Structure of Subcortico-cortical Tracts in Middle-aged and Older Adults with Autism Spectrum Disorder

Overview

Journal Cereb Cortex

Publisher Oxford University Press

Specialty Neurology

Date 2024 Dec 21

PMID 39707985

Authors

Michaela Cordova

Janice Hau

Adam Schadler

Molly Wilkinson

Kalekirstos Alemu

Ian Shryock

Ashley Baker

Chantal Chaaban

Emma Churchill

Inna Fishman

Ralph-Axel Muller

Ruth A Carper

Affiliations

Soon will be listed here.

Abstract

Middle-aged and older adults with autism spectrum disorder may be susceptible to accelerated neurobiological changes in striato- and thalamo-cortical tracts due to combined effects of typical aging and existing disparities present from early neurodevelopment. Using magnetic resonance imaging, we employed diffusion-weighted imaging and automated tract-segmentation to explore striato- and thalamo-cortical tract microstructure and volume differences between autistic (n = 29) and typical comparison (n = 33) adults (40 to 70 years old). Fractional anisotropy, mean diffusivity, and tract volumes were measured for 14 striato-cortical and 12 thalamo-cortical tract bundles. Data were examined using linear regressions for group by age effects and group plus age effects, and false discovery rate correction was applied. Following false discovery rate correction, volumes of thalamocortical tracts to premotor, pericentral, and parietal regions were significantly reduced in autism spectrum disorder compared to thalamo-cortical groups, but no group by age interactions were found. Uncorrected results suggested additional main effects of group and age might be present for both tract volume and mean diffusivity across multiple subcortico-cortical tracts. Results indicate parallel rather than accelerated changes during adulthood in striato-cortical and thalamo-cortical tract volume and microstructure in those with autism spectrum disorder relative to thalamo-cortical peers though thalamo-cortical tract volume effects are the most reliable.

References

Happe F, Charlton R . Aging in autism spectrum disorders: a mini-review. Gerontology. 2011; 58(1):70-8. DOI: 10.1159/000329720. View

Langen M, Leemans A, Johnston P, Ecker C, Daly E, Murphy C . Fronto-striatal circuitry and inhibitory control in autism: findings from diffusion tensor imaging tractography. Cortex. 2011; 48(2):183-93. DOI: 10.1016/j.cortex.2011.05.018. View

Shukla D, Keehn B, Muller R . Tract-specific analyses of diffusion tensor imaging show widespread white matter compromise in autism spectrum disorder. J Child Psychol Psychiatry. 2010; 52(3):286-95. PMC: 4547854. DOI: 10.1111/j.1469-7610.2010.02342.x. View

Courchesne E, Carper R, Akshoomoff N . Evidence of brain overgrowth in the first year of life in autism. JAMA. 2003; 290(3):337-44. DOI: 10.1001/jama.290.3.337. View

Walsh M, Ofori E, Pagni B, Chen K, Sullivan G, Braden B . Preliminary findings of accelerated visual memory decline and baseline brain correlates in middle-age and older adults with autism: The case for hippocampal free-water. Front Aging Neurosci. 2022; 14:1029166. PMC: 9694823. DOI: 10.3389/fnagi.2022.1029166. View

Andersson J, Skare S, Ashburner J . How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage. 2003; 20(2):870-88. DOI: 10.1016/S1053-8119(03)00336-7. View

Sexton C, Walhovd K, Storsve A, Tamnes C, Westlye L, Johansen-Berg H . Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study. J Neurosci. 2014; 34(46):15425-36. PMC: 4228140. DOI: 10.1523/JNEUROSCI.0203-14.2014. View

Murata Y, Colonnese M . Thalamic inhibitory circuits and network activity development. Brain Res. 2018; 1706:13-23. PMC: 6363901. DOI: 10.1016/j.brainres.2018.10.024. View

Shaw K, McArthur D, Hughes M, Bakian A, Lee L, Pettygrove S . Progress and Disparities in Early Identification of Autism Spectrum Disorder: Autism and Developmental Disabilities Monitoring Network, 2002-2016. J Am Acad Child Adolesc Psychiatry. 2021; 61(7):905-914. PMC: 9353949. DOI: 10.1016/j.jaac.2021.11.019. View

10.

Koolschijn P, Geurts H . Gray Matter Characteristics in Mid and Old Aged Adults with ASD. J Autism Dev Disord. 2016; 46(8):2666-2678. PMC: 4938851. DOI: 10.1007/s10803-016-2810-9. View

11.

Zhu Y, Jiang X, Ji W . The Mechanism of Cortico-Striato-Thalamo-Cortical Neurocircuitry in Response Inhibition and Emotional Responding in Attention Deficit Hyperactivity Disorder with Comorbid Disruptive Behavior Disorder. Neurosci Bull. 2018; 34(3):566-572. PMC: 5960450. DOI: 10.1007/s12264-018-0214-x. View

12.

Johnson W, Li C, Rabinovic A . Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2006; 8(1):118-27. DOI: 10.1093/biostatistics/kxj037. View

13.

Wasserthal J, Neher P, Maier-Hein K . TractSeg - Fast and accurate white matter tract segmentation. Neuroimage. 2018; 183:239-253. DOI: 10.1016/j.neuroimage.2018.07.070. View

14.

Tang W, Zhu Q, Gong X, Zhu C, Wang Y, Chen S . Cortico-striato-thalamo-cortical circuit abnormalities in obsessive-compulsive disorder: A voxel-based morphometric and fMRI study of the whole brain. Behav Brain Res. 2016; 313:17-22. DOI: 10.1016/j.bbr.2016.07.004. View

15.

Boyle P, Cohen R, Paul R, Moser D, Gordon N . Cognitive and motor impairments predict functional declines in patients with vascular dementia. Int J Geriatr Psychiatry. 2002; 17(2):164-9. DOI: 10.1002/gps.539. View

16.

van de Vijver I, Ridderinkhof K, Harsay H, Reneman L, Cavanagh J, Buitenweg J . Frontostriatal anatomical connections predict age- and difficulty-related differences in reinforcement learning. Neurobiol Aging. 2016; 46:1-12. DOI: 10.1016/j.neurobiolaging.2016.06.002. View

17.

Hine J, Allin J, Allman A, Black M, Browning B, Ramsey B . Increasing Access to Autism Spectrum Disorder Diagnostic Consultation in Rural and Underserved Communities: Streamlined Evaluation Within Primary Care. J Dev Behav Pediatr. 2019; 41(1):16-22. PMC: 6933088. DOI: 10.1097/DBP.0000000000000727. View

18.

Aoki Y, Abe O, Nippashi Y, Yamasue H . Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies. Mol Autism. 2013; 4(1):25. PMC: 3726469. DOI: 10.1186/2040-2392-4-25. View

19.

Rosen T, Mazefsky C, Vasa R, Lerner M . Co-occurring psychiatric conditions in autism spectrum disorder. Int Rev Psychiatry. 2018; 30(1):40-61. DOI: 10.1080/09540261.2018.1450229. View

20.

Andrews D, Lee J, Harvey D, Waizbard-Bartov E, Solomon M, Rogers S . A Longitudinal Study of White Matter Development in Relation to Changes in Autism Severity Across Early Childhood. Biol Psychiatry. 2020; 89(5):424-432. PMC: 7867569. DOI: 10.1016/j.biopsych.2020.10.013. View