Variation in HLA‐associated risks of childhood insulin‐dependent diabetes in the finnish population: II. Haplotype effects

Abstract

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.

Class I and II HLA Genes Are Associated with Susceptibility and Age at Onset in Finnish Families with Type 1 Diabetes

“…The lack of statistical significance in the estimation of allele effects on susceptibility is most likely due to the small number of cases, because of ascertainment correction. In terms of direction of the association, our results are in close agreement to those obtained by Thomas et al [10]. In the joint allele main and haplotype effects model, DR2 was negatively associated with T1DM susceptibility, and DR3 and DR4 were positively associated, although not statistically significantly.…”

“…In the joint allele main and haplotype effects model, DR2 was negatively associated with T1DM susceptibility, and DR3 and DR4 were positively associated, although not statistically significantly. We note that, after ascertainment correction, data became too sparse for joint modeling of multilocus effects (locus interactions) on susceptibility and age at onset as suggested by Thomas et al [10] and Cordell et al [28]. Based on the haplotype effects only model (haplotype analysis), age at onset of DR4 carriers is modified by the alleles at A or B locus, and this is consistent with the finding of Valdes et al [12] with T1DM sibpairs.…”

“…We found significantly increased susceptibility associated with B62 and suggetive associations with A1 and DR4 in the Finnish data, and this is consistent with findings in the analysis of disease risk [10]. The lack of statistical significance in the estimation of allele effects on susceptibility is most likely due to the small number of cases, because of ascertainment correction.…”

“…In a previous study [9], we could not find any evidence of non-Mendelian transmission of HLA candidate genes in the Finnish population explaining even partially the observed increase in incidence of type 1 diabetes in Finland. A systematic evaluation of the joint risk of HLA A, B and DR loci and their haplotypes by Thomas et al [10] supported DR locus as a major contributor, and found some evidence of three-locus haplotype effects in the risk of T1DM. It has been proposed that genes at HLA class I region are related to the age-at-onset of T1DM [11][12], especially with HLA A locus alleles, but systematic statistical and genetic-epidemiological evaluation of the HLA class I and II associations of the age at onset in T1DM is lacking.…”

A Measure of Phase Ambiguity in Pairs of SNPs in the Presence ofLinkage Disequi librium

“…We also note that researchers have successfully employed the EM algorithm [5][6][7][8][9][10] and the empirical Bayes methods using Gibbs sampling [11][12][13][14] to estimate haplotype frequencies and/or to test the significance of the linkage disequilibrium. Since our paper focuses on the measurement of ambiguity once LD is known or estimated, we do not pursue these approaches further.…”