PubMed

Mol Cancer. 2023 Aug 10;22(1):128. doi: 10.1186/s12943-023-01802-1.ABSTRACTProtein regulator of cytokinesis 1 (PRC1) is involved in cytokinesis. Growing evidence suggests the association of PRC1 with multiple cancers. Here, we unveil that, in 28 cancer types, PRC1 is higher expressed in tumor tissues than in non-malignant tissues. Overexpression of PRC1 indicates unfavorable prognostic value, especially in ACC, LGG, KIRP, LICH, LUAD, MESO, PAAD, SARC and UCEC, while methylation of the PRC1 gene at sites associated with its inactivation has a favorable prognostic value in ACC, KIRP, LUAD, MESO, KIRP and LGG. Differentially expressed genes (DEGs) associated with high (> median) PRC1 expression contribute to key signaling pathways related with cell cycle, DNA damage and repair, EMT, cell migration, invasion and cell proliferation in most cancer types. More specifically, the DEGs involved in RAS/RAF/MAPK, PI3K/AKT, WNT, NOTCH, TGF-β, integrin, EMT process, focal adhesion, RHO GTPase-related pathway or microtubule cytoskeleton regulation are upregulated when PRC1 expression is above median, as confirmed for most cancers. Most importantly, high expression of PRC1 appears to be associated with an overabundance of poor-prognosis TH2 cells. Furthermore, positive correlations of PRC1 and some immune checkpoint genes (CD274, CTLA4, HAVCR2, LAG3, PDCD1, PDCD1LG2, TIGIT, and CD86) were observed in several cancers, especially BLCA, BRCA, KIRC, LUAD, LIHC, PRAD and THCA. These findings plead in favor of further studies validating the diagnostic and prognostic impact of PRC1 as well as the elaboration of pharmacological strategies for targeting PRC1.PMID:37563591 | DOI:10.1186/s12943-023-01802-1

Sci Rep. 2023 Aug 10;13(1):12990. doi: 10.1038/s41598-023-39661-x.ABSTRACTMetabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation.PMID:37563133 | DOI:10.1038/s41598-023-39661-x

Phytomedicine. 2023 Aug 5;119:155005. doi: 10.1016/j.phymed.2023.155005. Online ahead of print.ABSTRACTBACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is becoming a global epidemic without effective treatment currently available. NAFLD is characterized by an increase in hepatic de novo lipogenesis (DNL) and inadequate compensatory enhancement in fatty acid oxidation (FAO), which disturbs lipid homeostasis. In NAFLD, lipid metabolism relies heavily on metabolic reprogramming. Moreover, lipid metabolism plays an essential role in switching between lipogenesis and FAO, which is beneficial for the anti-NAFLD therapy. Our recent study demonstrated that the phytochemical tetrahydropalmatine (THP) has positive efficacy in hepatocellular carcinoma (HCC). However, it remains unclear whether the therapeutic benefits of THP are primarily due to delaying the progression of hepatic steatosis to HCC.PURPOSE: This work aimed to systemically evaluate the pharmacological functions and underlying mechanisms of THP in NAFLD using both in vitro and in vivo models.METHODS: NAFLD models were established using high-fat diet (HFD)-fed mice in vivo and palmitic acid- and oleic acid-challenged hepatocytes in vitro. Metabonomics analysis concomitant with biochemical indices and computational biology assays were performed comprehensively to reveal the key link between the treatment of NAFLD and the AMPK-SREBP-1c-Sirt1 signaling axis.RESULTS: Hepatic metabolomics analysis revealed that THP altered lipid metabolism by enhancing FAO and inhibiting glycolysis, tricarboxylic acid cycle, and urea cycle in HFD-fed mice. Analysis of gene expression showed that THP profoundly suppressed hepatic DNL and promoted FAO. THP supplementation not only significantly decreased body/liver weight gain and serum indices but also ameliorated hepatic steatosis. Simultaneously, impaired lipotoxicity was observed in vivo and in vitro after THP supplementation, protecting against steatosis-driven injury. Metabolic phenotype assays showed that THP promoted switching from glycolysis inhibition to FAO enhancement in steatotic cells, resulting in reprogramming lipid metabolism. Mechanistically, THP accelerated lipid oxidation by activating AMPK-SREBP-1c-Sirt1 axis signaling. Applying molecular docking combined with surface plasmon resonance and cellular thermal shift assay target engagement, as well as siRNA assays, AMPKα was confirmed as a direct molecular target of THP.CONCLUSION: In summary, THP ameliorates hepatic steatosis in NAFLD by switching lipid metabolism via the AMPK-SREBP-1c-Sirt1 pathway. This work provides an attractive phytochemical component for therapy against hepatic steatosis in NAFLD.PMID:37562090 | DOI:10.1016/j.phymed.2023.155005

