PubMed

Metabolites. 2023 Oct 7;13(10):1057. doi: 10.3390/metabo13101057.ABSTRACTAlcoholic liver disease (ALD) represents a significant global health concern, yet the available treatment options remain limited. Numerous studies have shown that gut microbiota is a critical target for the treatment of ALD. Additionally, there is increasing evidence that host metabolism also plays a crucial role in the development of ALD. Akkermansia muciniphila has been demonstrated to ameliorate experimental ALD through its modulatory effects on the intestinal vascular barrier, enhancement of mucus layer thickness, and promotion of intestinal tight junction proteins. Nevertheless, there is a dearth of studies investigating the impact of A. muciniphila on host metabolism and gut microbiota. Here, C57BL/6 mice were utilized to establish a modified NIAAA model in order to investigate the impact of the oral administration of A. muciniphila during the development of ALD. Furthermore, we employed targeted metabolomics to analyze the serum metabolomic profiles of the mice and 2bRAD-M sequencing to comprehensively examine the underlying mechanisms of the efficacy of A. muciniphila on ALD. Our results illustrated that the oral administration of A. muciniphila alleviated alcohol-induced liver injury in conjunction with encouraged serum levels of ornithine and diminished the elevation of oxalic acid levels induced by alcohol intake. In addition, A. muciniphila also inhibited the proliferation of harmful bacteria, such as Escherichia coli and Helicobacter hepaticus, induced by alcohol consumption while promoting the growth of butyrate-producing and commensal bacteria, including Paramuribaculum intestinale and Bacteroides ovatus. In conclusion, this study suggests that A. muciniphila restores ALD by regulating the gut microbiota, and this corrective effect is associated with alterations in the serum metabolism. Our research supplies a theoretical basis for developing A. muciniphila as an innovative generation of probiotic for preventing and managing ALD.PMID:37887381 | DOI:10.3390/metabo13101057

Metabolites. 2023 Oct 7;13(10):1055. doi: 10.3390/metabo13101055.ABSTRACTWe developed a machine-learning system for the selective diagnostics of adenocarcinoma (AD), squamous cell carcinoma (SQ), and small-cell carcinoma lung (SC) cancers based on their metabolomic profiles. The system is organized as two-stage binary classifiers. The best accuracy for classification is 92%. We used the biomarkers sets that contain mostly metabolites related to cancer development. Compared to traditional methods, which exclude hierarchical classification, our method splits a challenging multiclass task into smaller tasks. This allows a two-stage classifier, which is more accurate in the scenario of lung cancer classification. Compared to traditional methods, such a "divide and conquer strategy" gives much more accurate and explainable results. Such methods, including our algorithm, allow for the systematic tracking of each computational step.PMID:37887380 | DOI:10.3390/metabo13101055

Metabolites. 2023 Oct 5;13(10):1052. doi: 10.3390/metabo13101052.ABSTRACTCellular metabolomics provides insights into the metabolic processes occurring within cells and can help researchers understand how these processes are regulated and how they relate to cellular function, health, and disease. In this technical note, we investigated the effects of solvent evaporation equipment and storage condition on high-coverage cellular metabolomics. We previously introduced a robust CIL LC-MS-based cellular metabolomics workflow that encompasses various steps, including cell harvest, metabolic quenching, cell lysis, metabolite extraction, differential chemical isotope labeling, and LC-MS analysis. This workflow has consistently served as the cornerstone of our collaborative research and service projects. As a core facility catering to users with diverse research needs and financial resources, we have encountered scenarios requiring short-term sample storage. For example, the need often arises to transport samples at room temperature from user sites to our core facility. Herein, we present a study in which we compared different solvent evaporation methods (specifically, the nitrogen blowdown evaporator, SpeedVac concentrator, and lyophilizer) and diverse storage conditions (including dried samples stored in a freezer, samples stored in a freezer with methanol, dried samples stored at room temperature, and samples stored at room temperature with methanol). Our findings indicate that the choice of solvent evaporation equipment did not significantly impact the cellular metabolome. However, we observed a noteworthy change in the metabolome after 7 days of storage when cells were stored with methanol, regardless of whether they were kept at -80 °C or room temperature, in contrast to cells that were dried and frozen. Importantly, we detected no significant alterations in cells that were dried and stored at room temperature. In conclusion, to ensure the production of high-quality CIL LC-MS metabolomics results, we strongly recommend that, in situations where low-temperature storage is not feasible, cell samples should be thoroughly dried before storage or shipment at room temperature.PMID:37887377 | DOI:10.3390/metabo13101052

