ABSTRACT
Benign paroxysmal positional vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases, it is successfully treated using the canalith repositioning procedure, but it is often followed by continuous lightheadedness in the absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile of treating these patients with polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV of the posterior semicircular canal (PSC) successfully treated using the Semont maneuver. Supplementation with a polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment using self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and urine metabolomics analysis performed using 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported excellent or good efficacy in the treatment of RD with a significant decrease in VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment, namely 1-methylnicotinamide, anserine, hippurate, lysine, methyl succinate and urea, indicating the inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound could induce some metabolic changes that can help in recovery from RD. However, future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomics evaluation to other problems concerning the different clinical aspects of BPPV, such as the high rate of relapse.
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Precision medicine is imminent, and metabolomics is one of the main actors on stage. We summarize and discuss the current literature on the clinical application of metabolomic techniques as a possible tool to improve early diagnosis of autism spectrum disorder (ASD), to define clinical phenotypes and to identify co-occurring medical conditions. A review of the current literature was carried out after PubMed, Medline and Google Scholar were consulted. A total of 37 articles published in the period 2010-2022 was included. Selected studies involve as a whole 2079 individuals diagnosed with ASD (1625 males, 394 females; mean age of 10, 9 years), 51 with other psychiatric comorbidities (developmental delays), 182 at-risk individuals (siblings, those with genetic conditions) and 1530 healthy controls (TD). Metabolomics, reflecting the interplay between genetics and environment, represents an innovative and promising technique to approach ASD. The metabotype may mirror the clinical heterogeneity of an autistic condition; several metabolites can be expressions of dysregulated metabolic pathways thus liable of leading to clinical profiles. However, the employment of metabolomic analyses in clinical practice is far from being introduced, which means there is a need for further studies for the full transition of metabolomics from clinical research to clinical diagnostic routine.
Subject(s)
Autism Spectrum Disorder , Autistic Disorder , Female , Male , Humans , Autism Spectrum Disorder/diagnosis , Employment , Metabolomics , PhenotypeABSTRACT
Systemic lupus erythematosus (SLE) is a chronic inflammatory disease, and several studies have suggested possible early RV involvement. Aim of the study was to evaluate the 3D echo parameters of the right ventricle (RV) and the metabolomic profile to correlate both with SLE severity. Forty SLE patients, free of cardiovascular disease, were enrolled and the following 3D parameters were evaluated: the RV ejection fraction (RV-EF), longitudinal strain of the interventricular septum (Septal LS), longitudinal strain of the free wall (Free-LS) and the fractional area change (FAC). In addition, a metabolomic analysis was performed. Direct correlations were observed between TAPSE values and the RV 3D parameters. Then, when splitting the population according to the SDI value, it was found that patients with higher cumulative damage (≥3) had significantly lower FAC, RV-EF, Septal LS, and Free-LS values; the latter three parameters showed a significant correlation with the metabolic profile of the patients. Furthermore, the division based on SDI values identified different metabolic profiles related to the degree of RV dysfunction. The RV dysfunction induced by the chronic inflammatory state present in SLE can be identified early by 3D echocardiography. Its severity seems to be related to systemic organ damage and the results associated with a specific metabolic fingerprint constituted by 2,4-dihydroxybutyric acid, 3,4-dihydroxybutyric acid, citric acid, glucose, glutamine, glycine, linoleic acid, oleic acid, phosphate, urea, and valine.
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Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.
Subject(s)
Autism Spectrum Disorder , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/genetics , Brain-Gut Axis , Autism Spectrum Disorder/genetics , Autism Spectrum Disorder/metabolism , Cross-Sectional Studies , Bayes Theorem , Reproducibility of Results , CytokinesABSTRACT
Current treatment for Multiple Sclerosis (MS) consists of a multidisciplinary approach including disease-modifying therapies. The response to treatment is heterogeneous, representing a crucial challenge in the classification of patients. Metabolomics is an innovative tool that can identifies biomarkers/predictors of treatment response. We aimed to evaluate plasma metabolic changes in a group of naïve Relapsing-Remitting MS patients starting Fingolimod treatment, to find specific metabolomic features that predict the therapeutic response as well as the possible side effects. The study included 42 Relapsing-Remitting MS blood samples, of which 30 were classified as responders after two years of FINGO treatment, whereas 12 patients were Not-Responders. For fifteen patients, samples were collected at four time points: before starting the therapy; at six months after the initiation; at twelve months after; and at twenty-four months after initiation. The serum was analysed through Nuclear Magnetic Resonance and multivariate and univariate statistical analysis. Considering the single comparison between each time point, it was possible to identify a set of metabolites changing their concentrations based on the drug intake. FINGO influences aminoacidic and energy metabolisms and reduces oxidative stress and the activity of the immune system, both typical features of MS.