PLoS One. 2023 Aug 10;18(8):e0289738. doi: 10.1371/journal.pone.0289738. eCollection 2023.ABSTRACTRecently, numerous studies have reported on different predictive models of disease severity in COVID-19 patients. Herein, we propose a highly predictive model of disease severity by integrating routine laboratory findings and plasma metabolites including cytosine as a potential biomarker of COVID-19 disease severity. One model was developed and internally validated on the basis of ROC-AUC values. The predictive accuracy of the model was 0.996 (95% CI: 0.989 to 1.000) with an optimal cut-off risk score of 3 from among 6 biomarkers including five lab findings (D-dimer, ferritin, neutrophil counts, Hp, and sTfR) and one metabolite (cytosine). The model is of high predictive power, needs a small number of variables that can be acquired at minimal cost and effort, and can be applied independent of non-empirical clinical data. The metabolomics profiling data and the modeling work stemming from it, as presented here, could further explain the cause of COVID-19 disease prognosis and patient management.PMID:37561777 | DOI:10.1371/journal.pone.0289738

Plant Biotechnol J. 2023 Aug 10. doi: 10.1111/pbi.14154. Online ahead of print.ABSTRACTA novel metabolomics analysis technique, termed matrix-assisted laser desorption/ionization mass spectrometry imaging-based plant tissue microarray (MALDI-MSI-PTMA), was successfully developed for high-throughput metabolite detection and imaging from plant tissues. This technique completely overcomes the disadvantage that metabolites cannot be accessible on an intact plant tissue due to the limitations of the special structures of plant cells (e.g. epicuticular wax, cuticle and cell wall) through homogenization of plant tissues, preparation of PTMA moulds and matrix spraying of PTMA sections. Our study shows several properties of MALDI-MSI-PTMA, including no need of sample separation and enrichment, high-throughput metabolite detection and imaging (>1000 samples per day), high-stability mass spectrometry data acquisition and imaging reconstruction and high reproducibility of data. This novel technique was successfully used to quickly evaluate the effects of two plant growth regulator treatments (i.e. 6-benzylaminopurine and N-phenyl-N'-1,2,3-thiadiazol-5-ylurea) on endogenous metabolite expression in plant tissue culture specimens of Dracocephalum rupestre Hance (D. rupestre). Intra-day and inter-day evaluations indicated that the metabolite data detected on PTMA sections had good reproducibility and stability. A total of 312 metabolite ion signals in leaves tissues of D. rupestre were detected, of which 228 metabolite ion signals were identified, they were composed of 122 primary metabolites, 90 secondary metabolites and 16 identified metabolites of unknown classification. The results demonstrated the advantages of MALDI-MSI-PTMA technique for enhancing the overall detection ability of metabolites in plant tissues, indicating that MALDI-MSI-PTMA has the potential to become a powerful routine practice for high-throughput metabolite study in plant science.PMID:37561662 | DOI:10.1111/pbi.14154