Metabolites. 2023 Oct 4;13(10):1051. doi: 10.3390/metabo13101051.ABSTRACTThe application of metabolomics to the study of plants is growing because of the current development of analytical techniques. The most commonly used analytical technology driving plant metabolomics studies is Mass Spectrometry (MS) coupled to liquid chromatography (LC). In recent years, Nuclear Magnetic Resonance (NMR) spectroscopy, not requiring a previous chromatographic separation, has been receiving growing attention for metabolite fingerprinting of natural extracts. Herein, an integrated LC-MS and 1H NMR metabolomic approach provided a comprehensive phytochemical characterization of Symphytum anatolicum whole plant, taking into account both primary and specialized metabolites. Moreover, the NMR analyses provided direct quantitative information. Species belonging to the Symphytum genus, known as comfrey, have shown several biological activities including anti-inflammatory, analgesic, hepatoprotective, antifungal, and antibacterial. The LC-MS profile showed the presence of 21 main specialized metabolites, belonging to the classes of flavonoids, phenylpropanoids, salvianols, and oxylipins. The 1H NMR spectrum revealed the occurrence of metabolites including organic acids, phenolics, flavonoids, sugars, and amino acids. A quantitative analysis of these metabolites was performed and their concentration was obtained with respect to the known concentration of TSP, by means of the software package Chenomx which allows quantification of individual components in the NMR spectra. Furthermore, the phenolic content, antioxidant activity, glucosidase, and tyrosinase inhibitory activity of S. anatolicum extract were evaluated. The resulting bioactivity profile suggests how S. anatolicum represents a source of metabolites with health-promoting activity.PMID:37887376 | DOI:10.3390/metabo13101051

Metabolites. 2023 Oct 3;13(10):1050. doi: 10.3390/metabo13101050.ABSTRACTDoliocarpus dentatus is thought to have a wide variety of therapeutic phytochemicals that allegedly improve libido and cure impotence. Although a few biomarkers have been identified with potential antinociceptive and cytotoxic properties, an untargeted mass spectrometry-based metabolomics approach has never been undertaken to identify therapeutic biofingerprints for conditions, such as erectile dysfunction, in men. This study executes a preliminary phytochemical screening of the woody vine of two ecotypes of D. dentatus with renowned differences in therapeutic potential for erectile dysfunction. Liquid chromatography-mass spectrometry-based metabolomics was used to screen for flavonoids, terpenoids, and other chemical classes found to contrast between red and white ecotypes. Among the metabolite chemodiversity found in the ecotype screens, using a combination of GNPS, MS-DIAL, and SIRIUS, approximately 847 compounds were annotated at levels 2 to 4, with the majority of compounds falling under lipid and lipid-like molecules, benzenoids and phenylpropanoids, and polyketides, indicative of the contributions of the flavonoid, shikimic acid, and terpenoid biosynthesis pathways. Despite the extensive annotation, we report on 138 tentative compound identifications of potentially therapeutic compounds, with 55 selected compounds at a level-2 annotation, and 22 statistically significant therapeutic biomarkers, the majority of which were polyphenols. Epicatechin methyl gallate, catechin gallate, and proanthocyanidin A2 had the greatest significant differences and were also relatively abundant among the red and white ecotypes. These putatively identified compounds reportedly act as antioxidants, neutralizing damaging free radicals, and lowering cell oxidative stress, thus aiding in potentially preventing cellular damage and promoting overall well-being, especially for treating erectile dysfunction (ED).PMID:37887375 | DOI:10.3390/metabo13101050

