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

Maternal antenatal depression is associated with metabolic alterations that predict birth outcomes, neurodevelopment and mental health of the child

BACKGROUND

Evidence regarding metabolic alterations associated with maternal antenatal depression (AD) is limited, and their role as potential biomarkers improving the prediction of AD and adverse child birth, neurodevelopmental, and mental health outcomes remains unexplored.

METHODS

In a cohort of 331 mother-child dyads, we studied associations between AD (history of medical register diagnoses and/or Center of Epidemiological Studies Depression Scale score during pregnancy≥20) and 95 metabolic measures analyzed three times during pregnancy. We tested whether the AD-related metabolic measures increased variance explained in AD over its risk factors, and in child birth, neurodevelopmental, and mental health outcomes over AD. We replicated the findings in a cohort of 416 mother-child dyads.

RESULTS

Elastic net regression identified 15 metabolic measures that collectively explained 25% (p<0.0001) of variance in AD, including amino and fatty acids, glucose, inflammation, and lipids. These metabolic measures increased the variance explained in AD over its risk factors (32.3%,p<0.0001 vs. 12.6%,p=0.004), and in child gestational age (9.0%,p<0.0001 vs. 0.7%, p=0.34), birth weight(9.0%,p=0.03 vs. 0.7%, p=0.33), developmental milestones at the age of 2.3-5.7 years(21.0%,p=0.002 vs. 11.6%,p<0.001) and any mental or behavioral disorder by the age of 13.1-16.8 years(25.2%,p=0.03 vs. 5.0%,p=0.11) over AD, child sex and age. These findings replicated in the independent cohort.

CONCLUSIONS

AD is associated with alterations in 15 metabolic measures, which collectively improve the prediction of AD over its risk factors, and birth, neurodevelopmental and mental health outcomes of the child over AD. These metabolic measures may become biomarkers identifying at-risk mothers and children for personalized interventions.

Maternal obesity alters fetal neuroinflammation in a murine model of preterm birth

BACKGROUND

Preterm birth from intrauterine infection is a leading cause of neonatal neurologic morbidity. Likewise, maternal obesity is associated with intra-amniotic infection and inflammation. Whether maternal obesity is a risk factor for fetal brain injury that occurs with premature birth remains unknown. This study hypothesized that maternal obesity intensifies fetal neuroinflammation in the setting of premature delivery.

OBJECTIVE

This study aimed to examine the influence of maternal obesity on perinatal neuroinflammatory responses that arise with preterm birth using a murine model.

STUDY DESIGN

Dams with obesity were generated via a high-fat diet that was maintained throughout pregnancy. In parallel, dams without obesity (normal) received a control diet. All dams were paired with males on normal diet. Pregnant dams were randomized to receive an intrauterine administration of bacterial endotoxin (lipopolysaccharide) or the vehicle (phosphate-buffered saline) on embryo day 15.5 of what is typically a 19- to 21-day gestation. Fetal brains were harvested 6 hours after intrauterine administrations, and the expressions of key inflammatory cytokines (Il1b, Il6, and Tnf) and panels of metabolic, immune, and inflammatory genes were analyzed.

RESULTS

With the phosphate-buffered saline, there was no difference in gene expression related to maternal obesity. There were substantial differences in Il6 and immune/inflammatory expression profiles in fetal brains from dams with obesity vs normal dams that received lipopolysaccharide. Few differences were observed among the metabolic genes examined under these conditions. The gene expression pattern associated with maternal obesity correlated with pathways related to white matter injury.

CONCLUSION

The expression of neuroinflammatory markers instigated by bacterial endotoxin via intrauterine lipopolysaccharide was greater in embryo brains obtained from dams with obesity. Expression profiles suggest that in combination with intrauterine inflammation, maternal obesity may increase the risk of fetal white matter injury. Further investigation is warranted to understand the relationship between maternal health and neurologic outcomes associated with prematurity.

Associations of polymetabolic risk of high maternal pre-pregnancy body mass index with pregnancy complications, birth outcomes, and early childhood neurodevelopment: findings from two pregnancy cohorts

BACKGROUND

A substantial proportion of maternal pregnancy complications, adverse birth outcomes and neurodevelopmental delay in children may be attributable to high maternal pre-pregnancy Body Mass Index (BMI). However, BMI alone is insufficient for the identification of all at-risk mothers and children as many women with non-obesity(< 30 kg/m2) or normal weight(18.5-24.99 kg/m2) and their children may suffer from adversities. Evidence suggests that BMI-related metabolic changes during pregnancy may predict adverse mother-child outcomes better than maternal anthropometric BMI.

