Increased stool immunoglobulin A level in children with autism spectrum disorders

Gut microbiota metabolites, secretory immunoglobulin A and Bayley-III cognitive scores in children from the CHILD Cohort Study

Background

Dysbiosis of the gut microbiota has been demonstrated in neurodevelopmental disorders but the underlying mechanisms that may explain these associations are poorly understood. Gut secretory immunoglobulin A (SIgA) binds pathogenic microbes, preventing mucosal penetration. Gut microbes also influence SIgA production and its binding characteristics through short-chain fatty acid (SCFA) metabolites, allowing them to regulate the immune response. Serum IgA deficiency has been noted in children with autism spectrum disorders (ASD). In this study, we aimed to determine whether SIgA level in infancy is associated with gut microbiota taxonomy and metabolites, and neurodevelopmental outcomes in preschool children.

Methods

For a subsample of 178 children from the Canadian CHILD Cohort Study, gut microbiota of fecal samples collected at 3-4 months and 12 months was profiled using 16S rRNA sequencing. Gut bacterial metabolites levels and SIgA level were measured by nuclear magnetic resonance (NMR) based metabolomics and SIgA enzyme-linked immunosorbent assay at 3-4 months, respectively. Bayley-III Scale of Infant Development was assessed at 12 and 24 months. We evaluated direct relationships in multiple linear regression models and putative causal relationships in statistical mediation models.

Results

Propionate and butyrate levels at 3-4 months were associated with decreased Bayley cognitive score at 24 months (p-values: 0.01 and 0.02, respectively) in adjusted multiple linear regression models, but when we investigated an indirect relationship mediated by decreased SIgA level at 3-4 months, it did not reach statistical significance (p-values: 0.18 and 0.20, respectively). Lactate level at 3-4 months was associated with increased Bayley cognitive score at 24 months in adjusted multiple linear regression models (p-value: 0.01), but the statistical model mediated by increased SIgA level at 3-4 months did not reach statistical significance neither (p-value: 0.20).

Conclusions

Our study contributes to growing evidence that neurodevelopment is influenced by the infant gut microbiota and that it might involve SIgA level, but larger studies are required.

Contributions of Artificial Intelligence to Analysis of Gut Microbiota in Autism Spectrum Disorder: A Systematic Review

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder whose etiology is not known today, but everything indicates that it is multifactorial. For example, genetic and epigenetic factors seem to be involved in the etiology of ASD. In recent years, there has been an increase in studies on the implications of gut microbiota (GM) on the behavior of children with ASD given that dysbiosis in GM may trigger the onset, development and progression of ASD through the microbiota-gut-brain axis. At the same time, significant progress has occurred in the development of artificial intelligence (AI).

METHODS

The aim of the present study was to perform a systematic review of articles using AI to analyze GM in individuals with ASD. In line with the PRISMA model, 12 articles using AI to analyze GM in ASD were selected.

RESULTS

Outcomes reveal that the majority of relevant studies on this topic have been conducted in China (33.3%) and Italy (25%), followed by the Netherlands (16.6%), Mexico (16.6%) and South Korea (8.3%).

CONCLUSIONS

The bacteria Bifidobacterium is the most relevant biomarker with regard to ASD. Although AI provides a very promising approach to data analysis, caution is needed to avoid the over-interpretation of preliminary findings. A first step must be taken to analyze GM in a representative general population and ASD samples in order to obtain a GM standard according to age, sex and country. Thus, more work is required to bridge the gap between AI in mental health research and clinical care in ASD.

The search for gastrointestinal inflammation in autism: a systematic review and meta-analysis of non-invasive gastrointestinal markers

BACKGROUND

Gastrointestinal symptoms and inflammatory gastrointestinal diseases exist at higher rates in the autistic population. It is not clear however whether autism is associated with elevated gastrointestinal inflammation as studies examining non-invasive faecal biomarkers report conflicting findings. To understand the research landscape and identify gaps, we performed a systematic review and meta-analysis of studies measuring non-invasive markers of gastrointestinal inflammation in autistic and non-autistic samples. Our examination focused on faecal biomarkers as sampling is non-invasive and these markers are a direct reflection of inflammatory processes in the gastrointestinal tract.

METHODS

We extracted data from case-control studies examining faecal markers of gastrointestinal inflammation. We searched PubMed, Embase, Cochrane CENTRAL, CINAHL, PsycINFO, Web of Science Core Collection and Epistemonikos and forward and backwards citations of included studies published up to April 14, 2023 (PROSPERO CRD42022369279).

