PubMed

Front Pharmacol. 2025 Jan 27;16:1518481. doi: 10.3389/fphar.2025.1518481. eCollection 2025.ABSTRACTINTRODUCTION: Chronic nephrotoxicity caused by CNIs (CICN) manifests clinically as chronic kidney disease (CKD). Astragaloside IV (AS-IV) plays a certain role in the treatment of CKD. This study aimed to verify the ameliorative effects of AS-IV on CICN and further explore the mechanisms underlying the modulation of the "gut-transcriptome-metabolome coexpression network" by AS-IV within the context of the "gut-kidney axis" to improve CICN.METHODS: Five groups of 40 mice were studied: a normal group (N, olive oil), a model group (M, CsA, 30 mg kg--1 d-1), a low-dose AS-IV group (CsA + AS-IV, 30 mg kg-1 d-1 + 10 mg kg-1 d-1), a high-dose AS-IV group (CsA + AS-IV, 30 mg kg-1 d-1 + 20 mg kg-1 d-1), and a valsartan group (CsA + Val, 30 mg kg-1 d-1 + 10 mg kg-1 d-1). The gut microbiota, renal transcriptome, and urine metabolome were separately detected to construct a gut-transcriptome-metabolome coexpression network. The target species, target genes, and target metabolites of AS-IV were evaluated.RESULTS: CsA led to increased proteinuria and a deterioration of kidney function, accompanied by increased inflammation and oxidative stress, whereas AS-IV improved kidney damage. AS-IV inhibited intestinal permeability and disrupted the microbiota structure, increasing the abundance of Lactobacillus reuteri, Bifidobacterium animalis, Ignatzschineria indica, and Blautia glucerasea. Six coexpression pathways related to transcription and metabolism, including the citrate cycle, ascorbate and aldarate metabolism, proximal tubule bicarbonate reclamation, glycolysis/gluconeogenesis, ferroptosis, and drug metabolism-cytochrome P450, were identified. Seven target metabolites of AS-IV were identified in the 6 pathways, including UDP-D-galacturonic acid, 2-phenylethanol glucuronide, dehydroascorbic acid, isopentenyl pyrophosphate, alpha-D-glucose, 3-carboxy-1-hydroxypropylthiamine diphosphate and citalopram aldehyde. Five target genes of AS-IV, Ugt1a2, Ugt1a9, Ugt1a5, Pck1, and Slc7a11, were also identified and predicted by NONMMUT144584.1, MSTRG.30357.1 and ENSMUST00000174821. Lactobacillus reuteri was highly correlated with renal function and the target genes and metabolites of AS-IV. The target genes and metabolites of AS-IV were further validated. AS-IV inhibited intestinal-derived urinary toxins and improved renal tissue apoptosis, lipid accumulation, collagen deposition, and mitochondrial damage.CONCLUSION: AS-IV improved CICN through the coexpression of the gut-transcriptome-metabolome network. The six pathways related to energy metabolism driven by L. reuteri, including the citrate cycle, ascorbate and alderate metabolism, proximal tube bicarbonate metabolism, glycolysis/gluconeogenesis, ferroptosis, drug metabolism-cytochrome P450, are important mechanisms.PMID:39931687 | PMC:PMC11807982 | DOI:10.3389/fphar.2025.1518481

