Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children.

Rebecca J Schmidt,Donghai Liang,Paul Curtin,Stefanie A Busgang,Cecilia Giulivi

doi:10.3390/metabo11080545

Abstract

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.

Highlights

Introduction iationsCurrently, approximately 1 in 54 children has been identified with Autism SpectrumDisorders (ASD) in the United States according to estimates from the CDC’s Autism and Developmental Monitoring (ADDM) Network [1]
The covariates identified for inclusion in final models were child’s sex, gestational age at delivery, and maternal body mass index (BMI) before pregnancy
The overarching challenge has been that despite measures of heritability pointing to a strong genetic component for autism spectrum disorders (ASD) as it is for most complex traits in human populations, the failure to find causative alleles for traits that often have a high heritability is part of the larger ‘missing heritability’ problem in humans, where the sum of all the genetic effects associated with highly heritable traits is typically far less than the heritability measured

Summary

Introduction

Introduction iationsCurrently, approximately 1 in 54 children has been identified with Autism SpectrumDisorders (ASD) in the United States according to estimates from the CDC’s Autism and Developmental Monitoring (ADDM) Network [1]. Often clinical diagnosis is not made in children before significant neurological symptoms are evident, there is an immediate need for early detection of processes that are altered and could be used as markers for risk and to potentially inform effective interventions to allow them to develop life to their fullest. To fulfill this immediate need, metabolic profiling performed on readily-accessible body fluids, such as serum, plasma, blood, urine or saliva, is one of the most important.

Methods

Results

Conclusion