Thomas D, Pitkäniemi J, Langholz B, Tuomilehto-Wolf E, Tuomilehto J
Department of Preventive Medicine, University of Southern California, Los Angeles 90033-9987, USA.
Genet Epidemiol. 1995;12(5):455-66. doi: 10.1002/gepi.1370120503.
We fitted models for the main effects of alleles at the HLA-A, B, and DR loci and their haplotypes on the risk of insulin-dependent diabetes mellitus (IDDM). Empirical Bayes methods were used, assuming independent exchangeable normal priors for effects at each locus separately and for haplotype effects. A pure main effects model, pure haplotype effects model, and a combined model were fitted using Gibbs sampling. The main effects model showed that the DR locus had the largest variation in risk between alleles, followed by the B locus; significance tests for each allele in this model were in general agreement with those in the companion paper [Langholz et al. (1995) Genet Epidemiol 12:441-453], although all relative risks were shrunk toward 1.0 in the empirical Bayes analysis. The variance estimate for pure haplotype effects was substantially larger than for any of the three main effects considered in this analysis, but in the combined model, the DR locus showed larger variability than the haplotype deviations. We confirmed that haplotype A2/B56/DR4 previously reported to be common in Finnish diabetics does indeed confer unusually high risk (relative risk = 7.6, P < 0.001), but found this to be only 1.9 times higher than predicted by its component main effects (P = 0.046). All of the other haplotypes could be adequately explained by their main effects. Empirical Bayes methods provide a natural means of dealing with the problems of multiple comparisons, multicolinearity, and sparse data that complicate the analysis of HLA data.
我们针对人类白细胞抗原A、B和DR位点的等位基因及其单倍型对胰岛素依赖型糖尿病(IDDM)风险的主要影响进行了模型拟合。采用经验贝叶斯方法,分别对每个位点的效应以及单倍型效应假设独立可交换的正态先验。使用吉布斯抽样拟合了纯主效应模型、纯单倍型效应模型和组合模型。主效应模型显示,DR位点等位基因间的风险差异最大,其次是B位点;该模型中每个等位基因的显著性检验总体上与配套论文[Langholz等人(1995年),《遗传流行病学》12:441 - 453]中的检验结果一致,尽管在经验贝叶斯分析中所有相对风险都向1.0收缩。纯单倍型效应的方差估计值显著大于本分析中考虑的三个主效应中的任何一个,但在组合模型中,DR位点显示出比单倍型偏差更大的变异性。我们证实,先前报道在芬兰糖尿病患者中常见的单倍型A2/B56/DR4确实赋予了异常高的风险(相对风险 = 7.6,P < 0.001),但发现这仅比其组成主效应预测值高1.9倍(P = 0.046)。所有其他单倍型都可以由其主效应充分解释。经验贝叶斯方法为处理多重比较、多重共线性和稀疏数据等使HLA数据分析复杂化的问题提供了一种自然的手段。