Metabolites. 2023 Oct 2;13(10):1047. doi: 10.3390/metabo13101047.ABSTRACTHepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is the third leading cause of mortality globally. Patients with HCC have a poor prognosis due to the fact that the emergence of symptoms typically occurs at a late stage of the disease. In addition, conventional biomarkers perform suboptimally when identifying HCC in its early stages, heightening the need for the identification of new and more effective biomarkers. Using metabolomics and lipidomics approaches, this study aims to identify serum biomarkers for identification of HCC in patients with liver cirrhosis (LC). Serum samples from 20 HCC cases and 20 patients with LC were analyzed using ultra-high-performance liquid chromatography-Q Exactive mass spectrometry (UHPLC-Q-Exactive-MS). Metabolites and lipids that are significantly altered between HCC cases and patients with LC were identified. These include organic acids, amino acids, TCA cycle intermediates, fatty acids, bile acids, glycerophospholipids, sphingolipids, and glycerolipids. The most significant variability was observed in the concentrations of bile acids, fatty acids, and glycerophospholipids. In the context of HCC cases, there was a notable increase in the levels of phosphatidylethanolamine and triglycerides, but the levels of fatty acids and phosphatidylcholine exhibited a substantial decrease. In addition, it was observed that all of the identified metabolites exhibited a superior area under the receiver operating characteristic (ROC) curve in comparison to alpha-fetoprotein (AFP). The pathway analysis of these metabolites revealed fatty acid, lipid, and energy metabolism as the most impacted pathways. Putative biomarkers identified in this study will be validated in future studies via targeted quantification.PMID:37887372 | DOI:10.3390/metabo13101047

Metabolites. 2023 Oct 1;13(10):1046. doi: 10.3390/metabo13101046.ABSTRACTThe zebra mussel, Dreissena polymorpha, is extensively used as a sentinel species for biosurveys of environmental contaminants in freshwater ecosystems and for ecotoxicological studies. However, its metabolome remains poorly understood, particularly in light of the potential molecular sexual dimorphism between its different tissues. From an ecotoxicological point of view, inter-sex and inter-organ differences in the metabolome suggest variability in responsiveness, which can influence the analysis and interpretation of data, particularly in the case where males and females would be analyzed indifferently. This study aimed to assess the extent to which the molecular fingerprints of functionally diverse tissues like the digestive glands, gonads, gills, and mantle of D. polymorpha can reveal tissue-specific molecular sexual dimorphism. We employed a non-targeted metabolomic approach using liquid chromatography high-resolution mass spectrometry and revealed a significant sexual molecular dimorphism in the gonads, and to a lesser extent in the digestive glands, of D. polymorpha. Our results highlight the critical need to consider inter-sex differences in the metabolome of D. polymorpha to avoid confounding factors, particularly when investigating environmental effects on molecular regulation in the gonads, and to a lesser extent in the digestive glands.PMID:37887371 | DOI:10.3390/metabo13101046

Metabolites. 2023 Sep 26;13(10):1038. doi: 10.3390/metabo13101038.ABSTRACTVolumetric absorptive microsampling (VAMS) has arisen as a relevant tool in biological analysis, offering simplified sampling procedures and enhanced stability. Most of the attention VAMS has received in the past decade has been from pharmaceutical research, with most of the published work employing VAMS targeting drugs or other exogenous compounds, such as toxins and pollutants. However, biomarker analysis by employing blood microsampling has high promise. Herein, a comprehensive review on the applicability of VAMS devices for the analysis of endogenous metabolites/biomarkers was performed. The study presents a full overview of the analysis process, incorporating all the steps in sample treatment and validation parameters. Overall, VAMS devices have proven to be reliable tools for the analysis of endogenous analytes with biological importance, often offering improved analyte stability in comparison with blood under ambient conditions as well as a convenient and straightforward sample acquisition model.PMID:37887363 | DOI:10.3390/metabo13101038

