Human Metabolome Research Articles

Metabolomic interference induced by short-chain chlorinated paraffins in human normal hepatic cells

Short-chain chlorinated paraffins (SCCPs) are an emerging class of persistent organic pollutants (POPs) that are widely detected in environmental matrices and human samples. Because of their environmental persistence, long-range transport potential, bioaccumulation potential, and biotoxicity, SCCPs pose a significant threat to human health. In this study, metabolomics technology was applied to reveal the metabolomic interference in human normal hepatic (L02) cells after exposure to low (1 μg/L), moderate (10 μg/L), and high (100 μg/L) doses of SCCPs. Principal component analysis (PCA) and metabolic effect level index (MELI) values showed that all three SCCP doses caused notable metabolic perturbations in L02 cells. A total of 72 metabolites that were annotated by MS/MS and matched with the experimental spectra in the Human Metabolome Database (HMDB) or validated by commercially available standards were selected as differential metabolites (DMs) across all groups. The low-dose exposure group shared 33 and 36 DMs with the moderate- and high-dose exposure groups, respectively. The moderate-dose exposure group shared 46 DMs with the high-dose exposure group. In addition, 33 DMs were shared among the three exposure groups. Among the 72 DMs, 9, 9, and 45 metabolites participated in the amino acid, nucleotide, and lipid metabolism pathways, respectively. The results of pathway enrichment analysis showed that the most relevant metabolic pathways affected by SCCPs were the lipid metabolism, fatty acid β-oxidation, and nucleotide metabolism pathways, and that compared with low-dose exposure, moderate- and high-dose SCCP exposures caused more notable perturbations of these metabolic pathways in L02 cells. Exposure to SCCPs perturbed glycerophospholipid and sphingolipid metabolism. Significant alterations in the levels of phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins indicated SCCP-induced biomembrane damage. SCCPs inhibited fatty acid β-oxidation by decreasing the levels of short- and medium-chain acylcarnitines in L02 cells, indicating that the energy supplied by fatty acid oxidation was reduced in these cells. Furthermore, compared with low- and moderate-dose SCCPs, high-dose SCCPs produced a significantly stronger inhibition of fatty acid β-oxidation. In addition, SCCPs perturbed nucleotide metabolism. The higher hypoxanthine levels observed in L02 cells after SCCP exposures indicate that SCCPs may induce several adverse effects, including hypoxia, reactive oxygen species production, and mutagenesis in L02 cells.

Identification of primary metabolites in fungal species of Trichophyton mentagrophyte and Trichophyton rubrum by NMR spectroscopy.

Superficial mycoses are fungal infections limited to the outermost layers of the skin and its appendages. The chief causative agents of these mycoses are dermatophytes and yeasts. The diagnosis of dermatophytosis can be made by direct mycological examination with potassium hydroxide (10%-30%) of biological material obtained from patients with suspected mycosis, providing results more rapid than fungal cultures, which may take days or weeks. This information, together with clinical history and laboratory diagnosis, ensures that the appropriate treatment is initiated promptly. However, false negative results are obtained in 5%-15%, by conventional methods of diagnosis of dermatophytosis. To study the metabolic profiles of the commonly occurring dermatophytes by NMR spectroscopy. We have used 1D and 2D Nuclear Magnetic Resonance (NMR) experiments along with Human Metabolome Database (HMDB) and Chenomx database search for identification of primary metabolites in the methanol extract of two fungal species: Trichophyton mentagrophyte (T. mentagrophyte) and Trichophyton rubrum (T. rubrum). Both standard strains and representative number of clinical isolates of these two species were investigated. Further, metabolic profiles obtained were analysed using multivariate analysis. We have identified 23 metabolites in the T. mentagrophyte and another 23 metabolites in T. rubrum. Many important metabolites like trehalose, proline, mannitol, acetate, GABA and several other amino acids were detected, which provide the necessary components for fungal growth and metabolism. Altered metabolites were defined between Trichophyton mentagrophyte and T. rubrum strains. We have detected many metabolites in the two fungal species T. mentagrophyte and T. rubrum by using NMR spectroscopy. NMR spectroscopy provides a holistic snapshot of the metabolome of an organism. Key metabolic differences were identified between the two fungal strains. We need to perform more studies on metabolite profiling of the samples from these species for their rapid diagnosis and prompt treatment.