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Cancer cells adjust their metabolism to meet energy demands. In particular, glutamine addiction represents a distinctive feature of several types of tumors, including colorectal cancer. In this study, four colorectal cancer cell lines (Caco-2, HCT116, HT29 and SW480) were cultured with or without glutamine. The growth and proliferation rate, colony-forming capacity, apoptosis, cell cycle, redox homeostasis and metabolomic analysis were evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide test (MTT), flow cytometry, high-performance liquid chromatography and gas chromatography/mass spectrometry techniques. The results show that glutamine represents an important metabolite for cell growth and that its deprivation reduces the proliferation of colorectal cancer cells. Glutamine depletion induces cell death and cell cycle arrest in the GO/G1 phase by modulating energy metabolism, the amino acid content and antioxidant defenses. Moreover, the combined glutamine starvation with the glycolysis inhibitor 2-deoxy-D-glucose exerted a stronger cytotoxic effect. This study offers a strong rationale for targeting glutamine metabolism alone or in combination with glucose metabolism to achieve a therapeutic benefit in the treatment of colon cancer.
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BACKGROUND: Endometriosis affects women of reproductive age, and its pathogenesis is still unclear. Typically, it overlaps other similar medical and surgical conditions, determining a delay in early diagnosis. Metabolomics allows studying metabolic changes in different physiological or pathological states to discover new potential biomarkers. We used the gas chromatography-mass spectrometer (GC-MS) to explore metabolic alterations in endometriosis to better understand its pathophysiology and find new biomarkers. METHODS: Twenty-two serum samples of patients with symptomatic endometriosis and ten without it were collected and subjected to GC-MS analysis. Multivariate and univariate statistical analyses were performed, followed by pathway analysis. RESULTS: Partial least squares discriminant analysis was performed to determine the differences between the two groups (p = 0.003). Threonic acid, 3-hydroxybutyric acid, and proline increased significantly in endometriosis patients, while alanine and valine decreased. ROC curves were built to test the diagnostic power of metabolites. The pathway analysis identified the synthesis and degradation of ketone bodies and the biosynthesis of phenylalanine, tyrosine, and tryptophan as the most altered pathways. CONCLUSIONS: The metabolomic approach identifies metabolic alterations in women with endometriosis. These findings may improve our understanding of the pathophysiological mechanisms of disease and the discovery of new biomarkers.
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Otorhinolaryngology (Ear, Nose and Throat-ENT) focuses on inflammatory, immunological, infectious, and neoplastic disorders of the head and neck and on their medical and surgical therapy. The fields of interest of this discipline are the ear, the nose and its paranasal sinuses, the oral cavity, the pharynx, the larynx, and the neck. Besides surgery, there are many other diagnostic aspects of ENT such as audiology and Vestibology, laryngology, phoniatrics, and rhinology. A new advanced technology, named metabolomics, is significantly impacting the field of ENT. All the "omics" sciences, such as genomics, transcriptomics, and proteomics, converge at the level of metabolomics, which is considered the integration of all "omics." Its application will change the way several of ENT disorders are diagnosed and treated. This review highlights the power of metabolomics, including its pitfalls and promise, and several of its most relevant applications in ENT to provide a basic understanding of the metabolites associated with these districts. In particular, the attention has been focused on different heterogeneous diseases, from head and neck cancer to allergic rhinitis, hearing loss, obstructive sleep apnea, noise trauma, sinusitis, and Meniere's disease. In conclusion, metabolomics study indicates a "fil rouge" that links these pathologies to improve three aspects of patient care: diagnostics, prognostics, and therapeutics, which in one word is defined as precision medicine.
