Untargeted Metabolomics Screen of Mid-pregnancy Maternal Serum and Autism in Offspring

Disrupted fetal carbohydrate metabolism in children with autism spectrum disorder

BACKGROUND

Despite the power and promise of early detection and treatment in autism spectrum disorder (ASD), early-life biomarkers are limited. An early-life risk biosignature would advance the field's understanding of ASD pathogenies and targets for early diagnosis and intervention. We therefore sought to add to the growing ASD biomarker literature and evaluate whether fetal metabolomics are altered in idiopathic ASD.

METHODS

Banked cord blood plasma samples (N = 36 control, 16 ASD) were analyzed via gas chromatography and mass spectrometry (GC-MS). Samples were from babies later diagnosed with idiopathic ASD (non-familial, non-syndromic) or matched, neurotypical controls. Metabolite set enrichment analysis (MSEA) and biomarker prediction were performed (MetaboAnalyst).

RESULTS

We detected 76 metabolites in all samples. Of these, 20 metabolites differed significantly between groups: 10 increased and 10 decreased in ASD samples relative to neurotypical controls (p < 0.05). MSEA revealed significant changes in metabolic pathways related to carbohydrate metabolism and glycemic control. Untargeted principle components analysis of all metabolites did not reveal group differences, while targeted biomarker assessment (using only Fructose 6-phosphate, D-Mannose, and D-Fructose) by a Random Forest algorithm generated an area under the curve (AUC) = 0.766 (95% CI: 0.612-0.896) for ASD prediction.

CONCLUSIONS

Despite a high and increasing prevalence, ASD has no definitive biomarkers or available treatments for its core symptoms. ASD's earliest developmental antecedents remain unclear. We find that fetal plasma metabolomics differ with child ASD status, in particular invoking altered carbohydrate metabolism. While prior clinical and preclinical work has linked carbohydrate metabolism to ASD, no prior fetal studies have reported these disruptions in neonates or fetuses who go on to be diagnosed with ASD. Future work will investigate concordance with maternal metabolomics to determine maternal-fetal mechanisms.

Efficacy of sialic acid supplementation in early life in autism model rats

Autism spectrum disorder (ASD) is a set of heterogeneous neurodevelopmental conditions, the etiology of which remains elusive. Sialic acid (SA) is an essential nutrient for nervous system development, and previous studies reported that the levels of SA were decreased in the blood and saliva of ASD children. However, it is not clear whether SA supplementation can alleviate behavioral problems in autism. We administered SA intervention in the VPA-induced autism model rats, evaluated behavior performance, and measured the levels of Gne and St8sia2 genes, BDNF and anti-GM1. At the same time, untargeted metabolomics was used to characterize the metabolites. It was found that the stereotypical behaviors, social preference and cognitive function were improved after SA supplementation. Additionally, the number of hippocampal neurons was increased, and the shape was normalized. Moreover, 94 differentially abundant metabolites were identified between the high dose SA and VPA groups. These changes in metabolites were correlated with pyrimidine metabolism, lysine degradation metabolism, biosynthesis of amino acids, mineral absorption, protein digestion and absorption, galactose metabolism, phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism. In conclusion, SA could ameliorate ASD-like phenotypes and change metabolites in autistic animals, which suggests that it may be a therapeutic approach for ASD.

Amino Acid Patterns in Children with Autistic Spectrum Disorder: A Preliminary Biochemical Evaluation

BACKGROUND

The metabolism of plasma amino acid (AA) in children with autism spectrum disorder (ASD) has been extensively investigated, yielding inconclusive results. This study aims to characterize the metabolic alterations in AA profiles among early-diagnosed children with ASD and compare the findings with those from non-ASD children.

METHODS

We analyzed plasma AA profiles, measured by ion exchange chromatography, from 1242 ASD children (median age = 4 years; 81% male). Additionally, we studied AA profiles from 488 children, matched for age and free of ASD (control group). Principal component and cluster analysis were employed to explore potential associations within the ASD group and to identify subgroups.

RESULTS

We observed lower plasma levels of glutamine in children with ASD compared to non-ASD children (p < 0.001). Six essential, two conditionally essential, and four non-essential AA were found to be increased in children with ASD. The clustering analysis revealed two groups, labeled Neurological (NEU) and Nutritional (NUT), which included a majority of ASD children (94% and 78%, respectively). The NEU group exhibited high levels of taurine, aspartate, glutamic acid, and ornithine, while the NUT group showed elevated levels of branched-chain AA.