Front Nutr. 2025 Jan 27;12:1518525. doi: 10.3389/fnut.2025.1518525. eCollection 2025.ABSTRACTBACKGROUND: Active dietary flavonoids are a promising resource for novel drug discovery. Sweet potato, a widely cultivated functional crop, is abundant in flavonoids. However, the active ingredients associated with acute myeloid leukemia (AML) treatment and their underlying mechanisms have not been reported to date.OBJECTIVE: This study aims to identify novel drugs against AML from sweet potato by integrating metabolomics analysis, network pharmacology, and experimental validation.METHODS: Firstly, ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was employed to analyze the major constituents in sweet potato. Then, nine active ingredients were selected for validation of their anti-leukemia effects. Subsequently, three of them underwent network pharmacology analyses and in vitro experimental verification. Finally, the anti-leukemia effect of cynaroside was further confirmed through in vivo experimental validation.RESULTS: Firstly, the flavonoid content of stem, leaves, flesh, and peel from 13 sweet potato cultivars was examined. The leaves of Nanshu 017 exhibited the highest flavonoid content of 2.27% dry weight (DW). Then, an extract derived from these leaves was employed for in vitro experiments, demonstrating significant inhibition of AML cell growth. Subsequently, based on the results of metabolomics analysis and network pharmacology, cynaroside, nepitrin, and yuanhuanin were identified as potential antileukemia agents present in sweet potato for the first time; while CASP3, KDR, EGFR, and SRC were recognized as pivotal targets of these three monomers against AML. Finally, the antileukemia effects of cynaroside, nepitrin, and yuanhuanin were confirmed through in vitro and in vivo experimental validation.CONCLUSION: In summary, sweet potato leaves extract possesses an antileukemic effect while cynaroside, nepitrin, and yuanhuanin demonstrate potential as treatments for AML.PMID:39931370 | PMC:PMC11807822 | DOI:10.3389/fnut.2025.1518525

Front Plant Sci. 2025 Jan 27;15:1501966. doi: 10.3389/fpls.2024.1501966. eCollection 2024.ABSTRACTINTRODUCTION: In the present study, the flower of Chinese peony (CPF), major waste by-product of Chinese Herb Radix paeoniae, was comprehensively investigated for the first time.METHODS: A validated UHPLC Orbitrap Mass spectrometry combined a three-levels characterization strategy were used to analyze CPF samples from four representative cultivars. The anti-inflammatory and antioxidant activities were analyzed using RAW264.7 cells, and DPPH, ABTS, FRAP, and ORAC antioxidant assays.RESULTS: A total of 150 chemical components were identified in CPF, among them, more than 50 components were reported from this species for the first time, with potential new chemicals reported. 67 quantified or semi-quantified targeted metabolomics analysis indicated a clear distinction between flower parts and four cultivars. CPF demonstrated significant antioxidant activities and displayed anti-inflammatory effects by reducing nitric oxide, IL-6, and TNF-a release in LPS-induced macrophages. Correlation analysis highlighted a strong positive correlation between total phenolic content and DPPH ABTS, and FRAP antioxidant activities.DISCUSSION: The present study is the first to comprehensively investigate the chemical profile and bioactivities of CPF, which provide insights into further understanding of its health-promoting potential.PMID:39931332 | PMC:PMC11808149 | DOI:10.3389/fpls.2024.1501966

Food Sci Nutr. 2025 Feb 10;13(2):e70004. doi: 10.1002/fsn3.70004. eCollection 2025 Feb.ABSTRACTCoccinia grandis (L.) Voigt (C. grandis), a member of the Cucurbitaceae family, is recognized for its phytochemicals that possess antioxidant and antidiabetic properties, along with a wide array of nutritional and health-promoting benefits. However, a comprehensive investigation of the phytochemical profiles and biologically active constituents in different parts of C. grandis has not yet been reported. Therefore, this study aimed to evaluate the phytochemical constituents of three distinct parts of C. grandis (fruit, leaves, and stem) at the same growth stage. The phytochemicals in C. grandis were identified using UHPLC-HRMS-based untargeted metabolomics, followed by a quantitative analysis of the primary metabolites. The qualitative analysis revealed 60 secondary metabolites, including phenolic compounds (6 hydroxybenzoic acids, 22 hydroxycinnamic acids, 2 coumarins, 1 flavanone, 1 flavanonol, 2 flavones, 22 flavonols, and 2 lignans) and triterpenes (2 cucurbitacins). Furthermore, nine plant hormones and 30 amino acids were successfully identified. The quantitative analysis of 32 types of secondary metabolites indicated that the leaves contained the highest total amounts of flavonoids (501.37 mg/100 g) and hydroxycinnamic acids (1148.23 mg/100 g). Additionally, the analysis of amino acids revealed a total of 20 types, with the leaf extract exhibiting the highest total amounts of both essential and nonessential amino acids, followed by the fruit and stem extracts. In conclusion, the analysis of the primary and secondary metabolite composition and content of various parts of C. grandis demonstrated that the leaf extract replace with had the greatest functionality, suggesting its potential utility in the development of health functional foods.PMID:39931272 | PMC:PMC11808390 | DOI:10.1002/fsn3.70004

