Borecki I B, Lathrop G M, Bonney G E, Yaouanq J, Rao D C
Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110.
Am J Hum Genet. 1990 Sep;47(3):542-50.
Characterizing the distribution of parameters of iron metabolism by hemochromatosis genotype remains an important goal vis-à-vis potential screening strategies to identify individuals at genetic risk, since a specific marker to detect the abnormal gene has not been identified as yet. In the present investigation, we analyze serum iron values in ascertained families using a method which incorporates both segregation of the clinical affection status and the HLA linkage information to identify the underlying genotypes. The analysis is performed using an extension of the model presented by Bonney et al., comprising regressive models for segregation analysis and the multipoint linkage strategy implemented in LINKAGE. The gene was found to be completely recessive with respect to both clinical manifestations and serum iron abnormalities, with significant differences in expression by sex. Clinical manifestations were present for all male homozygotes in this data set, suggesting that the recessive hemochromatosis genotype is fully penetrant at all ages in males. This was not the case for younger females. Significant genotype-specific age and sex effects were found for serum iron values. It is interesting that deletion of the HLA marker information did not affect our ability to resolve the genetic model when we analyzed a bivariate phenotype. This serves as a reminder that a search for relevant biological markers can be equally important in discerning the genetic etiology of a disease trait, as a search for linked genetic markers.
鉴于尚未确定检测异常基因的特定标志物，通过血色素沉着症基因型来表征铁代谢参数的分布，对于识别具有遗传风险的个体的潜在筛查策略而言，仍然是一个重要目标。在本研究中，我们使用一种结合了临床患病状态的分离情况和HLA连锁信息的方法，来分析确诊家族中的血清铁值，以确定潜在的基因型。分析是使用Bonney等人提出的模型的扩展来进行的，该模型包括用于分离分析的回归模型以及在LINKAGE中实施的多点连锁策略。发现该基因在临床表现和血清铁异常方面均为完全隐性，且在表达上存在显著的性别差异。在该数据集中，所有男性纯合子均出现了临床表现，这表明隐性血色素沉着症基因型在男性所有年龄段均具有完全的外显率。年轻女性则并非如此。血清铁值存在显著的基因型特异性年龄和性别效应。有趣的是，当我们分析双变量表型时，删除HLA标志物信息并未影响我们解析遗传模型的能力。这提醒我们，寻找相关生物标志物在识别疾病性状的遗传病因方面，可能与寻找连锁遗传标志物同样重要。