Metabolomics. 2023 Aug 10;19(8):73. doi: 10.1007/s11306-023-02037-3.ABSTRACTOBJECTIVES: Currently, metabolic biomarkers with great practicability of gastric cancer (GC) and gastric precancerous lesions (GPL) are scarce. Thus, we are devoted to determining the plasma metabolic profiles of patients with GPL or GC and validate candidate biomarkers for disease diagnosis.METHODS: In this hospital-based case-control study, 68 plasma samples from 27 non-atrophic gastritis (NAG, control), 31 GPL, and 10 GC patients were collected for targeted metabolomics analysis. Univariate and multivariate analyses were used for selecting the differential metabolites. A receiver operating characteristic curve combined with binary logistic regression analysis was performed to test the diagnostic performance of the differential metabolites. Dietary data were obtained using a semiquantitative food frequency questionnaire.RESULTS: Distinct metabolomic profiles were noted for NAG, GPL, and GC. Compared to the NAG patients, the levels of 5 metabolites in the GPL group and 4 metabolites in the GC group were found to significantly elevate. Compared with the model involving 9 traditional risk factors (AUC: 0.89, 95%CI: 0.78-1.00), Trimethylamine N-oxide, the most significant metabolite (P = 2.00 × 10-5, FDR = 0.003, FC > 2, VIP > 2), showed a good diagnostic performance for the patients with GC (AUC: 0.90, 95%CI: 0.78-1.00), and its diagnostic performance has been further improved with the integration of Rhamnose (AUC: 0.96, 95%CI: 0.89-1.00).CONCLUSION: In our study, 9 defined metabolites might serve as meaningful biomarkers for identifying the high-risk population of GPL and GC, possibly enhancing the prevention and control of GPL and GC.PMID:37561286 | DOI:10.1007/s11306-023-02037-3

J Clin Endocrinol Metab. 2023 Aug 10:dgad452. doi: 10.1210/clinem/dgad452. Online ahead of print.ABSTRACTCONTEXT: Diabetic retinopathy (DR) is a specific microvascular complication in patients with diabetes and the leading cause of blindness. Recent advances in omics, especially metabolomics, offer possibility to identify novel potential biomarkers for DR.DESIGN, SETTING, AND METHODS: We performed a 12-year follow-up study including 1349 participants with type 2 diabetes (1021 without DR, 328 with DR) selected from the METSIM cohort. Individuals who had retinopathy before the baseline study were excluded (n = 63). The diagnosis of retinopathy was based on fundus photography examination. We performed nontargeted metabolomics profiling to identify metabolites associated with DR.RESULTS: We found 17 metabolites significantly associated with incident DR after the adjustment for confounding factors. Among amino acids, N-lactoyl isoleucine, N-lactoyl valine, N-lactoyl tyrosine, and N-lactoyl phenylalanine, N-(2-furoyl) glycine, and 5-hydroxylysine were associated with an increased risk of DR, and citrulline with a decreased risk of DR. Among the fatty acids N, N, N-trimethyl-5-aminovalerate was associated with an increased risk of DR, and myristoleate (14:1n5), palmitoleate (16:1n7) and 5-dodecenoate (12:1n7) with a decreased risk of DR. Sphingomyelin (d18:2/24:2), a sphingolipid, was significantly associated with a decreased risk of DR. Carboxylic acid maleate and organic compounds 3-hydroxypyridine sulfate, 4-vinylphenol sulfate, 4-ethylcatechol sulfate, and dimethyl sulfone were significantly associated with an increased risk of DR.CONCLUSIONS: Our study is the first large population-based longitudinal study to identify metabolites for DR. We found multiple metabolites associated with an increased and decreased risk for DR from several different metabolic pathways.PMID:37560996 | DOI:10.1210/clinem/dgad452