CONCLUSIONS

In children with ASD, we identified some heterogeneous AA patterns that may serve as biochemical signatures of neurological impairment in some individuals, while in others they may indicate nutritional dysregulation.

Untargeted Metabolomics Reveals Metabolic Link Between Histone H3K27 Demethylase UTX and Neurodevelopment

Ubiquitously transcribed tetratricopeptide repeat on chromosome X (UTX) is a chromatin modifier responsible for regulating the demethylation of histone H3 lysine 27 trimethylation (H3K27me3), which is crucial for human neurodevelopment. To date, the impact of UTX on neurodevelopment remains elusive. Therefore, this study aimed to investigate the potential molecular mechanisms underlying the effects of UTX on neurodevelopment through untargeted metabolomics based on ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). We found that UTX knockout in neurones leads to cell death and apoptosis in the hippocampus and cortex, as well as induces impaired learning and memory functions in mice. Moreover, UTX deletion contributed to significant metabolic perturbations in brain tissues. A total of 223 differential metabolites were identified between wild-type (WT) and UTX cKO mice. Pathway analysis indicated that the metabolic pathways mainly affected by UTX deletion were alanine, aspartate, and glutamate metabolism, resulting in significant alterations in L-alanine, L-aspartate, D-aspartate, N-acetylaspartylglutamate, L-glutamate, and argininosuccinic acid. These data emphasised that UTX may exert a key effect in neurodevelopment and that the underlying mechanism may be related to the regulation of the alanine, aspartate, and glutamate metabolism pathways, especially the characteristic metabolites involved in this pathway.

Exogenous ketone bodies and the ketogenic diet as a treatment option for neurodevelopmental disorders

Background

Despite being the most prevalent neurodevelopmental disorders, there are comparatively few treatment options available to patients presenting with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The ketogenic diet has historically shown therapeutic utility in treating refractory epilepsy, an adjacent neuropsychiatric condition, in children, adolescents and adults. The following review explores preclinical and clinical literature focusing on the therapeutic potential of the ketogenic diet and exogenous ketone body supplementation in treating common neurodevelopmental disorders.

Method

A narrative review of extant literature was conducted across the domains of perinatal nutrition, ASD, and ADHD. Preclinical and clinical studies focusing on the effect of either the ketogenic diet or exogenous ketone supplementation as a treatment option were included for review.

Results

14 preclinical and 10 clinical studies were included for discussion. Data supporting the use of a ketogenic intervention for neurodevelopmental disorders is mixed. High heterogeneity in study design was noted for preclinical models, ketogenic intervention, and outcomes measured.

Conclusion

Studies evaluating ketogenic interventions for neurodevelopmental disorders remain in their infancy in terms of both the depth and scope of available literature. The safety and tolerability of ketogenic diets and supplements means there would be value in exploring their effectiveness further in clinical studies.

Dysregulated metabolic pathways associated with air pollution exposure and the risk of autism: Evidence from epidemiological studies

Autism spectrum disorder (ASD) is a developmental disorder with symptoms that range from social and communication impairments to restricted interests and repetitive behavior and is the 4th most disabling condition for children aged 5-14. Risk factors of ASD are not fully understood. Environmental risk factors are believed to play a significant role in the ASD epidemic. Research focusing on air pollution exposure as an early-life risk factor of autism is growing, with numerous studies finding associations of traffic and industrial emissions with an increased risk of ASD. One of the possible mechanisms linking autism and air pollution exposure is metabolic dysfunction. However, there were no consensus about the key metabolic pathways and corresponding metabolite signatures in mothers and children that are altered by air pollution exposure and cause the ASD. Therefore, we performed a review of published papers examining the metabolomic signatures and metabolic pathways that are associated with either air pollution exposure or ASD risk in human studies. In conclusion, we found that dysregulated lipid, fatty acid, amino acid, neurotransmitter, and microbiome metabolisms are associated with both short-term and long-term air pollution exposure and the risk of ASD. These dysregulated metabolisms may provide insights into ASD etiology related to air pollution exposure, particularly during the perinatal period in which neurodevelopment is highly susceptible to damage from oxidative stress and inflammation.

