The urinary metabolomics profile of an Italian autistic children population and their unaffected siblings

Urine metabolomic profiles of autism and autistic traits-A twin study

Currently, there are no reliable biomarkers for autism diagnosis. The heterogeneity of autism and several co-occurring conditions are key challenges to establishing these. Here, we used untargeted mass spectrometry-based urine metabolomics to investigate metabolic differences for autism diagnosis and autistic traits in a well-characterized twin cohort (N = 105). We identified 208 metabolites in the urine samples of the twins. No clear, significant metabolic drivers for autism diagnosis were detected when controlling for other neurodevelopmental conditions. However, we identified nominally significant changes for several metabolites. For instance, phenylpyruvate (p = 0.019) and taurine (p = 0.032) were elevated in the autism group, while carnitine (p = 0.047) was reduced. We furthermore accounted for the shared factors, such as genetics within the twin pairs, and report additional metabolite differences. Based on the nominally significant metabolites for autism diagnosis, the arginine and proline metabolism pathway (p = 0.024) was enriched. We also investigated the association between quantitative autistic traits, as measured by the Social Responsiveness Scale 2nd Edition, and metabolite differences, identifying a greater number of nominally significant metabolites and pathways. A significant positive association between indole-3-acetate and autistic traits was observed within the twin pairs (adjusted p = 0.031). The utility of urine biomarkers in autism, therefore, remains unclear, with mixed findings from different study populations.

Infant microbes and metabolites point to childhood neurodevelopmental disorders

This study has followed a birth cohort for over 20 years to find factors associated with neurodevelopmental disorder (ND) diagnosis. Detailed, early-life longitudinal questionnaires captured infection and antibiotic events, stress, prenatal factors, family history, and more. Biomarkers including cord serum metabolome and lipidome, human leukocyte antigen (HLA) genotype, infant microbiota, and stool metabolome were assessed. Among the 16,440 Swedish children followed across time, 1,197 developed an ND. Significant associations emerged for future ND diagnosis in general and for specific ND subtypes, spanning intellectual disability, speech disorder, attention-deficit/hyperactivity disorder, and autism. This investigation revealed microbiome connections to future diagnosis as well as early emerging mood and gastrointestinal problems. The findings suggest links to immunodysregulation and metabolism, compounded by stress, early-life infection, and antibiotics. The convergence of infant biomarkers and risk factors in this prospective, longitudinal study on a large-scale population establishes a foundation for early-life prediction and intervention in neurodevelopment.

The tryptophan catabolite or kynurenine pathway in autism spectrum disorder; a systematic review and meta-analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social communication and interaction, as well as rigid and unchanging interests and behaviors. Several studies have reported that activated immune-inflammatory and nitro-oxidative pathways are accompanied by depletion of plasma tryptophan (TRP), increased competing amino acid (CAAs) levels, and activation of the TRP catabolite (TRYCAT) pathway. This study aims to systematically review and meta-analyze data on peripheral TRP, CAAs, TRYCAT pathway activity, and individual TRYCATs, including kynurenine (KYN) and kynurenic acid (KA) levels, in the blood and urine of ASD patients. After extensively searching PubMed, Google Scholar, and SciFinder, a total of 25 full-text papers were included in the analysis, with a total of 6653 participants (3557 people with ASD and 3096 healthy controls). Our results indicate that blood TRP and the TRP/CAAs ratio were not significantly different between ASD patients and controls (standardized mean difference, SMD = -0.227, 95% confidence interval, CI: -0.540; 0.085, and SMD = 0.158, 95% CI: -0.042; 0.359), respectively. The KYN/TRP ratio showed no significant difference between ASD and controls (SMD = 0.001, 95% CI: -0.169; 0.171). Blood KYN and KA levels were not significantly changed in ASD. Moreover, there were no significant differences in urine TRP, KYN, and KA levels between ASD and controls. We could not establish increases in neurotoxic TRYCATs in ASD. In conclusion, this study demonstrates no abnormalities in peripheral blood TRP metabolism, indoleamine 2,3-dioxygenase enzyme (IDO) activity, or TRYCAT production in ASD. Reduced TRP availability and elevated neurotoxic TRYCAT levels are not substantial contributors to ASD's pathophysiology.

IL-6, homocysteine, and autism spectrum phenotypes: an investigation among adults with autism spectrum disorder and their first-degree relatives

BACKGROUND

The importance of recognizing different kinds of autism spectrum presentations among adults, including subthreshold forms and the broad autism phenotype (BAP), has been increasingly highlighted in recent studies. Meanwhile, the possible involvement of immune system deregulation and altered methylation/trans-sulfuration processes in autism spectrum disorder (ASD) is gaining growing attention, but studies in this field are mainly focused on children. In this framework, the aim of this study was to compare plasmatic concentrations of IL-6 and homocysteine (HCY) among adults with ASD, their first-degree relatives, and healthy controls (CTLs), investigating also possible correlations with specific autism symptoms.

METHODS

Plasma concentrations of IL-6 and HCY were measured in a group of adult subjects with ASD, their first-degree relatives (BAP group), and healthy controls (CTL). All participants were also evaluated with psychometric instruments.

RESULTS

IL-6 and HCY concentrations were significantly higher in the ASD group than in CTLs, while BAP subjects reported intermediate results. Significant correlations were reported between biochemical parameters and psychometric scales, particularly for the dimension of ruminative thinking.

CONCLUSIONS

These findings support the hypothesis of a key involvement of HCY-related metabolism and immune system alteration in autism spectrum pathophysiology. HCY and IL-6 seem to show different associations with specific autism dimensions.