J Appl Physiol (1985). 2023 Aug 10. doi: 10.1152/japplphysiol.00226.2023. Online ahead of print.ABSTRACTChronic kidney disease (CKD)-related cachexia increases the risks of reduced physical activity and mortality. However, the physiological phenotype of skeletal muscle fatigue and changes in intramuscular metabolites during muscle fatigue in CKD-related cachexia remain unclear. In the present study, we performed detailed muscle physiological evaluation, analysis of mitochondrial function, and comprehensive analysis of metabolic changes before and after muscle fatigue in a 5/6 nephrectomized rat model of CKD. Wistar rats were randomized to a sham-operation (Sham) group that served as a control group or a 5/6 nephrectomy (Nx) group. Eight weeks after the operation, in situ torque and force measurements in plantar flexor muscles in Nx rats using electrical stimulation revealed a significant decrease in muscle endurance during subacute phase related to mitochondrial function. Muscle mass was reduced without changes in the proportions of fiber type-specific myosin heavy chain isoforms in Nx rats. Pyruvate-malate-driven state 3 respiration in isolated mitochondria were impaired in Nx rats. Protein expression levels of mitochondrial respiratory chain complexes III and V were decreased in Nx rats. Metabolome analysis revealed that the increased supply of acetyl CoA in response to fatigue was blunted in Nx rats. These findings suggest that CKD deteriorates skeletal muscle endurance in association with mitochondrial dysfunction and inadequate supply of acetyl-CoA during muscle fatigue.PMID:37560765 | DOI:10.1152/japplphysiol.00226.2023

Front Microbiol. 2023 Jul 25;14:1233512. doi: 10.3389/fmicb.2023.1233512. eCollection 2023.ABSTRACTHypsizygus marmoreus is one of the main industrially cultivated varieties of edible fungi, with a delicious taste and high nutritional value. However, the long harvest period of 130-150 days greatly limits its large-scale expansion. This study aimed to investigate the effects of central carbon metabolism (CCM) on the mycelial growth performance and fruiting body formation of H. marmoreus. Nine edible fungi with different harvest periods were collected and used to evaluate their intracellular carbon metabolic differences in the CCM, which revealed that the imbalanced distribution of intracellular carbon metabolic levels in the CCM of H. marmoreus might be one of the key factors resulting in a slow mycelial growth rate and a long harvest period. Further analysis by three strategies, including metabolomics, adaptation of different carbon sources, and chemical interference, confirmed that low carbon flux into the pentose phosphate pathway (PPP) limited the supply of raw materials, reduced power, and thus influenced the mycelial growth of H. marmoreus. Furthermore, four transformants with increased expression levels of glucose-6-phosphate dehydrogenase (G6PDH), a key rate-limiting enzyme in the PPP of H. marmoreus, were developed and showed more extracellular soluble protein secretion and higher sugar assimilation rates, as well as improved mycelial growth rates in bottle substrate mixtures. Finally, cultivation experiments indicated that the maturation periods of the fruiting body with ~4-5 days in advance and the maximum fruiting body yield of 574.8 g per bag with an increase of 7.4% were achieved by improving the G6PDH expression level of the PPP in H. marmoreus. This study showed that CCM played an important role in the mycelial growth and development of H. marmoreus, which provided new insights for future advancements in cultivating and breeding edible fungi.PMID:37560516 | PMC:PMC10407233 | DOI:10.3389/fmicb.2023.1233512

Front Neurol. 2023 Jul 25;14:1255513. doi: 10.3389/fneur.2023.1255513. eCollection 2023.NO ABSTRACTPMID:37560451 | PMC:PMC10408293 | DOI:10.3389/fneur.2023.1255513

