Evidence map›Paper›PMID 31086561›Full record

ArticleResearch in autism spectrum disorders2018

Maternal metabolic profile predicts high or low risk of an autism pregnancy outcome.

Kathryn Hollowood, Stepan Melnyk, Oleksandra Pavliv, Teresa Evans, Ashley Sides, Rebecca J Schmidt, Irva Hertz-Picciotto, William Elms, Elizabeth Guerrero, Uwe Kruger and 2 more

Abstract read
In one paragraph

Article in Research in autism spectrum disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
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  5. Article
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  8. Maternal risk factors vary between subpopulations of children with autism spectrum disorder.Autism research : official journal of the International Society for Autism Research · 2022
    Article
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  11. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Kathryn HollowoodDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8 St, Troy, NY, 12180, USA.
Stepan MelnykDepartment of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children's Research Institute, 4301 W Markham St, Little Rock, AR, 72205, USA.
Oleksandra PavlivDepartment of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children's Research Institute, 4301 W Markham St, Little Rock, AR, 72205, USA.
Teresa EvansDepartment of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children's Research Institute, 4301 W Markham St, Little Rock, AR, 72205, USA.
Ashley SidesTranslational Research Institute, University of Arkansas for Medical Sciences, 1301 W Markham St, Little Rock, AR, 72205, USA.
Rebecca J SchmidtDepartment of Public Health Sciences and the MIND Institute, University of California Davis School of Medicine, 1 Shields Ave, Davis, CA, 95616, USA.
Irva Hertz-PicciottoDepartment of Public Health Sciences and the MIND Institute, University of California Davis School of Medicine, 1 Shields Ave, Davis, CA, 95616, USA.
William ElmsDepartment of Public Health Sciences and the MIND Institute, University of California Davis School of Medicine, 1 Shields Ave, Davis, CA, 95616, USA.
Elizabeth GuerreroDepartment of Public Health Sciences and the MIND Institute, University of California Davis School of Medicine, 1 Shields Ave, Davis, CA, 95616, USA.
Uwe KrugerDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8 St, Troy, NY, 12180, USA.
Juergen HahnDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 8 St, Troy, NY, 12180, USA.
S Jill JamesDepartment of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children's Research Institute, 4301 W Markham St, Little Rock, AR, 72205, USA.

Funding

UC Davis Environmental Health Sciences Core CenterP30ES023513 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Nicholas J. KENYON · 2015 to 2026
$26.0M
Autism Risk, Prenatal Environmental Exposures, and Pathophysiologic MarkersR01ES020392 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HERTZ-PICCIOTTO, IRVA, OZONOFF, SALLY · 2011 to 2015
$9.0M
Environmental Influence on Infant Microbiome Development and ASD SymptomsR01ES028089 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI HERTZ-PICCIOTTO, IRVA, MILLS, DAVID ANDREW · 2016 to 2020
$3.6M
Folic Acid Prevention Pathways for ASD in High Risk FamiliesR01ES025574 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI SCHMIDT, REBECCA JEAN · 2015 to 2019
$3.1M
Modular and Project Based Training to Enhance Rigor and Reproducibility in Research for Diverse Biomedical CareersT32GM067545 · NIGMS · RENSSELAER POLYTECHNIC INSTITUTE · PI VASHISHTH, DEEPAK · 2004 to 2020
$3.0M
BUILDS MARBLES: Biorepository Upkeep and Infrastructure for Longitudinal Data Sharing for MARBLESR24ES028533 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI Brittany D. Chambers Butcher, Rebecca Jean Schmidt · 2017 to 2026
$2.3M
Modeling and Analysis of the Role of Microbiota Metabolites in T-Cell DifferentiationR01AI110642 · NIAID · TEXAS ENGINEERING EXPERIMENT STATION · PI ALANIZ, ROBERT CHRISTOPHER, HAHN, JUERGEN · 2015 to 2019
$2.0M
Metabolic Biomarkers of Autism: Predictive Potential and Genetic SusceptibilityR01HD051873 · NICHD · ARKANSAS CHILDREN'S HOSPITAL RES INST · PI JAMES, SANDRA JILL · 2006 to 2010
$1.8M
NIAID NIH HHS R01 AI110642NICHD NIH HHS R01 HD051873NIEHS NIH HHS P30 ES023513NIEHS NIH HHS R01 ES020392NIEHS NIH HHS R01 ES025574NIEHS NIH HHS R01 ES028089NIEHS NIH HHS R24 ES028533NIGMS NIH HHS T32 GM067545
6 · The paper itself

Abstract

backgroundCurrently there is no test for pregnant mothers that can predict the probability of having a child that will be diagnosed with autism spectrum disorder (ASD). Recent estimates indicate that if a mother has previously had a child with ASD, the risk of having a second child with ASD is ~18.7% (High Risk) whereas the risk of ASD in the general population is ~1.7% (Low Risk).

methodsIn this study, metabolites of the folate-dependent transmethylation and transsulfuration biochemical pathways of pregnant mothers were measured to determine whether or not the risk of having a child with autism could be predicted by her metabolic profile. Pregnant mothers who have had a child with autism before were separated into two groups based on the diagnosis of their child whether the child had autism (ASD) or not (TD). Then these mothers were compared to a group of control mothers who have not had a child with autism before. A total of 107 mothers were in the High Risk category and 25 mothers in the Low Risk category. The High Risk category was further separated into 29 mothers in the ASD group and 78 mothers in the TD group.

resultsThe metabolic results indicated that among High Risk mothers, it was not possible to predict an autism pregnancy outcome. However, the metabolic profile was able to predict with approximately 90% sensitivity and specificity whether a mother fell into the High Risk group (18.7% risk) or Low Risk group (1.7% risk).

conclusionsBased upon these measurements it is not possible to determine during a pregnancy if a child will be diagnosed with ASD by age 3. However, differences in the folate-dependent transmethylation and transsulfuration metabolites are indicative of the risk level (High Risk of 18.7% vs. Low Risk of 1.7%) of the mother for having a child with ASD.

Indexed as

AutismFisher Discriminant Analysisfolatemetabolic profilepregnancytransmethylationtranssulfuration

Identifiers

PMID31086561
PMCPMC6510509

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.