Sleep Disordered Breathing in Children with Autism Spectrum Disorder: An In-Depth Review of Correlations and Complexities

Sleep-disordered breathing is a significant problem affecting the pediatric population. These conditions can affect sleep quality and children's overall health and well-being. Difficulties in social interaction, communication, and repetitive behavioral patterns characterize autism spectrum disorder. Sleep disturbances are common in children with ASD. This literature review aims to gather and analyze available studies on the relationship between SDB and children with autism spectrum disorder. We comprehensively searched the literature using major search engines (PubMed, Scopus, and Web of Science). After removing duplicates, we extracted a total of 96 records. We selected 19 studies for inclusion after a thorough title and abstract screening process. Seven articles were ultimately incorporated into this analysis. The research findings presented herein emphasize the substantial influence of sleep-disordered breathing on pediatric individuals diagnosed with autism spectrum disorder (ASD). These findings reveal a high incidence of SDB in children with ASD, emphasizing the importance of early diagnosis and specialized treatment. Obesity in this population further complicates matters, requiring focused weight management strategies. Surgical interventions, such as adenotonsillectomy, have shown promise in improving behavioral issues in children with ASD affected by OSA, regardless of their obesity status. However, more comprehensive studies are necessary to investigate the benefits of A&T treatment, specifically in children with ASD and OSA. The complex relationship between ASD, SDB, and other factors, such as joint hypermobility and muscle hypotonia, suggests a need for multidisciplinary treatment approaches. Physiotherapy can play a critical role in addressing these intricate health issues. Early sleep assessments and tailored weight management strategies are essential for timely diagnosis and intervention in children with ASD. Policy initiatives should support these efforts to enhance the overall well-being of this population. Further research is crucial to understand the complex causes of sleep disturbances in children with ASD and to develop effective interventions considering the multifaceted nature of these conditions.

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.

Multi-level analysis of the gut-brain axis shows autism spectrum disorder-associated molecular and microbial profiles

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.

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.

Probiotic Yoghurt Enriched with Mango Peel Powder: Biotransformation of Phenolics and Modulation of Metabolomic Outputs after In Vitro Digestion and Colonic Fermentation

This study investigated the health-promoting effects and prebiotic functions of mango peel powder (MPP) both as a plain individual ingredient and when incorporated in yoghurt during simulated digestion and fermentation. The treatments included plain MPP, plain yoghurt (YA), yoghurt fortified with MPP (YB), and yoghurt fortified with MPP and lactic acid bacteria (YC), along with a blank (BL). The identification of polyphenols in the extracts of insoluble digesta and phenolic metabolites after the in vitro colonic fermentation were performed employing LC-ESI-QTOF-MS². These extracts were also subjected to pH, microbial count, production of SCFA, and 16S rRNA analyses. The characterisation of phenolic profiles identified 62 phenolic compounds. Among these compounds, phenolic acids were the major compounds that underwent biotransformation via catabolic pathways such as ring fission, decarboxylation, and dehydroxylation. Changes in pH indicated that YC and MPP reduced the media pH from 6.27 and 6.33 to 4.50 and 4.53, respectively. This decline in pH was associated with significant increases in the LAB counts of these samples. The Bifidobacteria counts were 8.11 ± 0.89 and 8.02 ± 1.01 log CFU/g in YC and MPP, respectively, after 72 h of colonic fermentation. Results also showed that the presence of MPP imparted significant variations in the contents and profiles of individual short chain fatty acids (SCFA) with more predominant production of most SCFA in the MPP and YC treatments. The 16s rRNA sequencing data indicated a highly distinctive microbial population associated with YC in terms of relative abundance. These findings suggested MPP as a promising ingredient for utilisation in functional food formulations aiming to enhance gut health.

Maternal Inflammation with Elevated Kynurenine Metabolites Is Related to the Risk of Abnormal Brain Development and Behavioral Changes in Autism Spectrum Disorder

Several studies show that genetic and environmental factors contribute to the onset and progression of neurodevelopmental disorders. Maternal immune activation (MIA) during gestation is considered one of the major environmental factors driving this process. The kynurenine pathway (KP) is a major route of the essential amino acid L-tryptophan (Trp) catabolism in mammalian cells. Activation of the KP following neuro-inflammation can generate various endogenous neuroactive metabolites that may impact brain functions and behaviors. Additionally, neurotoxic metabolites and excitotoxicity cause long-term changes in the trophic support, glutamatergic system, and synaptic function following KP activation. Therefore, investigating the role of KP metabolites during neurodevelopment will likely promote further understanding of additional pathophysiology of neurodevelopmental disorders, including autism spectrum disorder (ASD). In this review, we describe the changes in KP metabolism in the brain during pregnancy and represent how maternal inflammation and genetic factors influence the KP during development. We overview the patients with ASD clinical data and animal models designed to verify the role of perinatal KP elevation in long-lasting biochemical, neuropathological, and behavioral deficits later in life. Our review will help shed light on new therapeutic strategies and interventions targeting the KP for neurodevelopmental disorders.

Developmental pyrethroid exposure causes a neurodevelopmental disorder phenotype in mice

Neurodevelopmental disorders (NDDs) are a widespread and growing public health challenge, affecting as many as 17% of children in the United States. Recent epidemiological studies have implicated ambient exposure to pyrethroid pesticides during pregnancy in the risk for NDDs in the unborn child. Using a litter-based, independent discovery-replication cohort design, we exposed mouse dams orally during pregnancy and lactation to the Environmental Protection Agency's reference pyrethroid, deltamethrin, at 3 mg/kg, a concentration well below the benchmark dose used for regulatory guidance. The resulting offspring were tested using behavioral and molecular methods targeting behavioral phenotypes relevant to autism and NDD, as well as changes to the striatal dopamine system. Low-dose developmental exposure to the pyrethroid deltamethrin (DPE) decreased pup vocalizations, increased repetitive behaviors, and impaired both fear conditioning and operant conditioning. Compared with control mice, DPE mice had greater total striatal dopamine, dopamine metabolites, and stimulated dopamine release, but no difference in vesicular dopamine capacity or protein markers of dopamine vesicles. Dopamine transporter protein levels were increased in DPE mice, but not temporal dopamine reuptake. Striatal medium spiny neurons showed changes in electrophysiological properties consistent with a compensatory decrease in neuronal excitability. Combined with previous findings, these results implicate DPE as a direct cause of an NDD-relevant behavioral phenotype and striatal dopamine dysfunction in mice and implicate the cytosolic compartment as the location of excess striatal dopamine.