The association between hydration state and the metabolism of phospholipids and amino acids among young adults: a metabolomic analysis

BackgroundWater is vital for humans' survival and general health, which is involved in various metabolic activities. ObjectivesThe aim of this study was to investigate the variation in urine metabolome and associated metabolic pathways among people with different hydration states. MethodsA metabolomic analysis was conducted using 24-h urine samples collected during a cross-sectional study on fluid intake behavior from December 9 to 11, 2021, in Hebei, China. Subjects were divided into the optimal hydration (OH, ≤500 mOsm/kg, n = 21), middle hydration (500–800 mOsm/kg, n = 33), and hypohydration groups (HH, >800 mOsm/kg, n = 13) based on the 3-d average 24-h urine osmolality. Collected 24-h urine samples from 67 subjects (43 males and 34 females) were analyzed for urine metabolome using liquid chromatography-MS. ResultsThe untargeted metabolomic analysis yielded 1055 metabolites by peak intensities. Integrating the results of the orthogonal projections to latent structures discriminant analysis and fold change test, 115 differential metabolites between the OH and HH groups, including phospholipids (PLs) and lysophospholipids, were identified. Among the 115 metabolites identified as differential metabolites, 85 were recorded by the Human Metabolome Database and uploaded to the Kyoto Encyclopedia of Genes and Genomes databases for pathway analysis. Twenty-one metabolic pathways were recognized. Phenylalanine metabolism (0.50, P = 0.007), phenylalanine, tyrosine, and tryptophan biosynthesis (0.50, P = 0.051), glycerophospholipid metabolism (0.31, P < 0.001), sphingolipid metabolism (0.27, P = 0.029), and cysteine and methionine metabolism (0.10, P = 0.066) had the leading pathway impacts. ConclusionsWe found variations in the urinary PLs and amino acids among subjects with different hydration states. Pathways associated with these differential metabolites could further impact various physiologic and pathologic functions. A more comprehensive and in-depth investigation of the physiologic and pathologic impact of the hydration state and the underlying mechanisms to elucidate and advocate optimal fluid intake habits is needed.This trial was registered at Chinese Clinical Trial Registry as ChiCTR2100045268.

Anti-Shigella and antioxidant-based screening of some Cameroonian medicinal plants, UHPLC-LIT-MS/MS fingerprints, and prediction of pharmacokinetic and drug-likeness properties of identified chemicals.

Ethnopharmacological relevanceShigella infection is a public health problem responsible for approximately 700,000 deaths annually. The management of this disease is impaired by the emergence of multidrug-resistant Shigella species, highlighting the urgent need to search for alternative treatment options. In this regard, investigating medicinal plants traditionally used for the treatment of dysentery, diarrheal infections, and/or associated symptoms in endemic regions might provide an opportunity to identify phytochemicals that could be further used as a basis for the development of future anti-shigella drug candidates. Aim of the studyThis study was designed to investigate the anti-shigella and antioxidant-based ethnopharmacological potency of some Cameroonian medicinal plants with an emphasis on pharmacokinetic properties of the identified chemical pharmacophore. Materials and methodsBriefly, plant species were selected and collected based on their ethnopharmacological uses and information reported in the literature. Crude aqueous, ethanolic, methanolic, and hydroethanolic (30:70, v/v) extracts from these plants were prepared and then screened for their anti-Shigella activity against four Shigella strains and cytotoxicity against Vero and Raw cell lines using microdilution and resazurin-based methods, respectively. The antioxidant activities of potent extracts were evaluated using DPPH, ABTS, NO, and FRAP scavenging assays. The chemical profile of potent extracts was performed using the UHPLC-LIT-MS/MS and the pharmacokinetic properties, druglikeness, and likely molecular targets of the chemical scaffolds identified were predicted using SwissADME and SwissTargetPredictor. ResultsThirty-nine (39) plants belonging to 26 plant families were harvested. Out of the 228 extracts tested, 18 extracts originating from 6 plants (15.38 %) were active (MICs 250–1000 μg/mL) and nontoxic toward Vero (CC50 129.25–684.55 μg/mL) and Raw cell lines (CC50 336.20 to >1000 μg/mL). Six potent extracts from the two plants exhibited moderate to potent DPPH (SC50 8.870–54.410 μg/mL), ABTS (SC50 12.020–27.36 μg/mL), and NO (SC50 0.02–195.85 μg/mL) scavenging activities. Later, these extracts showed interesting ferric iron-reducing power (1.28–12.14 μg equivalent NH2OH/g of extract). The shortest onset of action time (4 and 6 h) observed following inhibition kinetics studies was observed with extracts BFSHE, PMSE, and PMSM. The UHPLC-LIT-MS/MS and some databases (Mass Spectral Library (NIST 14), Human Metabolome Database (HMD), MassBank, SuperNatural 3.0, The Food Database (FooDB), and Chemical Entities of Biological Interest (ChEBI)) allowed the annotation of 18 and 17 metabolites in the extracts from stem bark of P. macrophylla and B. ferruginea respectively. Pharmacokinetic prediction of these chemicals showed that compound 6 (4,6a-bis(Hydroxymethyl)-9a-methyl-3-oxo-1a,1b,3,5,6,6a,7a,9a-octahydrobis (oxireno)[2′,3':5,6; 2″,3'':9,10]cyclodeca[1,2-b]furan-5-yl methacrylate), compound 8 (Corynoxeine), and compounds 35 (Stachybotrydial acetate) demonstrated acceptable druglike and pharmacokinetic properties and might act through inhibition of kinase, transferase, protease, oxidoreductase, and family AG protein-linked receptors. ConclusionThe findings from this investigation demonstrated that Cameroonian medicinal plants are suitable reservoirs of anti-Shigella and antioxidant agents with good drug candidate properties.

