Maternal and cord plasma branched-chain amino acids and child risk of attention-deficit hyperactivity disorder: a prospective birth cohort study

Metabolomic Markers in Attention-Deficit/Hyperactivity Disorder (ADHD) among Children and Adolescents-A Systematic Review

Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.

Large-Scale Population-Based Studies of Blood Metabolome and Brain Health

Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n > 50 metabolites) and brain health reported in large-scale studies (n > 500 individuals).

Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder

The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.

Targeting the metabolic profile of amino acids to identify the key metabolic characteristics in cerebral palsy

Background

Cerebral palsy (CP) is a neurodevelopmental disorder characterized by motor impairment. In this study, we aimed to describe the characteristics of amino acids (AA) in the plasma of children with CP and identify AA that could play a potential role in the auxiliary diagnosis and treatment of CP.

Methods

Using high performance liquid chromatography, we performed metabolomics analysis of AA in plasma from 62 CP children and 60 healthy controls. Univariate and multivariate analyses were then applied to characterize different AA. AA markers associated with CP were then identified by machine learning based on the Lasso regression model for the validation of intra-sample interactions. Next, we calculated a discriminant formula and generated a receiver operating characteristic (ROC) curve based on the marker combination in the discriminant diagnostic model.

Results

A total of 33 AA were detected in the plasma of CP children and controls. Compared with controls, 5, 7, and 10 different AA were identified in total participants, premature infants, and full-term infants, respectively. Of these, β-amino-isobutyric acid [p = 2.9*10(-4), Fold change (FC) = 0.76, Variable importance of protection (VIP) = 1.75], tryptophan [p = 5.4*10(-4), FC = 0.87, VIP = 2.22], and asparagine [p = 3.6*10(-3), FC = 0.82, VIP = 1.64], were significantly lower in the three groups of CP patients than that in controls. The combination of β-amino-isobutyric acid, tryptophan, and taurine, provided high levels of diagnostic classification and risk prediction efficacy for preterm children with an area under the curve (AUC) value of 0.8741 [95% confidence interval (CI): 0.7322-1.000]. The discriminant diagnostic formula for preterm infant with CP based on the potential marker combination was defined by p = 1/(1 + e-(8.295-0.3848* BAIBA-0.1120*Trp + 0.0108*Tau)).

Conclusion

Full-spectrum analysis of amino acid metabolomics revealed a distinct profile in CP, including reductions in the levels of β-amino-isobutyric acid, tryptophan, and taurine. Our findings shed new light on the pathogenesis and diagnosis of premature infants with CP.

The Association between Macrosomia and Amino Acids' Levels in Maternal and Cord Sera: A Case-Control Study

This study aims to explore the relationship between macrosomia and amino acids in maternal and cord sera.

METHODS

In the case-control study, 78 pairs of mothers and newborns were recruited from December 2016 to November 2019. Participants were divided into the macrosomia group (BW ≥ 4000 g, n = 39) and the control group (BW between 2500 g and 3999 g, n = 39) according to the birth weight (BW) of newborns. Maternal vein blood samples were collected before delivery and cord vein blood samples were collected after birth. The levels of amino acids in maternal and cord sera were measured by liquid chromatography and mass spectrometry (LC-MS/MS) in the year 2021. The difference in amino acid levels in maternal and cord sera between the two groups was compared, and the contribution of each amino acid to the difference between the two groups was analyzed. Unconditional logistic regression analysis was used to test the relationship between macrosomia and amino acids.

RESULTS

In maternal serum during the antepartum, the levels of asparagine, glutamine, methionine, alanine, and threonine in the macrosomia group were higher but arginine was lower than that in the control group (p < 0.05). In cord serum, the levels of lysine, histidine, phenylalanine, arginine, tryptophan, valine, isoleucine, glutamate, tyrosine, and total essential amino acid (EAA) in the macrosomia group were lower while glutamine was higher than that in the control group (p < 0.05). The ratios of EAA, valine, threonine, methionine, tryptophan, and alanine in maternal serum to those in cord serum were higher, while the ratio of glutamine was lower in the macrosomia group (p < 0.05). Arginine and threonine in maternal serum and glutamate, glutamine, and histidine in cord serum were associated with macrosomia (p < 0.05).