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Chronic pain affects almost 20% of the European adult population and it significantly reduces patients' quality of life. Chronic pain is considered a multidimensional experience determined by the interaction of several genetic and environmental factors. The effect of specific genetic contributions is often unclear, and the interpretation of the results from studies focused on genetic influences on pain has been complicated by the existence of multiple pain phenotypes. A step forward from genetics could be given by the application of metabolomics and microbiomics tools. Metabolomics is a powerful approach for hypothesis generation in biology, and it aims to analyze low molecular weight compounds, either metabolic intermediates or metabolic end-products, resulting from human or microbial metabolism. Microbiomics is a fast-growing field in which all the microbes are examined together, and as a result, its perturbation may indicate the development of chronic diseases. By applying these methodologies for the study of chronic pain, several differences have been identified. The alteration of the choline-PAF pathway is an intriguing finding recognized by several groups. In our opinion, metabolomics and microbiomics techniques will allow significant progress into the medical field. Patients may benefit from the possibility of being stratified and classified based on their metabolic and microbial profile, which, in the next future, may lead to personalized therapy.
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Several metabolomics-based studies have provided evidence that autistic subjects might share metabolic abnormalities with gut microbiota dysbiosis and alterations in gut mucosal permeability. Our aims were to explore the most relevant metabolic perturbations in a group of autistic children, compared with their healthy siblings, and to investigate whether the increased intestinal permeability may be mirrored by specific metabolic perturbations. We enrolled 13 autistic children and 14 unaffected siblings aged 2-12 years; the evaluation of the intestinal permeability was estimated by the lactulose:mannitol test. The urine metabolome was investigated by proton nuclear magnetic resonance (1H-NMR) spectroscopy. The lactulose:mannitol test unveiled two autistic children with altered intestinal permeability. Nine metabolites significantly discriminated the urine metabolome of autistic children from that of their unaffected siblings; however, in the autistic children with increased permeability, four additional metabolites-namely, fucose, phenylacetylglycine, nicotinurate, and 1-methyl-nicotinamide, strongly discriminated their urine metabolome from that of the remaining autistic children. Our preliminary data suggest the presence of a specific urine metabolic profile associated with the increase in intestinal permeability.
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Traditional cardiovascular (CV) risk factors (RFs) and coronary artery disease (CAD) do not always show a direct correlation. We investigated the metabolic differences in a cohort of patients with a high CV risk profile who developed, or did not develop, among those enrolled in the Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation (CAPIRE) study. We studied 112 subjects with a high CV risk profile, subdividing them according to the presence (CAD/High-RFs) or absence of CAD (No-CAD/High-RFs), assessed by computed tomography angiography. The metabolic differences between the two groups were identified by gas chromatography-mass spectrometry. Characteristic patterns and specific metabolites emerged for each of the two phenotypic groups: high concentrations of pyruvic acid, pipecolic acid, p-cresol, 3-aminoisobutyric acid, isoleucine, glyceric acid, lactic acid, sucrose, phosphoric acid, trimethylamine-N-oxide, 3-hydroxy-3-methylglutaric acid, erythritol, 3-hydroxybutyric acid, glucose, leucine, and glutamic acid; and low concentrations of cholesterol, hypoxanthine, glycerol-3-P, and cysteine in the CAD/High-RFs group vs the No-CAD/High-RFs group. Our results show the existence of different metabolic profiles between patients who develop CAD and those who do not, despite comparable high CV risk profiles. A specific cluster of metabolites, rather than a single marker, appears to be able to identify novel predisposing or protective mechanisms towards CAD beyond classic CVRFs.
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OBJECTIVE: Obesity is one of the main risk factors for the development gestational diabetes mellitus (GDM). Thus, we aim to identify changes in the urinary metabolomics profile of obese women at first trimester of pregnancy in order to predict later GDM diagnosis. RESEARCH DESIGN AND METHODS: In this nested case-control study, urine samples collected in the first trimester of pregnancy obtained from obese women who developed GDM (n = 29) and obese women who did not develop diabetes (n = 25 NO GDM) were analyzed with Nuclear Magnetic Resonance spectroscopy combined with Multivariate Statistical Analysis. GDM diagnosis was obtained with one-step oral glucose load. RESULTS: OPLS-DA significantly separated the GDM women from NO GDM women. Specifically, GDM women were characterized by a higher level of tryptophan, trigonelline, hippurate, and threonine, and lower levels of 1-methylnicotinamide, 3-hydroxykynurenine, glycocholate, isoleucine, kynurenine, and valine compared to NO GDM women. CONCLUSION: In a prevalently Caucasian population, the changes of some metabolites such as tryptophan, trigonelline, and branch-chained amino acids in the urinary profile of obese women in the first trimester are able to make unequivocal prediction of those which later test positive for GDM. This approach could be useful to diagnose much earlier obese women with GDM allowing lifestyle counselling and other interventions.
