Evidence map›Paper›PMID 40703685›Full record

ReviewEwha medical journal2024

Etiologies underlying sex bias in autism spectrum disorder: a narrative review of preclinical rodent models.

Taeyoung Lee, Eunha Kim

Abstract readReview
In one paragraph

Review in Ewha medical journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Taeyoung LeeBK21 Graduate Program, Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0009-0005-2317-3451
Eunha KimBK21 Graduate Program, Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-7041-1727

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurodevelopmental disorders, which emerge early in development, include a range of neurological phenotypes and exhibit marked differences in prevalence between sexes. A male predominance is particularly pronounced in autism spectrum disorder (ASD). Although the precise cause of ASD is still unknown, certain genetic variations and environmental influences have been implicated as risk factors. Preclinical ASD models have been instrumental in shedding light on the mechanisms behind the sexual dimorphism observed in this disorder. In this review, we explore the potential processes contributing to sex bias by examining both intrinsic differences in neuronal mechanisms and the influence of external factors. We organize these mechanisms into six categories: 1) sexually dimorphic phenotypes in mice with mutations in ASD-associated genes related to synaptic dysfunction; 2) sex-specific microglial activity, which may disrupt neural circuit development by excessively pruning synapses during critical periods; 3) sex steroid hormones, such as testosterone and allopregnanolone, that differentially influence brain structure and function; 4) escape from X chromosome inactivation of the O-linked-N-acetylglucosamine transferase gene in the placenta; 5) sexually dimorphic activation of the integrated stress response pathway following maternal immune activation; and 6) immunological responses that are differentially regulated by sex. Understanding these mechanisms is essential for deciphering the underlying causes of ASD and may offer insights into other disorders with notable sex disparities.

Indexed as

Autism spectrum disorderGenetic variationPregnancyRisk factorsSex characteristics

Identifiers

PMID40703685
PMCPMC12093583

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.