RESULTS

There were few studies examining faecal markers of gastrointestinal inflammation in the autistic population, and many established markers have not been studied. Meta-analyses of studies examining calprotectin (n = 9) and lactoferrin (n = 3) were carried out. A total of 508 autistic children and adolescents and 397 non-autistic children and adolescents were included in the meta-analysis of calprotectin studies which found no significant group differences (ROM: 1.30 [0.91, 1.86]). Estimated differences in calprotectin were lower in studies with siblings and studies which did not exclude non-autistic controls with gastrointestinal symptoms. A total of 139 autistic participants and 75 non-autistic controls were included in the meta-analysis of lactoferrin studies which found no significant group differences (ROM: 1.27 [0.79, 2.04]).

LIMITATIONS

All studies included in this systematic review and meta-analysis examined children and adolescents. Many studies included non-autistic controls with gastrointestinal symptoms which limit the validity of their findings. The majority of studies of gastrointestinal inflammation focused on children under 12 with few studies including adolescent participants. Most studies that included participants aged four or under did not account for the impact of age on calprotectin levels. Future studies should screen for relevant confounders, include larger samples and explore gastrointestinal inflammation in autistic adolescents and adults.

CONCLUSIONS

There is no evidence to suggest higher levels of gastrointestinal inflammation as measured by calprotectin and lactoferrin are present in autistic children and adolescents at the population level. Preliminary evidence suggests however that higher calprotectin levels may be present in a subset of autistic participants, who may be clinically characterised by more severe gastrointestinal symptoms and higher levels of autistic traits.

Comprehensive systematic review and meta-analysis of the association between common genetic variants and autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is neurodevelopmental disorder characterized by stereotyped behavior and deficits in communication and social interactions. To date, numerous studies have investigated the associations between genetic variants and ASD risk. However, the results of these published studies lack a clear consensus. In the present study, we performed a systematic review on the association between genetic variants and ASD risk. Meanwhile, we conducted a meta-analysis on available data to identify the association between the single nucleotide polymorphisms (SNPs) of candidate genes and ASD risk.

METHODS

We systematically searched public databases including English and Chinese from their inception to August 1, 2022. Two independent reviewers extracted data and assessed study quality. Odds ratio and 95 % confidence interval were used as effect indexes to evaluate the association between the SNPs of candidate genes and the risk of ASD. Heterogeneity was explored through subgroup, sensitivity, and meta-regression analyses. Publication bias was assessed by using Egger's and Begg's tests for funnel plot asymmetry. In addition, TSA analysis were performed to confirm the study findings.

RESULTS

We summarized 84 SNPs of 32 candidate genes from 81 articles included in the study. Subsequently, we analyzed 16 SNPs of eight genes by calculating pooled ORs, and identified eight significant SNPs of contactin associated protein 2 (CNTNAP2), methylentetrahydrofolate reductase (MTHFR), oxytocin receptor (OXTR), and vitamin D receptor (VDR). Results showed that seven SNPs, including the CNTNAP2 rs2710102 (homozygote, heterozygote, dominant and allelic models) and rs7794745 (heterozygote and dominant models), MTHFR C677T (homozygote, heterozygote, dominant, recessive and allelic models) and A1298C (dominant and allelic models), OXTR rs2254298 (homozygote and recessive models), VDR rs731236 (homozygote, dominant, recessive and allelic models) and rs2228570 (homozygote and recessive models), were showed to be correlated with an increased ASD risk. By contrast, the VDR rs7975232 was correlated with a decreased the risk of ASD under the homozygote and allelic models.

CONCLUSION

Our study summarized research evidence on the genetic variants of ASD and provides a broad and detailed overview of ASD risk genes. The C677T and A1298C polymorphisms of MTHFR, rs2710102 and rs7794745 polymorphisms of CNTNAP2, rs2254298 polymorphism of OXTR, and rs731236 and rs2228570 polymorphisms of VDR were genetic risk factors. The rs7975232 polymorphism of VDR was a genetic protective factor for ASD. Our study provides novel clues to clinicians and healthcare decision-makers to predict ASD susceptibility.