Subject(s)
Diabetes, Gestational , Pregnancy , Female , Humans , Diabetes, Gestational/epidemiology , Pregnancy Trimester, First , Case-Control Studies , Proton Magnetic Resonance Spectroscopy , Tryptophan/metabolism , Metabolomics/methods , Obesity/complicationsABSTRACT
The purpose of this study was to assess whether metabolomics, associated with echocardiography, was able to highlight pathophysiological differences between obstructive (OHCM) or non-obstructive (NOHCM) hypertrophic cardiomyopathy. Thirty-one HCM patients underwent standard and advanced echocardiography; a plasma sample was collected for metabolomic analysis. Results. Patients with OHCM compared with subjects with NOHCM had higher values of 2DLVEF (66.5 ± 3.3% vs. 60.6 ± 1.8%, p < 0.01), S wave (7.6 ± 1.1 vs. 6.3 ± 0.7 cm/s, p < 0.01) and 3D global longitudinal strain (17.2 ± 4.2%, vs. 13.4 ± 1.3%, p < 0.05). A 2-group PLS-Discriminant Analysis was performed to verify whether the two HCM groups differed also based on the metabolic fingerprint. A clear clustering was shown (ANOVA p = 0.014). The most discriminating metabolites resulted as follows: in the NOHCM Group, there were higher levels of threitol, aminomalonic acid, and sucrose, while the OHCM Group presented higher levels of amino acids, in particular those branched chains, of intermediates of glycolysis (lactate) and the Krebs cycle (fumarate, succinate, citrate), of fatty acids (arachidonic acid, palmitoleic acid), of ketone bodies (2-OH-butyrate). Our data point out a different systolic function related to a specific metabolic activity in the two HCM phenotypic forms, with specific metabolites associated with better contractility in OHCM.
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Several differential panels of metabolites have been associated with the presence of metabolic syndrome and its related conditions, namely non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). This study aimed to perform a systematic review to summarize the most recent finding in terms of circulating biomarkers following NAFLD/NASH syndromes. Hence, the research was focused on NAFLD/NASH studies analysed by metabolomics approaches. Following Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a systematic search was conducted on the PubMed database. The inclusion criteria were (i) publication date between 2010 and 2021, (ii) presence of the combination of terms: metabolomics and NAFLD/NASH, and (iii) published in a scholarly peer-reviewed journal. Studies were excluded from the review if they were (i) single-case studies, (ii) unpublished thesis and dissertation studies, and (iii) not published in a peer-reviewed journal. Following these procedures, 10 eligible studies among 93 were taken into consideration. The metabolisms of amino acids, fatty acid, and vitamins were significantly different in patients affected by NAFLD and NASH compared to healthy controls. These findings suggest that low weight metabolites are an important indicator for NAFLD/NASH syndrome and there is a strong overlap between NAFLD/NASH and the metabolic syndrome. These findings may lead to new perspectives in early diagnosis, identification of novel biomarkers, and providing novel targets for pharmacological interventions.
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Necrotizing enterocolitis (NEC) is among the most relevant gastrointestinal diseases affecting mostly prematurely born infants with low birth weight. While intestinal dysbiosis has been proposed as one of the possible factors involved in NEC pathogenesis, the role of the gut microbiota remains poorly understood. In this study, the gut microbiota of preterm infants was explored to highlight differences in the composition between infants affected by NEC and infants prior to NEC development. A large-scale gut microbiome analysis was performed, including 47 shotgun sequencing data sets generated in the framework of this study, along with 124 retrieved from publicly available repositories. Meta-analysis led to the identification of preterm community state types (PT-CSTs), which recur in healthy controls and NEC infants. Such analyses revealed an overgrowth of a range of opportunistic microbial species accompanying the loss of gut microbial biodiversity in NEC subjects. Moreover, longitudinal insights into preterm infants prior to NEC development indicated Clostridium neonatale and Clostridium perfringens species as potential biomarkers for predictive early diagnosis of this disease. Furthermore, functional investigation of the enzymatic reaction profiles associated with pre-NEC condition suggested DL-lactate as a putative metabolic biomarker for early detection of NEC onset. IMPORTANCE Necrotizing enterocolitis (NEC) is a severe gastrointestinal disease occurring predominantly in premature infants whose etiology is still not fully understood. In this study, the analysis of infant fecal samples through shotgun metagenomics approaches revealed a marked reduction of the intestinal (bio)diversity and an overgrowth of (opportunistic) pathogens associated with the NEC development. In particular, dissection of the infant's gut microbiome before NEC diagnosis highlighted the potential involvement of Clostridium genus members in the progression of NEC. Remarkably, our analyses highlighted a gastrointestinal DL-lactate accumulation among NEC patients that might represent a novel potential functional biomarker for the early diagnosis of NEC.