Intestinal Barrier Dysfunction and Microbiota–Gut–Brain Axis: Possible Implications in the Pathogenesis and Treatment of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with multifactorial etiology, characterized by impairment in two main functional areas: (1) communication and social interactions, and (2) skills, interests and activities. ASD patients often suffer from gastrointestinal symptoms associated with dysbiotic states and a “leaky gut.” A key role in the pathogenesis of ASD has been attributed to the gut microbiota, as it influences central nervous system development and neuropsychological and gastrointestinal homeostasis through the microbiota–gut–brain axis. A state of dysbiosis with a reduction in the Bacteroidetes/Firmicutes ratio and Bacteroidetes level and other imbalances is common in ASD. In recent decades, many authors have tried to study and identify the microbial signature of ASD through in vivo and ex vivo studies. In this regard, the advent of metabolomics has also been of great help. Based on these data, several therapeutic strategies, primarily the use of probiotics, are investigated to improve the symptoms of ASD through the modulation of the microbiota. However, although the results are promising, the heterogeneity of the studies precludes concrete evidence. The aim of this review is to explore the role of intestinal barrier dysfunction, the gut–brain axis and microbiota alterations in ASD and the possible role of probiotic supplementation in these patients.

Metabolomics in Otorhinolaryngology

Otorhinolaryngology (Ear, Nose and Throat-ENT) focuses on inflammatory, immunological, infectious, and neoplastic disorders of the head and neck and on their medical and surgical therapy. The fields of interest of this discipline are the ear, the nose and its paranasal sinuses, the oral cavity, the pharynx, the larynx, and the neck. Besides surgery, there are many other diagnostic aspects of ENT such as audiology and Vestibology, laryngology, phoniatrics, and rhinology. A new advanced technology, named metabolomics, is significantly impacting the field of ENT. All the “omics” sciences, such as genomics, transcriptomics, and proteomics, converge at the level of metabolomics, which is considered the integration of all “omics.” Its application will change the way several of ENT disorders are diagnosed and treated. This review highlights the power of metabolomics, including its pitfalls and promise, and several of its most relevant applications in ENT to provide a basic understanding of the metabolites associated with these districts. In particular, the attention has been focused on different heterogeneous diseases, from head and neck cancer to allergic rhinitis, hearing loss, obstructive sleep apnea, noise trauma, sinusitis, and Meniere’s disease. In conclusion, metabolomics study indicates a “fil rouge” that links these pathologies to improve three aspects of patient care: diagnostics, prognostics, and therapeutics, which in one word is defined as precision medicine.

The Difference of Gut Microbiota and Their Correlations With Urinary Organic Acids Between Autistic Children With and Without Atopic Dermatitis

Autism is a kind of biologically based neurodevelopmental condition, and the coexistence of atopic dermatitis (AD) is not uncommon. Given that the gut microbiota plays an important role in the development of both diseases, we aimed to explore the differences of gut microbiota and their correlations with urinary organic acids between autistic children with and without AD. We enrolled 61 autistic children including 36 with AD and 25 without AD. The gut microbiota was sequenced by metagenomic shotgun sequencing, and the diversity, compositions, and functional pathways were analyzed further. Urinary organic acids were assayed by gas chromatography–mass spectrometry, and univariate/multivariate analyses were applied. Spearman correlation analysis was conducted to explore their relationships. In our study, AD individuals had more prominent gastrointestinal disorders. The alpha diversity of the gut microbiota was lower in the AD group. LEfSe analysis showed a higher abundance of Anaerostipes caccae, Eubacterium hallii, and Bifidobacterium bifidum in AD individuals, with Akkermansia muciniphila, Roseburia intestinalis, Haemophilus parainfluenzae, and Rothia mucilaginosa in controls. Meanwhile, functional profiles showed that the pathway of lipid metabolism had a higher proportion in the AD group, and the pathway of xenobiotics biodegradation was abundant in controls. Among urinary organic acids, adipic acid, 3-hydroxyglutaric acid, tartaric acid, homovanillic acid, 2-hydroxyphenylacetic acid, aconitic acid, and 2-hydroxyhippuric acid were richer in the AD group. However, only adipic acid remained significant in the multivariate analysis (OR = 1.513, 95% CI [1.042, 2.198], P = 0.030). In the correlation analysis, Roseburia intestinalis had a negative correlation with aconitic acid (r = -0.14, P = 0.02), and the latter was positively correlated with adipic acid (r = 0.41, P = 0.006). Besides, the pathway of xenobiotics biodegradation seems to inversely correlate with adipic acid (r = -0.42, P = 0.18). The gut microbiota plays an important role in the development of AD in autistic children, and more well-designed studies are warranted to explore the underlying mechanism.

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.

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).

Kynurenine pathway and autism spectrum phenotypes: an investigation among adults with autism spectrum disorder and their first-degree relatives

BACKGROUND

Increasing literature highlighted alterations of tryptophan (TRP) metabolism and kynurenine (KYN) pathway in children with autism spectrum disorder (ASD). However, no study specifically focused on adult samples. Meanwhile, several authors stressed the relevance of investigating neurobiological correlates of adult forms of ASD and of those subthreshold ASD manifestations frequently found in relatives of ASD probands, known as broad autism phenotype (BAP). This work aimed to evaluate circulating levels of TRP and metabolites of KYN pathway in a sample of ASD adults, their first-degree relatives and controls (CTLs), investigating also the correlations between biochemical variables' levels and ASD symptoms.