Pre-autism: What a paediatrician should know about early diagnosis of autism‎

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

Dietary pattern in autism increases the need for probiotic supplementation: A comprehensive narrative and systematic review on oxidative stress hypothesis

Autism spectrum disorders (ASDs) are associated with specific dietary habits, including limited food selection and gastrointestinal problems, resulting in an altered gut microbiota. Autistic patients have an elevated abundance of certain gut bacteria associated with increased oxidative stress in the gastrointestinal tract. Probiotic supplementation has been shown to decrease oxidative stress in a simulated gut model, but the antioxidant effects of probiotics on the oxidative stress of the gut in autistic patients have not been directly studied. However, it is speculated that probiotic supplementation may help decrease oxidative stress in the gastrointestinal tract of autistic patients due to their specific dietary habits altering the microbiota. PubMed, Scopus and Web of Science databases and Google Scholar were searched up to May 2023. This systematic-narrative review aims to present the latest evidence regarding the changes in eating habits of autistic children which may further increase the gut microbiota induced oxidative stress. Additionally, this review will assess the available literature on the effects of probiotic supplementation on oxidative stress parameters.

Inductively coupled plasma mass spectrometry based urine metallome to construct clinical decision models for autism spectrum disorder

BACKGROUND

The global prevalence of autism spectrum disorder (ASD) is on the rise, and high levels of exposure to toxic heavy metals may be associated with this increase. Urine analysis is a noninvasive method for investigating the accumulation and excretion of heavy metals. The aim of this study was to identify ASD-associated urinary metal markers.

METHODS

Overall, 70 children with ASD and 71 children with typical development (TD) were enrolled in this retrospective case-control study. In this metallomics investigation, inductively coupled plasma mass spectrometry was performed to obtain the urine profile of 27 metals.

RESULTS

Children with ASD could be distinguished from children with TD based on the urine metal profile, with ASD children showing an increased urine metal Shannon diversity. A metallome-wide association analysis was used to identify seven ASD-related metals in urine, with cobalt, aluminum, selenium, and lithium significantly higher, and manganese, mercury, and titanium significantly lower in the urine of children with ASD than in children with TD. The least absolute shrinkage and selection operator (LASSO) machine learning method was used to rank the seven urine metals in terms of their effect on ASD. On the basis of these seven urine metals, we constructed a LASSO regression model for ASD classification and found an area under the receiver operating characteristic curve of 0.913. We also constructed a clinical prediction model for ASD based on the seven metals that were different in the urine of children with ASD and found that the model would be useful for the clinical prediction of ASD risk.

CONCLUSIONS

The study findings suggest that altered urine metal concentrations may be an important risk factor for ASD, and we recommend further exploration of the mechanisms and clinical treatment measures for such alterations.

Gut Microbiota Ecology and Inferred Functions in Children With ASD Compared to Neurotypical Subjects

Autism spectrum disorders (ASDs) is a multifactorial neurodevelopmental disorder. The communication between the gastrointestinal (GI) tract and the central nervous system seems driven by gut microbiota (GM). Herein, we provide GM profiling, considering GI functional symptoms, neurological impairment, and dietary habits. Forty-one and 35 fecal samples collected from ASD and neurotypical children (CTRLs), respectively, (age range, 3–15 years) were analyzed by 16S targeted-metagenomics (the V3–V4 region) and inflammation and permeability markers (i.e., sIgA, zonulin lysozyme), and then correlated with subjects’ metadata. Our ASD cohort was characterized as follows: 30/41 (73%) with GI functional symptoms; 24/41 (58%) picky eaters (PEs), with one or more dietary needs, including 10/41 (24%) with food selectivity (FS); 36/41 (88%) presenting high and medium autism severity symptoms (HMASSs). Among the cohort with GI symptoms, 28/30 (93%) showed HMASSs, 17/30 (57%) were picky eaters and only 8/30 (27%) with food selectivity. The remaining 11/41 (27%) ASDs without GI symptoms that were characterized by HMASS for 8/11 (72%) and 7/11 (63%) were picky eaters. GM ecology was investigated for the overall ASD cohort versus CTRLs; ASDs with GI and without GI, respectively, versus CTRLs; ASD with GI versus ASD without GI; ASDs with HMASS versus low ASSs; PEs versus no-PEs; and FS versus absence of FS. In particular, the GM of ASDs, compared to CTRLs, was characterized by the increase of Proteobacteria, Bacteroidetes, Rikenellaceae, Pasteurellaceae, Klebsiella, Bacteroides, Roseburia, Lactobacillus, Prevotella, Sutterella, Staphylococcus, and Haemophilus. Moreover, Sutterella, Roseburia and Fusobacterium were associated to ASD with GI symptoms compared to CTRLs. Interestingly, ASD with GI symptoms showed higher value of zonulin and lower levels of lysozyme, which were also characterized by differentially expressed predicted functional pathways. Multiple machine learning models classified correctly 80% overall ASDs, compared with CTRLs, based on Bacteroides, Lactobacillus, Prevotella, Staphylococcus, Sutterella, and Haemophilus features. In conclusion, in our patient cohort, regardless of the evaluation of many factors potentially modulating the GM profile, the major phenotypic determinant affecting the GM was represented by GI hallmarks and patients’ age.

