OBJECTIVE: To explore the mechanism of Dihuang Yinzi (DHYZ) in the treatment of Alzheimer's disease (AD) by integrating metabolomics and experimental verification. METHODS: Forty-eight male APP/PS1 mice were divided into model, high- (DHYZ-H), medium- (DHYZ-M), and low-dose DHYZ (DHYZ-L) groups (12 mice per group) according to a random number table. Mice in DHYZ groups were gavaged with DHYZ 6.34, 12.68, and 25.35 g/(kg·d), respectively. Twelve C57BL/6 mice were gavaged with distilled water as the blank group. Metabolomics was used to analyze differential metabolites in the brains of mice. Morris water maze test was used to detect the memory abilities of mice. The hematoxylin-eosin staining and transmission electron microscopy were used to observe the general morphology and ultrastructure of neurons. The enzyme-linked immunosorbent assay was used to detect the levels of superoxide dismutase (SOD), reactive oxygen species (ROS), and amyloid β -protein 1-42 (A β_1-42). The real-time quantitative polymerase chain reaction was used to detect the mRNA expressions of density-regulated protein 1 (DRP1), fission 1 (FIS1), mitofusin-1 (MFN1), and optic atrophy protein 1 (OPA1). Western blot was used to detect the protein expressions of cyclic adenosine monophosphate (cAMP), protein kinase A (PKA), cAMP response binding protein (CREB), brain-derived neurotrophic factor (BDNF), synapsin 1 (SYN1), synaptophysin (SYP), and postsynaptic density protein 95 (PSD95). RESULTS: A total of 82 differential metabolites were identified in the brains of APP/PS1 mice, among which 7 differential metabolites could be regulated by DHYZ. After DHYZ intervention, the memory abilities of mice significantly increased (P<0.05 or P<0.01), the number of synapses and neurons in the hippocampus increased, and the mitochondrial morphology and structure were relatively intact. The DHYZ groups exhibited a significant reduction in hippocampal ROS and A β_1-42 levels, along with a significant elevation in SOD level (P<0.05 or P<0.01). The mRNA expressions of DRP1 and FIS1 were reduced, while the mRNA expressions of MFN1 and OPA1 were increased after DHYZ treatment (P<0.05 or P<0.01). The cAMP/PKA/CREB-BDNF pathway was activated, and the expressions of SYN1, SYP and PSD95 proteins were significantly increased in the DHYZ-H group (P<0.05 or P<0.01). CONCLUSIONS DHYZ could improve mitochondrial dynamics and synaptic plasticity in APP/PS1 mice, inhibit oxidative stress, and thereby enhancing learning and memory abilities in APP/PS1 mice. Its mechanism might be related to activation of the cAMP/PKA/CREB-BDNF signaling pathway.
Animals ; Brain-Derived Neurotrophic Factor/metabolism* ; Male ; Cyclic AMP Response Element-Binding Protein/metabolism* ; Brain/drug effects* ; Metabolomics ; Mice, Inbred C57BL ; Neuronal Plasticity/drug effects* ; Drugs, Chinese Herbal/therapeutic use* ; Cyclic AMP-Dependent Protein Kinases/metabolism* ; Cyclic AMP/metabolism* ; Reactive Oxygen Species/metabolism* ; Amyloid beta-Protein Precursor/metabolism* ; Mice, Transgenic ; Mice ; Amyloid beta-Peptides/metabolism* ; Signal Transduction/drug effects* ; Alzheimer Disease/drug therapy* ; Superoxide Dismutase/metabolism*

OBJECTIVES: Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. METHODS: NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. RESULTS: A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. CONCLUSIONS This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.
Humans ; Multiple Myeloma/drug therapy* ; Machine Learning ; Male ; Female ; Metabolomics/methods* ; Middle Aged ; Aged ; Treatment Outcome ; Transcriptome ; Computational Biology ; Adult ; Multiomics

