Metabolomics: Perspectives on Clinical Employment in Autism Spectrum Disorder.

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.

Urinary metabolome of infants with colic treated with Lactobacillus reuteri DSM 17938: a pilot randomized trial.

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.

A 1H NMR metabolomic approach for the estimation of the time since death using aqueous humour: an animal model.

INTRODUCTION: The estimation of the time since death, or post-mortem interval (PMI), still remains a main conundrum in forensic science. Several approaches have been so far proposed from either a qualitative or a quantitative point of view, but they still lack reliability and robustness. Recently, metabolomics has shown to be a potential tool to investigate the time-related post-mortem metabolite modifications in animal models. OBJECTIVES: Here we propose, for the first time, the use of a 1H NMR metabolomic approach for the estimation of PMI from aqueous humour (AH) in an ovine model. METHODS: AH samples were collected at different times after death (from 118 to 1429 min). 1H NMR experiments were performed and spectral data analysed by multivariate statistical tools. RESULTS: A multivariate calibration model was built to estimate PMI on the basis of the metabolite content of the samples. The model was validated with an independent test set, obtaining a prediction error of 59 min for PMI < 500 min, 104 min for PMI from 500 to 1000 min, and 118 min for PMI > 1000 min. Moreover, the metabolomic approach suggested a picture of the mechanisms underlying the post-mortem biological modifications, highlighting the role played by taurine, choline, and succinate. CONCLUSION: The time-related modifications of the 1H NMR AH metabolomic profile seem to be encouraging in addressing the issue of a reproducible and robust model to be employed for the estimation of the time since death.

Urinary 1H NMR metabolomics profile of Italian citizens exposed to background levels of arsenic: a (pre)cautionary tale.

Objectives: Arsenic is a toxic metal ubiquitous in the environment and in daily life items. Long-term arsenic exposure is associated with severe adverse health effects involving various target organs. It would be useful to investigate the existence of metabolic alterations associated with lifestyle and/or with the environment. For this purpose, we studied the correlation between urinary arsenic levels and urinary proton nuclear magnetic resonance spectroscopy (1H NMR) metabolomics profiles in a non-occupationally nor environmentally arsenic exposed general population.Methods: Urine samples were collected from 86 healthy subjects. Total and non-alimentary urinary arsenic (U-naAs) levels, namely the sum of arsenite, arsenate, monomethylarsonate and dimethylarsinate, were measured and 1H NMR analysis was performed. Orthogonal Projection to Latent Structures was applied to explore the correlation between the metabolomics profiles and U-naAs levels.Results: Despite the extremely low U-naAs levels (mean value = 6.13 ± 3.17 µg/g creatinine) of our studied population a urinary metabolomics profile related to arsenic was identified.Conclusion: The identified profile could represent a fingerprint of early arsenic biological effect and could be used in further studies as an indicator of susceptibility, also in subjects exposed to a low arsenic dose, with implications in occupational health, toxicology, and public health.

Salivary Metabolomics Fingerprint of Chronic Apical Abscess with Sinus Tract: A Pilot Study.

Chronic apical abscess (CAA) is a lesion of apical periodontitis mostly characterized by areas of liquefactive necrosis with disintegrating polymorphonuclear neutrophils surrounded by macrophages. Its presence leads to local bacterial infection, systemic inflammatory response, pain, and swelling. The use of a novel approach for the study of CAA, such as metabolomics, seems to be important since it has proved to be a powerful tool for biomarkers discovery which could give novel molecular insight on CAA. So, the aim of this study was to verify the possibility to identify the metabolic fingerprint of CAA through the analysis of saliva samples. Nineteen patients were selected for this study: eleven patients affected by CAA with a sinus tract constituted the study group whereas eight patients without clinical and radiographic signs of CAA formed the healthy control group. Saliva samples were collected from each subject and immediately frozen at -80°C. Metabolomic profiles were obtained using a gas chromatography/mass spectrometry instrument. Subsequently, in order to compare the two groups, a multivariate statistical model was built that resulted to be statistically significant. The class of metabolites characterizing the CAA patients was closely related to the bacterial catabolism, tissue necrosis, and presence of a sinus tract. These preliminary results, for the first time, indicate that saliva samples analyzed by means of GC/MS metabolomics may be useful for identifying the presence of CAA, leading to new insights into this disease.