Disrupted Prenatal Metabolism May Explain the Etiology of Suboptimal Neurodevelopment: A Focus on Phthalates and Micronutrients and their Relationship to Autism Spectrum Disorder

Pregnancy is a time of high metabolic coordination, as maternal metabolism adapts to support the growing fetus. Many of these changes are coordinated by the placenta, a critical fetal endocrine organ and the site of maternal-fetal crosstalk. Dysregulation in maternal and placental metabolism during pregnancy has been linked to adverse outcomes, including altered neurodevelopment. Autism spectrum disorder (ASD) is a neurodevelopmental disorder linked to metabolic alterations in both children and their mothers. Prenatal environmental exposures have been linked to risk of ASD through dysregulated maternal, placental, and fetal metabolism. In this review, we focus on recent studies investigating the associations between prenatal metabolism in the maternal-placental-fetal unit and the impact of prenatal environmental exposures to phthalates and micronutrients on ASD risk. By identifying the mechanisms through which phthalates and other ubiquitous endocrine disrupting chemicals influence development, and how nutritional interventions can impact those mechanisms, we can identify promising ways to prevent suboptimal neurodevelopment.

Maternal Steroid Hormone Levels in Early Pregnancy and Autism in the Offspring: A Population-Based, Nested Case-Control Study

BACKGROUND

A role for prenatal steroid hormones in the etiology of autism has been proposed, but evidence is conflicting.

METHODS

Here, we examined serum levels of maternal estradiol, testosterone, 17-hydroxyprogesterone (OHP), and cortisol from the first trimester of gestation (mean = 10.1 weeks) in relation to the odds of diagnosed autism with and without co-occurring intellectual disability (ID) in the offspring (n = 118 autism with ID, n = 249 autism without ID, n = 477 control). Levels of maternal hormones were measured using highly sensitive liquid chromatography tandem mass spectrometry, standardized according to gestational timing of sample collection, and analyzed with restricted cubic spline logistic regression models adjusting for child's sex and maternal health, demographic, and socioeconomic factors.

RESULTS

We observed significant nonlinear associations between maternal estradiol, 17-OHP, and cortisol with autism, which varied with the presence of co-occurring ID. Compared to mean levels, lower levels of estradiol were associated with higher odds of autism with ID (odds ratio for concentrations 1 SD below the mean = 1.66; 95% CI, 1.24-2.11), while higher cortisol levels were associated with lower odds (odds ratio for 1 SD above the mean = 0.55; 95% CI, 0.36-0.88). In contrast, higher 17-OHP was associated with increased odds of autism without ID (odds ratio for 1 SD above the mean = 1.49; 95% CI, 1.11-1.99). We observed no evidence for interaction with sex of the child.

CONCLUSIONS

These findings support the notion that the maternal steroid hormonal environment in early pregnancy may contribute to autism, but also emphasize the complex relationship between early-life steroid exposure and autism.

Des-Arg(9) bradykinin as a causal metabolite for autism spectrum disorder

BACKGROUND

Early diagnosis and therapeutic interventions can greatly enhance the developmental trajectory of children with autism spectrum disorder (ASD). However, the etiology of ASD is not completely understood. The presence of confounding factors from environment and genetics has increased the difficulty of the identification of diagnostic biomarkers for ASD.

AIM

To estimate and interpret the causal relationship between ASD and metabolite profile, taking into consideration both genetic and environmental influences.

METHODS

A two-sample Mendelian randomization (MR) analysis was conducted using summarized data from large-scale genome-wide association studies (GWAS) including a metabolite GWAS dataset covering 453 metabolites from 7824 European and an ASD GWAS dataset comprising 18381 ASD cases and 27969 healthy controls. Metabolites in plasma were set as exposures with ASD as the main outcome. The causal relationships were estimated using the inverse variant weight (IVW) algorithm. We also performed leave-one-out sensitivity tests to validate the robustness of the results. Based on the drafted metabolites, enrichment analysis was conducted to interpret the association via constructing a protein-protein interaction network with multi-scale evidence from databases including Infinome, SwissTargetPrediction, STRING, and Metascape.

RESULTS

Des-Arg(9)-bradykinin was identified as a causal metabolite that increases the risk of ASD (β = 0.262, SE = 0.064, PIVW = 4.64 × 10-5). The association was robust, with no significant heterogeneity among instrument variables (PMR Egger = 0.663, PIVW = 0.906) and no evidence of pleiotropy (P = 0.949). Neuroinflammation and the response to stimulus were suggested as potential biological processes mediating the association between Des-Arg(9) bradykinin and ASD.