Subject(s)
Clostridium perfringens/isolation & purification , Clostridium/isolation & purification , Dysbiosis/microbiology , Enterocolitis, Necrotizing/microbiology , Gastrointestinal Microbiome/physiology , Infant, Premature, Diseases/microbiology , Biomarkers/analysis , Clostridium/genetics , Clostridium perfringens/genetics , Enterocolitis, Necrotizing/pathology , Feces/microbiology , Humans , Infant, Low Birth Weight/metabolism , Infant, Newborn , Infant, Premature , Intestines/microbiology , Lactic Acid/analysis , Metagenome/geneticsABSTRACT
Objective: To investigate changes in the urine metabolome of very low birth weight preterm newborns with necrotizing enterocolitis (NEC) and feed intolerance, we conducted a longitudinal study over the first 2 months of life. The metabolome of NEC newborns was compared with two control groups that did not develop NEC: the first one included preterm babies with feed intolerance, while the second one preterm babies with good feed tolerance. Methods: Newborns developing NEC within the 3 weeks of life were identified as early onset NEC, while the remaining as late onset NEC. Case-control matching was done according to the gestational age (±1 week), birth weight (± 200 g), and postnatal age. A total of 96 urine samples were collected and analyzed. In newborns with NEC, samples were collected before, during and after the diagnosis over the first 2 months of life, while in controls samples were collected as close as possible to the postnatal age of newborns with NEC. Proton nuclear magnetic resonance (1H NMR) spectroscopy was used for metabolomic analysis. Data were analyzed by univariate and multivariate statistical analysis. Results: In all the preterm newborns, urine levels of betaine, glycine, succinate, and citrate positively correlated with postnatal age. Suberate and lactate correlated with postnatal age in preterms with NEC and in controls with food intolerance, while N,N-dimethylglycine (N,N-DMG) correlated only in controls with good digestive tolerance. Preterm controls with feed intolerance showed a progressive significant decrease of N-methylnicotinamide and carnitine. Lactate, betaine, myo-inositol, urea, creatinine, and N,N-dimethylglycine discriminated late-onset NEC from controls with good feed tolerance. Conclusion: Our findings are discussed in terms of contributions from nutritional and clinical managements of patients and gut microbiota.
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BACKGROUND: Patients at risk of breast cancer are submitted to mammography, resulting in a classification of the lesions following the Breast Imaging Reporting and Data System (BI-RADS®). Due to BI-RADS 3 classification problems and the great uncertainty of the possible evolution of this kind of tumours, the integration of mammographic imaging with other techniques and markers of pathology, as metabolic information, may be advisable. DESIGN AND METHODS: Our study aims to evaluate the possibility to quantify by gas chromatography-mass spectrometry (GC-MS) specific metabolites in the plasma of patients with mammograms classified from BI-RADS 3 to BI-RADS 5, to find similarities or differences in their metabolome. Samples from BI-RADS 3 to 5 patients were compared with samples from a healthy control group. This pilot project aimed at establishing the sensitivity of the metabolomic classification of blood samples of patients undergoing breast radiological analysis and to support a better classification of mammographic cases. RESULTS: Metabolomic analysis revealed a panel of metabolites more abundant in healthy controls, as 3-aminoisobutyric acid, cholesterol, cysteine, stearic, linoleic and palmitic fatty acids. The comparison between samples from BI-RADS 3 and BI-RADS 5 patients, revealed the importance of 4-hydroxyproline, found in higher amount in BI-RADS 3 subjects. CONCLUSION: Although the low sample number did not allow the attainment of high validated statistical models, some interesting data were obtained, revealing the potential of metabolomics for an improvement in the classification of different mammographic lesions.
