Maternal and cord blood molecular features associated with autism risk

summary: A new study associates certain molecules found in maternal blood and cord blood samples with an increased risk of a child being later diagnosed with autism. Several of the identified molecules are involved in inflammation, neurotoxicity, impaired neurotransmission, and disruption of membrane integrity.

sauce: Columbia University

In a new study, researchers uncover perturbations in levels of molecular compounds in maternal and cord blood that are associated with subsequent diagnosis of autism spectrum disorder (ASD). Identification of these compounds may shed light on the biological processes that cause ASD and open the door to early diagnosis and treatment.

The study was led by researchers from the Columbia University Mailman School of Public Health and the Norwegian Institute of Public Health.Findings will appear in the journal molecular psychiatry.

The researchers investigated plasma samples from 408 mothers during the second trimester (17–21 weeks) of pregnancy and 1,208 umbilical cord blood samples from 418 children at birth through the Norwegian Autism Birth Cohort (ABC). The levels of different compounds were analyzed. Compounds were analyzed to see if they are relevant to the clinical diagnosis of autism in 3-5 year olds. Researchers used a chromatography/mass spectrometry-based metabolomics assay to measure levels of the compound. They used machine learning to assess the compound’s predictive value as a biomarker for ASD.

The researchers tested 12 compounds from mid-gestation (MMG) samples from mothers of ASD girls, 3 compounds from MMG samples from boys with ASD, 8 compounds from cord blood (CB) samples from girls with ASD, and CB samples from boys with ASD. discovered 12 compounds from Autism includes inflammation, disruption of membrane integrity, and disorders of neurotransmission and neurotoxicity.

Machine learning analysis suggested the potential utility of the compound as a biomarker for early identification of children at risk for ASD, especially cord blood biomarkers.

This study identifies several differences in biomarker levels between boys and girls, including an imbalance in lipid chemical clusters in maternal blood that is associated with autism in girls but not boys. This finding may provide insight into the higher frequency of cognitive impairment in girls than in boys with ASD.

The study builds on research published in 2022 by the same group of scientists that found that ASD risk is associated with a grouping of inflammation-related molecules.

“Our latest findings add to the evidence that chemical compounds can be used as early biomarkers for autism spectrum disorders, and rapid developments in machine learning make such diagnostic tests feasible. “Biostatistics, Center for Infection and Immunity (CII), Columbia Mailman School of Public Health.

“The Autism Birth Cohort (ABC) is incorporated into a large population-based Norwegian Mother-Father-Child Cohort Study (MoBa) involving over 114,000 offspring and their parents. , were recruited in early pregnancy between 1999 and 2009.

ASD diagnoses in children are primarily obtained through collaboration with national registries. Together, the ABC, MoBa, and registry data represent a unique resource for current and future research on the causes of ASD,” said co-author Camilla, Director of the Norwegian Institute of Public Health. Stoltenberg, MD said. Founder of ABC Research.

About 1 in 44 children in the United States has an autism spectrum disorder. Intervention is most effective when implemented early. However, the average age of diagnosis she is 4-5 years old.

Therefore, in addition to providing insight into the etiology of these disorders, our findings may lead to tests for early diagnosis that improve outcomes,” said senior author W. Ian Lipkin, said John Snow, MD, Professor of Epidemiology and CII Director.

Other co-authors include Columbia Mailman’s Ayan Roy, Keming Zhang, Michaeline Bresnahan, and Ezra Susser. Siri Mjaaland, Ted Reichborn-Kjennerud, and Per Magnus, Norwegian Institute of Public Health, Oslo. Yimeng Shang, Pennsylvania State University; Oliver Fine, University of California, Davis;

Funding: This study was supported by the National Institutes of Health (grant NS047537, NS086122), the Jane Botsford Johnson Foundation, the Norwegian Ministry of Health and Medical Services, the Norwegian Ministry of Education and Research, and the Norwegian Research Council (grant 189457, 190694, and 196452). The authors declare no competing interests.

About the Autism Birth Cohort (ABC) Study

The Autism Birth Cohort (ABC) study was conducted within a large Norwegian cohort of over 100,000 children followed prenatally. ABC is a joint effort of investigators from the Norwegian National Institute of Public Health (NIPH) and the Columbia Mailman School and is overseen by a four-person steering committee. Colombian postman Ian Lipkin and Ezra Suther. The scope, depth and breadth of both biological and societal data on ASD are unique.

About this Autism Research News

author: Timothy Paul
sauce: Columbia University
contact: Timothy Paul – Columbia University
image: image is public domain

Original research: closed access.
“Metabolomics analysis of maternal midgestation plasma and cord blood in autism spectrum disorder” Xiaoyu (Jason) Che et al. molecular psychiatry

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overview

Metabolomics analysis of maternal midgestation plasma and cord blood in autism spectrum disorder

The discovery of prenatal and neonatal molecular biomarkers has the potential to provide insight into autism spectrum disorders (ASD) and facilitate early diagnosis.

Plasma samples collected from mothers at 17–21 weeks of gestation in a Norwegian autism birth cohort were used to characterize the metabolomic profile of ASD (maternal second trimester, MMG, n= 408) and from children of date of birth (cord blood, CB, n= 418). Associations were analyzed using gender-stratified adjusted logistic regression models with Bayesian analysis. A chemical enrichment analysis (ChemRICH) was performed to determine the altered chemical clusters.

We also employed machine learning algorithms to assess the utility of metabolomics as an ASD biomarker. ASD and various compounds such as arachidonic acid, glutamic acid, glutamine, and metabolite clusters such as hydroxyeicopentaenoic acid, phosphatidylcholine, and ceramide in MMG and CB plasma consistent with inflammation, disruption of membrane integrity, and impaired neurotransmission identified a relationship with and neurotoxicity.

Girls with ASD have an imbalance of ether/non-ether phospholipids in MMG plasma, similar to that seen in other neurodevelopmental disorders. ASD boys in the CB analysis had the highest number of dysregulated chemical clusters.

A machine-learning classifier distinguished ASD cases from controls in a region under receiver operating characteristic (AUROC) values ​​ranging from 0.710 to 0.853. Predictive performance was better for CB analysis than for MMG.

These findings may provide new insights into gender differences in ASD and may influence the discovery of biomarkers that may enable early detection and intervention.