METHODS

A sample of ASD adults, together with a group of first-degree relatives (BAP group) and unrelated CTLs were assessed by means of psychometric scales. Circulating levels of TRP, KYN, quinolinic acid (QA), and kynurenic acid (KYNA) were assessed in all subjects.

RESULTS

ASD patients reported significantly higher total scores than the other groups on all psychometric scales. BAP subjects scored significantly higher than CTLs. ASD patients reported significantly lower TRP levels than BAP and CTL groups. Moreover, significantly lower levels of KYNA were reported in both ASD and BAP groups than in CTLs. Specific patterns of associations were found between autism symptoms and biochemical variables.

CONCLUSIONS

Our findings confirm in adult samples the presence of altered TRP metabolism through KYN pathway. The intermediate alterations reported among relatives of ASD patients further stress the presence of a continuum between subthreshold and full-threshold ASD phenotypes also from a biochemical perspective.

Effect of Supplementation on Levels of Homovanilic and Vanillylmandelic Acids in Children with Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are characterized by numerous comorbidities, including various metabolic and nutritional abnormalities. In many children with ASD, problems with proper nutrition can often lead to inadequate nutrient intake and some disturbances in metabolic profiles, which subsequently correlate with impaired neurobehavioural function. The purpose of this study was to investigate and compare the relationship between supplementation, levels of homovanillic acid (HVA) and vanillylmandelic acid (VMA) and the behaviour of children with ASD using quantitative urinary acid determination and questionnaires provided by parents/caregivers. The study was carried out on 129 children between 3 and 18 years of age. HVA and VMA were extracted and derivatized from urinary samples and simultaneously analyzed by gas chromatography-mass spectrometry (GC-MS). In addition, parents/caregivers of children with ASD were asked to complete questionnaires containing information about their diet and intake/non-intake of supplements. The application of the Mann–Whitney U test showed a statistically significant difference between the level of HVA and vitamin B supplementation (p = 1.64 × 10⁻²) and also omega-6 fatty acids supplementation and the levels of HVA (p = 1.50 × 10⁻³) and VMA (p = 2.50 × 10⁻³). In some children, a reduction in the severity of autistic symptoms (better response to own name or better reaction to change) was also observed. These results suggest that supplementation affects the levels of HVA and VMA and might also affect the children’s behaviour. Further research on these metabolites and the effects of supplementation on their levels, as well as the effects on the behaviour and physical symptoms among children with ASD is needed.

Urinary metabolomics using gas chromatography-mass spectrometry: potential biomarkers for autism spectrum disorder

BACKGROUND

Diagnosis of autism spectrum disorder (ASD) is generally made phenotypically and the hunt for ASD-biomarkers continues. The purpose of this study was to compare urine organic acids profiles of ASD versus typically developing (TD) children to identify potential biomarkers for diagnosis and exploration of ASD etiology.

METHODS

This case control study was performed in the Department of Pathology and Laboratory Medicine in collaboration with the Department of Pediatrics and Child Health, Aga Khan University, Pakistan. Midstream urine was collected in the first half of the day time before noon from the children with ASD diagnosed by a pediatric neurologist based on DSM-5 criteria and TD healthy controls from August 2019 to June 2021. The urine organic acids were analyzed by Gas Chromatography-Mass Spectrometry. To identify potential biomarkers for ASD canonical linear discriminant analysis was carried out for the organic acids, quantified in comparison to an internal standard.

RESULTS

A total of 85 subjects were enrolled in the current study. The mean age of the ASD (n = 65) and TD groups (n = 20) was 4.5 ± 2.3 and 6.4 ± 2.2 years respectively with 72.3% males in the ASD group and 50% males in the TD group. Parental consanguinity was 47.7 and 30% in ASD and TD groups, respectively. The common clinical signs noted in children with ASD were developmental delay (70.8%), delayed language skills (66.2%), and inability to articulate sentences (56.9%). Discriminant analysis showed that 3-hydroxyisovalericc, homovanillic acid, adipic acid, suberic acid, and indole acetic were significantly different between ASD and TD groups. The biochemical classification results reveal that 88.2% of cases were classified correctly into ASD& TD groups based on the urine organic acid profiles.

CONCLUSION

3-hydroxy isovaleric acid, homovanillic acid, adipic acid, suberic acid, and indole acetic were good discriminators between the two groups. The discovered potential biomarkers could be valuable for future research in children with ASD.

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.

Could Candida Overgrowth Be Involved in the Pathophysiology of Autism?

The purpose of this review is to summarize the current acquiredknowledge of Candida overgrowth in the intestine as a possible etiology of autism spectrum disorder (ASD). The influence of Candida sp. on the immune system, brain, and behavior of children with ASD isdescribed. The benefits of interventions such as a carbohydrates-exclusion diet, probiotic supplementation, antifungal agents, fecal microbiota transplantation (FMT), and microbiota transfer therapy (MTT) will be also discussed. Our literature query showed that the results of most studies do not fully support the hypothesis that Candida overgrowth is correlated with gastrointestinal (GI) problems and contributes to autism behavioral symptoms occurrence. On the one hand, it was reported that the modulation of microbiota composition in the gut may decrease Candida overgrowth, help reduce GI problems and autism symptoms. On the other hand, studies on humans suggesting the beneficial effects of a sugar-free diet, probiotic supplementation, FMT and MTT treatment in ASD are limited and inconclusive. Due to the increasing prevalence of ASD, studies on the etiology of this disorder are extremely needed and valuable. However, to elucidate the possible involvement of Candida in the pathophysiology of ASD, more reliable and well-designed research is certainly required.