Front Aging Neurosci. 2025 Jan 27;17:1530046. doi: 10.3389/fnagi.2025.1530046. eCollection 2025.ABSTRACTBACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder, with mild cognitive impairment (MCI) often serving as its precursor stage. Early intervention at the MCI stage can significantly delay AD onset.METHODS: This study employed untargeted urine metabolomics, with data obtained from the MetaboLights database (MTBLS8662), combined with orthogonal partial least squares-discriminant analysis (OPLS-DA) to examine metabolic differences across different stages of AD progression. A decision tree approach was used to identify key metabolites within significantly enriched pathways. These key metabolites were then utilized to construct and validate an AD progression prediction model.RESULTS: The OPLS-DA model effectively distinguished the metabolic characteristics at different stages. Pathway enrichment analysis revealed that Drug metabolism was significantly enriched across all stages, while Retinol metabolism was particularly prominent during the transition stages. Key metabolites such as Theophylline, Vanillylmandelic Acid (VMA), and Adenosine showed significant differencesdifferencesin the early stages of the disease, whereas 1,7-Dimethyluric Acid, Cystathionine, and Indole exhibited strong predictive value during the MCI to AD transition. These metabolites play a crucial role in monitoring AD progression. Predictive models based on these metabolites demonstrated excellent classification and prediction capabilities.CONCLUSION: This study systematically analyzed the dynamic metabolic differences during the progression of AD and identified key metabolites and pathways as potential biomarkers for early prediction and intervention. Utilizing urinary metabolomics, the findings provide a theoretical basis for monitoring AD progression and contribute to improving prevention and intervention strategies, thereby potentially delaying disease progression.PMID:39931229 | PMC:PMC11807997 | DOI:10.3389/fnagi.2025.1530046

J Inflamm Res. 2025 Feb 6;18:1855-1874. doi: 10.2147/JIR.S500014. eCollection 2025.ABSTRACTPURPOSE: To explore the protective effect and underlying mechanism of Quzhou Aurantii Fructus flavonoids (QAFF) on Ulcerative colitis (UC).METHODS: The constituents of QAFF were accurately determined by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The therapeutic impacts of QAFF were assessed in dextran sulfate sodium (DSS)-induced UC mice, focusing on the changes in body weight, disease activity index (DAI), colon length, histological assessment of colonic tissues, levels of pro-inflammatory cytokines, and expression of tight junction proteins. Western blotting confirmed key regulatory proteins within the differential signaling pathways, guided by transcriptome analysis. Additionally, the influence of QAFF on the gut microbiome was explored through 16S ribosomal RNA (rRNA) sequencing. The alterations in endogenous metabolites were detected by untargeted metabolomics, and their potential correlation with intestinal flora was then examined utilizing Spearman correlation analysis. Subsequently, the regulation of gut microbiome by QAFF was validated by fecal microbiota transplantation (FMT).RESULTS: Eleven flavonoids, including Naringin and hesperidin, were initially identified from QAFF. In vivo experiments demonstrated that QAFF effectively ameliorated colitis symptoms, reduced IL-6, IL-1β, and TNF-α levels, enhanced intestinal barrier integrity, and downregulated PI3K/AKT pathway activation. Furthermore, QAFF elevated the levels of beneficial bacteria like Lachnospiraceae_NK4A136_group and Alloprevotella and concurrently reduced the pathogenic bacteria such as Escherichia-Shigella, [Eubacterium]_siraeum_group, and Parabacteroides. Metabolomics analysis revealed that 34 endogenous metabolites exhibited significant alterations, predominantly associated with Glycerophospholipid metabolism. These metabolites were significantly correlated with those differential bacteria modulated by QAFF. Lastly, the administration of QAFF via FMT ameliorated the colitis symptoms.CONCLUSION: QAFF could ameliorate inflammatory responses and intestinal barrier dysfunction in DSS-induced UC mice probably by modulating the PI3K/AKT signaling pathway and gut microbiome, offering promising evidence for the therapeutic potential of QAFF in UC treatment.PMID:39931170 | PMC:PMC11809370 | DOI:10.2147/JIR.S500014

