods: To explore the biomarkers and mechanisms underlying the progression of PTB, plasma metabolomics sequencing was conducted on patients with severe PTB, non-severe PTB, and healthy individuals. Screening differential metabolites and metabolic pathways that can predict the progression of PTB, and verifying the function and mechanism of action of XO through experiments.

Results: The purine metabolism, sphingolipid metabolism, and amino acid metabolism between the three groups differ. In patients with severe PTB, the levels of xanthosine and hypoxanthine are increased, while the levels of D-tryptophan, dihydroceramide and uric acid are decreased. Inhibition of XO activity has been observed to reduce the levels of tumor necrosis factor (TNF-α), interleukin-1 beta (IL-1β), and interleukin-6 (IL-6), as well as to suppress the production of reactive oxygen species (ROS) and the activation of the NF-κB pathway, while also promoting the growth of MTB within cells.

Conclusion: D-tryptophan, xanthosine, and dihydroceramide can be utilized as biomarkers for progression of PTB, assisting in the evaluation of disease progression, and XO stands out as a potential therapeutic target for impeding the progression of PTB.

Introduction: Human metabolomics has made significant strides in understanding metabolic changes and their implications for human health, with promising applications in diagnostics and treatment, particularly regarding the gut microbiome. However, progress is hampered by issues with data comparability and reproducibility across studies, limiting the translation of these discoveries into practical applications.

Objectives: This study aims to evaluate the fit-for-purpose of a suite of human stool samples as potential candidate reference materials (RMs) and assess the state of the field regarding harmonizing gut metabolomics measurements.

Methods: An interlaboratory study was conducted with 18 participating institutions. The study allowed for the use of preferred analytical techniques, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR).

Results: Different laboratories used various methods and analytical platforms to identify the metabolites present in human stool RM samples. The study found a 40% to 70% recurrence in the reported top 20 most abundant metabolites across the four materials. In the full annotation list, the percentage of metabolites reported multiple times after nomenclature standardization was 36% (LC-MS), 58% (GC-MS) and 76% (NMR). Out of 9,300 unique metabolites, only 37 were reported across all three measurement techniques.

Conclusion: This collaborative exercise emphasized the broad chemical survey possible with multi-technique approaches. Community engagement is essential for the evaluation and characterization of common materials designed to facilitate comparability and ensure data quality underscoring the value of determining current practices, challenges, and progress of a field through interlaboratory studies.