Analysis of urinary organic acids by gas chromatography tandem mass spectrometry method for metabolic profiling applications

A sensitive, accurate and precise method was developed for the quantification of a large number of organic acids in human urine by GC-MS/MS. The analytes were selected based on their role as key metabolic intermediates; intermediates of Krebs cycle, fatty acid oxidation, glycolysis, down-stream metabolites of neurotransmitter synthesis and degradation, metabolites indicative of nutritional deficiencies, byproducts of microbial activity in the gastrointestinal tract (GI) etc. The most efficient sample preparation protocol was selected based on tests for extraction with different solvents such as MTBE and ethyl acetate under acidic conditions, whereas finally a more general protocol was applied with methanol. Regarding derivatization, methoxyamine with MSTFA, 1% TMCS was applied. The method was extensively validated, including stability study, ensuring accurate determination of the studied organic acids in human urine. Proof of its utility was exhibited in a set of samples from human volunteers. The method can find wide applicability in the context of metabolomics for clinical or nutritional studies.

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 (WQSRS)] to minimize the high multiple comparison burden. With WQSRS, 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.

Studying Autism Using Untargeted Metabolomics in Newborn Screening Samples

Main risk factors of autism spectrum disorder (ASD) include both genetic and non-genetic factors, especially prenatal and perinatal events. Newborn screening dried blood spot (DBS) samples have great potential for the study of early biochemical markers of disease. To study DBS strengths and limitations in the context of ASD research, we analyzed the metabolomic profiles of newborns later diagnosed with ASD. We performed LC-MS/MS-based untargeted metabolomics on DBS from 37 case-control pairs randomly selected from the iPSYCH sample. After preprocessing using MZmine 2.41, metabolites were putatively annotated using mzCloud, GNPS feature-based molecular networking, and MolNetEnhancer. A total of 4360 mass spectral features were detected, of which 150 (113 unique) could be putatively annotated at a high confidence level. Chemical structure information at a broad level could be retrieved for 1009 metabolites, covering 31 chemical classes. Although no clear distinction between cases and controls was revealed, our method covered many metabolites previously associated with ASD, suggesting that biochemical markers of ASD are present at birth and may be monitored during newborn screening. Additionally, we observed that gestational age, age at sampling, and month of birth influence the metabolomic profiles of newborn DBS, which informs us on the important confounders to address in future studies.

Gene-Environment Interactions in Developmental Neurotoxicity: a Case Study of Synergy between Chlorpyrifos and CHD8 Knockout in Human BrainSpheres

BACKGROUND

Autism spectrum disorder (ASD) is a major public health concern caused by complex genetic and environmental components. Mechanisms of gene-environment (G × E ) interactions and reliable biomarkers associated with ASD are mostly unknown or controversial. Induced pluripotent stem cells (iPSCs) from patients or with clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9)-introduced mutations in candidate ASD genes provide an opportunity to study (G × E ) interactions.

OBJECTIVES

In this study, we aimed to identify a potential synergy between mutation in the high-risk autism gene encoding chromodomain helicase DNA binding protein 8 (CHD8) and environmental exposure to an organophosphate pesticide (chlorpyrifos; CPF) in an iPSC-derived human three-dimensional (3D) brain model.

METHODS

This study employed human iPSC-derived 3D brain organoids (BrainSpheres) carrying a heterozygote CRISPR/Cas9-introduced inactivating mutation in CHD8 and exposed to CPF or its oxon-metabolite (CPO). Neural differentiation, viability, oxidative stress, and neurite outgrowth were assessed, and levels of main neurotransmitters and selected metabolites were validated against human data on ASD metabolic derangements.

RESULTS

Expression of CHD8 protein was significantly lower in CHD8 heterozygous knockout (C H D 8 + / - ) BrainSpheres compared with C H D 8 + / + ones. Exposure to CPF/CPO treatment further reduced CHD8 protein levels, showing the potential (G × E ) interaction synergy. A novel approach for validation of the model was chosen: from the literature, we identified a panel of metabolic biomarkers in patients and assessed them by targeted metabolomics in vitro. A synergistic effect was observed on the cholinergic system, S-adenosylmethionine, S-adenosylhomocysteine, lactic acid, tryptophan, kynurenic acid, and α -hydroxyglutaric acid levels. Neurite outgrowth was perturbed by CPF/CPO exposure. Heterozygous knockout of CHD8 in BrainSpheres led to an imbalance of excitatory/inhibitory neurotransmitters and lower levels of dopamine.

DISCUSSION

This study pioneered (G × E ) interaction in iPSC-derived organoids. The experimental strategy enables biomonitoring and environmental risk assessment for ASD. Our findings reflected some metabolic perturbations and disruption of neurotransmitter systems involved in ASD. The increased susceptibility of CHD 8 + / - BrainSpheres to chemical insult establishes a possibly broader role of (G × E ) interaction in ASD. https://doi.org/10.1289/EHP8580.