Metabolites. 2023 Sep 26;13(10):1037. doi: 10.3390/metabo13101037.ABSTRACTLung cancer is the leading cause of cancer-related death worldwide. Metabolic reprogramming is a fundamental trait associated with lung cancer development that fuels tumor proliferation and survival. Monitoring such metabolic pathways and their intermediate metabolites can provide new avenues concerning treatment strategies, and the identification of prognostic biomarkers that could be utilized to monitor drug responses in clinical practice. In this review, recent trends in the analytical techniques used for metabolome mapping of lung cancer are capitalized. These techniques include nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and imaging mass spectrometry (MSI). The advantages and limitations of the application of each technique for monitoring the metabolite class or type are also highlighted. Moreover, their potential applications in the analysis of many biological samples will be evaluated.PMID:37887362 | DOI:10.3390/metabo13101037

Metabolites. 2023 Sep 26;13(10):1035. doi: 10.3390/metabo13101035.ABSTRACTMetastatic soft-tissue sarcomas (mSTS) encompass a highly heterogeneous group of rare tumours characterized by different clinical behaviours and outcomes. Currently, prognostic factors for mSTS are very limited, posing significant challenges in predicting patient survival. Within a cohort of 39 mSTS patients undergoing trabectedin treatment, it was remarkable to find one patient who underwent 73 cycles of trabectedin achieving an unforeseen clinical outcome. To identify contributing factors to her exceptional long-term survival, we have explored circulation metabolomics and biohumoral biomarkers to uncover a potential distinct host biochemical phenotype. The long-term survival patient compared with the other mSTS patients exhibited a distinctive metabolic profile characterized by remarkably higher levels of ursodeoxycholic acid (UDCA) derivatives and vitamin D and lower levels of lithocholic acid (LCA) derivatives, as well as reduced levels of inflammatory C-Reactive Protein 4 (C-RP4) biomarker. Despite its exploratory nature, this study reveals a potential association between specific bile acid metabolic profiles and mSTS patients' prognosis. Enhanced clinical understanding of the interplay between bile acid metabolism and disease progression could pave the way for new targeted therapeutic interventions which may improve the overall survival of mSTS patients.PMID:37887360 | DOI:10.3390/metabo13101035

Cells. 2023 Oct 20;12(20):2492. doi: 10.3390/cells12202492.ABSTRACTAxonemal dyneins are highly complex microtubule motors that power ciliary motility. These multi-subunit enzymes are assembled at dedicated sites within the cytoplasm. At least nineteen cytosolic factors are specifically needed to generate dynein holoenzymes and/or for their trafficking to the growing cilium. Many proteins are subject to N-terminal processing and acetylation, which can generate degrons subject to the AcN-end rule, alter N-terminal electrostatics, generate new binding interfaces, and affect subunit stoichiometry through targeted degradation. Here, we have used mass spectrometry of cilia samples and electrophoretically purified dynein heavy chains from Chlamydomonas to define their N-terminal processing; we also detail the N-terminal acetylase complexes present in this organism. We identify four classes of dynein heavy chain based on their processing pathways by two distinct acetylases, one of which is dependent on methionine aminopeptidase activity. In addition, we find that one component of both the outer dynein arm intermediate/light chain subcomplex and the docking complex is processed to yield an unmodified Pro residue, which may provide a setpoint to direct the cytosolic stoichiometry of other dynein complex subunits that contain N-terminal degrons. Thus, we identify and describe an additional level of processing and complexity in the pathways leading to axonemal dynein formation in cytoplasm.PMID:37887336 | DOI:10.3390/cells12202492

Cells. 2023 Oct 16;12(20):2465. doi: 10.3390/cells12202465.ABSTRACTThe blackening of cut carrots causes substantial economic losses to the food industry. Blackening was not observed in carrots that had been stored underground for less than a year, but the susceptibility to blackening increased with the age of the carrots that were stored underground for longer periods. Samples of black, border, and orange tissues from processed carrot batons and slices, prepared under industry standard conditions, were analyzed to identify the molecular and metabolic mechanisms underpinning processing-induced blackening. The black tissues showed substantial molecular and metabolic rewiring and large changes in the cell wall structure, with a decreased abundance of xyloglucan, pectins (homogalacturonan, rhamnogalacturonan-I, galactan and arabinan), and higher levels of lignin and other phenolic compounds when compared to orange tissues. Metabolite profiling analysis showed that there was a major shift from primary to secondary metabolism in the black tissues, which were depleted in sugars, amino acids, and tricarboxylic acid (TCA) cycle intermediates but were rich in phenolic compounds. These findings suggest that processing triggers a release from quiescence. Transcripts encoding proteins associated with secondary metabolism were less abundant in the black tissues, but there were no increases in transcripts associated with oxidative stress responses, programmed cell death, or senescence. We conclude that restraining quiescence release alters cell wall metabolism and composition, particularly regarding pectin composition, in a manner that increases susceptibility to blackening upon processing.PMID:37887309 | DOI:10.3390/cells12202465

