Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, USA.
Department of Neurology, University of California San Francisco, San Francisco, USA.
Sci Adv. 2024 Jun 14;10(24):eadl5307. doi: 10.1126/sciadv.adl5307. Epub 2024 Jun 12.
Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism. However, isolating the gene-brain-behavior relationship from confounding sources of variability is a challenge. We demonstrate a novel technique, 3D transport-based morphometry (TBM), to extract the structural brain changes linked to genetic copy number variation (CNV) at the 16p11.2 region. We identified two distinct endophenotypes. In data from the Simons Variation in Individuals Project, detection of these endophenotypes enabled 89 to 95% test accuracy in predicting 16p11.2 CNV from brain images alone. Then, TBM enabled direct visualization of the endophenotypes driving accurate prediction, revealing dose-dependent brain changes among deletion and duplication carriers. These endophenotypes are sensitive to articulation disorders and explain a portion of the intelligence quotient variability. Genetic stratification combined with TBM could reveal new brain endophenotypes in many neurodevelopmental disorders, accelerating precision medicine, and understanding of human neurodiversity.
自闭症传统上是通过行为来诊断的，但它有很强的遗传基础。从遗传学角度入手的方法可以改变我们对自闭症的理解和治疗方式。然而，要将基因-大脑-行为的关系与混杂的变异性来源隔离开来，是一项挑战。我们展示了一种新颖的技术，即基于 3D 转运的形态计量学（TBM），以提取与 16p11.2 区域的拷贝数变异（CNV）相关的结构性大脑变化。我们确定了两种不同的表型。在来自 Simons 个体变异项目的数据中，仅通过大脑图像就可以检测到这些表型，从而实现了对 16p11.2 CNV 进行 89%至 95%测试准确性的预测。然后，TBM 使我们能够直接观察到驱动准确预测的表型，揭示了缺失和重复携带者之间剂量依赖性的大脑变化。这些表型对发音障碍敏感，解释了智商变异性的一部分。遗传分层与 TBM 相结合，可以揭示许多神经发育障碍中的新的大脑表型，从而加速精准医学和对人类神经多样性的理解。