Identifying Rare Genetic Variants of Immune Mediators as Risk Factors for Autism Spectrum Disorder

Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2−12 years old) and 107 healthy controls without ASD (20−78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis.

An anxious relationship between Autism Spectrum Disorder and Gut Microbiota: A tangled chemistry?

Autism spectrum disorder (ASD) is a serious multifactorial neurodevelopmental disorder often accompanied by strained social communication, repetitive behaviour, immune dysregulation, and gastrointestinal (GI) issues. Recent studies have recorded a link between dysbiosis in the gut microbiota (gm) and the primary stages of ASD. A bidirectional connection (also called microbiota-gut-brain-axis) exchanges information between the gut bacteria and central nervous system. When the homeostasis of the microenvironment of the gut is dysregulated, it causes oxidative stress, affecting neuronal cells and neurotransmitters, thereby causing neurodevelopmental disorders. Studies have confirmed a difference in the constitution of gut bacteria among ASD cases and their controls. Numerous studies on animal models of ASD have shown altered gm and its association with abnormal metabolite profile and altered behaviour phenotype. This process happens due to an abnormal metabolite production in gm, leading to changes in the immune system, especially in ASD. Hence, this review aims to question the current knowledge on gm dysbiosis and its related GI discomforts and ASD behavioural symptoms and shed light on the possible therapeutic approaches available to deal with this situation. Thereby, though it is understood that more research might be needed to prove an association or causal relationship between gm and ASD, therapy with the microbiome may also be considered as an effective strategy to combat this issue.

Immune-microbiome interplay and its implications in neurodegenerative disorders

The neurodegeneration and its related CNS pathologies need an urgent toolbox to minimize the global mental health burden. The neuroimmune system critically regulates the brain maturation and survival of neurons across the nervous system. The chronic manipulated immunological drive can accelerate the neuronal pathology hence promoting the burden of neurodegenerative disorders. The gut is home for trillions of microorganisms having a mutual relationship with the host system. The gut-brain axis is a unique biochemical pathway through which the gut residing microbes connects with the brain cells and regulates various physiological and pathological cascades. The gut microbiota and CNS communicate using a common language that synchronizes the tuning of immune cells. The intestinal gut microbial community has a profound role in the maturation of the immune system as well as the development of the nervous system. We have critically summarised the clinical and preclinical reports from the past a decade emphasising that the significant changes in gut microbiota can enhance the host susceptibility towards neurodegenerative disorders. In this review, we have discussed how the gut microbiota-mediated immune response inclines the host physiology towards neurodegeneration and indicated the gut microbiota as a potential future candidate for the management of neurodegenerative disorders.

Re-emerging concepts of immune dysregulation in autism spectrum disorders

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by communication and social interaction deficits, and by restricted interests and stereotyped, repetitive behavior patterns. ASD has a strong genetic component and a complex architecture characterized by the interplay of rare and common genetic variants. Recently, increasing evidence suggest a significant contribution of immune system dysregulation in ASD. The present paper reviews the latest updates regarding the altered immune landscape of this complex disorder highlighting areas with potential for biomarkers discovery as well as personalization of therapeutic approaches. Cross-talk between the central nervous system and immune system has long been envisaged and recent evidence brings insights into the pathways connecting the brain to the immune system. Disturbance of cytokine levels plays an important role in the establishment of a neuroinflammatory milieu in ASD. Several other immune molecules involved in antigen presentation and inflammatory cellular phenotypes are also at play in ASD. Maternal immune activation, the presence of brain-reactive antibodies and autoimmunity are other potential prenatal and postnatal contributors to ASD pathophysiology. The molecular players involved in oxidative-stress response and mitochondrial system function, are discussed as contributors to the pro-inflammatory pattern. The gastrointestinal inflammation pathways proposed to play a role in ASD are also discussed. Moreover, the body of evidence regarding some of the genetic factors linked to the immune system dysregulation is reviewed and discussed. Last, but not least, the epigenetic traits and their interactions with the immune system are reviewed as an expanding field in ASD research. Understanding the immune-mediated pathways that influence brain development and function, metabolism, and intestinal homeostasis, may lead to the identification of robust diagnostic or predictive biomarkers for ASD individuals. Thus, novel therapeutic approaches could be developed, ultimately aiming to improve their quality of life.

