Joint modeling of linkage and association: Identifying SNPs responsible for a linkage signal
Joint modeling of linkage and association: Identifying SNPs responsible for a linkage signal
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DOI：
10.1086/430277
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发表时间：
2005-06-01
影响因子：
9.8
通讯作者：
Abecasis, GR
中科院分区：
文献类型：
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作者：
Li, MY;Boehnke, M;Abecasis, GR
一旦确定了复杂疾病的遗传连锁，下一步通常是关联分析，其中连锁区域内的单核苷酸多态性（SNP）进行基因分型并测试与疾病的关联。如果SNP显示关联的证据，则了解候选SNP是否可以部分或全部解释连锁结果是有用的。我们提出了一种新的方法，量化的程度之间的连锁不平衡（LD）的候选SNP和推定的疾病位点，通过联合建模的连锁和关联。我们描述了一个简单的可能性的标记数据条件的性状数据为样本的受影响的同胞对，疾病的单倍型频率和疾病的单倍型频率作为参数。我们估计模型参数的最大似然法，并提出了两个似然比测试来表征候选SNP和疾病位点的关系。第一个测试评估候选SNP和疾病基因座是否处于连锁平衡，使得SNP在连锁信号中不起因果作用。第二个测试评估候选SNP和疾病基因座是否处于完全LD中，使得SNP或与其处于完全LD中的标记可以完全解释连锁信号。我们的方法还产生了一个遗传模型，其中包括疾病SNP单倍型频率和疾病SNP LD程度的参数估计。我们的方法提供了一个新的工具，用于检测连锁和关联，并可以扩展到研究设计，包括未受影响的家庭成员。
Once genetic linkage has been identified for a complex disease, the next step is often association analysis, in which single-nucleotide polymorphisms (SNPs) within the linkage region are genotyped and tested for association with the disease. If a SNP shows evidence of association, it is useful to know whether the linkage result can be explained, in part or in full, by the candidate SNP. We propose a novel approach that quantifies the degree of linkage disequilibrium (LD) between the candidate SNP and the putative disease locus through joint modeling of linkage and association. We describe a simple likelihood of the marker data conditional on the trait data for a sample of affected sib pairs, with disease penetrances and disease-SNP haplotype frequencies as parameters. We estimate model parameters by maximum likelihood and propose two likelihood-ratio tests to characterize the relationship of the candidate SNP and the disease locus. The first test assesses whether the candidate SNP and the disease locus are in linkage equilibrium so that the SNP plays no causal role in the linkage signal. The second test assesses whether the candidate SNP and the disease locus are in complete LD so that the SNP or a marker in complete LD with it may account fully for the linkage signal. Our method also yields a genetic model that includes parameter estimates for disease-SNP haplotype frequencies and the degree of disease-SNP LD. Our method provides a new tool for detecting linkage and association and can be extended to study designs that include unaffected family members.