Autism Polygenic Score Is Associated With Sex-Dependent Broadening of Brain Network Variability

Background: Autism polygenic scores (PGS) reliably predict case-control status yet explain little variance in autism-related traits. Landscape accounts of neurodevelopmental diversity propose that genetic liability broadens the range of viable neural configurations rather than shifting brain organisation toward dysfunction. We tested whether autism polygenic load is associated with increased variability in functional network organisation among non-autistic adults. Methods: We analysed resting-state functional connectivity from 910 non-autistic adults (aged 22-35) in the Human Connectome Project. Polygenic scores were derived from the iPSYCH autism GWAS at a pre-specified threshold (p = 0.1). Modularity (segregation) and global efficiency (integration) were computed at a pre-selected parcellation size and density (100-node, 20%), and residualised for age, intracranial volume, and head motion. Variance effects were assessed by variance regression including a PGS-by-sex interaction, decile-stratified dispersion trends, and PGS-balanced bootstrap resampling. Edge-wise analyses used false discovery rate correction. Results: Modularity variability broadened with polygenic load in a sex-dependent manner (sex-by-PGS beta = 1.92e-4, p = 0.031). Decile trends (male minus female difference = 0.82, p = 0.034) and balanced-bootstrap trends (difference = 1.19, p = 0.032) both differed by sex: variance increased across polygenic bins in males (r = 0.57, one-tailed p = 0.021) but not females. No comparable effect emerged for global efficiency (all p >= 0.54). Polygenic scores showed no association with social-cognitive difficulty (beta = 0.11, p = 0.209), mean network organisation, or connectivity after correction. Limitations: All participants were non-autistic adults and the analysis was cross-sectional. The identified effects are small and the sample size not sufficient to resolve very small effects often reported in genetics studies. Characterisation of genetic effects in women may be influenced by biases in the data used to calculate polygenic scores. Conclusions: Autism polygenic load broadened modular network configurations in males without shifting mean organisation or its behavioural correlates, offering partial support for landscape accounts.