Rapid Commun Mass Spectrom. 2025 May 30;39(10):e10007. doi: 10.1002/rcm.10007.ABSTRACTGancao Fuzi decoction (GCFZT) is a traditional Chinese formula, which has been commonly used in clinical practice to treat inflammatory diseases. However, the active substance of GCFZT in the treatment of inflammation is not fully clarified. In this study, we used orthogonal experiments to design different GCFZT formulations, resulting in a total of 16 GCFZT formulations. Subsequently, UPLC-Q-TOF-MS/MS was used to analyze the chemical composition of different formulations, and the anti-inflammatory activity differences of these formulations were evaluated through an LPS-induced RAW264.7 inflammatory cell model. Combined with machine learning algorithms such as PLS-DA and RF, four main active substances in GCFZT were screened. Finally, network pharmacology techniques were used to investigate the potential anti-inflammatory mechanisms of these main active substances, and the results showed that GCFZT mainly regulates the expression of core targets such as ALOX5, NFKB1, and TLR4 through main active substances such as chlorogenic acid, riboflavin, and formononetin, thereby affecting the NF kappa B signaling pathway, the Toll-like receptor signaling pathway, and the Th17 cell differentiation. This study provides a reference for the anti-inflammatory mechanism of GCFZT and a scientific basis for its clinical application.PMID:39930763 | DOI:10.1002/rcm.10007

J Obstet Gynaecol Res. 2025 Feb;51(2):e16229. doi: 10.1111/jog.16229.ABSTRACTBACKGROUND: The pathogenesis of preeclampsia (PE) remains unclear, but the interaction between intestinal flora and PE has been attention in recent studies. Several studies have shown that imbalanced intestinal flora plays an important role in the inducement of PE.PURPOSE: The potential correlation among intestinal flora, metabolites, and fetal growth restriction was explored by integrating data and analyzing neonatal growth. The study is hoped to provide references for subsequent studies.METHODS: A comparison between the intestinal flora of healthy pregnant women and pregnant with PE was conducted using 16S rRNA gene sequencing. Subsequently, the feces, serum and umbilical cord blood collected from healthy pregnant women and those with PE were analyzed using global untargeted metabolomics to identify differences in metabolites.RESULTS: The results showed that Bifidobacterium, Chryseobacterium, Eubacterium, Pravotella and Bacteroides are the core species associated with many metabolites. Normal-birth weight had a negative correlation with the abundance of raclopride, Phe-Gly-O and Lys-Phe-OH showed a positive correlation with Phosphonate and Lys-Gly. Simultaneously, these core metabolites showed a strong correlation with other growth indices (BPD, AC, FL). In summary, the imbalance of intestinal flora in pregnant women may alter the abundance of the core metabolites, thereby affecting the neonatal growth.CONCLUSIONS: A global untargeted metabolomics was performed on the samples including feces, serum, and umbilical cord blood. The integrated multi-omics analysis revealed the interaction among intestinal flora, metabolites and the clinical indices, demonstrating the potential effects of the imbalance of intestinal flora on neonatal growth in the pregnant women with PE.PMID:39930654 | DOI:10.1111/jog.16229

Plant J. 2025 Feb;121(3):e17252. doi: 10.1111/tpj.17252.ABSTRACTGlobal metabolic and transcriptional reprogramming is a common event in plant abiotic stress responses, however, the relevant molecular mechanisms remain largely unknown. Here, we characterized the physiological function and molecular mechanism for the rice UGT706F1. We found that UGT706F1 can be potently induced by high temperature. Its overexpression can markedly enhance the heat tolerance of rice through improving the capacity of scavenging reactive oxygen species, whereas its functional deletion results in heat sensitivity in rice. To investigate the regulatory mechanism of UGT706F1 in response to high temperature, we carried out extensive screening of the in vitro enzymatic activity of UGT706F1 and discovered that UGT706F1 exhibits broad-spectrum activity toward flavonoid compounds. Through targeted flavonoid metabolomics analysis, we further revealed that the overexpression of UGT706F1 elevated the content of diverse flavonoids and flavonoid glycosides in rice. Subsequently, via transcriptome analysis, we found that following heat treatment, the overexpression of UGT706F1 was capable of enhancing the transcriptional activity of those genes including the flavonoid synthases, heat shock factors, heat shock proteins, glutathione S-transferase, and various antioxidant enzymes. Furthermore, we identified an R2R3 MYB-type transcription factor MYB61 and demonstrated that MYB61 could directly bind the promoter of UGT706F1 and activate the transcription of UGT706F1. The overexpression of MYB61 also enhanced the heat tolerance and increased flavonoid glycosides. Overall, this study unveiled a novel pathway of the plant heat tolerance response mediated by MYB61-UGT706F1 module and identified a new UGT player for the metabolic and transcriptional regulation under high-temperature circumstance.PMID:39930614 | DOI:10.1111/tpj.17252

