INHERITANCE OF LIABILITY TO CERTAIN DISEASES ESTIMATED FROM INCIDENCE AMONG RELATIVES
INHERITANCE OF LIABILITY TO CERTAIN DISEASES ESTIMATED FROM INCIDENCE AMONG RELATIVES
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DOI：
10.1111/j.1469-1809.1965.tb00500.x
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发表时间：
1965-01-01
影响因子：
1.9
通讯作者：
FALCONER, DS
中科院分区：
文献类型：
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作者：
FALCONER, DS
不是由单一基因以简单方式遗传的疾病可能具有一定程度的遗传基础，这表明受影响个人亲属的发病率高于一般人群。提出了一种从已知事件推导出亲缘关系的方法。该方法基于一种潜在变量（长虚线）的假设，该变量被称为“责任”（长虚线），它表达了先天倾向和外部环境的结合，这些因素使个体或多或少有可能患上所讨论的疾病。个人是否受到影响，取决于他的责任是否超过或低于固定的阈值。亲属之间责任的相关性导致了责任的herttabty的估计，它估计了遗传因素作为个体之间责任差异的原因的相对重要性。从已发表的数据中分析了四个例子，并获得了以下对遗传力（[正负]标准误差）的估计：肾结石疾病，46[正负]9%；先天性幽门狭窄，79[正负]5%；内翻足，70[正负]8%；消化性溃疡，37[正负]6%。该方法可用于预测无法通过直接观测得知的事件。这些预测可能对遗传咨询和数据收集计划有用。
Diseases that are not inherited in a simple manner by a single gene may have some degree of hereditary basis, which shows in a higher incidence among relatives of affected individuals than among the general population. A method is presented by which the correlation between relatives can be derived from the known incidences. The method is based on the assumption of an underlying variable[long dash]called the liability[long dash]which expresses the combination of innate tendencies and external circumstances that make the individual more or less likely to develop the disease in question. Whether an individual is affected or not depends on whether his liability exceeds or falls short of a fixed threshold. The correlation of liability between relatives leads to an estimate of the herltablllty of liability, which estimates the relative importance of herediatary factors as causes of differences of liability between individuals. Four examples from published data are analysed and the following estimates of the heritability ([plus or minus] standard error) obtained: renal stone disease, 46 [plus or minus] 9%; congenital pyloric stenosis, 79 [plus or minus] 5%; club-foot, 70 [plus or minus] 8%; peptic ulcer, 37 [plus or minus] 6%. The method can be used to predict incidences not known by direct observation. The predictions could be useful in genetic counselling and in planning the collection of data.