Metabolomic insights into the therapeutic mechanisms of costus (Saussurea costus (Falc.) Lipsch.) root extract in propylthiouracil-induced hypothyroidism rat model

Ethnopharmacological relevanceSaussurea costus (Falc.) Lipschitz. is one of the most reputed medicinal plants as a traditional medicine in the Arab and Middle East regions in the treatment of thyroid disorders, however, more investigations are needed to fully understand its effectiveness and mechanism of action. Aim of the studyThe primary objective of the study was to assess the impact of Saussurea costus (COST) on the metabolic profiles of propylthiouracil (PTU)-induced hypothyroidism in rats. This involves a comprehensive examination of serum metabolites using UPLC/QqQ-MS analysis aiming to identify differential metabolites, elucidate underlying mechanisms, and evaluate the potential pharmacological effect of COST in restoring metabolic homeostasis. Materials and methodsHypothyroidism was induced in female Sprague-Dawley rats by oral administration of propylthiouracil (PTU). UPLC/QqQ MS analysis of serum samples from normal, PTU, and PTU + COST rats was utilized for annotation of intrinsic metabolites with the aid of online Human metabolome database (HMDB) and extensive literature surfing. Multivariate statistical analyses, including orthogonal partial least squares discriminant analysis (OPLS-DA), discerned variations between the different groups. Serum levels of T3, T4 and TSH in addition to arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) levels in thyroid gland tissues; Phospholipase A2 group IIA (PLA2G2A), and lipoprotein lipase (LPL) in liver tissues were assessed by specific ELISA kits. Gene expression for key proteins of the primary evolved pathwayswere quantified by one-step qRT-PCR technique. Histopathological evaluation of thyroid gland tissue was performed by an investigator blinded to the experimental group using light microscope. ResultsDistinct clustering in multivariate statistical analysis models indicated significant variations in serum chemical profiles among normal, disease, and treated groups. VIP values guided the selection of differential metabolites, revealing significant changes in metabolite concentrations. Subsequent to COST treatment, 43 differential intrinsic metabolites exhibited a notable tendency to revert towards normal levels. Annotated metabolites, such as lysophosphatidylcholine (LPC), L-acetylcarnitine, gamma-glutamylserine, and others, showed differential regulation in response to PTU and subsequent S. costus treatment. Notably, 21 metabolites were associated with polyunsaturated fatty acids (PUFAs) biosynthesis, arachidonic acid (ARA) metabolism, and glycerophospholipid metabolism exhibited significant changes on conducting metabolic pathway analysis. ConclusionsCOST improves PTU-induced hypothyroidism by regulating biosynthesis of PUFAs signified by n-3/n-6, ARA and glycerophospholipid metabolism. The study provides us a novel mechanism to explain the improvement of hypothyroidism and associated dyslipidemia by COST, depicts a metabolic profile of hypothyroidism, and gives us another point cut for further exploring the biomarkers and pathogenesis of hypothyroidism.