J Exp Clin Cancer Res. 2025 Feb 10;44(1):47. doi: 10.1186/s13046-025-03302-0.ABSTRACTThe focus of cancer immunotherapy has traditionally been on immune cells and tumor cells themselves, often overlooking the tumor secretome. This review provides a comprehensive overview of the intricate relationship between tumor cells and the immune response in cancer progression. It highlights the pivotal role of the tumor secretome - a diverse set of molecules secreted by tumor cells - in significantly influencing immune modulation, promoting immunosuppression, and facilitating tumor survival. In addition to elucidating these complex interactions, this review discusses current clinical trials targeting the tumor secretome and highlights their potential to advance personalized medicine strategies. These trials aim to overcome the challenges of the tumor microenvironment by designing therapies tailored to the secretome profiles of individual cancer patients. In addition, advances in proteomic techniques are highlighted as essential tools for unraveling the complexity of the tumor secretome, paving the way for improved cancer treatment outcomes.PMID:39930476 | DOI:10.1186/s13046-025-03302-0

Adv Exp Med Biol. 2025;1468:207-212. doi: 10.1007/978-3-031-76550-6_34.ABSTRACTDysregulation of lipid metabolism has been linked with risk for age-related retinal diseases including age-related macular degeneration (AMD). However, how dysregulated lipid metabolism contributes to AMD development is unknown. In this study, we evaluated the retinal and plasma lipidomes of a mouse model displaying retinal pigmented epithelium (RPE) pathologies that are observed in AMD including RPE dysmorphia and degeneration. We found that the RPE phenotypes in mice overexpressing transmembrane protein 135 (Tmem135 TG) are correlated with retinal and plasma lipidome changes. While distinct lipid profiles were observed in the retina and plasma of Tmem135 TG mice, a common finding in both retinal and plasma lipidomes was an increase of lipids containing C22:5. This data suggests that accumulation of C22:5-containing lipids may contribute to the development of the RPE pathologies in Tmem135 TG mice.PMID:39930197 | DOI:10.1007/978-3-031-76550-6_34

BMC Plant Biol. 2025 Feb 10;25(1):174. doi: 10.1186/s12870-025-06189-3.ABSTRACTSeagrasses maintain cellular water balance by regulating ion concentrations and accumulating organic osmolytes, enabling them to survive in the fluctuating salinity of intertidal environments. However, the molecular mechanisms underlying seagrass responses to salinity changes remain relatively understudied. To address this, we conducted a multi-omics analysis of Ruppia sinensis under low, moderate, and high salinity conditions to uncover the mechanisms behind its adaptation to salinity fluctuations. Our research revealed that the transition from low to high salinity significantly altered the physiological characteristics of R. sinensis. Simultaneously, the species enhanced its ability to cope with and adapt to salinity fluctuations by increasing antioxidant enzyme activity. Integration of multi-omics data further indicated that under high salinity conditions, R. sinensis synthesizes more flavonoids to bolster its adaptive capacity. Additionally, the phenylpropanoid metabolic pathway appears to play a crucial role in the response of R. sinensis to changes in water salinity.PMID:39930400 | DOI:10.1186/s12870-025-06189-3