CONCLUSION

Through the application of MR, this study provides practical insights into the potential causal association between plasma metabolites and ASD. These findings offer perspectives for the discovery of diagnostic or predictive biomarkers to support clinical practice in treating ASD.

Cord Blood Metabolite Profiles and Their Association with Autistic Traits in Childhood

Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental condition. Gene-environmental interactions in early stages of life might alter metabolic pathways, possibly contributing to ASD pathophysiology. Metabolomics may serve as a tool to identify underlying metabolic mechanisms contributing to ASD phenotype and could help to unravel its complex etiology. In a population-based, prospective cohort study among 783 mother-child pairs, cord blood serum concentrations of amino acids, non-esterified fatty acids, phospholipids, and carnitines were obtained using liquid chromatography coupled with tandem mass spectrometry. Autistic traits were measured at the children's ages of 6 (n = 716) and 13 (n = 648) years using the parent-reported Social Responsiveness Scale. Lower cord blood concentrations of SM.C.39.2 and NEFA16:1/16:0 were associated with higher autistic traits among 6-year-old children, adjusted for sex and age at outcome. After more stringent adjustment for confounders, no significant associations of cord blood metabolites and autistic traits at ages 6 and 13 were detected. Differences in lipid metabolism (SM and NEFA) might be involved in ASD-related pathways and are worth further investigation.

Association between Neuroligin-1 polymorphism and plasma glutamine levels in individuals with autism spectrum disorder

BACKGROUND

Unravelling the relationships between candidate genes and autism spectrum disorder (ASD) phenotypes remains an outstanding challenge. Endophenotypes, defined as inheritable, measurable quantitative traits, might provide intermediary links between genetic risk factors and multifaceted ASD phenotypes. In this study, we sought to determine whether plasma metabolite levels could serve as endophenotypes in individuals with ASD and their family members.

METHODS

We employed an untargeted, high-resolution metabolomics platform to analyse 14,342 features across 1099 plasma samples. These samples were collected from probands and their family members participating in the Autism Genetic Resource Exchange (AGRE) (N = 658), compared with neurotypical individuals enrolled in the PrecisionLink Health Discovery (PLHD) program at Boston Children's Hospital (N = 441). We conducted a metabolite quantitative trait loci (mQTL) analysis using whole-genome genotyping data from each cohort in AGRE and PLHD, aiming to prioritize significant mQTL and metabolite pairs that were exclusively observed in AGRE.

FINDINGS

Within the AGRE group, we identified 54 significant associations between genotypes and metabolite levels (P < 5.27 × 10-11), 44 of which were not observed in the PLHD group. Plasma glutamine levels were found to be associated with variants in the NLGN1 gene, a gene that encodes post-synaptic cell-adhesion molecules in excitatory neurons. This association was not detected in the PLHD group. Notably, a significant negative correlation between plasma glutamine and glutamate levels was observed in the AGRE group, but not in the PLHD group. Furthermore, plasma glutamine levels showed a negative correlation with the severity of restrictive and repetitive behaviours (RRB) in ASD, although no direct association was observed between RRB severity and the NLGN1 genotype.

INTERPRETATION

Our findings suggest that plasma glutamine levels could potentially serve as an endophenotype, thus establishing a link between the genetic risk associated with NLGN1 and the severity of RRB in ASD. This identified association could facilitate the development of novel therapeutic targets, assist in selecting specific cohorts for clinical trials, and provide insights into target symptoms for future ASD treatment strategies.

FUNDING

This work was supported by the National Institute of Health (grant numbers: R01MH107205, U01TR002623, R24OD024622, OT2OD032720, and R01NS129188) and the PrecisionLink Biobank for Health Discovery at Boston Children's Hospital.

Metabolomic analysis of maternal mid-gestation plasma and cord blood in autism spectrum disorders