Brain Behav Immun Health. 2023 Jul 31;32:100671. doi: 10.1016/j.bbih.2023.100671. eCollection 2023 Oct.ABSTRACTHuman-microorganism interactions play a key role in human health. However, the underlying molecular mechanisms remain poorly understood. Small-molecules that offer a functional readout of microbe-microbe-human relationship are of great interest for deeper understanding of the inter-kingdom crosstalk at the molecular level. Recent studies have demonstrated that small-molecules from gut microbiota act as ligands for specific human G protein-coupled receptors (GPCRs) and modulate a range of human physiological functions, offering a mechanistic insight into the microbe-human interaction. To this end, we focused on analysis of bacterial metabolites that are currently recognized to bind to GPCRs and are found to activate the known downstream signaling pathways. We further mapped the distribution of these molecules across the public mass spectrometry-based metabolomics data, to identify the presence of these molecules across body sites and their association with health status. By combining this with RNA-Seq expression and spatial localization of GPCRs from a public human protein atlas database, we inferred the most predominant GPCR-mediated microbial metabolite-human cell interactions regulating gut-immune-brain axis. Furthermore, by evaluating the intestinal absorption properties and blood-brain barrier permeability of the small-molecules we elucidated their molecular interactions with specific human cell receptors, particularly expressed on human intestinal epithelial cells, immune cells and the nervous system that are shown to hold much promise for clinical translational potential. Furthermore, we provide an overview of an open-source resource for simultaneous interrogation of bioactive molecules across the druggable human GPCRome, a useful framework for integration of microbiome and metabolite cataloging with mechanistic studies for an improved understanding of gut microbiota-immune-brain molecular interactions and their potential therapeutic use.PMID:37560037 | PMC:PMC10407893 | DOI:10.1016/j.bbih.2023.100671

Hortic Res. 2023 Jun 13;10(8):uhad126. doi: 10.1093/hr/uhad126. eCollection 2023 Aug.ABSTRACTIn plants, 5mC DNA methylation is an important and conserved epistatic mark involving genomic stability, gene transcriptional regulation, developmental regulation, abiotic stress response, metabolite synthesis, etc. However, the roles of 5mC DNA methylation modification (5mC methylation) in tea plant growth and development (in pre-harvest processing) and flavor substance synthesis in pre- and post-harvest processing are unknown. We therefore conducted a comprehensive methylation analysis of four key pre-harvest tissues (root, leaf, flower, and fruit) and two processed leaves during oolong tea post-harvest processing. We found that differential 5mC methylation among four key tissues is closely related to tissue functional differentiation and that genes expressed tissue-specifically, responsible for tissue-specific functions, maintain relatively low 5mC methylation levels relative to non-tissue-specifically expressed genes. Importantly, hypomethylation modifications of CsAlaDC and TS/GS genes in roots provided the molecular basis for the dominant synthesis of theanine in roots. In addition, integration of 5mC DNA methylationomics, metabolomics, and transcriptomics of post-harvest leaves revealed that content changes in flavor metabolites during oolong tea processing were closely associated with transcription level changes in corresponding metabolite synthesis genes, and changes in transcript levels of these important synthesis genes were strictly regulated by 5mC methylation. We further report that some key genes during processing are regulated by 5mC methylation, which can effectively explain the content changes of important aroma metabolites, including α-farnesene, nerolidol, lipids, and taste substances such as catechins. Our results not only highlight the key roles of 5mC methylation in important flavor substance synthesis in pre- and post-harvest processing, but also provide epimutation-related gene targets for future improvement of tea quality or breeding of whole-tissue high-theanine varieties.PMID:37560013 | PMC:PMC10407603 | DOI:10.1093/hr/uhad126

iScience. 2023 Jul 18;26(8):107413. doi: 10.1016/j.isci.2023.107413. eCollection 2023 Aug 18.ABSTRACTTo analyze the differences between different-sized Acipenser dabryanus, we randomly selected 600 3-month-old A. dabryanus juveniles. Four months later, the blood and white muscle of these fish were analyzed. The results showed no significant difference in the length-weight relationship (LWR) b value between the large and small A. dabryanus. The levels of serum growth hormone (gh) and insulin-like growth factor 1 (igf1) in the large A. dabryanus were significantly lower than those in the small, whereas the activity levels of Total superoxide dismutase (T-sod) and catalase (cat) were opposite to the results of gh and igf1. A total of 212 and 245 metabolites showed significant changes in the positive and negative polarity mode, respectively. Among 3,308 proteins identified, 69 proteins showed upregulated expression, and 185 proteins showed downregulated expression. These results indicated that the growth advantage of A. dabryanus was closely related to glycolysis, protein synthesis, and antioxidant function.PMID:37559901 | PMC:PMC10407750 | DOI:10.1016/j.isci.2023.107413

