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.

Background: Compared to breast-fed (BF), formula-fed (FF) infants exhibit more rapid weight gain, a different fecal microbial profile, as well as elevated serum insulin, insulin growth factor 1 (IGF-1), and branched chain amino acids (BCAAs). Since infant formula contains more protein and lower free amino acids than breast milk, it is thought that protein and/or free amino acids may be key factors that explain phenotypic differences between BF and FF infants. Methods: Newborn rhesus monkeys (Macaca mulatta) were either exclusively BF or fed regular formula or reduced protein formula either supplemented or not with a mixture of amino acids. Longitudinal sampling and clinical evaluation were performed from birth to 16 weeks including anthropometric measurements, intake records, collection of blood for hematology, serum biochemistry, hormones, and metabolic profiling, collection of urine for metabolic profiling, and collection of feces for 16s rRNA fecal microbial community profiling. Results: Reducing protein in infant formula profoundly suppressed intake, lowered weight gain and improved the FF-specific metabolic phenotype in the first month of age. This time-dependent change paralleled an improvement in serum insulin. All lower protein FF groups showed reduced protein catabolism with lower levels of blood urea nitrogen (BUN), urea, ammonia, albumin, creatinine, as well as lower excretion of creatinine in urine compared to infants fed regular formula. Levels of fecal microbes (Bifidobacterium and Ruminococcus from the Ruminococcaceae family), that are known to have varying ability to utilize complex carbohydrates, also increased with protein reduction. Adding free amino acids to infant formula did not alter milk intake or fecal microbial composition, but did significantly increase urinary excretion of amino acids and nitrogen-containing metabolites. However, despite the lower protein intake, these infants still exhibited a distinct FF-specific metabolic phenotype characterized by accelerated weight gain, higher levels of insulin and C-peptide as well as elevated amino acids including BCAA, lysine, methionine, threonine and asparagine. Conclusions: Reducing protein and adding free amino acids to infant formula resulted in growth and metabolic performance of infants that were more similar to BF infants, but was insufficient to reverse the FF-specific accelerated growth and insulin-inducing high BCAA phenotype.

Background: Compared to breast-fed (BF), formula-fed (FF) infants exhibit more rapid weight gain, a different fecal microbial profile, as well as elevated serum insulin, insulin growth factor 1 (IGF-1), and branched chain amino acids (BCAAs). Since infant formula contains more protein and lower free amino acids than breast milk, it is thought that protein and/or free amino acids may be key factors that explain phenotypic differences between BF and FF infants. Methods: Newborn rhesus monkeys (Macaca mulatta) were either exclusively BF or fed regular formula or reduced protein formula either supplemented or not with a mixture of amino acids. Longitudinal sampling and clinical evaluation were performed from birth to 16 weeks including anthropometric measurements, intake records, collection of blood for hematology, serum biochemistry, hormones, and metabolic profiling, collection of urine for metabolic profiling, and collection of feces for 16s rRNA fecal microbial community profiling. Results: Reducing protein in infant formula profoundly suppressed intake, lowered weight gain and improved the FF-specific metabolic phenotype in the first month of age. This time-dependent change paralleled an improvement in serum insulin. All lower protein FF groups showed reduced protein catabolism with lower levels of blood urea nitrogen (BUN), urea, ammonia, albumin, creatinine, as well as lower excretion of creatinine in urine compared to infants fed regular formula. Levels of fecal microbes (Bifidobacterium and Ruminococcus from the Ruminococcaceae family), that are known to have varying ability to utilize complex carbohydrates, also increased with protein reduction. Adding free amino acids to infant formula did not alter milk intake or fecal microbial composition, but did significantly increase urinary excretion of amino acids and nitrogen-containing metabolites. However, despite the lower protein intake, these infants still exhibited a distinct FF-specific metabolic phenotype characterized by accelerated weight gain, higher levels of insulin and C-peptide as well as elevated amino acids including BCAA, lysine, methionine, threonine and asparagine. Conclusions: Reducing protein and adding free amino acids to infant formula resulted in growth and metabolic performance of infants that were more similar to BF infants, but was insufficient to reverse the FF-specific accelerated growth and insulin-inducing high BCAA phenotype.

Blood is a rich biological sample routinely collected in clinical and epidemiological studies. With advancements in high throughput -omics technology, such as metabolomics, epidemiology can now delve more deeply and comprehensively into biological mechanisms involved in the etiology of diseases. However, the impact of the blood collection tube matrix of samples collected needs to be carefully considered to obtain meaningful biological interpretations and understand how the metabolite signatures are affected by different tube types. In the present study, we investigated whether the metabolic profile of blood collected as serum differed from samples collected as ACD plasma, citrate plasma, EDTA plasma, fluoride plasma, or heparin plasma. We identified and quantified 50 metabolites present in all samples utilizing nuclear magnetic resonance (NMR) spectroscopy. The heparin plasma tubes performed the closest to serum, with only three metabolites showing significant differences, followed by EDTA which significantly differed for five metabolites, and fluoride tubes which differed in eleven of the fifty metabolites. Most of these metabolite differences were due to higher levels of amino acids in serum compared to heparin plasma, EDTA plasma, and fluoride plasma. In contrast, metabolite measurements from ACD and citrate plasma differed significantly for approximately half of the metabolites assessed. These metabolite differences in ACD and citrate plasma were largely due to significant interfering peaks from the anticoagulants themselves. Blood is one of the most banked samples and thus mining and comparing samples between studies requires understanding how the metabolite signature is affected by the different media and different tube types.

