Structural Brain Imaging Correlates of ASD and ADHD Across the Lifespan: a Hypothesis-generating Review on Developmental ASD-ADHD Subtypes

Overview

Journal J Neural Transm (Vienna)

Specialties Neurology
Physiology

Date 2016 Dec 22

PMID 28000020

Citations 36

Authors

Nanda Rommelse

Jan K Buitelaar

Catharina A Hartman

Affiliations

Soon will be listed here.

Abstract

We hypothesize that it is plausible that biologically distinct developmental ASD-ADHD subtypes are present, each characterized by a distinct time of onset of symptoms, progression and combination of symptoms. The aim of the present narrative review was to explore if structural brain imaging studies may shed light on key brain areas that are linked to both ASD and ADHD symptoms and undergo significant changes during development. These findings may possibly pinpoint to brain mechanisms underlying differential developmental ASD-ADHD subtypes. To this end we brought together the literature on ASD and ADHD structural brain imaging symptoms and particularly highlight the adolescent years and beyond. Findings indicate that the vast majority of existing MRI studies has been cross-sectional and conducted in children, and sometimes did include adolescents as well, but without explicitly documenting on this age group. MRI studies documenting on age effects in adults with ASD and/or ADHD are rare, and if age is taken into account, only linear effects are examined. Data from various studies suggest that a crucial distinctive feature underlying different developmental ASD-ADHD subtypes may be the differential developmental thinning patterns of the anterior cingulate cortex and related connections towards other prefrontal regions. These regions are crucial for the development of cognitive/effortful control and socio-emotional functioning, with impairments in these features as key to both ASD and ADHD.

Citing Articles

Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance.

Sadat-Nejad Y, Vandewouw M, Cardy R, Lerch J, Taylor M, Iaboni A Front Child Adolesc Psychiatry. 2025; 2:1171337.

PMID: 39839588 PMC: 11747914. DOI: 10.3389/frcha.2023.1171337.

Interpretable and integrative deep learning for discovering brain-behaviour associations.

Ambroise C, Grigis A, Houenou J, Frouin V Sci Rep. 2025; 15(1):2312.

PMID: 39824899 PMC: 11742053. DOI: 10.1038/s41598-024-85032-5.

fMRI-Based Multi-class DMDC Model Efficiently Decodes the Overlaps between ASD and ADHD.

Zolghadr Z, Batouli S, Alavi Majd H, Shafaghi L, Mehrabi Y Basic Clin Neurosci. 2024; 15(3):367-382.

PMID: 39403359 PMC: 11470894. DOI: 10.32598/bcn.2023.4302.1.

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns.

Wang X, Zhao K, Yao L, Fonzo G, Satterthwaite T, Rekik I bioRxiv. 2024; .

PMID: 38496573 PMC: 10942316. DOI: 10.1101/2024.02.29.582790.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder.

You W, Li Q, Chen L, He N, Li Y, Long F BMC Med. 2024; 22(1):92.

PMID: 38433204 PMC: 10910790. DOI: 10.1186/s12916-024-03313-2.

References

Schumann C, Hamstra J, Goodlin-Jones B, Lotspeich L, Kwon H, Buonocore M . The amygdala is enlarged in children but not adolescents with autism; the hippocampus is enlarged at all ages. J Neurosci. 2004; 24(28):6392-401. PMC: 6729537. DOI: 10.1523/JNEUROSCI.1297-04.2004. View

Simons A, Eyskens F, Glazemakers I, Van West D . Can psychiatric childhood disorders be due to inborn errors of metabolism?. Eur Child Adolesc Psychiatry. 2016; 26(2):143-154. PMC: 5306168. DOI: 10.1007/s00787-016-0908-4. View

Vijayakumar N, Whittle S, Dennison M, Yucel M, Simmons J, Allen N . Development of temperamental effortful control mediates the relationship between maturation of the prefrontal cortex and psychopathology during adolescence: a 4-year longitudinal study. Dev Cogn Neurosci. 2014; 9:30-43. PMC: 6989743. DOI: 10.1016/j.dcn.2013.12.002. View

Lincoln S, Hooker C . Neural structure and social dysfunction in individuals at clinical high risk for psychosis. Psychiatry Res. 2014; 224(3):152-8. DOI: 10.1016/j.pscychresns.2014.08.008. View