METHODS

In a cohort of 425 mother-child dyads, we identified maternal BMI-defined metabolome based on associations of 95 metabolic measures measured three times during pregnancy with maternal pre-pregnancy BMI. We then examined whether maternal BMI-defined metabolome performed better than anthropometric BMI in predicting gestational diabetes, hypertensive disorders, gestational weight gain (GWG), Caesarian section delivery, child gestational age and weight at birth, preterm birth, admission to neonatal intensive care unit (NICU), and childhood neurodevelopment. Based on metabolic measures with the highest contributions to BMI-defined metabolome, including inflammatory and glycolysis-related measures, fatty acids, fluid balance, ketone bodies, lipids and amino acids, we created a set of maternal high BMI-related polymetabolic risk scores (PMRSs), and in an independent replication cohort of 489 mother-child dyads tested their performance in predicting the same set of mother-child outcomes in comparison to anthropometric BMI.

RESULTS

BMI-defined metabolome predicted all of the studied mother-child outcomes and improved their prediction over anthropometric BMI, except for gestational hypertension and GWG. BMI-related PMRSs predicted gestational diabetes, preeclampsia, Caesarian section delivery, admission to NICU, lower gestational age at birth, lower cognitive development score of the child, and improved their prediction over anthropometric BMI. BMI-related PMRSs predicted gestational diabetes, preeclampsia, Caesarean section delivery, NICU admission and child's lower gestational age at birth even at the levels of maternal non-obesity and normal weight.

CONCLUSIONS

Maternal BMI-defined metabolome improves the prediction of pregnancy complications, birth outcomes, and neurodevelopment in children over anthropometric BMI. The novel, BMI-related PMRSs generated based on the BMI-defined metabolome have the potential to become biomarkers identifying at-risk mothers and their children for timely targeted interventions even at the level of maternal non-obesity and normal weight.

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.

Maternal Inflammatory Biomarkers during Pregnancy and Early Life Neurodevelopment in Offspring: Results from the VDAART Study

Maternal infection and stress during the prenatal period have been associated with adverse neurodevelopmental outcomes in offspring, suggesting that biomarkers of increased inflammation in the mothers may associate with poorer developmental outcomes. In 491 mother-child pairs from the Vitamin D Antenatal Asthma Reduction Trial (VDAART), we investigated the association between maternal levels of two inflammatory biomarkers; interleukin-8 (IL-8) and C-Reactive Protein (CRP) during early (10-18 wks) and late (32-38 wks) pregnancy with offspring scores in the five domains of the Ages and Stages Questionnaire, a validated screening tool for assessing early life development. We identified a robust association between early pregnancy IL-8 levels and decreased fine-motor (β: -0.919, 95%CI: -1.425, -0.414, p = 3.9 × 10^-4) and problem-solving skills at age two (β: -1.221, 95%CI: -1.904, -0.414, p = 4.9 × 10^-4). Associations between IL-8 with other domains of development and those for CRP did not survive correction for multiple testing. Similarly, while there was some evidence that the detrimental effects of early pregnancy IL-8 were strongest in boys and in those who were not breastfed, these interactions were not robust to correction for multiple testing. However, further research is required to determine if other maternal inflammatory biomarkers associate with offspring neurodevelopment and work should continue to focus on the management of factors leading to increases in IL-8 levels in pregnant women.

Maternal pre-pregnancy obesity and offspring hyperactivity-inattention symptoms at 5 years in preterm and term children: a multi-cohort analysis

The objective of this study was to determine the relationship between maternal pre-pregnancy body mass index (BMI) and child hyperactivity-inattention symptoms (HIS) at 5 years, including preterm and term-born children, and to determine whether this association varied with gestational age. Maternal pre-pregnancy BMI and offspring HIS were assessed in 10,898 participants born ≥ 33 weeks of gestation from the ELFE cohort and 2646 children born between 23 and 34 weeks from the EPIPAGE 2 cohort. Reported pre-pregnancy weight (kg) and measured height (m) were collected from mothers at inclusion and used to classify BMI (kg/m²). Child HIS were evaluated using the Strengths and Difficulties Questionnaire around 5 years of age. Logistic regression estimated odds ratios (OR) of a high HIS score (≥ 90th percentile) in the ELFE cohort and generalized estimated equations were used in EPIPAGE 2 to account for non-independence of multiple births. As a negative control, paternal BMI was also considered as an exposure of interest in sensitivity analyses. Maternal pre-pregnancy obesity and overweight were associated with child HIS at 5 years in ELFE (adjusted OR [aOR] for obesity 1.27 [1.06, 1.53]; overweight aOR 1.16 [1.00, 1.36]) and pre-pregnancy obesity was associated with high HIS scores in preterm infants of EPIPAGE 2 (aOR 1.48 [1.06, 2.08]). In ELFE, the magnitude of the association increased with decreasing gestational age (interaction p = 0.02). High maternal pre-pregnancy BMI is associated with greater likelihood of high HIS scores in both at-term and preterm children at 5 years of age.