Metabolites and secretory immunoglobulins: messengers and effectors of the host-microbiota intestinal equilibrium

Maintaining commensal diversity is essential to host homeostasis, because microbial species provide a range of metabolic products and continuously educate the host immune system. The mucosal immune system must actively gather information about the composition of the microbiota, while offering an appropriate response. In mammals, bacterial sensing leads to the production of specific immunoglobulins (Ig), which reach the intestinal lumen as secretory Ig (SIg). Recent work has shed more light on the mechanisms by which SIg can shape bacterial repertoires and contribute to regulating host metabolism. In parallel, bacterial metabolites modulate Ig production and secretion. Here, we present an overview of the current knowledge of the relationship between bacterial metabolites and host SIg, correlating the disruption of this balance with chronic inflammation in humans.

Gut microbiota and neuropsychiatric disorders: Implications for neuroendocrine-immune regulation

Recently, increasing evidence has shown gut microbiota dysbiosis might be implicated in the physiological mechanisms of neuropsychiatric disorders. Altered microbial community composition, diversity and distribution traits have been reported in neuropsychiatric disorders. However, the exact pathways by which the intestinal microbiota contribute to neuropsychiatric disorders remain largely unknown. Given that the onset and progression of neuropsychiatric disorders are characterized with complicated alterations of neuroendocrine and immunology, both of which can be continually affected by gut microbiota via "microbiome-gut-brain axis". Thus, we assess the complicated crosstalk between neuroendocrine and immunological regulation might underlie the mechanisms of gut microbiota associated with neuropsychiatric disorders. In this review, we summarized clinical and preclinical evidence on the role of the gut microbiota in neuropsychiatry disorders, especially in mood disorders and neurodevelopmental disorders. This review may elaborate the potential mechanisms of gut microbiota implicating in neuroendocrine-immune regulation and provide a comprehensive understanding of physiological mechanisms for neuropsychiatric disorders.

Virulence factor-related gut microbiota genes and immunoglobulin A levels as novel markers for machine learning-based classification of autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition for which early identification and intervention is crucial for optimum prognosis. Our previous work showed gut Immunoglobulin A (IgA) to be significantly elevated in the gut lumen of children with ASD compared to typically developing (TD) children. Gut microbiota variations have been reported in ASD, yet not much is known about virulence factor-related gut microbiota (VFGM) genes. Upon determining the VFGM genes distinguishing ASD from TD, this study is the first to utilize VFGM genes and IgA levels for a machine learning-based classification of ASD. Sequence comparisons were performed of metagenome datasets from children with ASD (n = 43) and TD children (n = 31) against genes in the virulence factor database. VFGM gene composition was associated with ASD phenotype. VFGM gene diversity was higher in children with ASD and positively correlated with IgA content. As Group B streptococcus (GBS) genes account for the highest proportion of 24 different VFGMs between ASD and TD and positively correlate with gut IgA, GBS genes were used in combination with IgA and VFGMs diversity to distinguish ASD from TD. Given that VFGM diversity, increases in IgA, and ASD-enriched VFGM genes were independent of sex and gastrointestinal symptoms, a classification method utilizing them will not pertain only to a specific subgroup of ASD. By introducing the classification value of VFGM genes and considering that VFs can be isolated in pregnant women and newborns, these findings provide a novel machine learning-based early risk identification method for ASD.