J Allergy Clin Immunol. 2023 Aug 7:S0091-6749(23)00980-6. doi: 10.1016/j.jaci.2023.06.030. Online ahead of print.ABSTRACTBACKGROUND: Gestational vitamin D deficiency is implicated in development of respiratory diseases in the offspring, but the mechanism underlying this relationship is unknown.OBJECTIVES: To study the link between gestational vitamin D exposure and childhood asthma phenotypes using maternal blood metabolomics profiling.METHODS: Untargeted blood metabolomic profiles were acquired using liquid chromatography-mass spectrometry at one week postpartum from 672 women in the COPSAC2010 mother-child cohort, and at pregnancy week 32-38 from 779 women in the VDAART mother-child cohort. In COPSAC2010, we employed multivariate models and pathway-enrichment analysis to identify metabolites and pathways associated with gestational vitamin D blood levels and investigated their relationship with development of asthma phenotypes in early childhood. The findings were validated in VDAART and in cellular models.RESULTS: In COPSAC2010, higher vitamin D blood levels at one week postpartum were associated with distinct maternal metabolome perturbations with significant enrichment of the sphingomyelin pathway (p<.01). This vitamin D-related maternal metabolic profile at one week postpartum containing 46 metabolites was associated with decreased risk of recurrent wheeze (Hazard Ratio (HR)=0.92 [95% CI, 0.86-0.98], p=.01) and wheeze exacerbations (HR=0.90 [0.84-0.97], p=.01) at age 0-3 years. The same metabolic profile was similarly associated with decreased risk of asthma/wheeze at age 0-3 in VDAART (OR=0.92 [0.85-0.99], p=0.04). Human bronchial epithelial cells treated with high-dose vitamin D3 showed an increased cytoplasmatic sphingolipid level (p<0.01).CONCLUSION: This exploratory metabolomics study in two independent birth cohorts demonstrates that the beneficial effect of higher gestational vitamin D exposure on offspring respiratory health is characterized by specific maternal metabolic alterations during pregnancy, which involves the sphingomyelin pathway.PMID:37558060 | DOI:10.1016/j.jaci.2023.06.030

J Allergy Clin Immunol. 2023 Aug 7:S0091-6749(23)00982-X. doi: 10.1016/j.jaci.2023.08.001. Online ahead of print.NO ABSTRACTPMID:37558058 | DOI:10.1016/j.jaci.2023.08.001

Chemosphere. 2023 Aug 7:139745. doi: 10.1016/j.chemosphere.2023.139745. Online ahead of print.ABSTRACTNon-targeted and suspect screening analysis is gaining approval across the scientific and regulatory community to monitor the chemical status in the environment and thus environmental quality. These holistic screening analyses provides the means to perform suspect screening and go beyond to discover previously undescribed chemical pollutants in environmental samples. In a case study, we developed and optimized a high-resolution tandem mass spectrometry platform hyphenated with anion exchange chromatography to screen drinking water samples in Denmark. The optimized non-targeted screening method was able to detect anionic and polar compounds and was successfully applied to drinking water from two drinking water facilities. Following a data analysis pipeline optimization, anionic pesticide residues and other environmental contaminants were detected at confidence identification level 1 such as dimethachlor ESA, mecoprop, and dichlorprop in drinking water. In addition to these three substances, it was possible to detect another 1662 compounds, of which 97 were annotated at confidence identification level 2. More research is urgently needed to health risk prioritize the detected substances and to determine their concentrations.PMID:37558003 | DOI:10.1016/j.chemosphere.2023.139745

