Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Human-derived fecal microbiota transplantation alleviates social deficits of the BTBR mouse model of autism through a potential mechanism involving vitamin B6 metabolism

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by social communication deficiencies and stereotypic behaviors influenced by hereditary and/or environmental risk factors. There are currently no approved medications for treating the core symptoms of ASD. Human fecal microbiota transplantation (FMT) has emerged as a potential intervention to improve autistic symptoms, but the underlying mechanisms are not fully understood. In this study, we evaluated the effects of human-derived FMT on behavioral and multi-omics profiles of the BTBR mice, an established model for ASD. FMT effectively alleviated the social deficits in the BTBR mice and normalized their distinct plasma metabolic profile, notably reducing the elevated long-chain acylcarnitines. Integrative analysis linked these phenotypic changes to specific Bacteroides species and vitamin B6 metabolism. Indeed, vitamin B6 supplementation improved the social behaviors in BTBR mice. Collectively, these findings shed new light on the interplay between FMT and vitamin B6 metabolism and revealed a potential mechanism underlying the therapeutic role of FMT in ASD.IMPORTANCEAccumulating evidence supports the beneficial effects of human fecal microbiota transplantation (FMT) on symptoms associated with autism spectrum disorder (ASD). However, the precise mechanism by which FMT induces a shift in the microbiota and leads to symptom improvement remains incompletely understood. This study integrated data from colon-content metagenomics, colon-content metabolomics, and plasma metabolomics to investigate the effects of FMT treatment on the BTBR mouse model for ASD. The analysis linked the amelioration of social deficits following FMT treatment to the restoration of mitochondrial function and the modulation of vitamin B6 metabolism. Bacterial species and compounds with beneficial roles in vitamin B6 metabolism and mitochondrial function may further contribute to improving FMT products and designing novel therapies for ASD treatment.

Characterisation and critical processes identification for production of herbal preparations using 1H-NMR and chemometrics: A case study of Trichosanthis Pericarpium injection

INTRODUCTION

Herbal preparations are extensively utilised for the treatment of diseases in Asian countries. However, the variations in origin, climate, and production processes can lead to inconsistencies in the quality of herbal preparations. Existing quality control methods only target a few components in the finished product but ignore the control in the pharmaceutical process. Therefore, this study intends to develop a comprehensive component analysis method for intermediates in the pharmaceutical process to reveal the change patterns of substances and deepen the process understanding.

OBJECTIVE

This study aims to develop a rapid and comprehensive process characterisation and critical process identification method for herbal preparations.

METHODS

Six batches of Trichosanthis Pericarpium injection (TPI) intermediates were collected from the production process. Proton nuclear magnetic resonance (1H-NMR) spectra were acquired for qualitative and quantitative analysis of the se intermediates. Subsequently, chemometrics were used to identify critical processes and potential chemical markers.

RESULTS

A total of 39 components in intermediates were identified, and the transfer of 25 components during the production process was investigated. Column chromatography was determined as the critical process. Nine components were identified as chemical markers.

CONCLUSION

The application of 1H-NMR facilitated a comprehensive reflection of the chemical composition information of process intermediates, enabling investigations into the transfer of multi-component substances and accurate identification of critical processes and chemical markers.

Host-microbiome orchestration of the sulfated metabolome

Recent studies have demonstrated that metabolites produced by commensal bacteria causally influence health and disease. The sulfated metabolome is one class of molecules that has recently come to the forefront due to efforts to understand the role of these metabolites in host-microbiome interactions. Sulfated compounds have canonically been classified as waste products; however, studies have revealed a variety of physiological roles for these metabolites, including effects on host metabolism, immune response and neurological function. Moreover, recent research has revealed that commensal bacteria either chemically modify or synthesize a variety of sulfated compounds. In this Review, we explore how host-microbiome collaborative metabolism transforms the sulfated metabolome. We describe bacterial and mammalian enzymes that sulfonate and desulfate biologically relevant carbohydrates, amino acid derivatives and cholesterol-derived metabolites. We then discuss outstanding questions and future directions in the field, including potential roles of sulfated metabolites in disease detection, prevention and treatment. We hope that this Review inspires future research into sulfated compounds and their effects on physiology.

Using urine FTIR spectra to screen autism spectrum disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder caused by multiple factors, lacking clear biomarkers. Diagnosing ASD still relies on behavioural and developmental signs and usually requires lengthy observation periods, all of which are demanding for both clinicians and parents. Although many studies have revealed valuable knowledge in this field, no clearly defined, practical, and widely acceptable diagnostic tool exists. In this study, 26 children with ASD (ASD+), aged 3-5 years, and 26 sex and age-matched controls are studied to investigate the diagnostic potential of the Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The urine FTIR spectrum results show a downward trend in the 3000-2600/cm region for ASD+ children when compared to the typically developing (TD) children of the same age. The average area of this region is 25% less in ASD+ level 3 children, 29% less in ASD+ level 2 children, and 16% less in ASD+ level 1 children compared to that of the TD children. Principal component analysis was applied to the two groups using the entire spectrum window and five peaks were identified for further analysis. The correlation between the peaks and natural urine components is validated by artificial urine solutions. Less-than-normal levels of uric acid, phosphate groups, and ammonium ([Formula: see text]) can be listed as probable causes. This study shows that ATR-FTIR can serve as a practical and non-invasive method to screen ASD using the high-frequency region of the urine spectrum.

Investigating the Urinary Metabolome in the First Year of Life and Its Association with Later Diagnosis of Autism Spectrum Disorder or Non-Typical Neurodevelopment in the MARBLES Study

Developmental disabilities are often associated with alterations in metabolism. However, it remains unknown how early these metabolic issues may arise. This study included a subset of children from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) prospective cohort study. In this analysis, 109 urine samples collected at 3, 6, and/or 12 months of age from 70 children with a family history of ASD who went on to develop autism spectrum disorder (ASD n = 17), non-typical development (Non-TD n = 11), or typical development (TD n = 42) were investigated by nuclear magnetic resonance (NMR) spectroscopy to measure urinary metabolites. Multivariate principal component analysis and a generalized estimating equation were performed with the objective of exploring the associations between urinary metabolite levels in the first year of life and later adverse neurodevelopment. We found that children who were later diagnosed with ASD tended to have decreased urinary dimethylamine, guanidoacetate, hippurate, and serine, while children who were later diagnosed with Non-TD tended to have elevated urinary ethanolamine and hypoxanthine but lower methionine and homovanillate. Children later diagnosed with ASD or Non-TD both tended to have decreased urinary 3-aminoisobutyrate. Our results suggest subtle alterations in one-carbon metabolism, gut-microbial co-metabolism, and neurotransmitter precursors observed in the first year of life may be associated with later adverse neurodevelopment.

Relationship between Excreted Uremic Toxins and Degree of Disorder of Children with ASD

Autism spectrum disorder (ASD) is a complex developmental disorder in which communication and behavior are affected. A number of studies have investigated potential biomarkers, including uremic toxins. The aim of our study was to determine uremic toxins in the urine of children with ASD (143) and compare the results with healthy children (48). Uremic toxins were determined with a validated high-performance liquid chromatography coupled to mass spectrometry (LC-MS/MS) method. We observed higher levels of p-cresyl sulphate (pCS) and indoxyl sulphate (IS) in the ASD group compared to the controls. Moreover, the toxin levels of trimethylamine N-oxide (TMAO), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were lower in ASD patients. Similarly, for pCS and IS in children classified, according to the intensity of their symptoms, into mild, moderate, and severe, elevated levels of these compounds were observed. For mild severity of the disorder, elevated levels of TMAO and comparable levels of SDMA and ADMA for ASD children as compared to the controls were observed in the urine. For moderate severity of ASD, significantly elevated levels of TMAO but reduced levels of SDMA and ADMA were observed in the urine of ASD children as compared to the controls. When the results obtained for severe ASD severity were considered, reduced levels of TMAO and comparable levels of SDMA and ADMA were observed in ASD children.