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BACKGROUND: Traditional cardiovascular risk factors (RFs) and coronary artery disease (CAD) do not always run parallel. We investigated functional-metabolic correlations of CAD, RFs, or neither in the CAPIRE (Coronary Atherosclerosis in Outlier Subjects: Protective and Novel Individual Risk Factors Evaluation) 2 × 2 phenotypic observational study. METHODS: Two hundred and fortyone subjects were included based on RF burden, presence/absence of CAD (assessed by computed tomography angiography), age and sex. Participants displayed one of four phenotypes: CAD with ≥3 RFs, no-CAD with ≥3 RFs, CAD with ≤1 RF and no-CAD with ≤1 RF. Metabolites were identified by gas chromatography-mass spectrometry and pathways by metabolite set enrichment analysis. RESULTS: Characteristic patterns and specific pathways emerged for each phenotypic group: amino sugars for CAD/high-RF; urea cycle for no-CAD/high-RF; glutathione for CAD/low-RF; glycine and serine for no-CAD/low-RF. Presence of CAD correlated with ammonia recycling; absence of CAD with the transfer of acetyl groups into mitochondria; high-risk profile with alanine metabolism (all p < 0.05). The comparative case-control analyses showed a statistically significant difference for the two pathways of phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism in the CAD/Low-RF vs NoCAD/Low-RF comparison. CONCLUSIONS: The present 2 × 2 observational study identified specific metabolic pathways for each of the four phenotypes, providing novel functional insights, particularly on CAD with low RF profiles and on the absence of CAD despite high-risk factor profiles.
Subject(s)
Cardiovascular Diseases , Coronary Artery Disease , Coronary Angiography , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/epidemiology , Heart Disease Risk Factors , Humans , Phenotype , Risk FactorsABSTRACT
The diagnosis of mechanical asphyxia remains one of the most difficult issues in forensic pathology. Asphyxia ultimately results in cardiac arrest (CA) and, as there are no specific markers, the differential diagnosis of primitive CA and CA secondary to asphyxiation relies on circumstantial details and on the pathologist experience, lacking objective evidence. Histological examination is currently considered the gold standard for CA post-mortem diagnosis. Here we present the comparative results of histopathology versus those previously obtained by 1H nuclear magnetic resonance (NMR) metabolomics in a swine model, originally designed for clinical purposes, exposed to two different CA causes, namely ventricular fibrillation and asphyxia. While heart and brain microscopical analysis could identify the damage induced by CA without providing any additional information on the CA cause, metabolomics allowed the identification of clearly different profiles between the two groups and showed major differences between asphyxiated animals with good and poor outcomes. Minute-by-minute plasma sampling allowed to associate these modifications to the pre-arrest asphyxial phase showing a clear correlation to the cellular effect of mechanical asphyxia reproduced in the experiment. The results suggest that metabolomics provides additional evidence beyond that obtained by histology and immunohistochemistry in the differential diagnosis of CA.
Subject(s)
Asphyxia/diagnosis , Metabolomics/methods , Proton Magnetic Resonance Spectroscopy/methods , Animals , Asphyxia/metabolism , Asphyxia/pathology , Disease Models, Animal , Female , Histological Techniques , Humans , SwineABSTRACT
BACKGROUND: Lactobacillus reuteri DSM 17938 is the only probiotic recommended for treatment of colicky infants, but its mechanism of action is not clear. The study aim was to examine urinary metabolomic fingerprint of colicky breastfed infants before and after 1 month of orally administered Lactobacillus reuteri DSM 17938 or placebo. METHODS: This randomized, blinded, placebo-controlled clinical trial was carried out with a well-documented probiotic. Thirty-two infants were enrolled, 16 in the probiotic group and 16 in the placebo group. Urine samples were collected from each subject before starting supplementation and at the end of the study period. Metabolomic profiles were obtained using a gas chromatography/mass spectrometry instrument. Subsequently, to compare groups before and after probiotic supplementation, univariate and multivariate statistical analysis were performed. RESULTS: In the L. reuteri treated group all metabolites for all class of nutrients (sugars, amino acids, carboxylic acids) resulted more abundant after the study period. The comparison with a control group (placebo treated), confirmed this effect on urines. CONCLUSIONS: The metabolomic analysis of urine samples from infants treated with L. reuteri DSM 17938 allowed to detect some interesting features related to the effect of this treatment on urinary metabolome. To validate the results, a test on a larger cohort is required.