PHENOTYPE DELINEATION AND GENETIC MODELING OF AUTISM

研究自闭症的遗传学面临着特殊的挑战(由于 到诸如有限的垂直传输和小家庭规模等特征)， 除了通常的困难之外，建模复杂和 异质性疾病。因此，表型的澄清 表达自闭症的遗传易感性是至关重要的第一步 一步。一种探索自闭症和自闭症表型界限的方法 识别自闭症先证者的亲属，患有广泛或 多维表型将使用来自巴尔的摩的数据进行开发 自闭症的家庭研究。然后该方法将被复制，在准- 验证步骤，使用来自另外两组自闭症家庭的数据 (一个单工和一个多工)在爱荷华州收集，使用 仪器和措施类似或相同于 巴尔的摩研究中心。将测试识别受影响人员的方法 因为它在提高遗传建模能力方面的有效性，包括 分离和连锁分析。 将对这两个数据集进行分离分析 如上所述。链接研究将在模拟的情况下进行 数据：将模拟家系的性状和标记基因类型 我们实际观察到的家系的表型特征。 然后，基于似然的和非参数的连锁分析都将 为确定各种模型下的统计能力而进行的 错误分类方案。更广泛地说，我希望这项工作将 有助于开发正确分类的方法 表现为其他复杂疾病的家庭中受影响的亲属 不明确的表型表达，以及寻找其他基因 神经精神障碍。

Investigating the genetics of autism presents particular challenges (due to features such as limited vertical transmission, and small family size), over and above the usual difficulties of modeling complex and heterogeneous disorders. Therefore, clarification of the phenotypic expression of the genetic liability underlying autism is a critical first step. A method for exploring the phenotypic boundaries of autism and identifying relatives of autistic probands affected with a broad or multidimensional phenotype will be developed using data from the Baltimore Family Study of Autism. The method will then be replicated, in a quasi- validation step, with data from two additional sets of autism families (one simplex and one multiplex) collected in Iowa with the use of instruments and measures similar or identical to those used in the Baltimore study. The method for identifying the affected will be tested for its utility in improving the power of genetic modeling, including segregation and linkage analyses. The segregation analyses will be carried out on the two data sets described above. The linkage studies will be carried out with simulated data; both trait and marker genotypes will be simulated for pedigrees with the phenotypic characteristics of the families we have actually observed. Then both likelihood-based and non-parametric linkage analysis will be carried out to determine statistical power under various models and misclassification schemes. More generally, I hope this work will contribute to the development of methods for correctly classifying affected relatives in families expressing other complex disorders with ambiguous phenotypic expression, and to the search for genes for other neuropsychiatric disorders.