Differences of gut microbiota and behavioral symptoms between two subgroups of autistic children based on γδT cells-derived IFN-γ Levels: A preliminary study

Background

Autism Spectrum Disorders (ASD) are defined as a group of pervasive neurodevelopmental disorders, and the heterogeneity in the symptomology and etiology of ASD has long been recognized. Altered immune function and gut microbiota have been found in ASD populations. Immune dysfunction has been hypothesized to involve in the pathophysiology of a subtype of ASD.

Methods

A cohort of 105 ASD children were recruited and grouped based on IFN-γ levels derived from ex vivo stimulated γδT cells. Fecal samples were collected and analyzed with a metagenomic approach. Comparison of autistic symptoms and gut microbiota composition was made between subgroups. Enriched KEGG orthologues markers and pathogen-host interactions based on metagenome were also analyzed to reveal the differences in functional features.

Results

The autistic behavioral symptoms were more severe for children in the IFN-γ-high group, especially in the body and object use, social and self-help, and expressive language performance domains. LEfSe analysis of gut microbiota revealed an overrepresentation of Selenomonadales, Negatiyicutes, Veillonellaceae and Verrucomicrobiaceae and underrepresentation of Bacteroides xylanisolvens and Bifidobacterium longum in children with higher IFN-γ level. Decreased metabolism function of carbohydrate, amino acid and lipid in gut microbiota were found in the IFN-γ-high group. Additional functional profiles analyses revealed significant differences in the abundances of genes encoding carbohydrate-active enzymes between the two groups. And enriched phenotypes related to infection and gastroenteritis and underrepresentation of one gut-brain module associated with histamine degradation were also found in the IFN-γ-High group. Results of multivariate analyses revealed relatively good separation between the two groups.

Conclusions

Levels of IFN-γ derived from γδT cell could serve as one of the potential candidate biomarkers to subtype ASD individuals to reduce the heterogeneity associated with ASD and produce subgroups which are more likely to share a more similar phenotype and etiology. A better understanding of the associations among immune function, gut microbiota composition and metabolism abnormalities in ASD would facilitate the development of individualized biomedical treatment for this complex neurodevelopmental disorder.

Global metabolic profiles in a non-human primate model of maternal immune activation: implications for neurodevelopmental disorders

Epidemiological evidence implicates severe maternal infections as risk factors for neurodevelopmental disorders, such as ASD and schizophrenia. Accordingly, animal models mimicking infection during pregnancy, including the maternal immune activation (MIA) model, result in offspring with neurobiological, behavioral, and metabolic phenotypes relevant to human neurodevelopmental disorders. Most of these studies have been performed in rodents. We sought to better understand the molecular signatures characterizing the MIA model in an organism more closely related to humans, rhesus monkeys (Macaca mulatta), by evaluating changes in global metabolic profiles in MIA-exposed offspring. Herein, we present the global metabolome in six peripheral tissues (plasma, cerebrospinal fluid, three regions of intestinal mucosa scrapings, and feces) from 13 MIA and 10 control offspring that were confirmed to display atypical neurodevelopment, elevated immune profiles, and neuropathology. Differences in lipid, amino acid, and nucleotide metabolism discriminated these MIA and control samples, with correlations of specific metabolites to behavior scores as well as to cytokine levels in plasma, intestinal, and brain tissues. We also observed modest changes in fecal and intestinal microbial profiles, and identify differential metabolomic profiles within males and females. These findings support a connection between maternal immune activation and the metabolism, microbiota, and behavioral traits of offspring, and may further the translational applications of the MIA model and the advancement of biomarkers for neurodevelopmental disorders such as ASD or schizophrenia.

Immediate-Early Modifications to the Metabolomic Profile of the Perilymph Following an Acoustic Trauma in a Sheep Model

The pathophysiological mechanisms of noise-induced hearing loss remain unknown. Identifying biomarkers of noise-induced hearing loss may increase the understanding of pathophysiological mechanisms of deafness, allow for a more precise diagnosis, and inform personalized treatment. Emerging techniques such as metabolomics can help to identify these biomarkers. The objective of the present study was to investigate immediate-early changes in the perilymph metabolome following acoustic trauma. Metabolomic analysis was performed using liquid chromatography coupled to mass spectrophotometry to analyze metabolic changes in perilymph associated with noise-induced hearing loss. Sheep (n = 6) were exposed to a noise designed to induce substantial hearing loss. Perilymph was collected before and after acoustic trauma. Data were analyzed using univariate analysis and a supervised multivariate analysis based on partial least squares discriminant analysis. A metabolomic analysis showed an abundance of 213 metabolites. Four metabolites were significantly changed following acoustic trauma (Urocanate (p = 0.004, FC = 0.48), S-(5’-Adenosyl)-L-Homocysteine (p = 0.06, FC = 2.32), Trigonelline (p = 0.06, FC = 0.46) and N-Acetyl-L-Leucine (p = 0.09, FC = 2.02)). The approach allowed for the identification of new metabolites and metabolic pathways involved with acoustic trauma that were associated with auditory impairment (nerve damage, mechanical destruction, and oxidative stress). The results suggest that metabolomics provides a powerful approach to characterize inner ear metabolites which may lead to identification of new therapies and therapeutic targets.

First Metabolomic Signature of Blood-Brain Barrier Opening Induced by Microbubble-Assisted Ultrasound

Microbubble (MB)-assisted ultrasound (US) is a promising physical method to increase non-invasively, transiently, and precisely the permeability of the blood-brain barrier (BBB) to therapeutic molecules. Previous preclinical studies established the innocuity of this procedure using complementary analytical strategies including transcriptomics, histology, brain imaging, and behavioral tests. This cross-sectional study using rats aimed to investigate the metabolic processes following acoustically-mediated BBB opening in vivo using multimodal and multimatrices metabolomics approaches. After intravenous injection of MBs, the right striata were exposed to 1-MHz sinusoidal US waves at 0.6 MPa peak negative pressure with a burst length of 10 ms, for 30 s. Then, the striata, cerebrospinal fluid (CSF), blood serum, and urine were collected during sacrifice in three experimental groups at 3 h, 2 days, and 1 week after BBB opening (BBBO) and were compared to a control group where no US was applied. A well-established analytical workflow using nuclear magnetic resonance spectrometry and non-targeted and targeted high-performance liquid chromatography coupled to mass spectrometry were performed on biological tissues and fluids. In our experimental conditions, a reversible BBBO was observed in the striatum without physical damage or a change in rodent weight and behavior. Cerebral, peri-cerebral, and peripheral metabolomes displayed specific and sequential metabolic kinetics. The blood serum metabolome was more impacted in terms of the number of perturbated metabolisms than in the CSF, the striatum, and the urine. In addition, perturbations of arginine and arginine-related metabolisms were detected in all matrices after BBBO, suggesting activation of vasomotor processes and bioenergetic supply. The exploration of the tryptophan metabolism revealed a transient vascular inflammation and a perturbation of serotoninergic neurotransmission in the striatum. For the first time, we characterized the metabolic signature following the acoustically-mediated BBBO within the striatum and its surrounding biological compartments.