OBJECTIVES: To explore the therapeutic mechanism of Arctium lappa extract for treatment of Post-Viral Pneumonia Pulmonary Fibrosis (PPF). METHODS: The chemical constituents of Arctium lappa extracts were identified using UHPLC-Q-TOF-MS/MS. Mouse models of pulmonary fibrosis established by tracheal instillation of bleomycin were treated with Arctium lappa extract, and body weight changes were recorded and lung tissue pathology was examined using HE and Masson staining. Metabolomics analysis was used to identify the differential metabolites and the associated metabolic pathways in the treated mice. The common targets of viral pneumonia and pulmonary fibrosis were acquired from the publicly available databases, and the core targets and active constituents were screened using the protein-protein interaction (PPI) network, GO and KEGG enrichment analyses, and molecular docking, and a "gene-metabolite" regulatory network was constructed. The expressions of the core targets were detected in the lung tissues of the treated mice using Western blotting. RESULTS: Fifty-three chemical constituents were identified from Arctium lappa extract. In the mouse models of pulmonary fibrosis, treatment with Arctium lappa extract significantly improved weight loss and ameliorated lung inflammation and fibrosis. The differential metabolites in the treated mice were enriched in energy metabolism pathways involving citrate cycle, pentose phosphate pathway, glycolysis, tryptophan metabolism, glutamate metabolism and glutathione metabolism, which regulated the production of energy metabolism intermediates. Twenty-three key active compounds (mostly lignans and phenolic acids) and 82 core targets were screened, which were associated with the non-canonical Smad signaling pathways (including PI3K/AKT, HIF-1, MAPK, and Foxo) that participated in the regulation of energy metabolism. Arctium lappa extract also regulated the expressions of epithelial-mesenchymal transition (EMT)‑related proteins (fibronectin, vimentim, and Snail, etc.) and inhibited MAPK signaling pathway activation. CONCLUSIONS Preliminary findings suggest that Arctium lappa treats fibrosis by regulating metabolism to inhibit EMT and involves the modulation of non-canonical Smad signaling pathways, such as MAPK providing theoretical support for its clinical application and further research in treating PPF.
Arctium/chemistry* ; Animals ; Pulmonary Fibrosis/metabolism* ; Mice ; Metabolomics ; Network Pharmacology ; Plant Extracts/pharmacology* ; Signal Transduction ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation

OBJECTIVES: To investigate the impact of hepatitis B virus (HBV) infection on oral microbiota and metabolites in patients with metabolic dysfunction-associated fatty liver disease (MAFLD) and the underlying mechanisms. METHODS: This prospective study was conducted in 47 MAFLD patients complicated with chronic hepatitis B (CHB) and 48 MAFLD patients without CHB enrolled from November, 2023 to January, 2024. Fasting tongue coating samples were collected from the patients for analyzing microbial community structures and metabolites using high-throughput 16S rDNA sequencing and non-targeted metabolomics techniques, and their associations with clinical indicators and biological pathways were explored using correlation analysis and functional annotation. RESULTS: The levels of fasting blood glucose, total cholesterol (TC), gamma-glutamyl transferase (GGT), and severity of fatty liver were all significantly lower in MAFLD+CHB group than in MAFLD group. Microbiota analysis showed that the abundances of Patescibacteria (at the phylum level), Hydrogenophaga, and Absconditabacteriales (at the genus level) were significantly increased, while the abundance of Megasphaera was decreased in MAFLD+CHB group. The differential microbiota were significantly correlated with TC, GGT and low-density lipoprotein (r=-0.68‒0.75). Metabolomics analysis revealed that 469 metabolites (including lipids and amino acids) were upregulated and 2306 (including organic oxygen-containing compounds and phenylpropanoids) were downregulated in MAFLD+CHB group, for which KEGG enrichment analysis suggested abnormal activation of the linoleic acid metabolism and glycerophospholipid metabolism pathways. Correlation analysis between microbiota and metabolites indicated that Patescibacteria and Megasphaera, which were positively correlated with lipid metabolites and negatively with fatty acid metabolites, respectively, jointly affected glycolipid metabolism and oxidative stress pathways. CONCLUSIONS Compared to patients with MAFLD alone, MAFLD patients with concurrent chronic HBV infection showed lower levels in some lipid metabolism indicators and the degree of hepatic steatosis, accompanied by alterations in oral microbiota structure and metabolic profiles. The precise mechanisms involved require further investigation to be fully elucidated.
Humans ; Lipid Metabolism ; Prospective Studies ; Microbiota ; Hepatitis B, Chronic/microbiology* ; Male ; Female ; Adult ; Fatty Liver/microbiology* ; Middle Aged ; Mouth/microbiology* ; Metabolomics