SperMD: the expression atlas of sperm maturation

The impairment of sperm maturation is one of the major pathogenic factors in male subfertility, a serious medical and social problem affecting millions of global couples. Regrettably, the existing research on sperm maturation is slow, limited, and fragmented, largely attributable to the lack of a global molecular view. To fill the data gap, we newly established a database, namely the Sperm Maturation Database (SperMD, http://bio-add.org/SperMD). SperMD integrates heterogeneous multi-omics data (170 transcriptomes, 91 proteomes, and five human metabolomes) to illustrate the transcriptional, translational, and metabolic manifestations during the entire lifespan of sperm maturation. These data involve almost all crucial scenarios related to sperm maturation, including the tissue components of the epididymal microenvironment, cell constituents of tissues, different pathological states, and so on. To the best of our knowledge, SperMD could be one of the limited repositories that provide focused and comprehensive information on sperm maturation. Easy-to-use web services are also implemented to enhance the experience of data retrieval and molecular comparison between humans and mice. Furthermore, the manuscript illustrates an example application demonstrated to systematically characterize novel gene functions in sperm maturation. Nevertheless, SperMD undertakes the endeavor to integrate the islanding omics data, offering a panoramic molecular view of how the spermatozoa gain full reproductive abilities. It will serve as a valuable resource for the systematic exploration of sperm maturation and for prioritizing the biomarkers and targets for precise diagnosis and therapy of male subfertility.

Metabolomic signature between diabetic and non-diabetic obese patients: A protocol for systematic review.

Type 2 diabetes mellitus (T2DM) is a chronic and progressive condition defined by hyperglycemia caused by abnormalities in insulin production, insulin receptor sensitivity, or both. Several studies have revealed that higher body mass index (BMI) is associated with increasing risk of developing diabetes. In this study, we perform a protocol for systematic review to explore metabolite biomarkers that could be used to identify T2DM in obese subjects. The protocol of this review was registered in PROSPERO (CRD42023405518). Three databases, EMBASE, PubMed, and Web of Science were selected to collect potential literature from their inceptions to July December 2023. Data for collection will include title, authors, study subjects, publication date, sample size, detection and analytical platforms, participant characteristics, biological samples, confounding factors, methods of statistical analysis, the frequency and directions of changes in potential metabolic biomarkers, and major findings. Pathway analysis of differential metabolites will be performed with MetaboAnalyst 5.0 based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Human Metabolome Database. The results of this systematic review will be published in a peer-reviewed journal. This systematic review will summarize the potential biomarkers and metabolic pathways to provide a new reference for the prevention and treatment of T2DM in obese subjects.

Integrative polygenic analysis of the protective effects of fatty acid metabolism on disease as modified by obesity.

Dysregulation of fatty acid metabolites can play a crucial role in the progression of complex diseases, such as cardiovascular disease, digestive diseases, and metabolic diseases. Metabolites can have either protective or risk effects on a disease; however, the details of such associations remain contentious. In this study, we demonstrate an integrative PheWAS approach to establish high confidence, causally suggestive of metabolite-disease associations for three fatty acid metabolites, namely, omega-3 fatty acids, omega-6 fatty acids, and docosahexaenoic acid, for 1,254 disease endpoints. Metabolite-disease associations were established if there was a concordant direction of effect and significance for metabolite level and genetic risk score for the metabolite. There was enrichment for metabolite associations with diseases of the respiratory system for omega-3 fatty acids, diseases of the circulatory system and endocrine system for omega-6 fatty acids, and diseases of the digestive system for docosahexaenoic acid. Upon performing Mendelian randomization on a subset of the outcomes, we identified 3, 6, and 15 significant diseases associated with omega-3 fatty acids, omega-6 fatty acids, and docosahexaenoic acid, respectively. We then demonstrate a class of prevalence-risk relationships indicative of (de)canalization of disease under high and low fatty acid metabolite levels. Finally, we show that the interaction between the metabolites and obesity demonstrates that the degree of protection afforded by fatty acid metabolites is strongly modulated by underlying metabolic health. This study evaluated the disease architectures of three polyunsaturated fatty acids (PUFAs), which were validated by several PheWAS modes of support. Our results not only highlight specific diseases associated with each metabolite but also disease group enrichments. In addition, we demonstrate an integrative PheWAS methodology that can be applied to other components of the human metabolome or other traits of interest. The results of this study can be used as an atlas to cross-compare genetic with non-genetic disease associations for the three PUFAs investigated. The findings can be explored through our R shiny app at https://pufa.biosci.gatech.edu.