Metabolomic Perspectives in Antiblastic Cardiotoxicity and Cardioprotection.

Despite advances in supportive and protective therapy for myocardial function, cardiovascular diseases due to antineoplastic therapy-primarily cardiomyopathy associated with contractile dysfunction-remain a major cause of morbidity and mortality. Because of the limitations associated with current therapies, investigators are searching for alternative strategies that can timely recognise cardiovascular damage-thus permitting a quick therapeutic approach-or prevent the development of the disease. Damage to the heart can result from both traditional chemotherapeutic agents, such as anthracyclines, and new targeted therapies, such as tyrosine kinase inhibitors. In recent years, metabolomics has proved to be a practical tool to highlight fundamental changes in the metabolic state in several pathological conditions. In this article, we present the state-of-the-art technology with regard to the metabolic mechanisms underlying cardiotoxicity and cardioprotection.

The Metabolomic Profile of Lymphoma Subtypes: A Pilot Study.

Lymphoma defines a group of different diseases. This study examined pre-treatment plasma samples from 66 adult patients (aged 20-74) newly diagnosed with any lymphoma subtype, and 96 frequency matched population controls. We used gas chromatography-mass spectrometry (GC-MS) to compare the metabolic profile by case/control status and across the major lymphoma subtypes. We conducted univariate and multivariate analyses, and partial least square discriminant analysis (PLS-DA). When compared to the controls, statistically validated models were obtained for diffuse large B-cell lymphoma (DLBCL), chronic lymphocytic leukemia (CLL), multiple myeloma (MM), and Hodgkin lymphoma (HL), but not follicular lymphoma (FL). The metabolomic analysis highlighted interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects: Important metabolites, such as hypoxanthine and elaidic acid, were more abundant in all lymphoma subtypes. The small sample size of the individual lymphoma subtypes prevented obtaining PLS-DA validated models, although specific peculiar features of each subtype were observed; for instance, fatty acids were most represented in MM and HL patients, while 2-aminoadipic acid, 2-aminoheptanedioic acid, erythritol, and threitol characterized DLBCL and CLL. Metabolomic analysis was able to highlight interesting differences between lymphoma patients and population controls, allowing the discrimination between pathologic and healthy subjects. Further studies are warranted to understand whether the peculiar metabolic patterns observed might serve as early biomarkers of lymphoma.

Impact of Early Postnatal Nutrition on the NMR Urinary Metabolic Profile of Infant.

NMR-based metabolomics was used to compare the metabolic urinary profiles of exclusively breast-fed term infants (n = 11) with those of a double-blinded controlled trial with 49 formula-fed term newborns randomized to receive either an infant formula enriched by functional ingredients (n = 24) or a standard formula (n = 25). Anthropometric measurements and urine samples were taken at enrollment (within the first month of life), at around 60 days of life, and at the end of study period (average age of 130 days). The metabolic profiles were examined in relation to time and diet strategy. A common age-dependent modification of the urine metabolome was observed for the three types of nutrition, mainly characterized by similar temporal trends of choline, betaine, myoinositol, taurine, and citrate. Contrariwise, differences in the metabolic profiles were identified according to the type of diet (human versus formula milk), while no significant difference was observed between the two formulas. These modifications are discussed mainly in terms of the different milk compositions. Despite the low number of enrolled infants (n = 60), these findings pointed out the potential of the metabolomics approach for neonatal nutritional science, in particular to provide important contributions to the optimization of formula milk.

Metabolomic patterns associated to QTc interval in shiftworkers: an explorative analysis.