Altered gut microbiota and mucosal immunity in patients with schizophrenia

Evidence shows that gut microbiota may play important roles in schizophrenia pathogenesis via the "gut-brain" axis, but the mechanisms remain unclear. Here, eighty-four patients with schizophrenia and 84 sex- and age-matched healthy controls were enrolled. Shotgun metagenomic sequencing and 16S rRNA sequencing were performed, and the gut microbiota-associated epitopes (MEs) were predicted, which, together with IgA content, were used to determine the gut microbiota composition associated with gut immune status. Patients with schizophrenia had significantly reduced gut microbiota richnesses compared with those of the healthy controls, and the gut microbiota compositions clearly distinguished the patients with schizophrenia from the healthy controls. Based on two-stage metagenomic-wide association studies, nineteen gut microbiota taxonomies were associated with schizophrenia, and the microbial dysbiosis (MD) index was calculated based on the abundance of differential taxonomies. We found that MD index was positively correlated with MEs diversity and gut IgA levels, and negatively correlated with gut microbiota richness. Glutamate synthase (GOGAT) was more active in the guts of patients with schizophrenia than in those of healthy controls, and high GOGAT activity was associated with altered gut microbiota taxonomies associated with gut IgA levels. Our results may imply a role of the microbiome in the etiology of schizophrenia and contribute to the development of microbiome targeted interventions for schizophrenia.

Alterations in Gut Glutamate Metabolism Associated with Changes in Gut Microbiota Composition in Children with Autism Spectrum Disorder

Changes in the gut microenvironment may influence the pathogenesis of autism spectrum disorders (ASD). Here, we investigated the composition of the gut microbiota and metabolites in children with ASD. Ninety-two children with ASD and 42 age-matched children exhibiting typical development (TD) were enrolled in the two-stage study. In the discovery stage, shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) were performed simultaneously on fecal samples obtained from 43 children in the ASD group and 31 children in the TD group. Systematic bioinformatic analyses were performed to identify gut metabolites associated with altered gut microbiota composition. At the validation stage, differential metabolites were tested using LC-MS with an additional 49 and 11 children in the ASD and TD groups, respectively. Altered glutamate metabolites were found in the ASD group, along with a decline in 2-keto-glutaramic acid and an abundance of microbiota associated with glutamate metabolism. These changes in glutamate metabolism were correlated with lower levels of the highly abundant bacteria Bacteroides vulgatus and higher levels of the potentially harmful Eggerthella lenta and Clostridium botulinum. Lower gut cortisol levels have also been identified in the ASD group and associated with changes in gut microbiota glutamate metabolism. Finally, gut 2-keto-glutaramic acid was validated as a potential biomarker for ASD. The significant changes in the gut microenvironment in children with ASD may provide new insight into the cause of ASD and aid in the search for diagnostic and therapeutic approaches. IMPORTANCE Multiple lines of evidence suggest that the gut microbiota may play an important role in the pathogenesis of ASD, but the specific mechanism is still unclear. Through a comprehensive gut metagenomic and metabolome study of children with ASD, alterations in gut metabolite composition were found in children with ASD, and these alterations were linked to changes in gut microbiota composition. This may give us a deeper understanding of the role of gut microbiota in the pathogenesis of ASD.

Altered Urinary Amino Acids in Children With Autism Spectrum Disorders

Autism spectrum disorders (ASD) affect 1% of children. Although there is no cure, early diagnosis and behavioral intervention can relieve the symptoms. The clinical heterogeneity of ASD has created a need for improved sensitive and specific laboratory diagnostic methods. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis of the metabolome has shown great potential to uncover biomarkers for complex diseases such as ASD. Here, we used a two-step discovery–validation approach to identify potential novel metabolic biomarkers for ASD. Urine samples from 57 children with ASD and 81 matched children with typical development (TD) were analyzed by LS-MS/MS to assess differences in urinary amino acids and their metabolites (referred to as UAA indicators). A total of 63 UAA indicators were identified, of which 21 were present at significantly different levels in the urine of ASD children compared with TD children. Of these 21, the concentrations of 19 and 10 were higher and lower, respectively, in the urine of ASD children compared with TD children. Using support vector machine modeling and receiver operating characteristic curve analysis, we identified a panel of 7 UAA indicators that discriminated between the samples from ASD and TD children (lysine, 2-aminoisobutyric acid, 5-hydroxytryptamine, proline, aspartate, arginine/ornithine, and 4-hydroxyproline). Among the significantly changed pathways in ASD children were the ornithine/urea cycle (decreased levels of the excitatory amino acid aspartate [p = 2.15 × 10^-10] and increased arginine/ornithine [p = 5.21 × 10^-9]), tryptophan metabolism (increased levels of inhibitory 5-hydroxytryptamine p = 3.62 × 10^-9), the methionine cycle (increased methionine sulfoxide [p = 1.46 × 10^-10] and decreased homocysteine [p = 2.73 × 10^-7]), and lysine metabolism (reduced lysine [p = 7.8 × 10^-9], α-aminoadipic acid [p = 1.16 × 10^-9], and 5-aminovaleric acid [p = 1.05 × 10^-5]). Collectively, the data presented here identify a possible imbalance between excitatory and inhibitory amino acid metabolism in ASD children. The significantly altered UAA indicators could therefore be potential diagnostic biomarkers for ASD.

