Polygenic Dissection of Synaptic Pruning and Glutamatergic Signaling: Contrasting Mechanisms in ASD and ADHD

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Authors: Ngo Cheung
Cited by: 0

Abstract

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) often travel together clinically, yet they present very different pictures in day-to-day life. To see where their biology overlaps and where it parts company, we re-examined the largest available genome-wide association studies for each condition. Three complementary tools—MAGMA for gene and gene-set tests, stratified LD-score regression for partitioned heritability, and S-PrediXcan for tissue-specific transcriptome-wide association—were trained on two candidate pathways: glutamatergic neurotransmission and synaptic pruning. The picture that emerged is one of partial overlap with notable biases. Genes that build and regulate glutamatergic synapses were strongly enriched in ASD (e.g., 1.45-fold heritability boost for the core set), but they left only faint traces in ADHD. Markers of synaptic pruning, in contrast, were enriched for both disorders; yet once glutamatergic genes were removed from the lists, the pruning signal stayed significant only for ADHD. Transcriptomic clues echoed that split: in ASD, predicted down-regulation of GABBR1 may worsen hyper-excitability and drive compensatory over-pruning, whereas in ADHD up-regulation of cytoskeletal and guidance genes hints at delayed synapse elimination. Taken together, the results suggest a spectrum. ASD risk seems to couple excess excitation with secondary over-pruning, leading to the under-connected social circuits seen on imaging. ADHD, by contrast, appears rooted in sluggish pruning, leaving networks in an immature, hyper-connected state. Pinpointing when and how pruning goes off-track could open a new window for intervention and illustrates the value of pathway-level dissection in comorbid neurodevelopmental disorders.

Fields of Study & Subjects

Attention Deficit Hyperactivity Disorder Autism Spectrum Disorder Research Functional Brain Connectivity Studies

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
6 January 2026
Document type
Preprint