The discovery of prenatal and neonatal molecular biomarkers has the potential to yield insights into autism spectrum disorder (ASD) and facilitate early diagnosis. We characterized metabolomic profiles in ASD using plasma samples collected in the Norwegian Autism Birth Cohort from mothers at weeks 17-21 gestation (maternal mid-gestation, MMG, n = 408) and from children on the day of birth (cord blood, CB, n = 418). We analyzed associations using sex-stratified adjusted logistic regression models with Bayesian analyses. Chemical enrichment analyses (ChemRICH) were performed to determine altered chemical clusters. We also employed machine learning algorithms to assess the utility of metabolomics as ASD biomarkers. We identified ASD associations with a variety of chemical compounds including arachidonic acid, glutamate, and glutamine, and metabolite clusters including hydroxy eicospentaenoic acids, phosphatidylcholines, and ceramides in MMG and CB plasma that are consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission and neurotoxicity. Girls with ASD have disruption of ether/non-ether phospholipid balance in the MMG plasma that is similar to that found in other neurodevelopmental disorders. ASD boys in the CB analyses had the highest number of dysregulated chemical clusters. Machine learning classifiers distinguished ASD cases from controls with area under the receiver operating characteristic (AUROC) values ranging from 0.710 to 0.853. Predictive performance was better in CB analyses than in MMG. These findings may provide new insights into the sex-specific differences in ASD and have implications for discovery of biomarkers that may enable early detection and intervention.

Dysregulation of immune and metabolism pathways in maternal immune activation induces an increased risk of autism spectrum disorders

AIMS

Maternal immune activation (MIA) via infection during pregnancy is known to be an environmental risk factor for neurodevelopmental disorders and the development of autism spectrum disorders (ASD) in the offspring, but it still remains elusive that the molecular relevance between infection-induced abnormal neurodevelopmental events and an increased risk for ASD development.

MAIN METHODS

Fully considering the extremely high genetic heterogeneity of ASD and the universality of risk-gene with minimal effect-sizes, the gene and pathway-based association analysis was performed with the transcriptomic and DNA methylation landscapes of temporal human embryonic brain development and ASD, and the time-course transcriptional profiling of MIA. We conducted the transcriptional profiling of mouse abnormal neurodevelopment two days following induced MIA via LPS injection at E10.5.

KEY FINDINGS

A novel evidence was proved that illustrated altering four immune and metabolism-related risk pathways, including starch and sucrose metabolism, ribosome, protein processing in endoplasmic reticulum, and retrograde endocannabinoid signaling pathway, which were prominent involvement in the process of MIA regulating abnormal fetal brain development to induce an increased risk of ASD. Here, we have observed that almost all key genes within these risk pathways are significantly differentially expressed at embryonic days (E) 10.5-12.5, which is considered to be the optimal coincidence window of mouse embryonic brain development to study the intimate association between MIA and ASD using mouse animal models.

SIGNIFICANCE

There search establishes that MIA causes dysregulation of immune and metabolic pathways, which leads to abnormal embryonic neurodevelopment, thus promoting development of ASD symptoms in offspring.

Steroid hormone pathways, vitamin D and autism: a systematic review

The origins of the male preponderance in autism incidence remain unclear. The idea that perinatal factors associated with sex differentiation (e.g., steroid hormone pathways) may increase the possibility of the emergence of autism is complementary to the hypothesis that female individuals are intrinsically less likely to develop autism. Empirical evidence for the mechanistic roles of in utero steroid hormones in autism etiology is accumulating but inconsistent. We conducted a systematic review using rigorous criteria for the measurements of steroids and vitamin D exposure, to summarize the potential contributing roles of prenatal and early postnatal steroids and vitamin D alterations to the emergence of autism. We searched PubMed, PsychInfo, Scopus, and included 22 studies for qualitative synthesis. Among them, six studies examined the association of autism diagnoses in offspring and levels of steroids and precursor steroid hormones in the fetal environment, eight studies examined the associations between autism and maternal and fetal blood vitamin D levels during pregnancy and at birth, and eight studies examined the associations between offspring autism diagnoses and maternal hyperandrogenemia diagnosed before pregnancy. We identified promising and complex results regarding the relations between steroid metabolism and autism. The interpretation of findings was limited by the mostly observational study designs, insufficient investigation of the effects of offspring sex, confounders and their cumulative effects on the development of the child, and unclear impact of the timing of steroids exposure and their effects on fetal neurodevelopment.

Liquid Biopsy in Adverse Neurodevelopment of Children: Problems and Prospects

Neurodevelopmental disorders in children have an important impact on the quality of life in the whole life cycle. Severe neurodevelopmental disorders will become a serious social and family burden and an important social and economic problem. The early and middle childhood is the critical period of children's neurodevelopment. Early diagnosis of neurological disorders plays an important role in guiding children's neurological development. Existing monitoring tools lack prenatal and even early assessment of children's neurodevelopment, so reliable biomarkers are conducive to personalized care at an earlier stage. In this review, we will discuss different methods of neurodevelopmental monitoring at different times and the role and evaluation of liquid biopsy in neurodevelopmental monitoring.

