Evidence map›Paper›PMID 32565887›Full record

ArticleResearch in autism spectrum disorders2019

Thinning Faster? Age-Related Cortical Thickness Differences in Adults with Autism Spectrum Disorder.

B Blair Braden, Cory Riecken

Open access · greenAbstract read
In one paragraph

Article in Research in autism spectrum disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

  1. Cognitive and Cerebral Aging Research in Autism: A Systematic Review on an Emerging Topic.Autism research : official journal of the International Society for Autism Research · 2025
    Pooled it
  2. Article
  3. Autism and Cortical Thickness Deviation From Neurotypical Controls: Evidence for a Spatial Association With Serotonin Receptors.Autism research : official journal of the International Society for Autism Research · 2026
    Article
  4. Cortical Thickness and Curvature in Autism and ADHD: A Mega-Analysis.bioRxiv : the preprint server for biology · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. International journal of molecular sciences · 2023
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Electrophysiological signatures of brain aging in autism spectrum disorder.Cortex; a journal devoted to the study of the nervous system and behavior · 2022
    Article
  18. Review
  19. Article
  20. 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

2 authors at 1 institution in 1 country.

B Blair BradenDepartment of Speech and Hearing Science, Arizona State University, 976 S Forest Mall, Tempe, AZ 85281.
Cory RieckenDepartment of Speech and Hearing Science, Arizona State University, 976 S Forest Mall, Tempe, AZ 85281.
Arizona State University · US

Funding

Sex-Specific Brain and Behavioral Predictors of Cognitive Aging in Middle-Aged Adults with Autism Spectrum DisorderK01MH116098 · NIMH · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI BRADEN, BRITTANY BLAIR · 2018 to 2022
$760k
Translational Developmental Neuroscience of AutismK23MH087770 · NIMH · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DI MARTINO, ADRIANA · 2010 to 2013
$644k
Enhancement of the 1000 Functional Connectome ProjectR03MH096321 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI BISWAL, BHARAT BHUSAN, MILHAM, MICHAEL PETER · 2012 to 2013
$158k
NIMH NIH HHS K01 MH116098NIMH NIH HHS K23 MH087770NIMH NIH HHS R03 MH096321
6 · The paper itself

Abstract

backgroundOver the course of the last 30 years, autism spectrum disorder (ASD) diagnoses have increased, thus identifying a large group of aging individuals with ASD. Currently, little is known regarding how aging will affect these individual's neuroanatomy, compared to the neurotypical (NT) population. Because of the anatomical overlap of ASD-related cortical pathology and age-related cortical thinning, both following an anterior-to-posterior severity gradient, we hypothesize adults with ASD will show larger age-related cortical thinning than NT adults.

methodsWe analyzed cortical measurements using available data from the multi-site Autism Brain Imaging Data Exchange I (ABIDE I; n=282) and our own cohort of middle-age to older adults with and without ASD (n=47) mostly available in ABIDE II (n=35). We compared correlations between cortical measures and age in right-handed adults with ASD (n=157) and similar NT adults (n = 172), controlling for IQ and site. Participants were 18 to 64 years of age (mean=29.8 years; median=26 years).

resultsWe found significant differences between diagnosis groups in the relationship between age and cortical thickness for areas of left frontal lobe (pars opercularis), temporal lobe (inferior gyrus, middle gyrus, banks of the superior temporal sulcus, and entorhinal cortex), parietal lobe (inferior gyrus), and lateral occipital lobe. For all areas, adults with ASD showed a greater negative correlation between age and cortical thickness than NT adults.

conclusionAs hypothesized, adults with ASD demonstrated exacerbated age-related cortical thinning, compared to NT adults. These differences were the largest and most extensive in the left temporal lobe. Future longitudinal work is warranted to investigate whether differences in brain age trajectories will translate to unique behavioral needs in older adults with ASD.

Indexed as

AgingASDAutismBrainCortical ThicknessGray MatterMRITemporal Lobe

Identifiers

PMID32565887
PMCPMC7304569
OpenAlexW2940161306

What OpenQuestion holds

Textmetadata
LicenceTDM
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.