a. Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
b. State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
c. Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu 211166, China;
d. The Second People's Hospital of Changzhou, the Third Affiliated Hospital of Nanjing Medical University, Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu 213003, China;
e. State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Innovation Center of Suzhou Nanjing Medical University, Suzhou, Jiangsu 215000, China;
f. Child Mental Health Research Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
Funds:
This work was supported by the National Natural Science of China (82322032 and 82221005), the Outstanding Youth Foundation of Jiangsu Province (BK20220050), the National Key Research & Development (R&D) Program of China (2024YFC2706800 and 2021YFC2700600), the Major Project of Changzhou Medical Center (CZKY1040101), the Major Project of Taizhou Clinical Medical College (TZKY20240003), the Major Program of Gusu School (GSKY20210102) and the China Postdoctoral Science Foundation (2024M760296).
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.
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