Association between human blood metabolome and the risk of delirium: a Mendelian Randomization study.

Delirium significantly contributes to both mortality and morbidity among hospitalized older adults. Furthermore, delirium leads to escalated healthcare expenditures, extended hospital stays, and enduring cognitive deterioration, all of which are acknowledged detrimental outcomes. Nonetheless, the current strategies for predicting and managing delirium remain constrained. Our aim was to employ Mendelian randomization (MR) to investigate the potential causal relationship between metabolites and delirium, as well as to identify potential therapeutic targets. We identified 129 distinct blood metabolites from three genome-wide association studies (GWASs) conducted on the metabolome, involving a total of 147,827 participants of European descent. Genetic information pertaining to delirium was sourced from the ninth iteration of the Finngen Biobank, encompassing 359,699 individuals of Finnish ancestry. We conducted MR analyses to evaluate the connections between blood metabolites and delirium. Additionally, we extended our analysis to encompass the entire phenome using MR, aiming to uncover potential on-target consequences resulting from metabolite interventions. In our investigation, we discovered three metabolites serving as causal mediators in the context of delirium: clinical low density lipoprotein cholesterol (LDL-C) (odds ratio [OR]: 1.47, 95% confidence interval [CI]: 1.25-1.73, p = 3.92 x 10-6), sphingomyelin (OR: 1.47, 95% CI: 1.25-1.74, p = 5.97 x 10-6), and X-11593-O-methylascorbate (OR: 0.21, 95% CI: 0.10-0.43, p = 1.86 x 10-5). Furthermore, utilizing phenome-wide MR analysis, we discerned that clinical LDL-C, sphingomyelin, and O-methylascorbate not only mediate delirium susceptibility but also impact the risk of diverse ailments. (1) Limited representation of the complete blood metabolome, (2) reliance on the PheCode system based on hospital diagnoses may underrepresent conditions with infrequent hospital admissions, and (3) limited to European ancestry. The genetic prediction of heightened O-methylascorbate levels seems to correspond to a diminished risk of delirium, in contrast to the association of elevated clinical LDL-C and sphingomyelin levels with an amplified risk. A comprehensive analysis of side-effect profiles has been undertaken to facilitate the prioritization of drug targets. Notably, O-methylascorbate emerges as a potentially auspicious target for mitigating and treating delirium, offering the advantage of lacking predicted adverse side effects.

The Urinary Metabolome of Newborns with Perinatal Complications.

Maternal pathological conditions such as infections and chronic diseases, along with unexpected events during labor, can lead to life-threatening perinatal outcomes. These outcomes can have irreversible consequences throughout an individual's entire life. Urinary metabolomics can provide valuable insights into early physiological adaptations in healthy newborns, as well as metabolic disturbances in premature infants or infants with birth complications. In the present study, we measured 180 metabolites and metabolite ratios in the urine of 13 healthy (hospital-discharged) and 38 critically ill newborns (admitted to the neonatal intensive care unit (NICU)). We used an in-house-developed targeted tandem mass spectrometry (MS/MS)-based metabolomic assay (TMIC Mega) combining liquid chromatography (LC-MS/MS) and flow injection analysis (FIA-MS/MS) to quantitatively analyze up to 26 classes of compounds. Average urinary concentrations (and ranges) for 167 different metabolites from 38 critically ill NICU newborns during their first 24 h of life were determined. Similar sets of urinary values were determined for the 13 healthy newborns. These reference data have been uploaded to the Human Metabolome Database. Urinary concentrations and ranges of 37 metabolites are reported for the first time for newborns. Significant differences were found in the urinary levels of 44 metabolites between healthy newborns and those admitted at the NICU. Metabolites such as acylcarnitines, amino acids and derivatives, biogenic amines, sugars, and organic acids are dysregulated in newborns with bronchopulmonary dysplasia (BPD), asphyxia, or newborns exposed to SARS-CoV-2 during the intrauterine period. Urine can serve as a valuable source of information for understanding metabolic alterations associated with life-threatening perinatal outcomes.

Human Urinary Metabolomics as Biomarkers in Tobacco Users: A Systematic Review.