NMR-Based Metabolomics of Rat Hippocampus, Serum, and Urine in Two Models of Autism

Autism spectrum disorders (ASDs) are increasingly diagnosed as developmental disabilities of unclear etiology related to genetic, epigenetic, or environmental factors. The diagnosis of ASD in children is based on the recognition of typical behavioral symptoms, while no reliable biomarkers are available. Rats in whom ASD-like symptoms are due to maternal administration of the teratogenic drugs valproate or thalidomide on critical day 11 of pregnancy are widely used models in autism research. The present studies, aimed at detecting changes in the levels of hydrophilic and hydrophobic metabolites, were carried out on 1-month-old rats belonging to the abovementioned two ASD models and on a control group. Analysis of both hydrophilic and hydrophobic metabolite levels gives a broader view of possible mechanisms involved in the pathogenesis of autism. Hippocampal proton magnetic resonance (MRS) spectroscopy and ex vivo nuclear magnetic resonance (NMR) analysis of serum and urine samples were used. The results were analyzed using advanced statistical tests. Both the results of our present MRS studies of the hippocampus and of the NMR studies of body fluids in both ASD models, particularly from the THAL model, appeared to be consistent with previously published NMR results of hippocampal homogenates and data from the literature on autistic children. We detected symptoms of disturbances in neurotransmitter metabolism, energy deficit, and oxidative stress, as well as intestinal malfunction, which shed light on the pathogenesis of ASD and could be used for diagnostic purposes. These results confirm the usefulness of the noninvasive techniques used in ASD studies.

Metabolic Profile and Pathological Alterations in the Muscle of Patients with Early-Stage Amyotrophic Lateral Sclerosis

Diverse biomarkers and pathological alterations have been found in muscle of patients with Amyotrophic lateral sclerosis (ALS), but the relation between such alterations and dysfunction in energetic metabolism remains to be investigated. We established the metabolome of muscle and serum of ALS patients and correlated these findings with the clinical status and pathological alterations observed in the muscle. We obtained data from 20 controls and 17 ALS patients (disease duration: 9.4 ± 6.8 months). Multivariate metabolomics analysis identified a distinct serum metabolome for ALS compared to controls (p-CV-ANOVA < 0.035) and revealed an excellent discriminant profile for muscle metabolome (p-CV-ANOVA < 0.0012). Citramalate was discriminant for both muscle and serum. High lauroylcarnitine levels in muscle were associated with low Forced Vital Capacity. Transcriptomics analysis of key antioxidant enzymes showed an upregulation of SOD3 (p = 0.0017) and GLRX2(1) (p = 0.0022) in ALS muscle. Analysis of mitochondrial enzymatic activity in muscle revealed higher complex II/CS (p = 0.04) and lower LDH (p = 0.03) activity in ALS than in controls. Our study showed, for the first time, a global dysfunction in the muscle of early-stage ALS patients. Furthermore, we identified novel metabolites to be employed as biomarkers for diagnosis and prognosis of ALS patients.

Multivariate Analysis of Metabolomic and Nutritional Profiles among Children with Autism Spectrum Disorder

There have been promising results regarding the capability of statistical and machine-learning techniques to offer insight into unique metabolomic patterns observed in ASD. This work re-examines a comparative study contrasting metabolomic and nutrient measurements of children with ASD (n = 55) against their typically developing (TD) peers (n = 44) through a multivariate statistical lens. Hypothesis testing, receiver characteristic curve assessment, and correlation analysis were consistent with prior work and served to underscore prominent areas where metabolomic and nutritional profiles between the groups diverged. Improved univariate analysis revealed 46 nutritional/metabolic differences that were significantly different between ASD and TD groups, with individual areas under the receiver operator curve (AUROC) scores of 0.6–0.9. Many of the significant measurements had correlations with many others, forming two integrated networks of interrelated metabolic differences in ASD. The TD group had 189 significant correlation pairs between metabolites, vs. only 106 for the ASD group, calling attention to underlying differences in metabolic processes. Furthermore, multivariate techniques identified potential biomarker panels with up to six metabolites that were able to attain a predictive accuracy of up to 98% for discriminating between ASD and TD, following cross-validation. Assessing all optimized multivariate models demonstrated concordance with prior physiological pathways identified in the literature, with some of the most important metabolites for discriminating ASD and TD being sulfate, the transsulfuration pathway, uridine (methylation biomarker), and beta-amino isobutyrate (regulator of carbohydrate and lipid metabolism).

Curcumin and NCLX inhibitors share anti-tumoral mechanisms in microsatellite-instability-driven colorectal cancer

BACKGROUND AND AIMS

Recent evidences highlight a role of the mitochondria calcium homeostasis in the development of colorectal cancer (CRC). To overcome treatment resistance, we aimed to evaluate the role of the mitochondrial sodium-calcium-lithium exchanger (NCLX) and its targeting in CRC. We also identified curcumin as a new inhibitor of NCLX.

METHODS

We examined whether curcumin and pharmacological compounds induced the inhibition of NCLX-mediated mitochondrial calcium (mtCa2+) extrusion, the role of redox metabolism in this process. We evaluated their anti-tumorigenic activity in vitro and in a xenograft mouse model. We analyzed NCLX expression and associations with survival in The Cancer Genome Atlas (TCGA) dataset and in tissue microarrays from 381 patients with microsatellite instability (MSI)-driven CRC.

RESULTS

In vitro, curcumin exerted strong anti-tumoral activity through its action on NCLX with mtCa2+ and reactive oxygen species overload associated with a mitochondrial membrane depolarization, leading to reduced ATP production and apoptosis. NCLX inhibition with pharmacological and molecular approaches reproduced the effects of curcumin. NCLX inhibitors decreased CRC tumor growth in vivo. Both transcriptomic analysis of TCGA dataset and immunohistochemical analysis of tissue microarrays demonstrated that higher NCLX expression was associated with MSI status, and for the first time, NCLX expression was significantly associated with recurrence-free survival.

CONCLUSIONS

Our findings highlight a novel anti-tumoral mechanism of curcumin through its action on NCLX and mitochondria calcium overload that could benefit for therapeutic schedule of patients with MSI CRC.

Senecavirus A- and Non-Infected Cells at Early Stage of Infection: Comparative Metabolomic Profiles

Senecavirus A (SVA), classified into the genus Senecavirus in the family Picornaviridae, causes an infectious disease in pigs. This virus can efficiently replicate in some non-pig-derived cells, such as the BHK cell line and its derivative (BSR-T7/5 cell line). We had recovered a wild-type SVA from its cDNA clone previously, and then uncovered the proteomic profile of SVA-infected BSR-T7/5 cells at 12 h post inoculation (hpi). In order to explore the cellular metabolomics further, the SVA-inoculated BSR-T7/5 cell monolayer was collected at 12 hpi for assay via liquid chromatography-tandem mass spectrometry (LC-MS/MS). The resultant data set was comprehensively analyzed using bioinformatics tools. A total of 451 metabolites were identified using in-house and public databases. Out of these metabolites, sixty-one showed significantly differential values (p value < 0.05). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to analyze metabolic pathways of the significantly differential metabolites. There were eighty-one identified KEGG pathways, out of which twenty-seven showed their p values < 0.05. The pyrimidine metabolism revealed the minimum p value and the maximum number of significantly differential metabolites, implying the pyrimidine played a key role in cellular metabolism after SVA infection. SVA replication must rely on the cellular metabolism. The present study on metabolomics would shed light on impacts of SVA-induced multiple interactions among metabolites on cells or even on natural hosts.

Alteration of the Intestinal Permeability Are Reflected by Changes in the Urine Metabolome of Young Autistic Children: Preliminary Results

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.

Metabolomics profiling of valproic acid-induced symptoms resembling autism spectrum disorders using 1H NMR spectral analysis in rat model

Prenatal exposure to valproic acid (VPA) has been implicated in the manifestation of autism spectrum disorder (ASD)-like behavioral and functional changes both in human and rodents including mice and rats. The objective of this study was to determine metabolomics profiling and biomarkers related to VPA-induced symptoms resembling ASD using proton nuclear magnetic resonance (1H-NMR) spectral data. VPA was administered to pregnant rats at gestation day 12.5 and effects measured subsequently in male 4-week-old offspring pups. The sociability of VPA-treated animals was significantly diminished and exhibited ASD-like behavior as evidenced by reduction of social adaptation disorder and lack of social interactions. To find biomarkers related to ASD, the following were collected prefrontal brain cortices, urine bladder and blood samples directly from heart puncture. In all samples, principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) displayed significant clustering pattern differences between control and treated groups. Valine, taurine, myo-inositol, 3-hydroxybutyrate and 1,3-dihydroxyacetone were significantly decreased in brain cortices in treated rats. Serum metabolites of glucose, creatine phosphate, lactate, glutamine and threonine were significantly increased in VPA-administered animals. Urinary metabolites of pimelate, 3-hydroxyisovalerate and valerate were significantly reduced in VPA-treated rat, whereas galactose and galactonate levels were elevated. Various metabolites were associated with mitochondrial dysfunction metabolism and central nervous system disorders. Data demonstrated that VPA-induced alterations in endogenous metabolites of serum, urine, and brain cortex which might prove useful as biomarkers for symptoms resembling ASD as a model of this disorder.

