存在选择和测量误差时复杂表型复发风险的潜在类别分析：一项关于自闭症的双生子和家族史研究
Latent-class analysis of recurrence risks for complex phenotypes with selection and measurement error: a twin and family history study of autism.
作者信息
Pickles A, Bolton P, Macdonald H, Bailey A, Le Couteur A, Sim C H, Rutter M
机构信息
MRC Child Psychiatry Unit, Institute of Psychiatry, London, United Kingdom.
出版信息
Am J Hum Genet. 1995 Sep;57(3):717-26.
Abstract
The use of the family history method to examine the pattern of recurrence risks for complex disorders such as autism is not straightforward. Problems such as uncertain phenotypic definition, unreliable measurement with increased error rates for more distant relatives, and selection due to reduced fertility all complicate the estimation of risk ratios. Using data from a recent family history study of autism, and a similar study of twins, this paper shows how a latent-class approach can be used to tackle these problems. New findings are presented supporting a multiple-locus model of inheritance, with three loci giving the best fit.
摘要
运用家族病史法来研究诸如自闭症等复杂疾病的复发风险模式并非易事。诸如表型定义不明确、对较远亲属测量不可靠且错误率增加以及因生育力下降导致的选择等问题，都使风险比率的估计变得复杂。本文利用近期一项自闭症家族病史研究以及一项类似的双胞胎研究的数据，展示了如何运用潜在类别方法来解决这些问题。文中呈现的新发现支持了一种多位点遗传模型，其中三个位点拟合效果最佳。
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