Urine as a biofluid has been rarely used as a diagnostic fluid in oral diseases. The article aims to systematically review the utility of human urinary carcinogen metabolites as an approach for obtaining important information about tobacco and cancer. The following article reviews the use of urine and its metabolites as biomarkers in various lesions of the oral cavity including oral squamous cell carcinoma and as a screening method in evaluating tobacco and its components. A bibliographic comprehensive search was carried out in the main databases: PUBMED, SciELO, Google Scholar, VHL, and LILACS for articles that were published from 1985 to 2020. The inclusion criteria were "urinary metabolites," "oral cancer/HNSCC," "body fluids," "tobacco," and "metabolomics." A total of 55 articles were collected which included laboratory studies, systematic reviews, and literature of urinary metabolites in tobacco users. Most of the studies carried out show accurate results with high sensitivity of urinary metabolite biomarkers in individuals with tobacco-based habits and lesions caused by them. The review indicates that urinary metabolite analysis demonstrates its applicability for the diagnosis and prognosis of disease. Urine is a remarkable and useful biofluid for routine testing and provides an excellent resource for the discovery of novel biomarkers, with an advantage over tissue biopsy samples due to the ease and less invasive nature of collection.

In utero exposures to perfluoroalkyl substances and the human fetal liver metabolome in Scotland: a cross-sectional study

Perfluoroalkyl and polyfluoroalkyl substances are classed as endocrine disrupting compounds but continue to be used in many products such as firefighting foams, flame retardants, utensil coatings, and waterproofing of food packaging. Perfluoroalkyl exposure aberrantly modulates lipid, metabolite, and bile acid levels, increasing susceptibility to onset and severity of metabolic diseases, such as diabetes and metabolic dysfunction-associated steatotic liver disease. To date, most studies in humans have focused on perfluoroalkyl-exposure effects in adults. In this study we aimed to show if perfluoroalkyls are present in the human fetal liver and if they have metabolic consequences for the human fetus. In this cross-sectional study, human fetal livers from elective termination of pregnancies at the Aberdeen Pregnancy Counselling Service, Aberdeen, UK, were analysed by both targeted (bile acids and perfluoroalkyl substances) and combined targeted and untargeted (lipids and polar metabolites) mass spectrometry based metabolomic analyses, as well as with RNA-Seq. Only fetuses from normally progressing pregnancies (determined at ultrasound scan before termination), terminated for non-medical reasons, from women older than 16 years, fluent in English, and between 11 and 21 weeks of gestation were collected. Women exhibiting considerable emotional distress or whose fetuses had anomalies identified at ultrasound scan were excluded. Stringent bioinformatic and statistical methods such as partial correlation network analysis, linear regression, and pathway analysis were applied to this data to investigate the association of perfluoroalkyl exposure with hepatic metabolic pathways. Fetuses included in this study were collected between Dec 2, 2004, and Oct 27, 2014. 78 fetuses were included in the study: all 78 fetuses were included in the metabolomics analysis (40 female and 38 male) and 57 fetuses were included in the RNA-Seq analysis (28 female and 29 male). Metabolites associated with perfluoroalkyl were identified in the fetal liver and these varied with gestational age. Conjugated bile acids were markedly positively associated with fetal age. 23 amino acids, fatty acids, and sugar derivatives in fetal livers were inversely associated with perfluoroalkyl exposure, and the bile acid glycolithocholic acid was markedly positively associated with all quantified perfluoroalkyl. Furthermore, 7α-hydroxy-4-cholesten-3-one, a marker of bile acid synthesis rate, was strongly positively associated with perfluoroalkyl levels and was detectable as early as gestational week 12. Our study shows direct evidence for the in utero effects of perfluoroalkyl exposure on specific key hepatic products. Our results provide evidence that perfluoroalkyl exposure, with potential future consequences, manifests in the human fetus as early as the first trimester of gestation. Furthermore, the profiles of metabolic changes resemble those observed in perinatal perfluoroalkyl exposures. Such exposures are already linked with susceptibility, initiation, progression, and exacerbation of a wide range of metabolic diseases. UK Medical Research Council, Horizon Europe Program of the European Union, Seventh Framework Programme of the European Union, NHS Grampian Endowments grants, European Partnership for the Assessment of Risks from Chemicals, Swedish Research Council, Formas, Novo Nordisk Foundation, and the Academy of Finland.