Multiplexed Analysis of Endogenous Guanidino Compounds via Isotope-Coded Doubly Charged Labeling: Application to Lung Cancer Tissues as a Case

Endogenous guanidino compounds (GCs), nitrogen-containing metabolites, have very important physiological activities and participate in biochemical processes. Therefore, accurately characterizing the distribution of endogenous GCs and monitoring their concentration variations are of great significance. In this work, a new derivatization reagent, 4,4'-bis[3-(dimethylamino)propyl]benzyl (BDMAPB), with isotope-coded reagents was designed and synthesized for doubly charged labeling of GCs. BDMAPB-derivatized GCs not only promote the MS signal but also form multicharged quasimolecular ions and abundant fragment ions. With this reagent, an isotope-coded doubly charged labeling (ICDCL) strategy was developed for endogenous GCs with high-resolution liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF MS). The core of this methodology is a 4-fold multiplexed set of [d₀]-/[d₄]-/[d₈]-/[d₁₂]-BDMAPB that yields isotope-coded derivatized GCs. Following a methodological assessment, good linear responses in the range of 25 nM to 1 μM with correlation coefficients over 0.99 were achieved. The limit of detection and the limit of quantitation were below 5 and 25 nM, respectively. The intra- and interday precisions were less than 18%, and the accuracy was in the range of 77.3-122.0%. The percentage recovery in tissues was in the range of 85.1-113.7%. The results indicate that the developed method facilitates long-term testing and ensures accuracy and reliability. Finally, the method was applied for the simultaneous analysis of endogenous GCs in four types of lung tissues (solid adenocarcinoma, solid squamous-cell carcinoma, ground-glass carcinoma, and paracancerous tissues) for absolute quantification, nontargeted screening, and metabolic difference analysis. It is strongly believed that ICDCL combined with isotope-coded BDMAPB will benefit the analysis and study of endogenous GCs.

The Brain-Gut-Microbiome System: Pathways and Implications for Autism Spectrum Disorder

Gastrointestinal dysfunction is one of the most prevalent physiological symptoms of autism spectrum disorder (ASD). A growing body of largely preclinical research suggests that dysbiotic gut microbiota may modulate brain function and social behavior, yet little is known about the mechanisms that underlie these relationships and how they may influence the pathogenesis or severity of ASD. While various genetic and environmental risk factors have been implicated in ASD, this review aims to provide an overview of studies elucidating the mechanisms by which gut microbiota, associated metabolites, and the brain interact to influence behavior and ASD development, in at least a subgroup of individuals with gastrointestinal problems. Specifically, we review the brain-gut-microbiome system and discuss findings from current animal and human studies as they relate to social-behavioral and neurological impairments in ASD, microbiota-targeted therapies (i.e., probiotics, fecal microbiota transplantation) in ASD, and how microbiota may influence the brain at molecular, structural, and functional levels, with a particular interest in social and emotion-related brain networks. A deeper understanding of microbiome-brain-behavior interactions has the potential to inform new therapies aimed at modulating this system and alleviating both behavioral and physiological symptomatology in individuals with ASD.

Altered Metabolic Characteristics in Plasma of Young Boys with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a serious neurodevelopmental disorder with no clinical biomarker. This study used untargeted metabolomic analysis to identify metabolic characteristics in plasma that can distinguish ASD children. 29 boys with ASD (3.02 ± 0.67 years) and 30 typically developing (TD) boys (3.13 ± 0.46 years) were recruited. Developmental and behavioral assessments were conducted in ASD group. Samples of plasma were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The association between metabolite concentration and scale score was assessed by Spearman rank correlation. Altered metabolic characteristics were found in boys with ASD. In Receiver Operating Characteristic (ROC) analysis, ornithine had the highest AUC (Area under ROC) value. Furthermore, the concentration of choline and ornithine was negatively correlated with ABC-language score in ASD group.

Plasma metabolomics of autism spectrum disorder and influence of shared components in proband families

Prevalence of autism spectrum disorder (ASD) has been increasing in the United States in the past decades. The exact mechanisms remain enigmatic, and diagnosis of the disease still relies primarily on assessment of behavior. We first used a case-control design (75 idiopathic cases and 29 controls, enrolled at Boston Children's Hospital from 2007-2012) to identify plasma biomarkers of ASD through a metabolome-wide association study approach. Then we leveraged a family-based design (31 families) to investigate the influence of shared genetic and environmental components on the autism-associated features. Using untargeted high-resolution mass spectrometry metabolomics platforms, we detected 19 184 features. Of these, 191 were associated with ASD (false discovery rate < 0.05). We putatively annotated 30 features that had an odds ratio (OR) between <0.01 and 5.84. An identified endogenous metabolite, O-phosphotyrosine, was associated with an extremely low autism odds (OR 0.17; 95% confidence interval 0.06-0.39). We also found that glutathione metabolism was associated with ASD (P = 0.048). Correlations of the significant features between proband and parents were low (median = 0.09). Of the 30 annotated features, the median correlations within families (proband-parents) were -0.15 and 0.24 for the endogenous and exogenous metabolites, respectively. We hypothesize that, without feature identification, family-based correlation analysis of autism-associated features can be an alternative way to assist the prioritization of potentially diagnostic features. A panel of ASD diagnostic metabolic markers with high specificity could be derived upon further studies.

Profiles of urine and blood metabolomics in autism spectrum disorders

Early diagnosis and treatment for autism spectrum disorder (ASD) pose challenges. The current diagnostic approach for ASD is mainly clinical assessment of patient behaviors. Biomarkers-based identification of ASD would be useful for pediatricians. Currently, there is no specific treatment for ASD, and evidence for the efficacy of alternative treatments remains inconclusive. The prevalence of ASD is increasing, and it is becoming more urgent to find the pathogenesis of such disorder. Metabolomic studies have been used to deeply investigate the alteration of metabolic pathways, including those associated with ASD. Metabolomics is a promising tool for identifying potential biomarkers and possible pathogenesis of ASD. This review comprehensively summarizes and discusses the abnormal metabolic pathways in ASD children, as indicated by evidence from metabolomic studies in urine and blood. In addition, the targeted interventions that could correct the metabolomic profiles relating to the improvement of autistic behaviors in affected animals and humans have been included. The results revealed that the possible underlying pathophysiology of ASD were alterations of amino acids, reactive oxidative stress, neurotransmitters, and microbiota-gut-brain axis. The potential common pathways shared by animal and human studies related to the improvement of ASD symptoms after pharmacological interventions were mammalian-microbial co-metabolite, purine metabolism, and fatty acid oxidation. The content of this review may contribute to novel biomarkers for the early diagnosis of ASD and possible therapeutic paradigms.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

Maternal and cord plasma metabolomics were used to elucidate biological pathways associated with increased diagnosis risk for autism spectrum disorders (ASD). Metabolome-wide associations were assessed in both maternal and umbilical cord plasma in relation to diagnoses of ASD and other non-typical development (Non-TD) compared to typical development (TD) in the Markers of Autism risk in Babies: Learning Early Signs (MARBLES) cohort study of children born to mothers who already have at least one child with ASD. Analyses were stratified by sample matrix type, machine mode, and annotation confidence level. Dimensionality reduction techniques were used [i.e, principal component analysis (PCA) and random subset weighted quantile sum regression (WQS_RS)] to minimize the high multiple comparison burden. With WQS_RS, a metabolite mixture obtained from the negative mode of maternal plasma decreased the odds of Non-TD compared to TD. These metabolites, all related to the prostaglandin pathway, underscored the relevance of neuroinflammation status. No other significant findings were observed. Dimensionality reduction strategies provided confirming evidence that a set of maternal plasma metabolites are important in distinguishing Non-TD compared to TD diagnosis. A lower risk for Non-TD was linked to anti-inflammatory elements, thereby linking neuroinflammation to detrimental brain function consistent with studies ranging from neurodevelopment to neurodegeneration.