BMC Plant Biol. 2025 Feb 11;25(1):178. doi: 10.1186/s12870-025-06154-0.ABSTRACTGlobally, rice bacterial blight disease causes significant yield losses. Metabolomics is a vital tool for understanding this disease by analyzing metabolite levels and pathways involved in resistance and susceptibility. It enables the development of disease-resistant rice varieties and sustainable disease management strategies. This study has focused on the metabolic response to bacterial blight disease in three rice varieties: the near isogenic rice line IRBB27, wild rice (Oryza minuta-CG154:IRGC No. 93259, accession No. EC861737), and the susceptible control IR24. However, detailed metabolomics studies in wild rice remain largely unexplored. So, metabolic analysis with untargeted liquid chromatography mass spectrometry analysis (LC-MS/MS) was performed at various time points, including pre infection and post infection at 12 h and 24 h with Xanthomonas oryzae pv. oryzae (Xoo). In this study, a total of 6067 metabolites were identified. Pre-infection stage of the susceptible, resistant, and wild rice had 675, 660, and 702 identified metabolites, respectively, but these numbers were altered at post-infection stages. Various defense-related metabolites, including amino acids, flavonoids, alkaloids, terpenoids, nucleotide derivatives, organic acids, inorganic compounds, fatty acid and lipid derivatives have been identified. PCA and PLS-DA plots revealed differences in the metabolome among susceptible, resistant, and wild genotypes, suggesting distinct metabolic profiles for each. In this study, we found 149 metabolites were upregulated and 162 downregulated in the wild type (CG154) compared to the susceptible cultivar (IR24). Similarly, 85 metabolites were upregulated and 92 downregulated in the resistant near isogenic line (IRBB27) compared to IR24, while 156 were upregulated and 149 downregulated in CG154 compared to IRBB27. Key metabolites, including flavonoids, terpenoids, and phenolic compounds, showed significantly higher levels (P ≤ 0.01) in resistant varieties. These identified defense metabolites could serve as potential biomarkers for bacterial blight resistance in rice. The findings from this study have important implications for the development of new rice cultivars with tolerance to bacterial blight disease.PMID:39930388 | DOI:10.1186/s12870-025-06154-0

BMC Plant Biol. 2025 Feb 10;25(1):173. doi: 10.1186/s12870-025-06163-z.ABSTRACTBACKGROUND: Chrysanthemum (Chrysanthemum × morifolium) is one of the four major cut flowers worldwide and is valued for ornamental, culinary, and medicinal purposes. Terpenoids are key components of the fragrance of chrysanthemum; they not only serve to repel insect herbivores and promote pollination but also impact the value of the plant. However, the terpene production of chrysanthemum and the regulatory mechanisms involved remain unclear.RESULTS: We used gas chromatography‒mass spectrometry (GC‒MS) to identify 177 compounds, including 106 terpenes, in ten chrysanthemum cultivars. Monoterpene derivatives and sesquiterpenes were the most common. Next, we identified 27 candidate hub genes for terpene production in chrysanthemum via combined transcriptome and metabolome analysis, as well as weighted gene coexpression network analysis. The three terpenes synthesis-related genes were significantly expressed in the disc florets of the different chrysanthemum cultivars. We concluded that the transcription factors TCP8, TCP5, ATHB8, ATHB7, HAT22, TGA1, TGA4, and WHY1 may regulate terpene synthesis.CONCLUSIONS: In this study, we profiled terpenes in chrysanthemum florets and constructed a key terpene-transcription factor network related to terpene synthesis. These findings lay the groundwork for future research into the mechanism of terpene synthesis in chrysanthemum as well as in other plants.PMID:39930381 | DOI:10.1186/s12870-025-06163-z

BMC Genomics. 2025 Feb 11;26(1):130. doi: 10.1186/s12864-025-11330-5.ABSTRACTSolute carriers (SLC) are integral membrane proteins responsible for transporting a wide variety of metabolites, signaling molecules and drugs across cellular membranes. Despite key roles in metabolism, signaling and pharmacology, around one third of SLC proteins are 'orphans' whose substrates are unknown. Experimental determination of SLC substrates is technically challenging, given the wide range of possible physiological candidates. Here, we develop a predictive algorithm to identify correlations between SLC expression levels and intracellular metabolite concentrations by leveraging existing cancer multi-omics datasets. Our predictions recovered known SLC-substrate pairs with high sensitivity and specificity compared to simulated random pairs. CRISPR-Cas9 dependency screen data and metabolic pathway adjacency data further improved the performance of our algorithm. In parallel, we combined drug sensitivity data with SLC expression profiles to predict new SLC-drug interactions. Together, we provide a novel bioinformatic pipeline to predict new substrate predictions for SLCs, offering new opportunities to de-orphanise SLCs with important implications for understanding their roles in health and disease.PMID:39930358 | DOI:10.1186/s12864-025-11330-5