Background: Developmental disabilities are defined by delays in learning, language, and behavior, yet growing evidence has revealed disturbances in metabolic systems that may also be present. Little is known about whether these metabolic issues contribute to the symptoms or severity of these disabilities, or whether sex plays a role in these associations, given that boys are disproportionately affected by some developmental disabilities. Here we sought to investigate the correlation between psychometric scores, sex, and the plasma metabolome. Methods: The plasma metabolomes of children with autism spectrum disorder (ASD; n = 167), idiopathic developmental delay (i-DD; n = 51), Down syndrome (DS; n = 31), and typically developing controls (TD; n = 193) were investigated using NMR spectroscopy. Spearman rank correlations and multiple linear regression models (adjusted for child's neurodevelopmental diagnosis, child's sex, child's age, child's race/ethnicity, maternal age at child's birth, and parental homeownership) were used to examine the association between plasma metabolites and sex in relation to psychometric measures of cognitive skills, adaptive behavior, and maladaptive behavior in our study population. Results: Higher levels of metabolites involved in cellular energy and mitochondrial function among children with ASD (fumarate and cis-aconitate), DS (lactate), and TD (pyruvate) are associated with poorer cognitive and adaptive subscales. Similarly, higher o-acetylcarnitine associated with deficits in cognitive subscales among all DS cases and TD boys, and carnitine correlated with increased maladaptive behavior among girls with ASD and girls with DS. Among children with DS, elevated myo-inositol, ornithine, and creatine correlated with poorer scores across several subscales. Even among TD cases, elevated 3-hydroxybutyrate correlated with decreased receptive language. In contrast, higher levels of glutamate were associated with better socialization skills among ASD cases. Even after adjusting for the child's neurodevelopmental diagnosis, sex, and other possible confounders, key metabolites including glycolysis metabolites (lactate and pyruvate), ketone bodies (3-hydroxybutyrate and acetoacetate), TCA cycle metabolites (cis-aconitate and fumarate), as well as ornithine were associated with deficits in multiple domains of cognitive function, adaptive skills, and aberrant behaviors. Conclusions: Our results highlight that some plasma metabolites may relate to specific functional subdomains within cognitive, adaptive, and behavioral development with some variation by diagnosis and sex.

Background

Endocrine disrupting chemicals (EDCs) are widely used compounds with the potential to affect child neurodevelopmental outcomes including autism spectrum disorders (ASD). We aimed to examine the urinary concentrations of biomarkers of EDCs, including phthalates, phenols, and parabens, and investigate whether exposure during early infancy was associated with increased risk of later ASD or other non-typical development (Non-TD) or adverse cognitive development.

Methods

This analysis included infants from the Markers of Autism Risks in Babies-Learning Early Signs (MARBLES) study, a high-risk ASD cohort (n = 148; corresponding to 188 urine samples). Thirty-two EDC biomarkers were quantified in urine among infants 3 and/or 6 months of age. Trends in EDC biomarker concentrations were calculated using least square geometric means. At 36 months of age, children were clinically classified as having ASD (n = 36), nontypical development (Non-TD; n = 18), or typical development (TD; n = 81) through a clinical evaluation. Trinomial logistic regression analysis was used to test the associations between biomarkers with ASD, or Non-TD, as compared to children with TD. In single analyte analysis, generalized estimating equations were used to investigate the association between each EDC biomarkers and longitudinal changes in cognitive development using the Mullen Scales of Early Learning (MSEL) over the four assessment time points (6, 12, 24, and 36 months of age). Additionally, quantile g-computation was used to test for a mixture effect.

Results

EDC biomarker concentrations generally decreased over the study period, except for mono-2-ethyl-5-carboxypentyl terephthalate. Overall, EDC biomarkers at 3 and/or 6 months of age were not associated with an increased risk of ASD or Non-TD, and a few showed significant inverse associations. However, when assessing longitudinal changes in MSEL scores over the four assessment time points, elevated monoethyl phthalate (MEP) was significantly associated with reduced scores in the composite score (β = -0.16, 95% CI: 0.31, -0.02) and subscales of fine motor skills (β = -0.09, 95%CI: 0.17, 0.00), and visual reception (β = -0.11, 95% CI: 0.23, 0.01). Additionally, the sum of metabolites of di (2-ethylhexyl) terephthalate (ƩDEHTP) was associated with poorer visual reception (β = -0.09, 95% CI: 0.16, -0.02), and decreased composite scores (β = -0.11, 95% CI: 0.21, -0.01). Mixtures analyses using quantile g-computation analysis did not show a significant association between mixtures of EDC biomarkers and MSEL subscales or composite scores.

Conclusion

These findings highlight the potential importance of infant exposures on cognitive development. Future research can help further investigate whether early infant exposures are associated with longer-term deficits and place special attention on EDCs with increasing temporal trends and whether they may adversely affect neurodevelopment.