The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

BACKGROUND

Autism spectrum disorders (ASD) are associated with dysregulation of the microbiota-gut-brain axis, changes in microbiota composition as well as in the fecal, serum, and urine levels of microbial metabolites. Yet a causal relationship between dysregulation of the microbiota-gut-brain axis and ASD remains to be demonstrated. Here, we hypothesized that the microbial metabolite p-Cresol, which is more abundant in ASD patients compared to neurotypical individuals, could induce ASD-like behavior in mice.

RESULTS

Mice exposed to p-Cresol for 4 weeks in drinking water presented social behavior deficits, stereotypies, and perseverative behaviors, but no changes in anxiety, locomotion, or cognition. Abnormal social behavior induced by p-Cresol was associated with decreased activity of central dopamine neurons involved in the social reward circuit. Further, p-Cresol induced changes in microbiota composition and social behavior deficits could be transferred from p-Cresol-treated mice to control mice by fecal microbiota transplantation (FMT). We also showed that mice transplanted with the microbiota of p-Cresol-treated mice exhibited increased fecal p-Cresol excretion, compared to mice transplanted with the microbiota of control mice. In addition, we identified possible p-Cresol bacterial producers. Lastly, the microbiota of control mice rescued social interactions, dopamine neurons excitability, and fecal p-Cresol levels when transplanted to p-Cresol-treated mice.

CONCLUSIONS

The microbial metabolite p-Cresol induces selectively ASD core behavioral symptoms in mice. Social behavior deficits induced by p-Cresol are dependant on changes in microbiota composition. Our study paves the way for therapeutic interventions targeting the microbiota and p-Cresol production to treat patients with ASD. Video abstract.

A proteomic analysis of urine biomarkers in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by early-onset social-communication challenges, restricted and repetitive behaviors, or unusual sensory-motor behaviors. A lack of specific biomarkers hinders the early diagnosis and treatment of this disease in many children. This study analyzes and validates potential urinary biomarkers using mass spectrometry proteomics. Global proteomics profiles of urine from 19 ASD patients and 19 healthy control subjects were compared to identify significantly changed proteins. These proteins were validated with targeted proteomics using parallel reaction monitoring (PRM) in an independent validation set consisting of samples from 40 ASD patients and 38 healthy controls. A total of 34 significantly changed proteins were found in the discovery set, among which seven proteins were identified as potential biomarkers for ASD through PRM assays in the validation set. Of these seven proteins, immunoglobulin kappa variable 4-1, immunoglobulin kappa variable 3-20, and immunoglobulin lambda variable 1-51 were up-regulated, while ATP synthase F1 subunit alpha, 10 kDa heat shock protein, apolipoprotein C-III, and arylsulfatase F were down-regulated. Six of these seven proteins support previous findings that ASD is accompanied by altered immune response and lipid metabolism, as well as mitochondrial dysfunction. This study lays the groundwork for additional research using biomarkers to clinically diagnose ASD. The proteomics and PRM raw data of this study have been deposited under the accession number IPX0002592000 at iProX. SIGNIFICANCE: This study identified 34 proteins in urine of ASD patients that were significantly changed from the urinary proteins of healthy subjects using LC-MS/MS-based proteomics in a discovery set. Seven of these proteins were validated by PRM analysis in an independent validation set. This report represents the first description of combined label-free quantitative proteomics and PRM analysis of targeted proteins for discovery of ASD urinary biomarkers. The results will be helpful for early diagnosis and can provide additional insight into the molecular mechanisms of ASD.

Metabolomics analysis of maternal serum exposed to high air pollution during pregnancy and risk of autism spectrum disorder in offspring

BACKGROUND

Previously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring.

OBJECTIVES

To identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD.

METHODS

We obtained stored mid-pregnancy serum from 214 mothers who lived in California's Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman's average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter <2.5 μm) during the first trimester using the California Line Source Dispersion Model, version 4 (CALINE4). By utilizing liquid chromatography-high resolution mass spectrometry, we identified the metabolic profiles of maternal serum for 116 mothers with offspring who later developed ASD and 98 control mothers. Partial least squares discriminant analysis (PLS-DA) was employed to select metabolic features associated with air pollution exposure or autism risk in offspring. We also conducted extensive pathway enrichment analysis to elucidate potential ASD-related changes in the metabolome of pregnant women.

RESULTS

We extracted 4022 and 4945 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for potential confounders, we identified 167 and 222 discriminative features (HILIC and C18, respectively). Pathway enrichment analysis to discriminate metabolic features associated with ASD risk indicated various metabolic pathway perturbations linked to the tricarboxylic acid (TCA) cycle and mitochondrial function, including carnitine shuttle, amino acid metabolism, bile acid metabolism, and vitamin A metabolism.

CONCLUSION

Using high resolution metabolomics, we identified several metabolic pathways disturbed in mothers with ASD offspring among women experiencing high exposure to traffic-related air pollution during pregnancy that were associated with mitochondrial dysfunction. These findings provide us with a better understanding of metabolic disturbances involved in the development of ASD under adverse environmental conditions.

Design of Multi-Shelled Hollow Cr2 O3 Spheres for Metabolic Fingerprinting

Schizophrenia (SZ) detection enables effective treatment to improve the clinical outcome, but objective and reliable SZ diagnostics are still limited. An ideal diagnosis of SZ suited for robust clinical screening must address detection throughput, low invasiveness, and diagnosis accuracy. Herein, we built a multi-shelled hollow Cr₂ O₃ spheres (MHCSs) assisted laser desorption/ionization mass spectrometry (LDI MS) platform for the direct metabolic profiling of biofluids towards SZ diagnostics. The MHCSs displayed strong light absorption for enhanced ionization and microscale surface roughness with stability for the effective LDI of metabolites. We profiled urine and serum metabolites (≈1 μL) with the enhanced LDI efficacy in seconds. We discriminated SZ patients (SZs) from healthy controls (HCs) with the highest area under the curve (AUC) value of 1.000 for the blind test. We identified four compounds with optimal diagnostic power as a simplified metabolite panel for SZ and demonstrated the metabolite quantification for clinic use. Our approach accelerates the growth of new platforms toward a precision diagnosis in the near future.

Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental condition with hallmark behavioral manifestations including impaired social communication and restricted repetitive behavior. In addition, many affected individuals display metabolic imbalances, immune dysregulation, gastrointestinal dysfunction, and altered gut microbiome compositions.

METHODS

We sought to better understand nonbehavioral features of ASD by determining molecular signatures in peripheral tissues through mass spectrometry methods (ultrahigh performance liquid chromatography-tandem mass spectrometry) with broad panels of identified metabolites. Herein, we compared the global metabolome of 231 plasma and 97 fecal samples from a large cohort of children with ASD and typically developing control children.

RESULTS

Differences in amino acid, lipid, and xenobiotic metabolism distinguished ASD and typically developing samples. Our results implicated oxidative stress and mitochondrial dysfunction, hormone level elevations, lipid profile changes, and altered levels of phenolic microbial metabolites. We also revealed correlations between specific metabolite profiles and clinical behavior scores. Furthermore, a summary of metabolites modestly associated with gastrointestinal dysfunction in ASD is provided, and a pilot study of metabolites that can be transferred via fecal microbial transplant into mice is identified.