The pursuit of healthy aging has long rendered aging and senescence captivating. Age-related ailments, such as cardiovascular diseases, diabetes, and neurodegenerative disorders, pose significant threats to individuals. Recent studies have shed light on the intricate mechanisms encompassing genetics, epigenetics, transcriptomics, and metabolomics in the processes of senescence and aging, as well as the establishment of age-related pathologies. Amidst these underlying mechanisms governing aging and related pathology metabolism assumes a pivotal role that holds promise for intervention and therapeutics. The advancements in metabolomics techniques and analysis methods have significantly propelled the study of senescence and aging, particularly with the aid of multiscale metabolomics which has facilitated the discovery of metabolic markers and therapeutic potentials. This review provides an overview of senescence and aging, emphasizing the crucial role metabolism plays in the aging process as well as age-related diseases.
Humans ; Aging/metabolism* ; Metabolomics/methods* ; Neurodegenerative Diseases/metabolism* ; Cardiovascular Diseases/metabolism*

Acute respiratory distress syndrome (ARDS) is a clinical syndrome characterized by diffuse alveolar and interstitial edema caused by damage to alveolar-capillary and epithelial cells, often induced by infection, sepsis, trauma, and other factors. It is marked by progressive hypoxemia and respiratory distress. Due to the diverse causes of ARDS, the unclear pathogenesis, and the absence of effective predictive markers or biomarkers, there are no effective treatment measures available, resulting in a high mortality rate. ARDS is increasingly recognized for its heterogeneity, biomarkers, and the emergence of new opportunities for the development of diagnostic tools and personalized treatment strategies provided by omics technologies. A single omics analysis cannot fully reveal the heterogeneity and complexity of ARDS, while multi-omics analysis can provide a more systematic and comprehensive understanding of ARDS. Using clinical samples is closer to the actual disease situation compared to animal models. Multi-omics studies based on clinical samples have achieved significant progress in elucidating the pathophysiology of ARDS, identifying ARDS subtypes, and identifying biomarkers related to ARDS. This review focuses on the current applications of genomics, transcriptomics, metabolomics, and proteomics analyses based on clinical samples in the ARDS field, with a focus on the application of these omics methods in ARDS heterogeneity, potential biomarkers, and pathogenesis. It also introduces the differences in the application of different clinical samples in ARDS omics research, in order to gain a deeper and more comprehensive understanding of the pathogenesis of ARDS and explore new strategies for its prevention and treatment.
Respiratory Distress Syndrome/diagnosis* ; Humans ; Metabolomics ; Proteomics ; Genomics ; Biomarkers ; Multiomics

Aconitum (Ranunculaceae) has a long-standing history in traditional Chinese medicine (TCM), where it has been widely used to treat conditions such as rheumatoid arthritis (RA), myocardial infarction, and heart failure. However, the potency of Aconitum alkaloids, the primary active components of Aconitum, also confers substantial toxicity. Therefore, assessing the efficacy and toxicity of these Aconitum alkaloids is crucial for ensuring clinical effectiveness and safety. Metabolomics, a quantitative method for analyzing low-molecular-weight metabolites involved in metabolic pathways, provides a comprehensive view of the metabolic state across multiple systems in vivo. This approach has become a vital investigative tool for facilitating the evaluation of their efficacy and toxicity, identifying potential sensitive biomarkers, and offering a promising avenue for elucidating the pharmacological and toxicological mechanisms underlying TCM. This review focuses on the applications of metabolomics in pharmacological and toxicological studies of Aconitum alkaloids in recent years and highlights the significant role of metabolomics in exploring compatibility detoxification and the mechanisms of TCM processing, aiming to identify more viable methods for characterizing toxic medicinal plants.
Aconitum/metabolism* ; Metabolomics/methods* ; Alkaloids/metabolism* ; Humans ; Animals ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional

Aconiti Lateralis Radix Praeparata (Fuzi) represents a significant traditional Chinese medicine (TCM) that exhibits both notable pharmacological effects and toxicity. Various processing methods are implemented to reduce the toxicity of raw Fuzi by modifying its toxic and effective components, primarily diterpenoid alkaloids. To comprehensively analyze the chemical variations between different Fuzi products, ultra-high performance liquid chromatography-linear ion trap quadrupole Orbitrap mass spectrometry (UHPLC-LTQ-Orbitrap MS) was employed to systematically characterize Shengfuzi, Heishunpian and Baifupian. A total of 249 diterpenoid alkaloids present in Shengfuzi were identified, while only 111 and 61 in Heishunpian and Baifupian were detected respectively, indicating substantial differences among these products. An untargeted metabolomics approach combined with multivariate statistical analysis revealed 42 potential chemical markers. Through subsequent validation using 52 batches of commercial Heishunpian and Baifupian samples, 8 robust markers distinguishing these products were identified, including AC1-propanoic acid-3OH, HE-glucoside, HE-hydroxyvaleric acid-2OH, dihydrosphingosine, N-dodecoxycarbonylvaline and three unknown compounds. Additionally, the MS imaging (MSI) technique was utilized to visualize the spatial distribution of chemical constituents in raw Fuzi, revealing how different processing procedures affect the chemical variations between Heishunpian and Baifupian. The distribution patterns of different diterpenoid alkaloid subtypes partially explained the chemical differences among products. This research provides valuable insights into the material basis for future investigations of different Fuzi products.
Diterpenes/chemistry* ; Alkaloids/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Aconitum/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Metabolomics ; Mass Spectrometry/methods* ; Plant Roots/chemistry* ; Molecular Structure

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling

Ophiopogon japonicus, a precious medicinal plant endemic to Zhejiang Province. Its tuberous roots are rich in bioactive components such as flavonoids, possessing anti-inflammatory, antioxidant, and immunomodulatory properties. To elucidate the impact of cadmium (Cd) stress on the accumulation and biosynthetic pathway of flavonoids in O. japonicus, this study exposed O. japonicus to different concentrations of Cd stress and explored the changes through integrated transcriptomics and metabolomics analysis. The results demonstrated that Cd stress (1 mg/L and 10 mg/L) significantly increased the content of flavonoids in O. japonicus in a concentration-dependent manner. The metabolomics analysis revealed a total of 110 flavonoids including flavones, flavanols, flavonols, flavone and flavonol derivatives, flavanones, isoflavonoids, chalcones and dihydrochalcones, and anthocyanins in O. japonicus, among which flavones, flavonols, flavone and flavonol derivatives, and anthocyanins increased under Cd stress. The transcriptomics analysis identified several key flavonoid biosynthesis-associated genes with up-regulated expression under Cd stress, including 14 genes encoding 4-coumarate CoA ligase (4CL), 2 genes encoding chalcone isomerase (CHI), and 14 genes encoding phenylalanine ammonia lyase (PAL). The gene-metabolite regulatory network indicated significant positive correlations of 4CL (Cluster-21637.5012, Cluster-21637.90648, and Cluster-21637.62637) and CHI (Cluster-21637.111909 and Cluster-21637.123300) with flavonoid metabolites, suggesting that these genes promoted the synthesis of specific flavonoid metabolites, which led to the accumulation of total flavonoids under Cd stress. These findings provide theoretical support for the cultivation and utilization of medicinal plants in Cd-contaminated environments and offered new perspectives for studying plant responses to heavy metal stress.
Cadmium/toxicity* ; Flavonoids/biosynthesis* ; Metabolomics ; Ophiopogon/drug effects* ; Stress, Physiological ; Transcriptome ; Gene Expression Profiling ; Gene Expression Regulation, Plant