Association between human blood metabolome and the risk of gastrointestinal tumors.

The prevalence of gastrointestinal tumors continues to be significant. To uncover promising therapeutic targets for these tumors, we rigorously executed a Mendelian randomization (MR) study to comprehensively screen the blood metabolomes for potential causal mediators of five frequently encountered gastrointestinal tumors (Liver Cancer, Colorectal Cancer, Esophageal Cancer, Gastric Cancer and Pancreatic Cancer). We selected a comprehensive set of 137 distinct blood metabolites derived from three large-scale genome-wide association studies (GWASs) involving a total of 147827 participants of European ancestry. The gastrointestinal tumors-related data were obtained from a GWAS conducted within the Finnish study. Through meticulous MR analyses, we thoroughly assessed the associations between blood metabolites and gastrointestinal tumors. Additionally, a phenome-wide MR (Phe-MR) analysis was employed to investigate the potential on-target side effects of metabolite interventions. We have identified 1 blood metabolites, namely isovalerylcarnitine (ORlog10: 1.01; 95%CI, 1.01-1.02; P = 1.81×10-7), as the potential causal mediators for liver cancer. However, no potential pathogenic mediators were detected for the other four tumors. The current systematic MR analysis elucidated the potential role of isovalerylcarnitine as a causal mediator in the development of liver cancer. Leveraging the power of Phe-MR study facilitated the identification of potential adverse effects associated with drug targets for liver cancer prevention. Considering the weighing of pros and cons, isovalerylcarnitine emerges as a promising candidate for targeted drug interventions in the realm of liver cancer prevention.

Large-Scale Population-Based Studies of Blood Metabolome and Brain Health.

Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n>50 metabolites) and brain health reported in large-scale studies (n>500 individuals).

Mechanism of acteoside in prevention and treatment of gouty arthritis based on liver metabolomics

This study aims to reveal the effect of acteoside on gouty arthritis(GA) in rats based on liver metabolomics. The ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) was employed to search for the potential biomarkers and metabolic pathways. SD rats were randomly assigned into blank, model, colchicine(0.3 mg·kg~(-1)), and high-, medium-, low-dose(200, 100, and 50 mg·kg~(-1), respectively) acteoside groups(n=7). The rats were administrated once a day for 7 continuous days. Monosodium urate(MSU) was used to induce GA model in rats during administration. The degree of joint swelling and pathological changes of synovial tissue in rats were observed, and the levels of interleukin(IL)-1β, IL-18 and tumor necrosis factor(TNF)-α in the synovial tissue of rats were measured. UPLC-Q-TOF-MS was employed to collect rat liver data, and Progenesis QI and EZ info were used for data analysis. Human Metabolomics Database(HMDB) and Kyoto Encyclopedia of Genes and Genomes(KEGG) were employed to predict the potential biomarkers and metabolic pathways. The results showed that acteoside alleviated joint swelling, reduced synovial tissue damage, and lowered the levels of inflammatory cytokines in GA rats. A total of 19 common biomarkers were identified, 17 of which can be regulated by acteoside. Seven metabolic pathways were enriched, such as glycerophospholipid metabolism, linoleic acid metabolism, and taurine and hypotaurine metabolism, among which glycerophospholipid metabolism was strongly disturbed. The metabolomics analysis suggested that acteoside may down-regulate the expression of inflammatory cytokines and alleviate the symptoms of GA rats by regulating glycerophospholipid metabolism, linoleic acid metabolism, and taurine and hypotaurine metabolism. The findings provide a reference for future research and development of acteoside.

COLMARppm: A Web Server Tool for the Accurate and Rapid Prediction of 1H and 13C NMR Chemical Shifts of Organic Molecules and Metabolites.