Biosensors (Basel). 2023 Oct 5;13(10):916. doi: 10.3390/bios13100916.ABSTRACTThe prevailing form of bacterial infection is within the urinary tract, encompassing a wide array of bacteria that harness the urinary metabolome for their growth. Through their metabolic actions, the chemical composition of the growth medium undergoes modifications as the bacteria metabolize urine compounds, leading to the subsequent release of metabolites. These changes can indirectly indicate the existence and proliferation of bacterial organisms. Here, we investigate the use of an electronic tongue, a powerful analytical instrument based on a combination of non-selective chemical sensors with a partial specificity for data gathering combined with principal component analysis, to distinguish between infected and non-infected artificial urine samples. Three prevalent bacteria found in urinary tract infections were investigated, Escherichia coli, Klebsiella pneumoniae, and Enterococcus faecalis. Furthermore, the electronic tongue analysis was supplemented with 1H NMR spectroscopy and flow cytometry. Bacteria-specific changes in compound consumption allowed for a qualitative differentiation between artificial urine medium and bacterial growth.PMID:37887109 | DOI:10.3390/bios13100916

Biosensors (Basel). 2023 Sep 26;13(10):907. doi: 10.3390/bios13100907.ABSTRACTBiological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as nanotechnology, microstrip cavity resonance measurement, etc. This article reviews single-cell isolation and sorting techniques, such as the micropipette separation method, separation and sorting system (dual electrophoretic array system), DEPArray sorting system (dielectrophoretic array system), cell selector sorting system, and microfluidic and valve devices, and discusses their respective advantages and disadvantages. Furthermore, it summarizes common single-cell electrical manipulations, such as single-cell amperometry (SCA), electrical impedance sensing (EIS), impedance flow cytometry (IFC), cell-based electrical impedance (CEI), microelectromechanical systems (MEMS), and integrated microelectrode array (IMA). The article also enumerates the application and significance of single-cell electrochemical analysis from the perspectives of CTC liquid biopsy, recombinant adenovirus, tumor cells like lung cancer DTCs (LC-DTCs), and single-cell metabolomics analysis. The paper concludes with a discussion of the current limitations faced by single-cell analysis techniques along with future directions and potential application scenarios.PMID:37887100 | DOI:10.3390/bios13100907

Biology (Basel). 2023 Oct 11;12(10):1326. doi: 10.3390/biology12101326.ABSTRACTThere is a growing demand for molecules of natural origin for biocontrol and biostimulation, given the current trend away from synthetic chemical products. Leachates extracted from plantain stems were obtained after biodegradation of the plant material. To characterize the leachate, quantitative determinations of nitrogen, carbon, phosphorus, and cations (K+, Ca2+, Mg2+, Na+), Q2/4, Q2/6, and Q4/6 absorbance ratios, and metabolomic analysis were carried out. The potential role of plantain leachates as fungicide, elicitor of plant defense, and/or plant biostimulant was evaluated by agar well diffusion method, phenotypic, molecular, and imaging approaches. The plant extracts induced a slight inhibition of fungal growth of an aggressive strain of Colletotrichum gloeosporioides, which causes anthracnose. Organic compounds such as cinnamic, ellagic, quinic, and fulvic acids and indole alkaloid such as ellipticine, along with some minerals such as potassium, calcium, and phosphorus, may be responsible for the inhibition of fungal growth. In addition, jasmonic, benzoic, and salicylic acids, which are known to play a role in plant defense and as biostimulants in tomato, were detected in leachate extract. Indeed, foliar application of banana leachate induced overexpression of LOXD, PPOD, and Worky70-80 genes, which are involved in phenylpropanoid metabolism, jasmonic acid biosynthesis, and salicylic acid metabolism, respectively. Leachate also activated root growth in tomato seedlings. However, the main impact of the leachate was observed on mature plants, where it caused a reduction in leaf area and fresh weight, the remodeling of stem cell wall glycopolymers, and an increase in the expression of proline dehydrogenase.PMID:37887036 | DOI:10.3390/biology12101326

