近日，美国Lewis Sigler综合基因组学研究所Olga G. Troyanskaya及其团队揭示了自闭症表型异质性的分解揭示了潜在的遗传程序。相关论文于2025年7月9日发表于国际顶尖学术期刊《自然—遗传学》杂志上。

使用生成混合建模方法，研究团队利用来自具有匹配遗传学的大型队列的广泛表型数据来识别自闭症的临床相关类别及其核心，相关和共同发生的特征模式，研究团队进一步验证并在独立队列中重复。该课题组人员证明了表型和临床结果与常见、新生和遗传变异的遗传和分子程序相对应，并进一步表征了被每一类突变集破坏的不同途径。值得注意的是，该课题组发现受影响基因发育时间的类别特异性差异与临床结果差异一致。这些分析证明了自闭症儿童的表型复杂性，确定了其异质性的遗传程序，并提出了特定的生物学失调模式和机制假设。

据了解，揭示自闭症的表型和遗传复杂性是极具挑战性的，但对于理解这种疾病的多种形式的生物学、遗传、轨迹和临床表现至关重要。

附：英文原文

Title: Decomposition of phenotypic heterogeneity in autism reveals underlying genetic programs

Author: Litman, Aviya, Sauerwald, Natalie, Green Snyder, LeeAnne, Foss-Feig, Jennifer, Park, Christopher Y., Hao, Yun, Dinstein, Ilan, Theesfeld, Chandra L., Troyanskaya, Olga G.

Issue&Volume: 2025-07-09

Abstract: Unraveling the phenotypic and genetic complexity of autism is extremely challenging yet critical for understanding the biology, inheritance, trajectory and clinical manifestations of the many forms of the condition. Using a generative mixture modeling approach, we leverage broad phenotypic data from a large cohort with matched genetics to identify robust, clinically relevant classes of autism and their patterns of core, associated and co-occurring traits, which we further validate and replicate in an independent cohort. We demonstrate that phenotypic and clinical outcomes correspond to genetic and molecular programs of common, de novo and inherited variation and further characterize distinct pathways disrupted by the sets of mutations in each class. Remarkably, we discover that class-specific differences in the developmental timing of affected genes align with clinical outcome differences. These analyses demonstrate the phenotypic complexity of children with autism, identify genetic programs underlying their heterogeneity, and suggest specific biological dysregulation patterns and mechanistic hypotheses.

DOI: 10.1038/s41588-025-02224-z

Source: https://www.nature.com/articles/s41588-025-02224-z