The type 1 diabetes - HLA susceptibility interactome--identification of HLA genotype-specific disease genes for type 1 diabetes

Abstract

Background: The individual contribution of genes in the HLA region to the risk of developing type 1 diabetes (T1D) is confounded by the high linkage disequilibrium (LD) in this region. Using a novel approach we have combined genetic association data with information on functional protein-protein interactions to elucidate risk independent of LD and to place the genetic association into a functional context.

Methodology/principal findings: Genetic association data from 2300 single nucleotide polymorphisms (SNPs) in the HLA region was analysed in 2200 T1D family trios divided into six risk groups based on HLA-DRB1 genotypes. The best SNP signal in each gene was mapped to proteins in a human protein interaction network and their significance of clustering in functional network modules was evaluated. The significant network modules identified through this approach differed between the six HLA risk groups, which could be divided into two groups based on carrying the DRB1*0301 or the DRB1*0401 allele. Proteins identified in networks specific for DRB1*0301 carriers were involved in stress response and inflammation whereas in DRB1*0401 carriers the proteins were involved in antigen processing and presentation.

Conclusions/significance: In this study we were able to hypothesise functional differences between individuals with T1D carrying specific DRB1 alleles. The results point at candidate proteins involved in distinct cellular processes that could not only help the understanding of the pathogenesis of T1D, but also the distinction between individuals at different genetic risk for developing T1D.

Figure 1. Overview of the developed approach.

A) Genes located in the HLA region were identified and B) mapped to nodes or proteins in a 2^nd order network in the InWeb. C) HLA proteins and their interaction partners were used as bait to produce virtual pull-downs of network modules. D) Identified network modules were reduced to only contain proteins from the HLA region, as these could be associated to signals from the TDT analysis. E) SNPs from the TDT analysis were mapped to genes + 2000 bp up- and downstream the transcription start and stop site respectively. The best SNP signal for each gene was then mapped to the corresponding proteins in the network modules.

Figure 2. P-value distribution for HLA specific networks and the reference group.

A) DR3/DR3: most extreme deviation higher D = 0.2083, p<0.001. B) DR3/DRX: most extreme deviation higher D = 0.3347, p<0.001. C) DR3/DR4: most extreme deviation lower D = 0.2890, p<0.001. D) DR4/DR4: most extreme deviation lower D = 0.4772, p<0.001. E) DR4/DRX: most extreme deviation lower D = 0.1586, p<0.001. F) DRX/DRX: most extreme deviation lower D = 0.3199, p<0.001. Dashed line: HLA risk group, solid line: reference group.

Figure 3. Consensus networks.

A) displays the consensus network for the DR3/DR3 and the DR3/DRX risk groups. B) displays the consensus network for the DR3/DR4 and the DR4/DRX risk group. C) displays the consensus network for the DR4/DR4 risk group. Proteins encoded from genes in the HLA region are shown in red.