Wallace G, Eisenberg I, Robustelli B, Dankner N, Kenworthy L, Giedd J . Longitudinal cortical development during adolescence and young adulthood in autism spectrum disorder: increased cortical thinning but comparable surface area changes. J Am Acad Child Adolesc Psychiatry. 2015; 54(6):464-9. PMC: 4540060. DOI: 10.1016/j.jaac.2015.03.007. View

Brieber S, Neufang S, Bruning N, Kamp-Becker I, Remschmidt H, Herpertz-Dahlmann B . Structural brain abnormalities in adolescents with autism spectrum disorder and patients with attention deficit/hyperactivity disorder. J Child Psychol Psychiatry. 2007; 48(12):1251-8. DOI: 10.1111/j.1469-7610.2007.01799.x. View

Mills K, Tamnes C . Methods and considerations for longitudinal structural brain imaging analysis across development. Dev Cogn Neurosci. 2014; 9:172-90. PMC: 6989768. DOI: 10.1016/j.dcn.2014.04.004. View

Arbabshirani M, Plis S, Sui J, Calhoun V . Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. Neuroimage. 2016; 145(Pt B):137-165. PMC: 5031516. DOI: 10.1016/j.neuroimage.2016.02.079. View

Lim L, Chantiluke K, Cubillo A, Smith A, Simmons A, Mehta M . Disorder-specific grey matter deficits in attention deficit hyperactivity disorder relative to autism spectrum disorder. Psychol Med. 2014; 45(5):965-76. PMC: 4413819. DOI: 10.1017/S0033291714001974. View

10.

Casey B, Jones R, Levita L, Libby V, Pattwell S, Ruberry E . The storm and stress of adolescence: insights from human imaging and mouse genetics. Dev Psychobiol. 2010; 52(3):225-35. PMC: 2850961. DOI: 10.1002/dev.20447. View

11.

Luby J, Belden A, Botteron K, Marrus N, Harms M, Babb C . The effects of poverty on childhood brain development: the mediating effect of caregiving and stressful life events. JAMA Pediatr. 2013; 167(12):1135-42. PMC: 4001721. DOI: 10.1001/jamapediatrics.2013.3139. View

12.

Khundrakpam B, Tohka J, Evans A . Prediction of brain maturity based on cortical thickness at different spatial resolutions. Neuroimage. 2015; 111:350-9. DOI: 10.1016/j.neuroimage.2015.02.046. View

13.

Marquand A, Wolfers T, Mennes M, Buitelaar J, Beckmann C . Beyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric Disorders. Biol Psychiatry Cogn Neurosci Neuroimaging. 2016; 1(5):433-447. PMC: 5013873. DOI: 10.1016/j.bpsc.2016.04.002. View

14.

Lenroot R, Gogtay N, Greenstein D, Wells E, Wallace G, Clasen L . Sexual dimorphism of brain developmental trajectories during childhood and adolescence. Neuroimage. 2007; 36(4):1065-73. PMC: 2040300. DOI: 10.1016/j.neuroimage.2007.03.053. View

15.

Ecker C, Bookheimer S, Murphy D . Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan. Lancet Neurol. 2015; 14(11):1121-34. DOI: 10.1016/S1474-4422(15)00050-2. View

16.

Fluegge K . Does environmental exposure to the greenhouse gas, NO, contribute to etiological factors in neurodevelopmental disorders? A mini-review of the evidence. Environ Toxicol Pharmacol. 2016; 47:6-18. DOI: 10.1016/j.etap.2016.08.013. View

17.

Francx W, Llera A, Mennes M, Zwiers M, Faraone S, Oosterlaan J . Integrated analysis of gray and white matter alterations in attention-deficit/hyperactivity disorder. Neuroimage Clin. 2016; 11:357-367. PMC: 4893015. DOI: 10.1016/j.nicl.2016.03.005. View

18.

McCarthy H, Skokauskas N, Frodl T . Identifying a consistent pattern of neural function in attention deficit hyperactivity disorder: a meta-analysis. Psychol Med. 2013; 44(4):869-80. DOI: 10.1017/S0033291713001037. View

19.

Sherman L, Rudie J, Pfeifer J, Masten C, McNealy K, Dapretto M . Development of the default mode and central executive networks across early adolescence: a longitudinal study. Dev Cogn Neurosci. 2014; 10:148-59. PMC: 4854607. DOI: 10.1016/j.dcn.2014.08.002. View

20.

Khundrakpam B, Reid A, Brauer J, Carbonell F, Lewis J, Ameis S . Developmental changes in organization of structural brain networks. Cereb Cortex. 2012; 23(9):2072-85. PMC: 3729193. DOI: 10.1093/cercor/bhs187. View