CONCLUSIONS

These findings support a connection between metabolism, gastrointestinal physiology, and complex behavioral traits and may advance discovery and development of molecular biomarkers for ASD.

Anti-depressant effect of Zhi-zi-chi decoction on CUMS mice and elucidation of its signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Zhi-zi-chi decoction (ZZCD) is used for treating depression as an effectively traditional Chinese medicine. Until now, studies on pharmacological research of ZZCD have mostly been centered in pharmacokinetic level. Little was known about its pharmacological mechanism of relieving depression.

AIM OF THE STUDY

This study was to evaluate the effect of ZZCD on relieving depression via behavioral tests, serum metabolomics and signaling target expression analysis on chronic unpredictable mild stress (CUMS) model mice.

MATERIALS AND METHODS

The CUMS exposure lasted 7 consecutive weeks. The mice were administrated with ZZCD for the last 3 weeks. Behavioral tests were applied and a serum metabolomics method based on UFLC/Q-TOF-MS with multivariate statistical and global metabolic network analysis was performed to identify relevant metabolites and pathways. Finally, the protein expressions in mouse hippocampi were determined by western blot to verify the metabolomics deduction.

RESULTS

Behavioral parameters were visibly changed after modeling, while high and medium dosage groups showed status improvement compared to the model group. Seventy six metabolites were identified as potential biomarkers from the metabolomics profiles in C₁₈ and HILIC systems. In addition, 9 significant pathways related to changed biomarkers were conducted. The pathways were closely connected by some key targets, which were significantly reduced in the model group compared with those in control group, while ZZCD treated groups showed corrections after 3-week administration. The results revealed that the anti-depression efficacy of ZZCD might be associated with PKA-CREB-BDNF-TrkB-PSD-95 pathway influenced by metabolic changes, verifying the pathway annotation speculation.

CONCLUSION

This study demonstrated that ZZCD had a positive treatment effect on CUMS depression model mice. Metabolomics results revealed the holistic and interconnected metabolic changes of ZZCD in CUMS mice. The metabolic pathway annotation suggested that the anti-depression mechanism of ZZCD might be related to signaling pathway in brain. PKA-CREB-BDNF-TrkB-PSD-95 signaling expression was a verification and complement to the metabolomics results.

The Role of Lipidomics in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental syndrome commonly diagnosed in early childhood; it is usually characterized by impairment in reciprocal communication and speech, repetitive behaviors, and social withdrawal with loss in communication skills. Its development may be affected by a variety of environmental and genetic factors. Trained physicians diagnose and evaluate the severity of ASD based on clinical evaluations of observed behaviors. As such, this approach is inevitably dependent on the expertise and subjective assessment of those administering the clinical evaluations. There is a need to identify objective biological markers associated with diagnosis or clinical severity of the disorder. Several important issues and concerns exist regarding the diagnostic competence of the many abnormal plasma metabolites produced in the different biochemical pathways evaluated in individuals with ASD. The search for high-performing bio-analytes to diagnose and follow-up ASD development is still a major target in medicine. Dysregulation in the oxidative stress response and proinflammatory processes are major etiological causes of ASD pathogenesis. Furthermore, dicarboxylic acid metabolites, cholesterol-related metabolites, phospholipid-related metabolites, and lipid transporters and mediators are impaired in different pathological conditions that have a role in the ASD etiology. A mechanism may exist by which pro-oxidant environmental stressors and abnormal metabolites regulate clinical manifestations and development of ASD.

Behavioral, Hormonal, Inflammatory, and Metabolic Effects Associated with FGF21-Pathway Activation in an ALS Mouse Model

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration occurs simultaneously with systemic metabolic dysfunction and neuro-inflammation. The fibroblast growth factor 21 (FGF21) plays an important role in the regulation of both phenomena and is a major hormone of energetic homeostasis. In this study, we aimed to determine the relevance of FGF21 pathway stimulation in a male mouse model of ALS (mutated SOD1-G93A mice) by using a pharmacological agonist of FGF21, R1Mab1. Mice (SOD1-WT and mutant SOD1-G93A) were treated with R1Mab1 or vehicle. Longitudinal data about clinical status (motor function, body weight) and biological parameters (including hormonal, immunological, and metabolomics profiles) were collected from the first symptoms to euthanasia at week 20. Multivariate models were performed to identify the main parameters associated with R1Mab1 treatment and to link them with clinical status, and metabolic pathways involving the discriminant metabolites were also determined. A beneficial clinical effect of R1Mab1 was revealed on slow rotarod (p = 0.032), despite a significant decrease in body weight of ALS mice (p < 0.001). We observed a decrease in serum TNF-α, MCP-1, and insulin levels (p = 0.0059, p = 0.003, and p = 0.01, respectively). At 16 weeks, metabolomics analyses revealed a clear discrimination (CV-ANOVA = 0.0086) according to the treatment and the most discriminant pathways, including sphingolipid metabolism, butanoate metabolism, pantothenate and CoA biosynthesis, and the metabolism of amino acids like tyrosine, arginine, proline, glycine, serine, alanine, aspartate, and glutamate. Mice treated with R1Mab1 had mildly higher performance on slow rotarod despite a decrease on body weight and could be linked with the anti-inflammatory effect of R1Mab1. These results indicate that FGF21 pathway is an interesting target in ALS, with a slight improvement in motor function combined with metabolic and anti-inflammatory effects.

Urinary Metabonomic Profiling Discriminates Between Children with Autism and Their Healthy Siblings

Background

Autism spectrum disorder (ASD) is a complicated neuropsychiatric disease that displays significant heterogeneity. The diagnosis of ASD is currently primarily dependent upon descriptions of clinical symptoms, and it remains urgent to find biological markers for the detection and diagnosis of autism. The current study applied the urinary metabolic profiling approach to characterize metabolic phenotypes in ASD.

Material/Methods

Urine was obtained from children with ASD and their matched healthy siblings. Samples were analyzed using ¹H NMR-based methods designed to measure a broad range of metabolites. Partial least-square-discriminant analysis (PLS-DA) was used to develop models to identify metabonomic variations that can be used to distinguish between individuals with ASD and their unaffected siblings.

Results

A significant difference was observed between the metabolomic profiles of children with ASD and that of their healthy siblings. An increase in the levels of tryptophan, hippurate, glycine, and creatine, and a decrease in trigonelline, melatonin, pantothenate, serotonin, and taurine were observed compared to the control group. We conclude that several metabolic pathways are affected by autism, which suggests that a gut-brain link may be important in the pathophysiology of ASD.

Conclusions

¹H NMR-based metabonomic analysis of the urine can determine perturbations of specific metabolic pathways related to ASD and help identify a characteristic metabolic fingerprint to better understand the disease and its causes.

A Novel UHPLC-MS Method Targeting Urinary Metabolomic Markers for Autism Spectrum Disorder

Autism spectrum disorder is a heterogeneous neurodevelopmental disease. Currently, no biomarker of this disease is known. Diagnosis is performed through observation, standardized behavioral scales, and interviews with parents. In practice, diagnosis is often delayed to the average age of four years or even more which adversely affects a child’s perspective. A laboratory method allowing to detect the disorder at earlier stages is of a great need, as this could help the patients to start with treatment at a younger age, even prior to the clinical diagnosis. Recent evidence indicates that metabolomic markers should be considered as diagnostic markers, also serving for further differentiation and characterization of different subgroups of the autism spectrum. In this study, we developed an ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry method for the simultaneous determination of six metabolites in human urine. These metabolites, namely methylguanidine, N-acetyl arginine, inosine, indole-3-acetic acid, indoxyl sulfate and xanthurenic acid were selected as potential biomarkers according to prior metabolomic studies. The analysis was carried out by means of reversed-phase liquid chromatography with gradient elution. Separation of the metabolites was performed on a Phenomenex Luna^® Omega Polar C18 (100 × 1.0 mm, 1.6 µm) column at a flow rate of 0.15 mL/min with acetonitrile/water 0.1% formic acid aqueous as the mobile phase. The analysis was performed on a group of children with autism spectrum disorder and age-matched controls. In school children, we have detected disturbances in the levels of oxidative stress markers connected to arginine and purine metabolism, namely methylguanidine and N-acetylargine. Also, products of gut bacteria metabolism, namely indoxyl sulfate and indole-3-acetic acid, were found to be elevated in the patients’ group. We can conclude that this newly developed method is fast, sensitive, reliable, and well suited for the quantification of proposed markers.

