Evidence map›Paper›PMID 31867092›Full record

ArticleMolecular autism2019

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder.

Birkan Tunç, Lisa D Yankowitz, Drew Parker, Jacob A Alappatt, Juhi Pandey, Robert T Schultz, Ragini Verma

Abstract read
In one paragraph

Article in Molecular autism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
–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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Digital tools for direct assessment of autism risk during early childhood: A systematic review.Autism : the international journal of research and practice · 2024
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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

7 authors.

Birkan Tunç1Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104 USA.ORCID 0000-0002-2294-4024
Lisa D Yankowitz1Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104 USA.
Drew Parker6DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 USA.
Jacob A Alappatt6DiCIPHR (Diffusion and Connectomics in Precision Healthcare Research) Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104 USA.
Juhi Pandey1Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104 USA.
Robert T Schultz *1Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104 USA.
Ragini Verma *4Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104 USA.

Funding

The Intellectual and Developmental Disabilities Research Center at CHOP/PennU54HD086984 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI YUDKOFF, MARC · 2016 to 2020
$6.3M
Harmonization for multisite Connectomics: parsing heterogeneity and creating markers in ASDR01MH117807 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI VERMA, RAGINI · 2019 to 2023
$3.6M
Temporal connectomics for infant brain: neurodevelopment modulated by pathologyR01HD089390 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI VERMA, RAGINI · 2017 to 2020
$2.3M
The fusiform and amygalda in the pathobiology of autismR01MH073084 · NIMH · YALE UNIVERSITY · PI SCHULTZ, ROBERT THOMAS · 2005 to 2009
$1.6M
NICHD NIH HHS R01 HD089390NICHD NIH HHS U54 HD086984NIMH NIH HHS R01 MH073084NIMH NIH HHS R01 MH117807
6 · The paper itself

Abstract

Background: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity. Methods: The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD ( Results: Machine learning model trained on all five metrics accurately predicted age in the TDC ( Limitations: This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable. Conclusions: Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Indexed as

Severity of Illness IndexAdolescentAdultAnisotropyAutism Spectrum DisorderBrainDiffusionFemaleHumansMaleMultivariate AnalysisSex CharacteristicsYoung AdultAutismBrain developmentHeterogeneityMachine learningNormative modelingSymptom severity

Identifiers

PMID31867092
PMCPMC6907209

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.