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<p>Autism spectrum disorder (ASD) presents a wide range of cognitive and language impairments. In this study, we investigated the genetic basis of non-verbal status in ASD using a comprehensive genomic approach. We identified a novel common variant, rs1944180 in <i>CNTN5</i>, significantly associated with non-verbal status through family-based Transmission Disequilibrium Testing. Polygenic risk score (PRS) analysis further showed that higher ASD PRS was significantly linked to non-verbal status (<i>p</i> = 0.034), specific to ASD and not related to other conditions such as bipolar disorder, schizophrenia and three language-related traits. Using structural equation modeling (SEM), we found two causal SNPs, rs1247761 located in <i>KCNMA1</i> and rs2524290 in <i>RAB3IL1</i>, linking ASD with language traits. The model indicated a unidirectional effect, with ASD driving language impairments. Additionally, <i>de novo</i> mutations (DNMs) were found to be related with ASD and interaction between common variants and DNMs significantly impacted non-verbal status (<i>p</i> = 0.038). Our findings also identified 5 high-risk ASD genes, and DNMs were enriched in glycosylation-related pathways. These results offer new insights into the genetic mechanisms underlying language deficits in ASD.</p>

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Unraveling genetic risk contributions to nonverbal status in autism spectrum disorder probands

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月7日

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  • Huan Liu,
  • Shenghan Wang,
  • Binbin Cao,
  • Jijun Zhu,
  • Zhifang Huang,
  • Pan Li,
  • Shunjie Zhang,
  • Xian Liu,
  • Jing Yu,
  • Zhongting Huang,
  • Linzhuo Lv,
  • Fuqiang Cai,
  • Weixin Liu,
  • Zhijian Song,
  • Yuxin Liu,
  • Tao Pang,
  • Suhua Chang,
  • Ying Chen,
  • Junfang Chen,
  • Wen-Xiong Chen

摘要

Autism spectrum disorder (ASD) presents a wide range of cognitive and language impairments. In this study, we investigated the genetic basis of non-verbal status in ASD using a comprehensive genomic approach. We identified a novel common variant, rs1944180 in CNTN5, significantly associated with non-verbal status through family-based Transmission Disequilibrium Testing. Polygenic risk score (PRS) analysis further showed that higher ASD PRS was significantly linked to non-verbal status (p = 0.034), specific to ASD and not related to other conditions such as bipolar disorder, schizophrenia and three language-related traits. Using structural equation modeling (SEM), we found two causal SNPs, rs1247761 located in KCNMA1 and rs2524290 in RAB3IL1, linking ASD with language traits. The model indicated a unidirectional effect, with ASD driving language impairments. Additionally, de novo mutations (DNMs) were found to be related with ASD and interaction between common variants and DNMs significantly impacted non-verbal status (p = 0.038). Our findings also identified 5 high-risk ASD genes, and DNMs were enriched in glycosylation-related pathways. These results offer new insights into the genetic mechanisms underlying language deficits in ASD.