Microbial regulation of offspring diseases mediated by maternal-associated microbial metabolites

The microbiota plays a crucial role in individuals’ early and long-term health. Previous studies indicated that the microbial regulation of health may start before birth. As the in utero environment is (nearly) sterile, the regulation is probably be originated from maternal microbiota and mediated by their metabolites transferred across the placenta. After the birth, various metabolites are continuously delivered to offspring through human milk feeding. Meanwhile, some components, for example, human milk oligosaccharides, in human milk can only be fermented by microbes, which brings beneficial effects on offspring health. Hence, we speculated that human milk-derived metabolites may also play roles in microbial regulation. However, reports between maternal-associated microbial metabolites and offspring diseases are still lacking and sparsely distributed in several fields. Also, the definition of the maternal-associated microbial metabolite is still unclear. Thus, it would be beneficial to comb through the current knowledge of these metabolites related to diseases for assisting our goals of early prediction, early diagnosis, early prevention, or early treatment through actions only on mothers. Therefore, this review aims to present studies showing how researchers came to the path of investigating these metabolites and then to present studies linking them to the development of offspring asthma, type 1 diabetes mellitus, food allergy, neonatal necrotizing enterocolitis, or autism spectrum disorder. Potential English articles were collected from PubMed by searching terms of disease(s), maternal, and a list of microbial metabolites. Articles published within 5 years were preferred.

Maternal Serum and Placental Metabolomes in Association with Prenatal Phthalate Exposure and Neurodevelopmental Outcomes in the MARBLES Cohort

Prenatal exposure to phthalates, a family of endocrine-disrupting plasticizers, is associated with disruption of maternal metabolism and impaired neurodevelopment. We investigated associations between prenatal phthalate exposure and alterations of both the maternal third trimester serum metabolome and the placental metabolome at birth, and associations of these with child neurodevelopmental outcomes using data and samples from the Markers of Autism Risk in Babies Learning Early Signs (MARBLES) cohort. The third trimester serum (n = 106) and placental (n = 132) metabolomes were investigated using 1H nuclear magnetic resonance spectroscopy. Children were assessed clinically for autism spectrum disorder (ASD) and cognitive development. Although none of the urinary phthalate metabolite concentrations were associated with maternal serum metabolites after adjustment for covariates, mixture analysis using quantile g-computation revealed alterations in placental metabolites with increasing concentrations of phthalate metabolites that included reduced concentrations of 2-hydoxybutyrate, carnitine, O-acetylcarnitine, glucitol, and N-acetylneuraminate. Child neurodevelopmental outcome was not associated with the third trimester serum metabolome, but it was correlated with the placental metabolome in male children only. Maternal phthalate exposure during pregnancy is associated with differences in the placental metabolome at delivery, and the placental metabolome is associated with neurodevelopmental outcomes in males in a cohort with high familial ASD risk.

Distinct metabolic profiles associated with autism spectrum disorder versus cancer in individuals with germline PTEN mutations

PTEN hamartoma tumor syndrome (PHTS), caused by germline PTEN mutations, has been associated with organ-specific cancers and autism spectrum disorder (ASD) and/or developmental delay (DD). Predicting precise clinical phenotypes in any one PHTS individual remains impossible. We conducted an untargeted metabolomics study on an age- and sex-matched series of PHTS individuals with ASD/DD, cancer, or both phenotypes. Using agnostic metabolomic-analyses from patient-derived lymphoblastoid cells and their spent media, we found 52 differentially abundant individual metabolites, 69 cell/media metabolite ratios, and 327 pair-wise metabotype (shared metabolic phenotype) ratios clearly distinguishing PHTS individuals based on phenotype. Network analysis based on significant metabolites pointed to hubs converging on PTEN-related insulin, MAPK, AMPK, and mTOR signaling cascades. Internal cross-validation of significant metabolites showed optimal overall accuracy in distinguishing PHTS individuals with ASD/DD versus those with cancer. Such metabolomic markers may enable more accurate risk predictions and prevention in individual PHTS patients at highest risk.