Inhibition of enteric methanogenesis in dairy cows induces changes in plasma metabolome highlighting metabolic shifts and potential markers of emission

There is scarce information on whether inhibition of rumen methanogenesis induces metabolic changes on the host ruminant. Understanding these possible changes is important for the acceptance of methane-reducing practices by producers. In this study we explored the changes in plasma profiles associated with the reduction of methane emissions. Plasma samples were collected from lactating primiparous Holstein cows fed the same diet with (Treated, n = 12) or without (Control, n = 13) an anti-methanogenic feed additive for six weeks. Daily methane emissions (CH₄, g/d) were reduced by 23% in the Treated group with no changes in milk production, feed intake, body weight, and biochemical indicators of health status. Plasma metabolome analyses were performed using untargeted [nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC–MS)] and targeted (LC–MS/MS) approaches. We identified 48 discriminant metabolites. Some metabolites mainly of microbial origin such as dimethylsulfone, formic acid and metabolites containing methylated groups like stachydrine, can be related to rumen methanogenesis and can potentially be used as markers. The other discriminant metabolites are produced by the host or have a mixed microbial-host origin. These metabolites, which increased in treated cows, belong to general pathways of amino acids and energy metabolism suggesting a systemic non-negative effect on the animal.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Pharmacology of enalapril in children: a review

Enalapril is an angiotensin-converting enzyme (ACE) inhibitor that is used for the treatment of (paediatric) hypertension, heart failure and chronic kidney diseases. Because its disposition, efficacy and safety differs across the paediatric continuum, data from adults cannot be automatically extrapolated to children. This review highlights paediatric enalapril pharmacokinetic data and demonstrates that these are inadequate to support with certainty an age-related effect on enalapril/enalaprilat pharmacokinetics. In addition, our review shows that evidence to support effective and safe prescribing of enalapril in children is limited, especially in young children and heart failure patients; studies in these groups are either absent or show conflicting results. We provide explanations for observed differences between age groups and indications, and describe areas for future research.

Integrated Systems Analysis Explores Dysfunctional Molecular Modules and Regulatory Factors in Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a genetic neurodevelopmental disorder involving multiple genes that occurs in early childhood, and a number of risk genes have been reported in previous studies. However, the molecular mechanism of the polygenic regulation leading to pathological changes in ASD remains unclear. First, we identified 8 dysregulated gene coexpression modules by analyzing blood transcriptome data from 96 children with ASD and 42 controls. These modules are rich in ASD risk genes and function related to metabolism, immunity, neurodevelopment, and signaling. The regulatory factors of each module including microRNA (miRNA) and transcription factors (TFs) were subsequently predicted based on transcriptional and posttranscriptional regulation. We identified a set of miRNAs that regulate metabolic and immune modules, as well as transcription factors that cause dysregulation of the modules, and we constructed a coregulatory network between the regulatory factors and modules. Our work reveals dysfunctional modules in children with ASD, elucidates the role of miRNA and transcription factor dysregulation in the pathophysiology of ASD, and helps us to further understand the underlying molecular mechanism of ASD.

Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

A metabolomics approach to investigate urine levels of neurotransmitters and related metabolites in autistic children

Since recently metabolic abnormalities in autistic children have been associated with ASD disturbs, the aim of this study is to determine the neurotransmitter levels in urine samples of autistic children and to analyse the altered metabolic pathway involved in their production. Thus, ASD-specific urinary metabolomic patterns were explored in 40 ASD children and 40 matched controls using untargeted metabolomics through UHPLC-mass spectrometry (Q-exactive analyser), and by using XCMS Metlin software for data interpretation. Through this new advanced technique, a more considerable number of urinary altered metabolites were recorded in autistic children, than in the previous investigations, which allowed us to collect metabolites involved in neurotransmitter production. In these subjects, a high amount of dopamine was revealed and an increased amount of homovanillic acid, to the detriment of noradrenaline and adrenaline production, as well as MHPG and vanillylmandelic acid, which were found lower. This indicates that the accumulation of dopamine is not due to its greater production, but its lesser biotransformation into noradrenaline, due to the blockage of the dopamine β-hydroxylase enzyme by 4-cresol and vitamin C, both found in high quantities in autistic subjects. Finally, a decreased amount of the active form of vitamin B6, pyridoxal phosphate (P5P), implicated in biotransformation of glutamate into γ-aminobutyric acid (GABA), was also detected, justifying the lower levels of latter. All of these alterations are correlated with a peculiar intestinal microbiome in autistic subjects, supporting the idea of a microbiota-gut-brain axis, then altered levels of neurotransmitters and altered neuronal transmission exist.

Targeted metabolomics highlights perturbed metabolism in the brain of autism spectrum disorder sufferers

INTRODUCTION

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficiencies in social interactions and communication, combined with restricted and repetitive behavioral issues.

OBJECTIVES

As little is known about the etiopathophysiology of ASD and early diagnosis is relatively subjective, we aim to employ a targeted, fully quantitative metabolomics approach to biochemically profile post-mortem human brain with the overall goal of identifying metabolic pathways that may have been perturbed as a result of the disease while uncovering potential central diagnostic biomarkers.

METHODS

Using a combination of ¹H NMR and DI/LC-MS/MS we quantitatively profiled the metabolome of the posterolateral cerebellum from post-mortem human brain harvested from people who suffered with ASD (n = 11) and compared them with age-matched controls (n = 10).

RESULTS

We accurately identified and quantified 203 metabolites in post-mortem brain extracts and performed a metabolite set enrichment analyses identifying 3 metabolic pathways as significantly perturbed (p < 0.05). These include Pyrimidine, Ubiquinone and Vitamin K metabolism. Further, using a variety of machine-based learning algorithms, we identified a panel of central biomarkers (9-hexadecenoylcarnitine (C16:1) and the phosphatidylcholine PC ae C36:1) capable of discriminating between ASD and controls with an AUC = 0.855 with a sensitivity and specificity equal to 0.80 and 0.818, respectively.

CONCLUSION

For the first time, we report the use of a multi-platform metabolomics approach to biochemically profile brain from people with ASD and report several metabolic pathways which are perturbed in the diseased brain of ASD sufferers. Further, we identified a panel of biomarkers capable of distinguishing ASD from control brains. We believe that these central biomarkers may be useful for diagnosing ASD in more accessible biomatrices.