Biology (Basel). 2023 Sep 30;12(10):1298. doi: 10.3390/biology12101298.ABSTRACTThis review discusses the transformative potential of integrating multi-omics data and artificial intelligence (AI) in advancing horticultural research, specifically plant phenotyping. The traditional methods of plant phenotyping, while valuable, are limited in their ability to capture the complexity of plant biology. The advent of (meta-)genomics, (meta-)transcriptomics, proteomics, and metabolomics has provided an opportunity for a more comprehensive analysis. AI and machine learning (ML) techniques can effectively handle the complexity and volume of multi-omics data, providing meaningful interpretations and predictions. Reflecting the multidisciplinary nature of this area of research, in this review, readers will find a collection of state-of-the-art solutions that are key to the integration of multi-omics data and AI for phenotyping experiments in horticulture, including experimental design considerations with several technical and non-technical challenges, which are discussed along with potential solutions. The future prospects of this integration include precision horticulture, predictive breeding, improved disease and stress response management, sustainable crop management, and exploration of plant biodiversity. The integration of multi-omics and AI holds immense promise for revolutionizing horticultural research and applications, heralding a new era in plant phenotyping.PMID:37887008 | DOI:10.3390/biology12101298

Biology (Basel). 2023 Sep 28;12(10):1294. doi: 10.3390/biology12101294.ABSTRACTParkinson's disease (PD) is one of the most common neurodegenerative disorders. The management of PD is a challenging aspect for general physicians and neurologists. It is characterized by the progressive loss of dopaminergic neurons. Impaired α-synuclein secretion and dopamine release may cause mitochondrial dysfunction and perturb energy metabolism, subsequently altering the activity and survival of dopaminergic neurons, thus perpetuating the neurodegenerative process in PD. While the etiology of PD remains multifactorial, emerging research indicates a crucial role of circadian dysfunction in its pathogenesis. Researchers have revealed that circadian dysfunction and sleep disorders are common among PD subjects and disruption of circadian rhythms can increase the risk of PD. Hence, understanding the findings of circadian biology from translational research in PD is important for reducing the risk of neurodegeneration and for improving the quality of life. In this review, we discuss the intricate relationship between circadian dysfunction in cellular metabolism and PD by summarizing the evidence from animal models and human studies. Understanding the metabolic basis of circadian dysfunction in PD may shed light on novel therapeutic approaches to restore circadian rhythm, preserve dopaminergic function, and ameliorate disease progression. Further investigation into the complex interplay between circadian rhythm and PD pathogenesis is essential for the development of targeted therapies and interventions to alleviate the burden of this debilitating neurodegenerative disorder.PMID:37887004 | DOI:10.3390/biology12101294

Anal Chem. 2023 Oct 27. doi: 10.1021/acs.analchem.3c03672. Online ahead of print.ABSTRACTTechnologies assessing the lipidomics, genomics, epigenomics, transcriptomics, and proteomics of tissue samples at single-cell resolution have deepened our understanding of physiology and pathophysiology at an unprecedented level of detail. However, the study of single-cell spatial metabolomics in undecalcified bones faces several significant challenges, such as the fragility of bone, which often requires decalcification or fixation leading to the degradation or removal of lipids and other molecules. As such, we describe a method for performing mass spectrometry imaging on undecalcified spine that is compatible with other spatial omics measurements. In brief, we use fresh-frozen rat spines and a system of carboxyl methylcellulose embedding, cryofilm, and polytetrafluoroethylene rollers to maintain tissue integrity while avoiding signal loss from variations in laser focus and artifacts from traditional tissue processing. This reveals various tissue types and lipidomic profiles of spinal regions at 10 μm spatial resolutions using matrix-assisted laser desorption/ionization mass spectrometry imaging. We expect this method to be adapted and applied to the analysis of the spinal cord, shedding light on the mechanistic aspects of cellular heterogeneity, development, and disease pathogenesis underlying different bone-related conditions and diseases. This study furthers the methodology for high spatial metabolomics of spines and adds to the collective efforts to achieve a holistic understanding of diseases via single-cell spatial multiomics.PMID:37886878 | DOI:10.1021/acs.analchem.3c03672