CONCLUSION

Most of the amino acid levels in the maternal sera of the macrosomia group are higher than those in the control group, while most of the amino acids' levels in the cord sera of the macrosomia group are lower than those in the control group. The ratios of some amino acids in maternal serum to those in cord serum were different between the two groups. Arginine and threonine in maternal serum and glutamate, glutamine, and histidine in cord serum are closely related to macrosomia.

Boston Birth Cohort profile: rationale and study design

In1998, the Boston Birth Cohort (BBC) was initiated at Boston Medical Center (BMC) in response to persistently high rates of preterm birth (PTB, defined as birth before 37 weeks of gestation) in the US population and the longstanding profound PTB disparity among Black, Indigenous, and people of color (BIPOC). The BBC encompasses two linked study protocols: The PTB Study serves as the baseline recruitment in the BBC. It aims to address fundamental questions about the causes and consequences of PTB. The study oversamples preterm babies using a case/control study design, in which cases are defined as mothers who deliver a preterm and/or low birthweight baby (<2500 grams regardless of gestational age). Controls are enrolled at a 2:1 control/case ratio and matched by maternal age (±5 years), self-reported race and ethnicity, and date of delivery (± 7 days for case delivery). From inception, it was designed as a comprehensive gene-environmental study of PTB. As a natural extension, the Children's Health Study, under a separate but linked Institutional Review Board protocol, is a longitudinal follow-up study of the participants who were recruited at birth in the PTB Study and who continue pediatric care at BMC. This linked model allows for investigation of early life origins of pediatric and chronic disease in a prospective cohort design. The BBC is one of the largest and longest National Institutes of Health-funded prospective birth cohort studies in the United States, consisting of 8733 mother-child dyads enrolled in the PTB Study at birth, and of those, 3592 children have been enrolled in the Children's Health Study, with a median follow-up of 14.5 years. The BBC mirrors the urban, underresourced, and underrepresented BIPOC population served by BMC. A high proportion of BBC children were born prematurely and had chronic health conditions (e.g., asthma, obesity, and elevated blood pressure) in childhood. The BBC's long-term goal has been to build a large, comprehensive database (epidemiological, clinical, and multiomics) and biospecimen repository to elucidate early life origins of pediatric and chronic diseases and identify modifiable upstream factors (e.g., psychosocial, environmental, and nutritional) to improve health across the life course for BIPOC mothers and children.

Investigation of metabolomic biomarkers for childhood executive function and the role of genetic and dietary factors: The GUSTO cohort

Background

Few studies have investigated molecular biomarkers of specific executive function (EF) skills in children. We aimed to characterise the prospective associations between metabolome and multiple domains of EF using a bidirectional design.

Methods

This study was conducted within a longitudinal birth cohort, the Growing Up in Singapore Towards healthy Outcomes (GUSTO). Circulating levels of 165 metabolites were quantified using a nuclear magnetic resonance based metabolomics platform (n = 457 (∼6yrs) and n = 524 (∼8yrs)). Parent-reported EF was available for 495 children (∼7yrs). Multivariate linear regression was used to assess the metabolite-EF relationships. We examined the role of body composition, dietary factors, and genetics in the metabolite-EF associations.

Findings

Higher leucine level (∼6yrs) was associated with poorer EF (∼7yrs, Initiate (P = 0.003) and Working Memory (P = 0.004)). EF (∼7yrs) was not associated with leucine (∼8yrs). Importantly, we found weak evidence for associations of dietary factors (∼5yrs) with leucine (∼6yrs) and EF (∼7yrs). Each copy of C allele in rs1260326 (a leucine-related polymorphism) was associated with higher leucine level and poorer Initiate and Working Memory (P < 0.05). Amongst those with less strongly genetically influenced leucine, inverse association between leucine and cognitive regulation were weaker among those with higher BMI.

Interpretation

The observed association between higher leucine level and poorer EF may be determined by genetics and may not be easily amenable to dietary interventions. Further research is needed for validation and to understand mechanisms.

Funding

Singapore National Research Foundation and Agency for Science, Technology and Research.