Search for Haplotype Interactions That Influence Susceptibility to Type 1 Diabetes, through Use of Unphased Genotype Data

Abstract

Type 1 diabetes is a T-cell-mediated chronic disease characterized by the autoimmune destruction of pancreatic insulin-producing beta cells and complete insulin deficiency. It is the result of a complex interrelation of genetic and environmental factors, most of which have yet to be identified. Simultaneous identification of these genetic factors, through use of unphased genotype data, has received increasing attention in the past few years. Several approaches have been described, such as the modified transmission/disequilibrium test procedure, the conditional extended transmission/disequilibrium test, and the stepwise logistic-regression procedure. These approaches are limited either by being restricted to family data or by ignoring so-called "haplotype interactions" between alleles. To overcome this limit, the present study provides a general method to identify, on the basis of unphased genotype data, the haplotype blocks that interact to define the risk for a complex disease. The principle underpinning the proposal is minimal entropy. The performance of our procedure is illustrated for both simulated and real data. In particular, for a set of Dutch type 1 diabetes data, our procedure suggests some novel evidence of the interactions between and within haplotype blocks that are across chromosomes 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 15, 16, 17, 19, and 21. The results demonstrate that, by considering interactions between potential disease haplotype blocks, we may succeed in identifying disease-predisposing genetic variants that might otherwise have remained undetected.

Haplotype Reconstruction for Diploid Populations

“…While the fi rst scenario has been well motivated in the literature [17,20] , the second one has attracted attention just recently [21] . The rationale of the second scenario may be outlined as follows: SNPs may, in practice, not reside on the same chromosome and therefore be physically unlinked.…”

“…The rationale of the second scenario may be outlined as follows: SNPs may, in practice, not reside on the same chromosome and therefore be physically unlinked. However, some of them may still interact with each other and in that, confer genetic risk to complex disease [21] . This implies that the two physically unlinked haplotypes may have the same parental identity if they are coupled with each other as the result of the potential interactions of disease genes in the gene network.…”

“…This implies that the two physically unlinked haplotypes may have the same parental identity if they are coupled with each other as the result of the potential interactions of disease genes in the gene network. It has been demonstrated by Zhang et al [21] that phasing two unphased genotype blocks together allows prediction of these interactions. Moreover, considering the potentially interacting SNPs as one block, that means in practice, combining all SNPs and phase them as a total, was shown to improve the accuracy of haplotype prediction.…”

Inflammatory Gene Haplotype-Interaction Networks Involved in Coronary Collateral Formation

“…As pointed out by Zhang et al [16] , the above logistic regression approach may be unable to detect the contributions of haplotype interactions to collateral formation. This is because the logistic regression approach allows only for testing genotype interactions; possibly miss the interactions reflected only at the haplotype level.…”

“…We first analyze the data with a stepwise logistic regression [15] . Then we conduct a search for locus-locus interactions through use of the haplotype entropy procedure [16] .…”