Br J Nutr. 2023 Oct 27:1-42. doi: 10.1017/S0007114523002490. Online ahead of print.ABSTRACTMetabolomics has been utilized in epidemiological studies to investigate biomarkers of nutritional status and metabolism in relation to non-communicable diseases. However, little is known about the effect of prandial status on several biomarker concentrations. Therefore, the aim of this intervention study was to investigate the effect of a standardized breakfast meal followed by food abstinence for 24 h on serum concentrations of amino acids, one-carbon metabolites, and B-vitamin biomarkers. 34 healthy subjects (18 males and 16 females) aged 20-30 years were served a breakfast meal (∼500 kcal) after which they consumed only water for 24 hours. Blood samples were drawn before, and at 13 standardized timepoints after the meal. Circulating concentrations of most amino acids and metabolites linked to one-carbon metabolism peaked within the first three hours after the meal. The branched-chain amino acids steadily increased from six or eight hours after the meal, while proline decreased in the same period. Homocysteine and cysteine concentrations immediately decreased after the meal but steadily increased from three and four hours until 24 hours. Flavin mononucleotide and riboflavin fluctuated immediately after the meal but increased from 6 hours, while folate increased immediately after the meal and remained elevated during the 24 hours. Our findings indicate that accurate reporting of time since last meal is crucial when investigating concentrations of certain amino acids and one-carbon metabolites. Our results suggest a need for caution when interpretating studies which utilize such biomarkers, but do not strictly control for time since the last meal.PMID:37886826 | DOI:10.1017/S0007114523002490

J Gerontol A Biol Sci Med Sci. 2023 Oct 27:glad249. doi: 10.1093/gerona/glad249. Online ahead of print.ABSTRACTMultimorbidity is the simultaneous presence of two or more chronic conditions. Metabolomics could identify biomarkers potentially related to multimorbidity. We aimed to identify groups of biomarkers and their association with different multimorbidity patterns. Cross-sectional analyses were conducted within the Seniors-ENRICA-2 cohort in Spain, with information from 700 individuals aged ≥65 years. Biological samples were analyzed using high-throughput proton nuclear magnetic resonance metabolomics. Biomarkers groups were identified with exploratory factor analysis, and multimorbidity was classified into three types: cardiometabolic, neuropsychiatric, and musculoskeletal. Logistic regression was used to estimate the association between biomarkers groups and multimorbidity patterns, after adjusting for potential confounders including sociodemographics, lifestyle, and body mass index. Three factors were identified: the "lipid metabolism" mainly reflected biomarkers related to lipid metabolism, such as very-low-density lipoprotein and low-density lipoprotein cholesterol; the "high-density lipoprotein cholesterol" mainly included high-density lipoprotein cholesterol subclasses and other lipids not included in the first factor; and the "amino acid/glycolysis/ketogenesis", composed of some amino acids, glycolysis-related metabolites and ketone bodies. Higher scores in the "lipid metabolism" factor were associated with a higher likelihood of cardiometabolic multimorbidity, odds ratio for tertile 3 vs. tertile 1 was 1.79 (95% confidence interval: 1.17-2.76). The "high-density lipoprotein cholesterol" factor was associated with lower odds of cardiometabolic multimorbidity [0.51 (0.32-0.82)], and the "amino acid/glycolysis/ketogenesis" factor was associated with more frequent cardiometabolic multimorbidity [1.85 (1.18-2.90)]. Different metabolomic biomarkers are associated with different multimorbidity patterns, therefore multiple biomarker measurements are needed for a complete picture of the molecular mechanisms of multimorbidity.PMID:37886823 | DOI:10.1093/gerona/glad249