Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference

Donato Liloia; Franco Cauda; Lucina Q Uddin; Jordi Manuello; Lorenzo Mancuso; Roberto Keller; Andrea Nani; Tommaso Costa

doi:10.1016/j.bpsc.2022.01.007

Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference

Biol Psychiatry Cogn Neurosci Neuroimaging. 2023 Nov;8(11):1075-1083. doi: 10.1016/j.bpsc.2022.01.007. Epub 2022 Feb 5.

Authors

Donato Liloia¹, Franco Cauda², Lucina Q Uddin³, Jordi Manuello⁴, Lorenzo Mancuso¹, Roberto Keller⁵, Andrea Nani¹, Tommaso Costa²

Affiliations

¹ GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy.
² GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin, Turin, Italy.
³ Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California.
⁴ GCS-fMRI Research Group, Koelliker Hospital, and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems Laboratory, Department of Psychology, University of Turin, Turin, Italy. Electronic address: jordi.manuello@unito.it.
⁵ Adult Autism Center, DSM Local Health Unit, ASL TO, Turin, Italy.

PMID: 35131520
DOI: 10.1016/j.bpsc.2022.01.007

Abstract

Background: Although neuroimaging research has identified atypical neuroanatomical substrates in individuals with autism spectrum disorder (ASD), it is at present unclear whether and to what extent disorder-selective gray matter alterations occur in this spectrum of conditions. In fact, a growing body of evidence shows a substantial overlap between the pathomorphological changes across different brain diseases, which may complicate identification of reliable neural markers and differentiation of the anatomical substrates of distinct psychopathologies.

Methods: Using a novel data-driven and Bayesian methodology with published voxel-based morphometry data (849 peer-reviewed experiments and 22,304 clinical subjects), this study performs the first reverse inference investigation to explore the selective structural brain alteration profile of ASD.

Results: We found that specific brain areas exhibit a >90% probability of gray matter alteration selectivity for ASD: the bilateral precuneus (Brodmann area 7), right inferior occipital gyrus (Brodmann area 18), left cerebellar lobule IX and Crus II, right cerebellar lobule VIIIA, and right Crus I. Of note, many brain voxels that are selective for ASD include areas that are posterior components of the default mode network.

Conclusions: The identification of these spatial gray matter alteration patterns offers new insights into understanding the complex neurobiological underpinnings of ASD and opens attractive prospects for future neuroimaging-based interventions.

Keywords: Activation likelihood estimation; Bayes factor modeling; Cerebellum; Forward inference; Medial frontoparietal network; Structural MRI.

MeSH terms

Autism Spectrum Disorder* / diagnostic imaging
Autism Spectrum Disorder* / pathology
Bayes Theorem
Brain / pathology
Gray Matter / pathology
Humans
Magnetic Resonance Imaging / methods