Background Recent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert maximum influence during different periods of development. This includes analyses of social communication difficulties that share, depending on their developmental stage, stronger genetic links with either autism spectrum disorder or schizophrenia. We developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social communication difficulties, during an approximately 10-year period spanning childhood and adolescence. Methods Longitudinally assessed quantitative social communication problems (N ≤ 5551) were studied in participants from a United Kingdom birth cohort (Avon Longitudinal Study of Parents and Children; age range, 8–17 years). Using standardized measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models incorporating whole-genome genotyping information. Analogous to twin research, genetic-relationship-matrix structural equation models included Cholesky decomposition, common pathway, and independent pathway models. Results A two-factor Cholesky decomposition model described the data best. One genetic factor was common to Social Communication Disorder Checklist measures across development; the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only approximately 50% of genetic variation at 17 years. Conclusions Using latent factor models, we identified developmental changes in the genetic architecture of social communication difficulties that enhance the understanding of autism spectrum disorder– and schizophrenia-related dimensions. More generally, genetic-relationship-matrix structural equation models present a framework for modeling shared genetic etiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.

中文翻译：

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社会交流行为的遗传结构内的发展变化：无关个体遗传变异的多变量研究

背景 最近对性状-障碍重叠的分析表明，精神病学维度可能与在不同发育时期发挥最大影响的不同基因组有关。这包括对社会沟通困难的分析，根据他们的发育阶段，这些困难与自闭症谱系障碍或精神分裂症有着更强的遗传联系。我们在无关个体中开发了一个多变量分析框架，以在跨越童年和青春期的大约 10 年期间直接模拟导致复杂特征（例如社会沟通困难）的遗传影响的发展概况。方法 在来自英国出生队列的参与者（雅芳父母和儿童纵向研究；年龄范围，8-17 岁）中研究纵向评估的定量社会沟通问题（N ≤ 5551）。使用标准化的测量方法，使用包含全基因组基因分型信息的新型多变量遗传关系矩阵结构方程模型研究遗传结构。类似于双胞胎研究，遗传关系矩阵结构方程模型包括 Cholesky 分解、共同路径和独立路径模型。结果 一个二因子 Cholesky 分解模型最好地描述了数据。一个遗传因素对于整个发展过程中的社交沟通障碍检查表测量是常见的；另一个解释了 11 年及以后的独立变化，与性状障碍重叠中的不同发育特征一致。重要的是，在 8 岁时起作用的遗传因素仅解释了 17 岁时大约 50% 的遗传变异。结论 使用潜在因素模型，我们确定了社会交流困难的遗传结构的发展变化，这些变化增强了对自闭症谱系障碍和精神分裂症相关维度的理解。更一般地说，遗传关系矩阵结构方程模型提供了一个框架，用于对表型之间的共享遗传病因进行建模，并且可以提供关于特征-障碍重叠的模式和连续性的先验信息。结论 使用潜在因素模型，我们确定了社会交流困难的遗传结构的发展变化，这些变化增强了对自闭症谱系障碍和精神分裂症相关维度的理解。更一般地说，遗传关系矩阵结构方程模型提供了一个框架，用于对表型之间的共享遗传病因进行建模，并且可以提供关于特征-障碍重叠的模式和连续性的先验信息。结论 使用潜在因素模型，我们确定了社会交流困难的遗传结构的发展变化，这些变化增强了对自闭症谱系障碍和精神分裂症相关维度的理解。更一般地说，遗传关系矩阵结构方程模型提供了一个框架，用于对表型之间的共享遗传病因进行建模，并且可以提供关于特征-障碍重叠的模式和连续性的先验信息。