The Autism Spectrum Disorder Subtypes Identification Based on Features of Structural and Functional Coupling

Area of Science:

• Neuroscience
• Genetics
• Medical Imaging

Background:

• Autism spectrum disorder (ASD) presents significant clinical and biological heterogeneity.
• Identifying distinct ASD subtypes is crucial for understanding neurobiology and developing personalized treatments.
• Current approaches often overlook multi-modal imaging data interactions.

Purpose of the Study:

• To develop a novel approach combining structural and functional neuroimaging data for ASD subtype identification.
• To reveal quantitative biomarkers and elucidate the biological basis of ASD subgroups.
• To potentially improve ASD diagnosis and guide targeted interventions.

Main Methods:

• Utilized Diffusion Tensor Imaging (DTI) and functional Magnetic Resonance Imaging (fMRI) data from the ABIDE database.
• Integrated structural and functional MRI data using skeleton-based white matter (WM) functional analysis.
• Employed WM low-frequency oscillations (LFOs) for clustering individuals with ASD into distinct neurological subgroups.

Main Results:

• Identified two distinct ASD neurosubtypes based on WM functional connectivity and diffusion metrics.
• Subtype 1 showed reduced fractional anisotropy (FA) in the posterior cingulate cortex (PCC).
• Subtype 2 exhibited reduced FA and higher mean diffusivity (MD) in the anterior cingulate cortex, middle temporal gyrus, parahippocampus, and thalamus, with lower IQ scores.

Conclusions:

• The study successfully identified two distinct ASD neurosubtypes, highlighting the disorder's heterogeneity.
• Unique biomarkers associated with each subgroup offer potential neurological signatures for individuals with autism.
• This differentiation enhances understanding of ASD and supports personalized therapeutic strategies and early interventions.