Evidence map›Paper›PMID 39282332›Full record

ArticlebioRxiv : the preprint server for biology2024

Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD Suggest Age Mediates Subtypes of ASD.

Haylee J Ressa, Benjamin T Newman, Zachary Jacokes, James C McPartland, Natalia M Kleinhans, T Jason Druzgal, Kevin A Pelphrey, John Darrell Van Horn

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Haylee J RessaDepartment of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903.
Benjamin T NewmanDepartment of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903.ORCID 0000-0002-0668-2853
Zachary JacokesSchool of Data Science, University of Virginia, Elson Building, Charlottesville, VA 22903.
James C McPartlandYale Child Study Center and the Yale Center for Brain and Mind Health, Yale School of Medicine, Sterling Hall of Medicine, New Haven, CT 06520.
Natalia M KleinhansUniversity of Washington Integrated Brain Imaging Center, Eunice Kennedy Shriver Intellectual and Developmental Disabilities Research Center, Seattle, WA 98195.
T Jason DruzgalDepartment of Neurology, University of Virginia, School of Medicine, Gilmer Hall, Charlottesville, VA 2290.
Kevin A PelphreyDepartment of Neurology, University of Virginia, School of Medicine, Gilmer Hall, Charlottesville, VA 2290.
John Darrell Van HornDepartment of Psychology, University of Virginia, Gilmer Hall, Charlottesville, VA 22903.ORCID 0000-0003-1537-0816

Funding

Multimodal Developmental Neurogenetics of Females with ASDR01MH100028 · NIMH · YALE UNIVERSITY · PI Allison Elizabeth Jack, LAUREN KENWORTHY · 2012 to 2026
$37.8M
NIMH NIH HHS R01 MH100028
6 · The paper itself

Abstract

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, this study aims to first associate a broad array of behavioral metrics with neuroimaging markers of ASD, and to explore the prevalence of ASD subtypes using a neuroimaging driven perspective. Analyzing 273 participants (148 with ASD) ages 8 to 17 through an NIH-sponsored Autism Centers of Excellence network (MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics, alongside different directional correlations between different behavioral metrics. Stronger associations with individual subcategories from each test rather than summary scores suggest that different neuronal profiles may be masked by composite test scores. Machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. This suggests that if ASD can be definitively subtyped, these subtypes may show different behavioral trajectories across the developmental period. Clustering identified a pattern of restrictive and repetitive behavior in some participants and a second group that was defined by high sensory sensitivity and language performance.

Identifiers

PMID39282332
PMCPMC11398530

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.