Brain Behav Immun. 2023 Aug 7:S0889-1591(23)00233-7. doi: 10.1016/j.bbi.2023.08.010. Online ahead of print.ABSTRACTBACKGROUND: Chronic psychological distress is associated with increased risk of cardiovascular disease (CVD) and investigators have posited inflammatory factors may be centrally involved in these relationships. However, mechanistic evidence and molecular underpinnings of these processes remain unclear, and data are particularly sparse among women. This study examined if a metabolite profile linked with distress would be associated with increased CVD risk and inflammation-related risk factors.METHODS: A plasma metabolite-based distress score (MDS) of twenty chronic psychological distress-related metabolites was developed in cross-sectional, 1:1 matched case-control data comprised of 558 women from the Nurses' Health Study (NHS; 279 women with distress, 279 controls). This MDS was then evaluated in two other cohorts: the Women's Health Initiative Observational Cohort (WHI-OS) and the Prevención con Dieta Mediterránea (PREDIMED) trial. We tested the MDS's association with risk of future CVD in each sample and with levels of C-reactive protein (CRP) in the WHI-OS. The WHI-OS subsample included 944 postmenopausal women (472 CHD cases; mean time to event=5.8 years), the PREDIMED subsample included 980 men and women (224 CVD cases, mean time to event=3.1 years).RESULTS: In the WHI-OS, a 1-SD increase in the plasma MDS was associated with a 20% increased incident CHD risk (odds ratio [OR]=1.20, 95% CI: 1.04 - 1.38), adjusting for known CVD risk factors excluding total and HDL cholesterol. This association was attenuated after including total and HDL cholesterol. CRP mediated an average 12.9% (95% CI: 4.9% - 28%, p <10-15) of the total effect of MDS on CHD risk, when adjusting for matching factors. This effect was attenuated after adjusting for known CVD risk factors. Of the metabolites in the MDS, tryptophan and threonine were inversely associated with incident CHD risk in univariate models. In PREDIMED, each one SD increase in the MDS was associated with an OR of 1.19 (95% CI: 1.00 - 1.41) for incident CVD risk, after adjusting all risk factors. Similar associations were observed in men and women. Four metabolites in the MDS were associated with incident CVD risk in PREDIMED in univariate models. Biliverdin and C36:5 phosphatidylcholine (PC) plasmalogen had inverse associations; C16:0 ceramide and C18:0 lysophosphatidylethanolamine(LPE) each had positive associations with CVD risk.CONCLUSIONS: Our study points to molecular alterations that may underlie the association between chronic distress and subsequent risk of cardiovascular disease in adults.PMID:37557964 | DOI:10.1016/j.bbi.2023.08.010

Brain Behav Immun. 2023 Aug 7:S0889-1591(23)00232-5. doi: 10.1016/j.bbi.2023.08.009. Online ahead of print.ABSTRACTThe gut microbiota has been causally linked to cognitive development. We aimed to identify metabolites mediating its effect on cognitive development, and foods or nutrients related to most promising metabolites. Faeces from 5-year-old children (DORIAN-PISAC cohort, including 90 general population families with infants, 42/48 females/males, born in 2011-2014) were transplanted (FMT) into C57BL/6 germ-free mice. Children and recipient mice were stratified by cognitive phenotype, or based on protective metabolites. Food frequency questionnaires were obtained in children. Cognitive measurements in mice included five Y-maze tests until 23 weeks post-FMT, and (at 23 weeks) PET-CT for brain metabolism and radiodensity, and ultrasound-based carotid vascular indices. Children (faeces, urine) and mice (faeces, plasma) metabolome was measured by 1H-NMR spectroscopy, and the faecal microbiota was profiled in mice by 16S rRNA amplicon sequencing. Cognitive scores of children and recipient mice were correlated. FMT-dependent modifications of brain metabolism were observed. Mice receiving FMT from high-cognitive or protective metabolite-enriched children developed superior cognitive-behavioural performance. A panel of metabolites, namely xanthine, hypoxanthine, formate, mannose, tyrosine, phenylalanine, glutamine, was found to mediate the gut-cognitive axis in donor children and recipient mice. Vascular indices partially explained the metabolite-to-phenotype relationships. Children's consumption of legumes, whole-milk yogurt and eggs, and intake of iron, zinc and vitamin D appeared to support protective gut metabolites. Overall, metabolites involved in inflammation, purine metabolism and neurotransmitter synthesis mediate the gut-cognitive axis, and holds promise for screening. The related dietary and nutritional findings offer leads to microbiota-targeted interventions for cognitive protection, with long-lasting effects.PMID:37557963 | DOI:10.1016/j.bbi.2023.08.009