Despite rapid progress in metabolomics research, a major bottleneck is the large number of metabolites whose chemical structures are unknown or whose spectra have not been deposited in metabolomics databases. Nuclear magnetic resonance (NMR) spectroscopy has a long history of elucidating chemical structures from experimentally measured 1H and 13C chemical shifts. One approach to characterizing the chemical structures of an unknown metabolite is to predict the 1H and 13C chemical shifts of candidate compounds (e.g., metabolites from the Human Metabolome Database (HMDB)) and compare them with chemical shifts of the unknown. However, accurate prediction of NMR chemical shifts in aqueous solution is challenging due to limitations of experimental chemical shift libraries and the high computational cost of quantum chemical methods. To improve NMR prediction accuracy and applicability, an empirical prediction strategy is introduced here to provide an accurately predicted chemical shift for organic molecules and metabolites within seconds. Unique features of COLMARppm include (i) the training library exclusively consisting of high quality NMR spectra measured under standard conditions in aqueous solution, (ii) utilization of NMR motif information, and (iii) leveraging of the improved prediction accuracy for the automated assignment of experimental chemical shifts for candidate structures. COLMARppm is demonstrated in terms of accuracy and speed for a set of 20 compounds taken from the HMDB for chemical shift prediction and resonance assignment. COLMARppm is applicable to a wide range of small molecules and can be directly incorporated into metabolomics workflows.

Exploring applications of non-targeted analysis in the characterization of the prenatal exposome

Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n = 592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n = 860,000 chemicals) and Human Metabolome Database (n = 3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72 % of the features (total features = 32,197, levels 1–4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.

Association between human blood metabolome and the risk of hypertension

Hypertension, commonly referred to as high blood pressure, is a chronic medical condition characterized by persistently elevated blood pressure levels. It is a prevalent global health issue, affecting a significant portion of the population worldwide. Hypertension is often asymptomatic, making it a silent but potentially dangerous condition if left untreated. Genetic instruments for 1,091 were from a recent comprehensive metabolome genome-wide association study (GWAS). Summary statistics of diastolic blood pressure (DBP) and systolic blood pressure (SBP) involving 757,601 sample size were analyzed. Two-sample Mendelian Randomization (MR) was conducted to assess causal effect of metabolites on DBP and SBP risk, and reverse MR analysis was performed to identify the DBP/SBP causal effect on blood metabolites. Twelve and twenty-two metabolites were identified to be associated with DBP and SBP, respectively. Sensitive analysis showed four metabolites had robustness association on BP. Reverse MR demonstrated DBP and SBP could decrease the tricosanoyl sphingomyelin (d18:1/23:0)* level and increase the 2-hydroxyhippurate (salicylurate) level in blood, respectively. Our findings reveal an association between blood metabolites and blood pressure (DBP and SBP), suggesting potential therapeutic targets for hypertension intervention.

Once upon a Time Oral Microbiota: A Cinderella or a Protagonist in Autism Spectrum Disorder?

Autism spectrum disorder (ASD) is a neurodevelopmental disorder evolving over the lifetime of individuals. The oral and gut microbial ecosystems are closely connected to each other and the brain and are potentially involved in neurodevelopmental diseases. This narrative review aims to identify all the available evidence emerging from observational studies focused on the role of the oral microbiome in ASD. A literature search was conducted using PubMed and the Cochrane Library for relevant studies published over the last ten years. Overall, in autistic children, the oral microbiota is marked by the abundance of several microbial species belonging to the Proteobacteria phylum and by the depletion of species belonging to the Bacteroidetes phylum. In mouse models, the oral microbiota is marked by the abundance of the Bacteroidetes phylum. Oral dysbiosis in ASD induces changes in the human metabolome, with the overexpression of metabolites closely related to the pathogenesis of ASD, such as acetate, propionate, and indoles, together with the underexpression of butyrate, confirming the central role of tryptophan metabolism. The analysis of the literature evidences the close relationship between oral dysbiosis and autistic core symptoms; the rebuilding of the oral and gut ecosystems by probiotics may significantly contribute to mitigating the severity of ASD symptoms.

Predicting pathways for old and new metabolites through clustering

The diverse metabolic pathways are fundamental to all living organisms, as they harvest energy, synthesize biomass components, produce molecules to interact with the microenvironment, and neutralize toxins. While the discovery of new metabolites and pathways continues, the prediction of pathways for new metabolites can be challenging. It can take vast amounts of time to elucidate pathways for new metabolites; thus, according to HMDB (Human Metabolome Database), only 60% of metabolites get assigned to pathways. Here, we present an approach to identify pathways based on metabolite structure. We extracted 201 features from SMILES annotations and identified new metabolites from PubMed abstracts and HMDB. After applying clustering algorithms to both groups of features, we quantified correlations between metabolites, and found the clusters accurately linked 92% of known metabolites to their respective pathways. Thus, this approach could be valuable for predicting metabolic pathways for new metabolites.