Massively parallel characterization of non-coding de novo mutations in autism spectrum disorder.

Scientists studied genetic changes outside of protein-coding regions in autism. They examined nearly 228,000 genetic variations and found 238 that affect how genes are controlled. Only certain types of these changes - those that reduce gene activity in important genes - were linked to increased autism risk. The research identified 42 potentially important genetic changes in 41 genes, including 29 genes not previously connected to autism.

This study analyzed 227,878 non-coding de novo mutations from major autism cohorts using advanced computational and experimental methods. Researchers identified 238 mutations with confirmed functional effects on gene regulation, comprising 137 down-regulatory and 101 up-regulatory mutations. Critically, only down-regulatory mutations affecting loss-of-function intolerant genes showed significant association with ASD risk (odds ratio 4.34). The study identified 42 potential ASD-risk mutations across 41 candidate genes, including 29 previously unreported genes.

These findings expand understanding of how non-coding genetic variants contribute to autism by disrupting gene regulation, particularly in genes that are highly sensitive to functional disruption.

Findings suggest genetic testing for autism should consider non-coding regulatory regions, particularly those affecting gene expression in loss-of-function intolerant genes. May inform development of more comprehensive genetic screening approaches and identification of new therapeutic targets.

Sample sizes not reported for individual analyses. Functional validation limited to reporter assays. Clinical significance of identified mutations requires validation in independent cohorts. Long-term clinical outcomes not assessed.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder where de novo mutations play a significant role. Although coding mutations in ASD have been extensively characterized, the impact of non-coding de novo mutations (ncDNMs) remains less understood. Here, we integrate cortex cell-specific cis-regulatory element annotations, a deep learning-based variant prediction model, and massively parallel reporter assays to systematically evaluate the functional impact of 227,878 ncDNMs from Simons Simplex Collection (SSC) and Autism Speaks MSSNG resource (MSSNG) cohorts. Our analysis identifies 238 ncDNMs with confirmed functional regulatory effects, including 137 down-regulated regulatory mutations (DrMuts) and 101 up-regulated regulatory mutations (UrMuts).

Subsequent association analyses reveal that only DrMuts regulating loss-of-function (LoF) intolerant genes rather than other ncDNMs are significantly associated with the risk of ASD (Odds ratio = 4.34; P = 0.001). A total of 42 potential ASD-risk DrMuts across 41 candidate ASD-susceptibility genes are identified, including 12 recognized and 29 unreported genes. Interestingly, these noncoding disruptive mutations tend to be observed in genes extremely intolerant to LoF mutations. Our study introduces an optimized approach for elucidating the functional roles of ncDNMs, thereby expanding the spectrum of pathogenic variants and deepening our understanding of the complex molecular mechanisms underlying ASD.