Anal Chem. 2023 Aug 9. doi: 10.1021/acs.analchem.3c02246. Online ahead of print.ABSTRACTMetabolic pathways are regarded as functional and basic components of the biological system. In metabolomics, metabolite set enrichment analysis (MSEA) is often used to identify the altered metabolic pathways (metabolite sets) associated with phenotypes of interest (POI), e.g., disease. However, in most studies, MSEA suffers from the limitation of low metabolite coverage. Random walk (RW)-based algorithms can be used to propagate the perturbation of detected metabolites to the undetected metabolites through a metabolite network model prior to MSEA. Nevertheless, most of the existing RW-based algorithms run on a general metabolite network constructed based on public databases, such as KEGG, without taking into consideration the potential influence of POI on the metabolite network, which may reduce the phenotypic specificities of the MSEA results. To solve this problem, a novel pathway analysis strategy, namely, differential correlation-informed MSEA (dci-MSEA), is proposed in this paper. Statistically, differential correlations between metabolites are used to evaluate the influence of POI on the metabolite network, so that a phenotype-specific metabolite network is constructed for RW-based propagation. The experimental results show that dci-MSEA outperforms the conventional RW-based MSEA in identifying the altered metabolic pathways associated with colorectal cancer. In addition, by incorporating the individual-specific metabolite network, the dci-MSEA strategy is easily extended to disease heterogeneity analysis. Here, dci-MSEA was used to decipher the heterogeneity of colorectal cancer. The present results highlight the clustering of colorectal cancer samples with their cluster-specific selection of differential pathways and demonstrate the feasibility of dci-MSEA in heterogeneity analysis. Taken together, the proposed dci-MSEA may provide insights into disease mechanisms and determination of disease heterogeneity.PMID:37557184 | DOI:10.1021/acs.analchem.3c02246

J Pharm Biomed Anal. 2023 Aug 1;235:115620. doi: 10.1016/j.jpba.2023.115620. Online ahead of print.ABSTRACTFicus species (Moraceae) have been used for nutrition and traditional medicine, and plants from this family are phytochemically abundant and serve as a potential source of natural products. As a result of the inherent complexity of the plant metabolomes and the fact that these Ficus species chemical space has not yet been fully decoded, it is still difficult to characterize their phytochemistry. Therefore, this study, we suggest the use of the molecular networking to elucidate the chemical classes existing in leaves of three Ficus species (F. deltoidei Jack, F. drupacea Thunb and F. sycomorus L.) and highlight the importance of molecular networking in examining their chemotaxonomy . By using computational tools, 90 metabolites were annotated , including phenolic acids, flavonoids, furanocoumarins, fatty acids and terpenoids. Phenolic acids were detected as the main class present in the three studied species. Flavonoids-C-glycosides, flavonoids-O-glycosides and isoflavonoids were mainly present in F. drupacea and F. sycomorus, while furanocoumarins were proposed in F. sycomorus. Vomifoliol-based sesquiterpenes were proposed in F. deltoidei. The chemotaxonomic differentiation agreed with the DNA fingerprinting using SCOT and ISSR markers. F. deltoidei, in particular, had a divergent chemical fingerprint as well as a different genotype. Chemotype differentiation using chemical fingerprints, in conjunction with the proposed genetic markers, creates an effective identification tool for the quality control of the raw materials and products derived from those three Ficus species. As well, F. drupacea exploited the most potent inhibition of H. pylori with MIC of 7.81 µg/ mL compared with clarithromycin. Overall, molecular networking provides a promising approach for the exploration of the chemical space of plant metabolomes and the elucidation of chemotaxonomy.PMID:37557066 | DOI:10.1016/j.jpba.2023.115620