OBJECTIVES: (1)H NMR-metabolomic approach was used to investigate QTc interval correlation with plasma metabolic profiles in shiftworkers. METHODS: Socio-demographic data, electrocardiographic QTc interval and plasma metabolic profiles from 32 male shiftworkers, were correlated by multivariate regression analysis. RESULTS: We found a positive correlation between QTc interval values, body mass index, glycemia and lactate level and a negative correlation between QTc interval and both pyroglutamate and 3-hydroxybutyrate plasma level. CONCLUSIONS: Our analysis provides evidence of the association between clinical, metabolic profiles and QTc interval values. This could be used to identify markers of early effects and/or susceptibility in shiftworkers.

Discovery of biochemical biomarkers for aggression: A role for metabolomics in psychiatry.

Human aggression encompasses a wide range of behaviors and is related to many psychiatric disorders. We introduce the different classification systems of aggression and related disorders as a basis for discussing biochemical biomarkers and then present an overview of studies in humans (published between 1990 and 2015) that reported statistically significant associations of biochemical biomarkers with aggression, DSM-IV disorders involving aggression, and their subtypes. The markers are of different types, including inflammation markers, neurotransmitters, lipoproteins, and hormones from various classes. Most studies focused on only a limited portfolio of biomarkers, frequently a specific class only. When integrating the data, it is clear that compounds from several biological pathways have been found to be associated with aggressive behavior, indicating complexity and the need for a broad approach. In the second part of the paper, using examples from the aggression literature and psychiatric metabolomics studies, we argue that a better understanding of aggression would benefit from a more holistic approach such as provided by metabolomics. © 2016 Wiley Periodicals, Inc.

Identifying the role of cytochrome c in post-resuscitation pathophysiology.

Cytochrome c, an electron carrier that normally resides in the mitochondrial intermembrane space, may translocate to the cytosol under ischemic and hypoxic conditions and contribute to mitochondrial permeability transition pore opening. In addition, reperfusion of brain tissue following ischemia initiates a cell death cascade that includes cytochrome c-mediated induction of apoptosis. Further studies are needed to determine the contribution of cytochrome c in the regulation of cell death, as well as its value as an in vivo prognostic marker after cardiac arrest and resuscitation.

Perinatal asphyxia: a review from a metabolomics perspective.

Perinatal asphyxia is defined as an oxygen deprivation that occurs around the time of birth, and may be caused by several perinatal events. This medical condition affects some four million neonates worldwide per year, causing the death of one million subjects. In most cases, infants successfully recover from hypoxia episodes; however, some patients may develop HIE, leading to permanent neurological conditions or impairment of different organs and systems. Given its multifactor dependency, the timing, severity and outcome of this disease, mainly assessed through Sarnat staging, are of difficult evaluation. Moreover, although the latest newborn resuscitation guideline suggests the use of a 21% oxygen concentration or room air, such an approach is still under debate. Therefore, the pathological mechanism is still not clear and a golden standard treatment has yet to be defined. In this context, metabolomics, a new discipline that has described important perinatal issues over the last years, proved to be a useful tool for the monitoring, the assessment, and the identification of potential biomarkers associated with asphyxia events. This review covers metabolomics research on perinatal asphyxia condition, examining in detail the studies reported both on animal and human models.

Thermal and nonthermal signatures of the Unruh effect in Casimir-Polder forces.

We show that Casimir-Polder forces between two relativistic uniformly accelerated atoms exhibit a transition from the short distance thermal-like behavior predicted by the Unruh effect to a long distance nonthermal behavior, associated with the breakdown of a local inertial description of the system. This phenomenology extends the Unruh thermal response detected by a single accelerated observer to an accelerated spatially extended system of two particles, and we identify the characteristic length scale for this crossover with the inverse of the proper acceleration of the two atoms. Our results are derived separating at fourth order in perturbation theory the contributions of vacuum fluctuations and radiation reaction field to the Casimir-Polder interaction between two atoms moving in two generic stationary trajectories separated by a constant distance and linearly coupled to a scalar field. The field can be assumed in its vacuum state or at finite temperature, resulting in a general method for the computation of Casimir-Polder forces in stationary regimes.