Application of Metabolomics in Pediatric Asthma: Prediction, Diagnosis and Personalized Treatment

Asthma in children remains a significant public health challenge affecting 5–20% of children in Europe and is associated with increased morbidity and societal healthcare costs. The high variation in asthma incidence among countries may be attributed to differences in genetic susceptibility and environmental factors. This respiratory disorder is described as a heterogeneous syndrome of multiple clinical manifestations (phenotypes) with varying degrees of severity and airway hyper-responsiveness, which is based on patient symptoms, lung function and response to pharmacotherapy. However, an accurate diagnosis is often difficult due to diversities in clinical presentation. Therefore, identifying early diagnostic biomarkers and improving the monitoring of airway dysfunction and inflammatory through non-invasive methods are key goals in successful pediatric asthma management. Given that asthma is caused by the interaction between genes and environmental factors, an emerging approach, metabolomics—the systematic analysis of small molecules—can provide more insight into asthma pathophysiological mechanisms, enable the identification of early biomarkers and targeted personalized therapies, thus reducing disease burden and societal cost. The purpose of this review is to present evidence on the utility of metabolomics in pediatric asthma through the analysis of intermediate metabolites of biochemical pathways that involve carbohydrates, amino acids, lipids, organic acids and nucleotides and discuss their potential application in clinical practice. Also, current challenges on the integration of metabolomics in pediatric asthma management and needed next steps are critically discussed.

Dysbiosis of Gut Fungal Microbiota in Children with Autism Spectrum Disorders

In this study, we tested the feces of children with ASD and those of healthy children, and the overall changing of the gut fungal community was observed in ASD children compared with controls. However, there were no abundant fungi populations showed significant variations between the ASD and Control group both at phylum and class level. Among the 507 genera identified, Saccharomyces and Aspergillus showed significant differences between ASD (59.07%) and Control (40.36%), indicating that they may be involved in the abnormal gut fungal community structure of ASD. When analyzed at the species level, a decreased abundance in Aspergillus versicolor was observed while Saccharomyces cerevisiae was increased in children with ASD relative to controls. Overall, this study characterized the fungal microbiota profile of children with ASD and identified potential diagnostic species closely related to the immune response in ASD.

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.

Gut microbiota metabolites in autistic children: An epigenetic perspective

Gut microbiota has become an issue of great importance recently due to its major role in autism spectrum disorder (ASD). Over the past three decades, there has been a sustained research activity focused to explain the actual mechanism by which gut microbiota triggers/develops autism. Several genetic and epigenetic factors are involved in this disorder, with epigenetics being the most active area of research. Although the constant investigation and advancements, epigenetic implications in ASD still need a deeper functional/causal analysis. In this review, we describe the major gut microbiota metabolites and how they induce epigenetic changes in ASD along with interactions through the gut-brain axis.

Autism Spectrum Disorder from the Womb to Adulthood: Suggestions for a Paradigm Shift

The wide spectrum of unique needs and strengths of Autism Spectrum Disorders (ASD) is a challenge for the worldwide healthcare system. With the plethora of information from research, a common thread is required to conceptualize an exhaustive pathogenetic paradigm. The epidemiological and clinical findings in ASD cannot be explained by the traditional linear genetic model, hence the need to move towards a more fluid conception, integrating genetics, environment, and epigenetics as a whole. The embryo-fetal period and the first two years of life (the so-called 'First 1000 Days') are the crucial time window for neurodevelopment. In particular, the interplay and the vicious loop between immune activation, gut dysbiosis, and mitochondrial impairment/oxidative stress significantly affects neurodevelopment during pregnancy and undermines the health of ASD people throughout life. Consequently, the most effective intervention in ASD is expected by primary prevention aimed at pregnancy and at early control of the main effector molecular pathways. We will reason here on a comprehensive and exhaustive pathogenetic paradigm in ASD, viewed not just as a theoretical issue, but as a tool to provide suggestions for effective preventive strategies and personalized, dynamic (from womb to adulthood), systemic, and interdisciplinary healthcare approach.

Comparison of the Metabolic Profiles in the Plasma and Urine Samples Between Autistic and Typically Developing Boys: A Preliminary Study

Background: Autism spectrum disorder (ASD) is defined as a pervasive developmental disorder which is caused by genetic and environmental risk factors. Besides the core behavioral symptoms, accumulated results indicate children with ASD also share some metabolic abnormalities. Objectives: To analyze the comprehensive metabolic profiles in both of the first-morning urine and plasma samples collected from the same cohort of autistic boys. Methods: In this study, 30 autistic boys and 30 tightly matched healthy control (HC) boys (age range: 2.4~6.7 years) were recruited. First-morning urine and plasma samples were collected and the liquid chromatography-mass spectrometry (LC-MS) was applied to obtain the untargeted metabolic profiles. The acquired data were processed by multivariate analysis and the screened metabolites were grouped by metabolic pathway. Results: Different discriminating metabolites were found in plasma and urine samples. Notably, taurine and catechol levels were decreased in urine but increased in plasma in the same cohort of ASD children. Enriched pathway analysis revealed that perturbations in taurine and hypotaurine metabolism, phenylalanine metabolism, and arginine and proline metabolism could be found in both of the plasma and urine samples. Conclusion: These preliminary results suggest that a series of common metabolic perturbations exist in children with ASD, and confirmed the importance to have a comprehensive analysis of the metabolites in different biological samples to reveal the full picture of the complex metabolic patterns associated with ASD. Further targeted analyses are needed to validate these results in a larger cohort.

Metabolomics analysis of microbiota-gut-brain axis in neurodegenerative and psychiatric diseases

Gut microbiota represents a complex physiological ecosystem that influences the host health. Alterations in the microbiome metabolism affect the body homeostasis and they have been associated with the development of different human neurodegenerative and neuropsychiatric disorders, such as Alzheimer's disease, autism spectrum disorder, bipolar disorder, depression, Huntington's disease, Parkinson's disease, posttraumatic stress disorder and schizophrenia. The development of these complex diseases is influenced by various factors, including genetic predisposition and environmental triggers. Gut microbiota has recently emerged as an important actor in their physiopathology that has been shown to play a role in inflammation, oxidative stress, and gut permeability. Therefore, targeting the metabolites that are produced by or associated with the gut microbiota may help us understand how imbalance in the gut-brain axis affects human health. This review offers a comprehensive overview of the literature on this matter, offering the readers an insight in the state-of-art metabolic measurements of the gut-brain axis in various brain-related diseases.