Integrating Autism Spectrum Disorder Pathophysiology: Mitochondria, Vitamin A, CD38, Oxytocin, Serotonin and Melatonergic Alterations in the Placenta and Gut

BACKGROUND

A diverse array of data has been associated with autism spectrum disorder (ASD), reflecting the complexity of its pathophysiology as well as its heterogeneity. Two important hubs have emerged, the placenta/prenatal period and the postnatal gut, with alterations in mitochondria functioning crucial in both.

METHODS

Factors acting to regulate mitochondria functioning in ASD across development are reviewed in this article.

RESULTS

Decreased vitamin A, and its retinoic acid metabolites, lead to a decrease in CD38 and associated changes that underpin a wide array of data on the biological underpinnings of ASD, including decreased oxytocin, with relevance both prenatally and in the gut. Decreased sirtuins, poly-ADP ribose polymerase-driven decreases in nicotinamide adenine dinucleotide (NAD+), hyperserotonemia, decreased monoamine oxidase, alterations in 14-3-3 proteins, microRNA alterations, dysregulated aryl hydrocarbon receptor activity, suboptimal mitochondria functioning, and decreases in the melatonergic pathways are intimately linked to this. Many of the above processes may be modulating, or mediated by, alterations in mitochondria functioning. Other bodies of data associated with ASD may also be incorporated within these basic processes, including how ASD risk factors such as maternal obesity and preeclampsia, as well as more general prenatal stressors, modulate the likelihood of offspring ASD.

CONCLUSION

Such a mitochondria-focussed integrated model of the pathophysiology of ASD has important preventative and treatment implications.

A systematic review of gut-immune-brain mechanisms in Autism Spectrum Disorder

Despite decades of research, the etiological origins of Autism Spectrum Disorder (ASD) remain elusive. Recently, the mechanisms of ASD have encompassed emerging theories involving the gastrointestinal, immune, and nervous systems. While each of these perspectives presents its own set of supporting evidence, the field requires an integration of these modular concepts and an overarching view of how these subsystems intersect. In this systematic review, we have synthesized relevant evidences from the existing literature, evaluating them in an interdependent manner and in doing so, outlining their possible connections. Specifically, we first discussed gastrointestinal and immuno-inflammation pathways in-depth, exploring the relationships between microbial composition, bacterial metabolites, gut mucosa, and immune system constituents. Accounting for temporal differences in the mechanisms involved in neurodevelopment, prenatal and postnatal phases were further elucidated, where the former focused on maternal immune activation (MIA) and fetal development, while the latter addressed the role of immune dysregulation in contributing to atypical neurodevelopment. As autism remains, foremost, a neurodevelopmental disorder, this review presents an integration of disparate modules into a "Gut-Immune-Brain" paradigm. Existing gaps in the literature have been highlighted, and possible avenues for future research with an integrated physiological perspective underlying ASD have also been suggested.

The Perturbance of Microbiome and Gut-Brain Axis in Autism Spectrum Disorders

Gastrointestinal problems have been documented in Autism Spectrum Disorder (ASD). Studies have found that these disturbances may be associated with an altered gut microbiome in ASD. Furthermore, in ASD, these alterations are implicated in increased gut permeability, or “leaky gut”, which allows bacterial metabolites to cross the gut barrier, impacting neurodevelopment during early childhood in susceptible subjects by way of gut-brain axis. In our review, we will discuss the interaction of gut microbiota and brain development in ASD and the signaling mechanisms underlying this interaction. We will also explore the potential for treatment of ASD by targeting the microbiome with probiotics. Finally, this paper will attempt to provide significance to the aggregation of the research in this area of research; providing our interpretations and assessments of future of this field.