Environmental Chemical Diethylhexyl Phthalate Alters Intestinal Microbiota Community Structure and Metabolite Profile in Mice

Exposure to environmental chemicals during windows of development is a potentially contributing factor in gut microbiota dysbiosis and linked to chronic diseases and developmental disorders. We used a community-level model of microbiota metabolism to investigate the effects of diethylhexyl phthalate (DEHP), a ubiquitous plasticizer implicated in neurodevelopmental disorders, on the composition and metabolite outputs of gut microbiota in young mice. Administration of DEHP by oral gavage increased the abundance of Lachnoclostridium, while decreasing Clostridium sensu stricto Addition of DEHP to in vitro-cultured cecal microbiota increased the abundance of Paenibacillus and Lachnoclostridium Untargeted metabolomics showed that DEHP broadly altered the metabolite profile in the culture. Notably, DEHP enhanced the production of p-cresol while inhibiting butyrate synthesis. Metabolic model-guided correlation analysis indicated that the likely sources of p-cresol are Clostridium species. Monoculture of Lachnoclostridium bolteae confirmed that it is capable of producing p-hydroxyphenylacetic acid, the immediate precursor of p-cresol, and that the species' growth is enhanced upon DEHP exposure. Taken together, these findings suggest a model where DEHP increases production of p-cresol, a bacterial metabolite linked with neurodevelopmental disorders, by expanding the abundance of species that synthesize the metabolite's precursor.IMPORTANCE Several previous studies have pointed to environmental chemical exposure during windows of development as a contributing factor in neurodevelopmental disorders and correlated these disorders with microbiota dysbiosis; however, little is known about how the chemicals specifically alter the microbiota to interfere with development. The findings reported in this paper unambiguously establish that a pollutant linked with neurodevelopmental disorders can directly modify the microbiota to promote the production of a potentially toxic metabolite (p-cresol) that has also been correlated with neurodevelopmental disorders. Furthermore, we used a novel modeling strategy to identify the responsible enzymes and bacterial sources of this metabolite. To the best of our knowledge, the present study is the first to characterize the functional consequence of phthalate exposure on a developed microbiota. Our results suggest that specific bacterial pathways could be developed as diagnostic and therapeutic targets against health risks posed by ingestion of environmental chemicals.

Metabolomics analysis of children with autism, idiopathic-developmental delays, and Down syndrome

Although developmental delays affect learning, language, and behavior, some evidence suggests the presence of disturbances in metabolism are associated with psychiatric disorders. Here, the plasma metabolic phenotype of children with autism spectrum disorder (ASD, n = 167), idiopathic-developmental delay (i-DD, n = 51), and Down syndrome (DS, n = 31), as compared to typically developed (TD, n = 193) controls was investigated in a subset of children from the case-control Childhood Autism Risk from Genetics and the Environment (CHARGE) Study. Metabolome profiles were obtained using nuclear magnetic resonance spectroscopy and analyzed in an untargeted manner. Forty-nine metabolites were identified and quantified in each sample that included amino acids, organic acids, sugars, and other compounds. Multiple linear regression analysis revealed significant associations between 11 plasma metabolites and neurodevelopmental outcome. Despite the varied origins of these developmental disabilities, we observed similar perturbation in one-carbon metabolism pathways among DS and ASD cases. Similarities were also observed in the DS and i-DD cases in the energy-related tricarboxylic acid cycle. Other metabolites and pathways were uniquely associated with DS or ASD. By comparing metabolic signatures between these conditions, the current study expands on extant literature demonstrating metabolic alterations associated with developmental disabilities and provides a better understanding of overlapping vs specific biological perturbations associated with these disorders.

Elucidating the interaction of kansui and licorice by comparative plasma/tissue metabolomics and a heatmap with relative fold change

Although compatibility is highly advocated in traditional Chinese medicine (TCM), inappropriate combination of some herbs may reduce the therapeutic action and even produce toxic effects. Kansui and licorice, one of TCM "Eighteen Incompatible Medicaments", are the most representative cases of improper herbal combination, which may still be applied simultaneously under given conditions. However, the potential mechanism of their compatibility and incompatibility is unclear. In the present study, two different ratios of kansui and licorice, representing their compatibility and incompatibility respectively, were designed to elucidate their interaction by comparative plasma/tissue metabolomics and a heatmap with relative fold change. As a result, glycocholic acid, prostaglandin F2a, dihydroceramide and sphinganine were screened out as the principal alternative biomarkers of compatibility group; sphinganine, dihydroceramide, arachidonic acid, leukotriene B4, acetoacetic acid and linoleic acid were those of incompatibility group. Based on the values of biomarkers in each tissue, the liver was identified as the compatible target organ, while the heart, liver, and kidney were the incompatible target organs. Furthermore, important pathways for compatibility and incompatibility were also constructed. These results help us to better understand and utilize the two herbs, and the study was the first to reveal some innate characters of herbs related to TCM "Eighteen Incompatible Medicaments".

Biomarkers in aggression

Aggressive behavior exerts an enormous impact on society remaining among the main causes of worldwide premature death. Effective primary interventions, relying on predictive models of aggression that show adequate sensitivity and specificity are currently lacking. One strategy to increase the accuracy and precision of prediction would be to include biological data in the predictive models. Clearly, to be included in such models, biological markers should be reliably associated with the specific trait under study (i.e., diagnostic biomarkers). Aggression, however, is phenotypically highly heterogeneous, an element that has hindered the identification of reliable biomarkers. However, current research is trying to overcome these challenges by focusing on more homogenous aggression subtypes and/or by studying large sample size of aggressive individuals. Further advance is coming by bioinformatics approaches that are allowing the integration of inter-species biological data as well as the development of predictive algorithms able to discriminate subjects on the basis of the propensity toward aggressive behavior. In this review we first present a brief summary of the available evidence on neuroimaging of aggression. We will then treat extensively the data on genetic determinants, including those from hypothesis-free genome-wide association studies (GWAS) and candidate gene studies. Transcriptomic and neurochemical biomarkers will then be reviewed, and we will dedicate a section on the role of metabolomics in aggression. Finally, we will discuss how biomarkers can inform the development of new pharmacological tools as well as increase the efficacy of preventive strategies.

Untargeted Metabolomics for Autism Spectrum Disorders: Current Status and Future Directions

Autism spectrum disorders (ASDs) are a group of neurodevelopment disorders characterized by childhood onset deficits in social communication and interaction. Although the exact etiology of most cases of ASDs is unknown, a portion has been proposed to be associated with various metabolic abnormalities including mitochondrial dysfunction, disorders of cholesterol metabolism, and folate abnormalities. Targeted biochemical testing like plasma amino acid and acylcarnitine profiles have demonstrated limited utility in helping to diagnose and manage such patients. Untargeted metabolomics has emerged, however, as a promising tool in screening for underlying biochemical abnormalities and managing treatment and as a means of investigating possible novel biomarkers for the disorder. Here, we review the principles and methodology behind untargeted metabolomics, recent pilot studies utilizing this technology, and areas in which it may be integrated into the care of children with this disorder in the future.

Identification of gender-related metabolic disturbances in autism spectrum disorders using urinary metabolomics

Autism spectrum disorders (ASD) are a highly heterogeneous group of neurodevelopmental disorders that are more commonly diagnosed in boys than in girls. The reasons for gender differences in ASD are unknown and no definitive current evidence can explain male predominance. Therefore, in search for laboratory biomarkers responsible for ASD, a comprehensive metabolomics study was performed by metabolic profiling of urine samples in 51 ASD subjects and 51 age- and sex-matched children with typical development. Orthogonal partial least-squares discriminant analysis (OPLS-DA) models with poor quality failed to perform the analysis based on gender in the ASD and control groups. OPLS-DA models based on single-sex samples, especially in female subjects, had better clustering between the ASD and control groups with an increase in the R² and Q² values compared with those in the whole group. Significantly increased levels of adenine, 2-Methylguanosine, creatinine, and 7alpha-hydroxytestololactone and a decrease in creatine were observed in the female ASD subjects. In particular, 7alpha-hydroxytestololactone, which has a structure similar to that of testolactone, was positively correlated with adenine (Pearson correlation coefficient, r = 0.738, p < 0.01), creatinine (r = 0.826, p < 0.01), and 2-Methylguanosine (r = 0.757, p < 0.01) and negatively correlated with creatine (r=-0.413, p < 0.05). A receiver operating characteristic curve analysis using the creatinine:creatine ratio yielded an area under the curve of 0.913 (95% CI: 0.806-1). These metabolites may be sex-related or sex-sensitive to an extent and can be valuable for identification of the molecular pathways involved in the gender bias in manifestation of ASD. The creatinine:creatine ratio has a potential to be a good predictor of ASD in the female subjects.