Big data in severe mental illness: the role of electronic monitoring tools and metabolomics

There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.

Autism Spectrum Disorder Associated With Gut Microbiota at Immune, Metabolomic, and Neuroactive Level

There is increasing evidence suggesting a link between the autism spectrum disorder (ASD) and the gastrointestinal (GI) microbiome. Experimental and clinical studies have shown that patients diagnosed with ASD display alterations of the gut microbiota. These alterations do not only extend to the gut microbiota composition but also to the metabolites they produce, as a result of its connections with diet and the bidirectional interaction with the host. Thus, production of metabolites and neurotransmitters stimulate the immune system and influence the central nervous system (CNS) by stimulation of the vagal nerve, as an example of the gut-brain axis pathway. In this review we compose an overview of the interconnectivity of the different GI-related elements that have been associated with the development and severity of the ASD in patients and animal models. We review potential biomarkers to be used in future studies to unlock further connections and interventions in the treatment of ASD.

Altered gut microbial profile is associated with abnormal metabolism activity of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a severe neurodevelopmental disorder. To enhance the understanding of the gut microbiota structure in ASD children at different ages as well as the relationship between gut microbiota and fecal metabolites, we first used the 16S rRNA sequencing to evaluate the gut microbial population in a cohort of 143 children aged 2-13 years old. We found that the α-diversity of ASD group showed no significant change with age, while the TD group showed increased α-diversity with age, which indicates that the compositional development of the gut microbiota in ASD varies at different ages in ways that are not consistent with TD group. Recent studies have shown that chronic constipation is one of the most commonly obvious gastrointestinal (GI) symptoms along with ASD core symptoms. To further investigate the potential interaction effects between ASD and GI symptoms, the 30 C-ASD and their aged-matched TD were picked out to perform metagenomics analysis. We observed that C-ASD group displayed decreased diversity, depletion of species of Sutterella, Prevotella, and Bacteroides as well as dysregulation of associated metabolism activities, which may involve in the pathogenesis of C-ASD. Consistent with metagenomic analysis, liquid chromatography-mass spectrometry (LC/MS) revealed some of the differential metabolites between C-ASD and TD group were involved in the metabolic network of neurotransmitters including serotonin, dopamine, histidine, and GABA. Furthermore, we found these differences in metabolites were associated with altered abundance of specific bacteria. The study suggested possible future modalities for ASD intervention through targeting the specific bacteria associated with neurotransmitter metabolism.

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.

Dysfunctional d-aspartate metabolism in BTBR mouse model of idiopathic autism

BACKGROUND

Autism spectrum disorders (ASD) comprise a heterogeneous group of neurodevelopmental conditions characterized by impairment in social interaction, deviance in communication, and repetitive behaviors. Dysfunctional ionotropic NMDA and AMPA receptors, and metabotropic glutamate receptor 5 activity at excitatory synapses has been recently linked to multiple forms of ASD. Despite emerging evidence showing that d-aspartate and d-serine are important neuromodulators of glutamatergic transmission, no systematic investigation on the occurrence of these D-amino acids in preclinical ASD models has been carried out.

METHODS

Through HPLC and qPCR analyses we investigated d-aspartate and d-serine metabolism in the brain and serum of four ASD mouse models. These include BTBR mice, an idiopathic model of ASD, and Cntnap2^-/-, Shank3^-/-, and 16p11.2^+/- mice, three established genetic mouse lines recapitulating high confidence ASD-associated mutations.

RESULTS

Biochemical and gene expression mapping in Cntnap2^-/-, Shank3^-/-, and 16p11.2^+/- failed to find gross cerebral and serum alterations in d-aspartate and d-serine metabolism. Conversely, we found a striking and stereoselective increased d-aspartate content in the prefrontal cortex, hippocampus and serum of inbred BTBR mice. Consistent with biochemical assessments, in the same brain areas we also found a robust reduction in mRNA levels of d-aspartate oxidase, encoding the enzyme responsible for d-aspartate catabolism.

CONCLUSIONS

Our results demonstrated the presence of disrupted d-aspartate metabolism in a widely used animal model of idiopathic ASD.

GENERAL SIGNIFICANCE

Overall, this work calls for a deeper investigation of D-amino acids in the etiopathology of ASD and related developmental disorders.

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.

The bacterial neurometabolic signature of the gut microbiota of young children with autism spectrum disorders

Introduction. The human gut microbiota is currently seen as an important factor that can promote autism spectrum disorder (ASD) development in children.

Aim. This study aimed to detect differences in the taxonomic composition and content of bacterial genes encoding key enzymes involved in the metabolism of neuroactive biomarker compounds in the metagenomes of gut microbiota of children with ASD and neurotypical children.

Methodology. A whole metagenome sequencing approach was used to obtain metagenomic data on faecal specimens of 36 children with ASD and 21 healthy neurotypical children of 3–5 years old. Taxonomic analysis was conducted using MetaPhlAn2. The developed bioinformatics algorithm and created catalogue of the orthologues were applied to identify bacterial genes of neuroactive compounds in the metagenomes. For the identification of metagenomic signatures of children with ASD, Wilcoxon's test and adjustment for multiple comparisons were used.

Results. Statistically significant differences with decreases in average abundance in the microbiota of ASD children were found for the genera Barnesiella and Parabacteroides and species Alistipes putredinis , B. caccae , Bacteroides intestinihominis, Eubacterium rectale , Parabacteroides distasonis and Ruminococcus lactaris . Average relative abundances of the detected genes and neurometabolic signature approach did not reveal many significant differences in the metagenomes of the groups that were compared. We noted decreases in the abundance of genes linked to production of GABA, melatonine and butyric acid in the ASD metagenomes.

