Zhang Yuan, Ahsan Mian Umair, Wang Kai
Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
iScience. 2025 Aug 5;28(9):113258. doi: 10.1016/j.isci.2025.113258. eCollection 2025 Sep 19.
Previous genetic studies in Autism Spectrum Disorder (ASD) identified hundreds of high-confidence ASD genes enriched with likely deleterious protein-coding mutations (DNMs). Multiple studies also demonstrated that DNMs in the non-coding genome can contribute to ASD risk. However, the identification of individual risk genes enriched with noncoding DNMs has remained largely unexplored. We analyzed two datasets with over 5000 ASD families to assess the contribution of noncoding DNMs. We used two methods to assess statistical significance for noncoding DNMs: a point-based test that analyzes sites that are likely functional, and a segment-based test that analyzes 1 kb genomic segments with segment-specific background mutation rates. We found that coding and noncoding DNMs in are associated with ASD risk. Further application of these approaches on large-scale whole genome sequencing data will help identify additional candidate ASD risk genes.
先前针对自闭症谱系障碍(ASD)的基因研究确定了数百个高可信度的ASD基因,这些基因富含可能有害的蛋白质编码突变(DNM)。多项研究还表明,非编码基因组中的DNM可能会增加患ASD的风险。然而,富含非编码DNM的个体风险基因的鉴定在很大程度上仍未得到探索。我们分析了两个包含5000多个ASD家庭的数据集,以评估非编码DNM的作用。我们使用两种方法来评估非编码DNM的统计显著性:一种基于位点的测试,分析可能具有功能的位点;另一种基于片段的测试,分析具有片段特异性背景突变率的1kb基因组片段。我们发现,编码和非编码DNM都与ASD风险相关。将这些方法进一步应用于大规模全基因组测序数据,将有助于识别更多的ASD风险候选基因。