Evidence map›Paper›PMID 35185642›Full record

ArticleFrontiers in psychiatry2021

Associations Among Maternal Metabolic Conditions, Cord Serum Leptin Levels, and Autistic Symptoms in Children.

Toshiki Iwabuchi, Nagahide Takahashi, Tomoko Nishimura, Md Shafiur Rahman, Taeko Harada, Akemi Okumura, Hitoshi Kuwabara, Shu Takagai, Yoko Nomura, Hideo Matsuzaki and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
0.7field-weighted citation impact, top 36% of its field
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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
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 at 5 institutions in 2 countries.

Toshiki IwabuchiResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Nagahide TakahashiResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Tomoko NishimuraResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Md Shafiur RahmanResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Taeko HaradaResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Akemi OkumuraResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Hitoshi KuwabaraUnited Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Shu TakagaiUnited Graduate School of Child Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Yoko NomuraQueens College and Graduate Center, City University of New York, New York City, NY, United States.
Hideo MatsuzakiResearch Center for Child Mental Development, University of Fukui, Fukui, Japan.
Norio OzakiDepartment of Child and Adolescent Psychiatry, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Kenji J TsuchiyaResearch Center for Child Mental Development, Hamamatsu University School of Medicine, Hamamatsu, Japan.
Hamamatsu University School of Medicine · JPNagoya University · JPSaitama Medical University · JPThe Graduate Center, CUNY · USUniversity of Fukui · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccumulating evidence has shown that maternal metabolic conditions, such as pre-pregnancy overweight, diabetes mellitus, and hypertensive disorders of pregnancy (HDP) are potential risk factors of autism spectrum disorder (ASD). However, it remains unclear how these maternal conditions lead to neurodevelopmental outcomes in the offspring, including autistic symptoms. Leptin, an adipokine that has pro-inflammatory effects and affects fetal neurodevelopment, is a candidate mediator of the association between maternal metabolic factors and an increased risk of ASD. However, whether prenatal exposure to leptin mediates the association between maternal metabolic conditions and autistic symptoms in children has not been investigated yet.

methodsThis study investigated the associations between mothers' metabolic conditions (pre-pregnancy overweight, diabetes mellitus during or before pregnancy, and HDP), leptin concentrations in umbilical cord serum, and autistic symptoms among 762 children from an ongoing cohort study, using generalized structural equation modeling. We used the Social Responsive Scale, Second Edition (SRS-2) at 8-9 years old to calculate total T-scores. Additionally, we used the T-scores for two subdomains: Social Communication and Interaction (SCI) and Restricted Interests and Repetitive Behavior (RRB).

resultsUmbilical cord leptin levels were associated with pre-pregnancy overweight [coefficient = 1.297, 95% confidence interval (CI) 1.081-1.556, DISCUSSION: The present study uncovered an association between cord leptin levels and autistic symptoms in children, while maternal metabolic conditions did not have an evident direct influence on the outcome. These results imply that prenatal pro-inflammatory environments affected by maternal metabolic conditions may contribute to the development of autistic symptoms in children. The findings warrant further investigation into the role of leptin in the development of autistic symptoms.

Indexed as

autism spectrum disorderdiabetes mellitushypertensive disorders of pregnancyleptinmaternal metabolic conditionsoverweight

Identifiers

PMID35185642
PMCPMC8851349
OpenAlexW4210818275

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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.