Conclusion. For the first time, the neurometabolic signature of the gut microbiota of young children with ASD is presented. The data can help to provide a comparative assessment of the transcriptional and metabolomic activity of the identified genes.

How could metabolomics change pediatric health?

In the last years, 'omics' technologies, and especially metabolomics, emerged as expanding scientific disciplines and promising technologies in the characterization of several pathophysiological processes.In detail, metabolomics, able to detect in a dynamic way the whole set of molecules of low molecular weight in cells, tissues, organs, and biological fluids, can provide a detailed phenotypic portray, representing a metabolic "snapshot."Thanks to its numerous strength points, metabolomics could become a fundamental tool in human health, allowing the exact evaluation of individual metabolic responses to pathophysiological stimuli including drugs, environmental changes, lifestyle, a great number of diseases and other epigenetics factors.Moreover, if current metabolomics data will be confirmed on larger samples, such technology could become useful in the early diagnosis of diseases, maybe even before the clinical onset, allowing a clinical monitoring of disease progression and helping in performing the best therapeutic approach, potentially predicting the therapy response and avoiding overtreatments. Moreover, the application of metabolomics in nutrition could provide significant information on the best nutrition regimen, optimal infantile growth and even in the characterization and improvement of commercial products' composition.These are only some of the fields in which metabolomics was applied, in the perspective of a precision-based, personalized care of human health.In this review, we discuss the available literature on such topic and provide some evidence regarding clinical application of metabolomics in heart diseases, auditory disturbance, nephrouropathies, adult and pediatric cancer, obstetrics, perinatal conditions like asphyxia, neonatal nutrition, neonatal sepsis and even some neuropsychiatric disorders, including autism.Our research group has been interested in metabolomics since several years, performing a wide spectrum of experimental and clinical studies, including the first metabolomics analysis of human breast milk. In the future, it is reasonable to predict that the current knowledge could be applied in daily clinical practice, and that sensible metabolomics biomarkers could be easily detected through cheap and accurate sticks, evaluating biofluids at the patient's bed, improving diagnosis, management and prognosis of sick patients and allowing a personalized medicine. A dream? May be I am a dreamer, but I am not the only one.

Pediatric Acute-onset Neuropsychiatric Syndrome and Mycoplasma Pneumoniae Infection: A Case Report Analysis with a Metabolomics Approach

Pediatric Acute-onset Neuropsychiatric Syndrome (PANS) is a clinical condition characterized by a sudden and dramatic obsessive-compulsive disorder with a suggested post-infectious immune-mediated etiology. This condition is accompanied by an extensive series of relatively serious neuropsychiatric symptoms. The diagnosis of PANS is made by "exclusion", as the individual PANS symptoms overlap with a multiplicity of psychiatric disorders with the onset in childhood. A number of researchers accumulated evidence to support the hypothesis that PANS was closely associated with a number of infections. In the last decade, metabolomics played an essential role in improving the knowledge of complex biological systems and identifying potential new biomarkers as indicators of pathological progressions or pharmacologic responses to therapy. The metabolome is considered the most predictive phenotype, capable of recognizing epigenetic differences, reflecting more closely the clinical reality at any given moment and thus providing extremely dynamic data. In the present work, the most recent hypothesis and suggested mechanisms of this condition are reviewed and the case of a 10 - year-old girl with PANS is described, before and after clarithromycin treatment. The main results of this case report are discussed from a metabolomics point of view. The alteration of several metabolic pathways concerning the microbial activity highlights the possible role of the microbiome in the development of PANS. Furthermore, different metabolic perturbations at the level of protein biosynthesis, energy and amino acid metabolisms are observed and discussed. Based on our observations, it is believed that metabolomics is a promising technology to unravel the mysteries of PANS in the near future.

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.

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.

Metabolic profiling in children with autism spectrum disorder with and without mental regression: preliminary results from a cross-sectional case-control study

INTRODUCTION

It is challenging to establish the mechanisms involved in the variety of well-defined clinical phenotypes in autism spectrum disorder (ASD) and the pathways involved in their pathogeneses.

OBJECTIVES

The aim of the present study was to evaluate the metabolomic profiles of children with ASD subclassified by mental regression (AR) phenotype and with no regression (ANR).

METHODS

The present study was a cross-sectional case-control study. Thirty children aged 2-6 years with ASD were included: 15 with ANR and 15 with AR. In addition, a control group of 30 normally developing children was selected and matched to the ASD group by sex and age. Plasma samples were analyzed with a metabolomics single platform methodology based on liquid chromatography-mass spectrometry. Univariate and multivariate analysis, including orthogonal partial least squares-discriminant analysis modeling and Shared-and-Unique-Structures plots, were performed using MetaboAnalyst 4.0 and SIMCA-P 15. The primary endpoint was the metabolic signature profiling among healthy children and autistic children and their subgroups.

RESULTS

Metabolomic profiles of 30 healthy children, 15 ANR and 15 AR were compared. Several differences between healthy children and children with ASD were detected, involving mainly amino acid, lipid and nicotinamide metabolism. Furthermore, we report subtle differences between the ANR and AR groups.

CONCLUSIONS

In this study, we report, for the first time, the plasmatic metabolomic profiles of children with ASD, including two different phenotypes based on mental regression status. The use of a liquid chromatography-mass spectrometry platform approach for metabolomics in ASD children using plasma appears to be very efficient and adds further support to previous findings in urine. Furthermore, the present study documents several changes related to amino acid, NAD⁺ and lipid metabolism that, in some cases, such as arginine and glutamate pathway alterations, seem to be associated with the AR phenotype. Further targeted analyses are needed in a larger cohort to validate the results presented herein.