Geroscience. 2025 Feb 10. doi: 10.1007/s11357-025-01553-5. Online ahead of print.ABSTRACTChronic, low-grade inflammation is a hallmark of aging and various age-related diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD). The prevalence of metabolic dysfunction-associated steatohepatitis (MASH), an advanced form of MASLD, increases with age and contributes to morbidity and mortality among the elderly. This study investigates the role of necroptosis, a programmed cell death pathway that promotes inflammation, in liver inflammaging and age-associated MASLD by utilizing genetic ablation models of two key necroptosis proteins, Mlkl or Ripk3. The absence of Mlkl or Ripk3 significantly reduced liver inflammation, steatosis, and fibrosis in aged male mice, supporting the role of necroptosis in age-associated MASLD. Additionally, Mlkl or Ripk3 deletion impacted other non-necroptotic cellular processes that drive inflammation and MASLD, such as cellular senescence, apoptosis, and autophagy in aged liver. Levels of plasma TNFα and IL6, key proinflammatory cytokines associated with inflammaging, are reduced in Mlkl-/- or Ripk3-/- aged mice, supporting a systemic effect of necroptosis inhibition on inflammation. Proteomic analysis of liver tissues emphasizes the critical role of lipid and immune regulatory processes in maintaining liver homeostasis when Mlkl or Ripk3 is absent in aging liver. While Mlkl deletion did not affect the lifespan of mice, Ripk3 deletion shortened it. Additionally, Mlkl deficiency improved insulin sensitivity, whereas Ripk3 deficiency exacerbated glucose intolerance in aged mice. Thus, selective inhibition of Mlkl, not Ripk3, represents a potential therapeutic avenue for mitigating age-related liver disease and enhancing metabolic outcomes in the elderly.PMID:39930289 | DOI:10.1007/s11357-025-01553-5

Clin Rheumatol. 2025 Feb 10. doi: 10.1007/s10067-025-07355-6. Online ahead of print.ABSTRACTRheumatoid arthritis (RA) is a systemic chronic autoimmune disease characterized by joint damage and systemic involvement. Despite advancements in understanding RA, early diagnosis and effective treatment remain challenging due to the complex pathogenesis and limited specificity of current biomarkers. Metabolomics, offers a promising approach for identifying new biomarkers to assess treatment responsiveness in RA. A systematic review was conducted to identify key metabolites and metabolic pathways that may reveal responsiveness to different drug therapy strategies (methotrexate, TNF, and IL-6 inhibitors) in RA treatment. The systematic search was conducted in PubMed and Google Scholar in accordance with PRISMA recommendations. The risk of bias and the quality of the final selected studies were assessed in duplicate using the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool and using the QUADOMICS tool. Eighteen studies were eligible for data extraction. Metabolomic studies revealed distinct profiles for responders and non-responders to different RA treatments. For methotrexate therapy, key metabolites included for example: homocysteine, glycerol-3-phosphate, and diphosphoglyceric acid. TNF inhibitor response was associated mainly with changes in carbohydrate derivatives and amino acids. IL-6 inhibitor studies identified metabolites such as N-acetylglucosamine, N-acetylgalactosamine, and N-acetylneuraminic acid as potential predictors of response. Across studies, metabolomic profiles demonstrated high sensitivity and specificity in distinguishing responders from non-responders. These studies collectively highlight alterations in TCA cycle metabolites, amino acids, nucleotide metabolism, and lipid profiles, among others. This review supports the identification of better treatment strategies choosing methotrexate, TNF, or IL-6 inhibitors as therapeutic interventions based on metabolomics profiling.PMID:39930277 | DOI:10.1007/s10067-025-07355-6