Optomechanical Rydberg-atom excitation via dynamic Casimir-Polder coupling.

We study the optomechanical coupling of a oscillating effective mirror with a Rydberg atomic gas, mediated by the dynamical atom-mirror Casimir-Polder force. This coupling may produce a near-field resonant atomic excitation whose probability scales as ∝(d(2)an(4)t)(2)/z(0)(8), where z(0) is the average atom-surface distance, d the atomic dipole moment, a the mirror's effective oscillation amplitude, n the initial principal quantum number, and t the time. We propose an experimental configuration to realize this system with a cold atom gas trapped at a distance ∼2×10 µm from a semiconductor substrate whose dielectric constant is periodically driven by an external laser pulse, hence realizing an effective mechanical mirror motion due to the periodic change of the substrate from transparent to reflecting. For a parabolic gas shape, this effect is predicted to excite about ∼10(2) atoms of a dilute gas of 10(3) trapped Rydberg atoms with n=75 after about 0.5 µs, which is high enough to be detected in typical Rydberg gas experimental conditions.

Clinical Efficacy and Metabolomics Modifications Induced by Polyphenol Compound Supplementation in the Treatment of Residual Dizziness following Semont Maneuver in Benign Paroxysmal Positional Vertigo (BPPV) of the Posterior Semicircular Canal (PSC): Preliminary Results.

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.

1H NMR metabolite fingerprinting as a new tool for body fluid identification in forensic science.

In this feasibility study, we propose, for the first time, (1)H NMR spectroscopy coupled with mathematical strategies as a valid tool for body fluid (BF) trace identification in forensic science. In order to assess the ability of this approach to identify traces composed either by a single or by two different BFs, samples of blood, urine, saliva, and semen were collected from different donors, and binary mixtures were prepared. (1)H NMR analyses were carried out for all samples. Spectral data of the whole set were firstly submitted to unsupervised principal component analysis (PCA); it showed that samples of the same BF cluster well on the basis of their characterizing molecular components and that mixtures exhibit intermediate characteristics among BF typologies. Furthermore, samples were divided into a training set and a test set. An average NMR spectral profile for each typology of BF was obtained from the training set and validated as representative of each BF class. Finally, a fitting procedure, based on a system of linear equations with the four obtained average spectral profiles, was applied to the test set and the mixture samples; it showed that BFs can be unambiguously identified, even as components of a mixture. The successful use of this mathematical procedure has the advantage, in forensics, of overcoming bias due to the analyst's personal judgment. We therefore propose this combined approach as a valid, fast, and non-destructive tool for addressing the challenges in the identification of composite traces in forensics.

Metabolomics in adult and pediatric nephrology.

Metabolomics, the latest of the "omics" sciences, has a non-selective approach and can thus lead to the identification of all the metabolites (molecules < 1 kDa) in a biological system. The metabolomic profile can be considered the most predictive phenotype capable of evaluating epigenetic modifications determined by external factors. It is so close to the phenotype as to be considered the phenotype itself in its unique individuality (fingerprinting), both in health (phenome), and disease (diseasome). Urine, compared to other biological liquids, has the advantage of being a complex fluid with many components, including intermediate metabolites. Metabolomics may thus play a role in the study of different kidney diseases and overcome diagnostic difficulties. We shall present the studies that to our knowledge have been published on Nephrology and Pediatric Nephrology. Some are experimental while others are clinical. We have not considered carcinomas and transplantations. Although scarce, the data on adults and the very few ones in pediatrics are quite interesting. Further studies on kidneys are needed to determine the practical clinical impact of metabolomics in kidney renal pathologies. The "multiplatform" "omic" study of urine and namely metabolomics can contribute to improving early diagnosis and the outcome of kidney diseases.

Metabolomic Changes in Patients Affected by Multiple Sclerosis and Treated with Fingolimod.

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.

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolites Analysis in Endometriosis Patients: A Prospective Observational Translational Study.

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.

Right Ventricular Subclinical Dysfunction in SLE Patients Correlates with Metabolomic Fingerprint and Organ Damage.

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.