Subcortical volumes in middle-aged and older adults with and without autism spectrum disorder
Poster No:
378
Submission Type:
Abstract Submission
Authors:
Michaela Cordova1, Stephanie Pedrahita2, Annika Linke3, Gioia Toro4, Molly Wilkinson1, Jiwandeep Kohli5, Janice Hau3, Inna Fishman6, Ralph-Axel Mueller4, Ruth Carper4
Institutions:
1SDSU/UC San Deigo, San Diego, CA, 2San Diego State University, San diego, CA, 3San Diego State University, San Diego, CA, 4San Diego Research Foundation, San Diego, CA, 5University of California, San Diego, San Diego, CA, 6SDSU, San Diego, CA
First Author:
Co-Author(s):
Introduction:
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition with known behavioral and neurobiological correlates. In youth, those with ASD show significant differences in subcortical volumes (caudate, putamen, nucleus accumbens, and thalamus) compared to their neurotypical (NT) peers. Such volume differences have been linked to ASD-related behaviors in children and younger adults, including atypical response to reward and social challenges. In the NT population, these volumes decrease after age 40, with associated declines in memory, attention, and processing speed. Together these findings suggest that middle-aged and older autistic adults may experience an interplay between long-standing reduced subcortical volume (at least since childhood) combined with normal age-related changes after 40+ years. This may place them at risk for accelerated volume changes, with important implications for overall function. In this study, we hypothesized steeper age-associated subcortical volume decline among middle-aged and older adults with ASD, in comparison to NT peers.
Methods:
Data were collected on 40–70-year-old adults with ASD and NT participants enrolled in an ongoing longitudinal study on aging in autism. ASD diagnoses were confirmed by an expert clinician using DSM-5 criteria. NT participants had no family or personal history of ASD or serious mental illness. Magnetic resonance imaging (MRI) data (T1-weighted anatomical images: TR=8.78ms, TE=3.66ms, resolution=0.8mm3) were collected on a 3T GE Discovery MR750 scanner. The Human Connectome Project (HCP) pipeline version 5.3.0 was used for preprocessing and results were visually inspected for quality assurance. An automated subcortical segmentation approach (SynthSeg, Freesurfer 7.3.1) was then used to parcellate subcortical regions. Briefly, SynthSeg employs a convolutional neural network previously trained on randomized synthetic data, to segment regions of interest (ROIs) and estimate corresponding volumes. Bilateral thalamus, caudate, putamen, nucleus accumbens and pallidum were selected for analyses. Accuracy of SynthSeg parcellations was reviewed using a 4-point scale (4=excellent, 1=unusable). Only ROIs rated 3 or 4 were included in analyses, with unusable data excluded on a per-subject, per-ROI basis. Groups were matched on age, sex, non-verbal IQ, ethnicity, and contrast-to-noise ratio. General linear models were applied to test for age-by-diagnosis interaction effects, as well as main effects of diagnostic group or age on each ROI volume, while controlling for the effects of total intracranial volume (TIV).
Results:
Following SynthSeg QA, the following data were considered usable: caudate N=69, putamen N=68 (ASD=28, NT=40), nucleus accumbens N=69, thalamus N=53 (ASD=24, NT=29). The pallidum was excluded entirely due to low N (ASD=2, NT=4). There were no significant age-by-diagnosis interaction effects across all models. The ASD sample showed significantly lower volumes of the left putamen and left nucleus accumbens compared to their NT peers (Figure 1). There were significant age effects such that greater age was associated with lower subcortical volumes in the bilateral caudate and putamen (Figure 2).
Conclusions:
Subcortical nuclei play a role in many of the symptoms of ASD, and they are known to decrease in size during typical aging. Negative age effects found here are consistent with the previous literature. While our findings of lower subcortical volumes in the ASD than the NT group were also partially consistent with past reports, our hypothesis of accelerated volume decline was not supported. However, analysis of longitudinal measures (now being collected) and larger sample sizes will be more definitive. Neurobiological change during aging in ASD remains severely understudied but the current report, along with an increasing body of literature, has begun to make inroads.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 1
Lifespan Development:
Aging 2
Modeling and Analysis Methods:
Segmentation and Parcellation
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Subcortical Structures
Keywords:
Aging
Autism
Basal Ganglia
STRUCTURAL MRI
Thalamus
1|2Indicates the priority used for review
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