Adv Exp Med Biol. 2025;1468:267-271. doi: 10.1007/978-3-031-76550-6_44.ABSTRACTThe retina is one of the most metabolically active tissues in the human body and has its own complex metabolic environment as the different cell types in this tissue are interconnected to maintain a healthy retinal homeostasis. Any disturbances in the homeostatic balance may have a severe impact on retinal function affecting vision. About 341 genes are listed in the RetNet database as being causative for monogenic inherited retinal diseases. By intersecting this list with the Mammalian Metabolic Enzyme Database, we identified 28 metabolic genes that can result in diseases such as retinitis pigmentosa, Leber congenital amaurosis, or optic atrophy when mutated. Alongside inherited retinal diseases, metabolism also plays a prominent role in acquired retinal diseases. Metabolomics studies have been performed on patients with age-related macular degeneration, diabetic retinopathy, and glaucoma revealing dysregulated metabolic pathways, such as lipid, amino acid, and purine metabolism, in the onset of disease. Although there are distinct pathophysiological differences between inherited and acquired retinal disorders, diving deeper into the role of metabolism and how metabolic dysfunction may overlap with different pathologies, could give us indications on how to design approaches to normalize the homeostatic balance in the retina as treatment options to protect vision.PMID:39930207 | DOI:10.1007/978-3-031-76550-6_44

World J Microbiol Biotechnol. 2025 Feb 11;41(2):68. doi: 10.1007/s11274-025-04285-y.ABSTRACTOmics technologies are a set of disciplines that analyze large-scale molecular data to understand biological systems in a holistic way. These technologies aim to reveal the structure, functions and interactions of organisms by studying processes at many levels of biomolecules, from the genome to metabolism. Lactobacillomics is introduced as an interdisciplinary field that integrates multiple "omics" technologies-including genomics, transcriptomics, proteomics, metabolomics, and metagenomics- to provide a comprehensive insight into "lactic acid bacteria" species. Lactobacillomics aims to elucidate the genetic, metabolic, and functional characteristics of lactic acid bacteria (LAB) species, providing insights into the mechanisms underlying their probiotic effects and contributions to the host microbiome. By analyzing genomes and metabolic pathways, researchers can identify specific genes responsible for health-promoting functions and desirable fermentation characteristics, which can guide the development of targeted probiotic strains with optimized health benefits. The integration of these omics data allows facilitating the discovery of biomarkers for health and disease states, the development of new probiotics tailored to specific populations or health conditions, and the optimization of fermentation processes to enhance the safety, flavor, and nutritional profile of fermented foods. A comprehensive review and bibliometric analysis were conducted to provide an overview of this promising field between 2005 and 2025 by examining Web of Science Core Collection data. Research results reveal trending topics, future perspectives, and key areas of growth within lactic acid bacteria (LAB) studies, particularly as they intersect with omics technologies.PMID:39930163 | DOI:10.1007/s11274-025-04285-y

Sci Rep. 2025 Feb 10;15(1):4963. doi: 10.1038/s41598-025-87288-x.ABSTRACTProfound metabolomic alterations occur during COVID-19. Early identification of the subset of hospitalised COVID-19 patients at risk of developing severe disease is critical for optimal resource utilization and prompt treatment. This work explores the metabolomic profile of hospitalised adult COVID-19 patients with severe disease, and establishes a predictive signature for disease progression. Within 48 hours of admission, serum samples were collected from 148 hospitalised patients for nuclear magnetic resonance (NMR) spectroscopy. Lipoprotein profiling was performed using the 1H-NMR-based Liposcale test, while low molecular weight metabolites were analysed using one-dimensional Carr-Purcell-Meiboom-Gill pulse spectroscopy and an adaptation of the Dolphin method for lipophilic extracts. Severe COVID-19, per WHO's Clinical Progression Scale, was characterized by altered lipoprotein distribution, elevated signals of glyc-A and glyc-B, a shift towards a catabolic state with elevated levels of branched-chain amino acids, and accumulation of ketone bodies. Furthermore, COVID-19 patients initially presenting with moderate disease but progressing to severe stages exhibited a distinct metabolic signature. Our multivariate model demonstrated a cross-validated AUC of 0.82 and 72% predictive accuracy for severity progression. NMR spectroscopy-based metabolomic profiling enables the identification of moderate COVID-19 patients at risk of disease progression, aiding in resource allocation and early intervention.PMID:39929875 | DOI:10.1038/s41598-025-87288-x