Maternal early-pregnancy body mass index-associated metabolomic component and mental and behavioral disorders in children

Maternal pre-pregnancy obesity and/or higher body mass index (BMI) have been associated with neurodevelopmental and mental health adversities in children. While maternal metabolomic perturbations during pregnancy may underpin these associations, the existing evidence is limited to studying individual metabolites, not capturing metabolic variation specific to maternal BMI, and not accounting for the correlated nature of the metabolomic measures. By using multivariate supervised analytical methods, we first identified maternal early-pregnancy BMI-associated metabolomic component during pregnancy. We then examined whether this component was associated with mental and behavioral disorders in children, improved the prediction of the child outcomes over maternal BMI, and what proportion of the effect of maternal BMI on the child outcomes this component mediated. Early-pregnancy BMI of 425 mothers participating in the PREDO study was extracted from the national Medical Birth Register. During pregnancy, mothers donated up to three blood samples, from which a targeted panel of 68 metabolites were measured. Mental and behavioral disorders in children followed-up from birth until 8.4-12.8 years came from the Care Register for Health Care. Of the 68 metabolites averaged across the three sampling points, 43 associated significantly with maternal early-pregnancy BMI yielding a maternal early-pregnancy BMI-associated metabolomic component (total variance explained, 55.4%; predictive ability, 52.0%). This metabolomic component was significantly associated with higher hazard of any mental and behavioral disorder [HR 1.45, 95%CI(1.15, 1.84)] and relative risk of having a higher number of co-morbid disorders [RR 1.43, 95%CI(1.12, 1.69)] in children. It improved the goodness-of-model-fit over maternal BMI by 37.7-65.6%, and hence the predictive significance of the model, and mediated 60.8-75.8% of the effect of maternal BMI on the child outcomes. Maternal BMI-related metabolomic perturbations during pregnancy are associated with a higher risk of mental and behavioral disorders in children. These findings may allow identifying metabolomic targets for personalized interventions.

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.

Maternal and fetal metabolomic alterations in maternal lipopolysaccharide exposure-induced male offspring glucose metabolism disorders

Maternal lipopolysaccharide (LPS) exposure during pregnancy induces metabolic abnormalities in male offspring, but the underlying mechanisms remain unclear. The purpose of this study was to investigate the effects of maternal LPS exposure during pregnancy on metabolic profiling of maternal serum and male fetal liver using Liquid Chromatograph Mass Spectrometer techniques. From day 15 to day 17 of gestation, pregnant mice were administered intraperitoneal LPS (experimental group) (50 μg/kg/d) or saline (control group). On day 18 of gestation, maternal serum and male fetal liver were collected. After LPS exposure, levels of 38 and 75 metabolites, mainly glycerophospholipid and fatty acid metabolites, were altered in maternal serum and male fetal liver, respectively. It was found that in maternal serum and male fetal livers, the glycerophospholipids containing saturated fatty acids (SFAs) and the SFAs were upregulated, while the glycerophospholipids containing polyunsaturated fatty acids (PUFAs) and the PUFAs were downregulated. This concordance between maternal and fetal alterations in glycerophospholipid and fatty acid metabolites may be a metabolomic signature of the early intrauterine period and may provide insight into the mechanisms by which maternal LPS exposure induces disorders of glucose metabolism in male offspring.

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.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Altered metabolism of mothers of young children with Autism Spectrum Disorder: a case control study

Background

Previous research studies have demonstrated abnormalities in the metabolism of mothers of young children with autism.

Methods

Metabolic analysis was performed on blood samples from 30 mothers of young children with Autism Spectrum Disorder (ASD-M) and from 29 mothers of young typically-developing children (TD-M). Targeted metabolic analysis focusing on the folate one-carbon metabolism (FOCM) and the transsulfuration pathway (TS) as well as broad metabolic analysis were performed. Statistical analysis of the data involved both univariate and multivariate statistical methods.

Results

Univariate analysis revealed significant differences in 5 metabolites from the folate one-carbon metabolism and the transsulfuration pathway and differences in an additional 48 metabolites identified by broad metabolic analysis, including lower levels of many carnitine-conjugated molecules.

Multivariate analysis with leave-one-out cross-validation allowed classification of samples as belonging to one of the two groups of mothers with 93% sensitivity and 97% specificity with five metabolites. Furthermore, each of these five metabolites correlated with 8–15 other metabolites indicating that there are five clusters of correlated metabolites. In fact, all but 5 of the 50 metabolites with the highest area under the receiver operating characteristic curve were associated with the five identified groups. Many of the abnormalities appear linked to low levels of folate, vitamin B12, and carnitine-conjugated molecules.

Conclusions

Mothers of children with ASD have many significantly different metabolite levels compared to mothers of typically developing children at 2–5 years after birth.