HLA genetic association analysis using the sequence feature variant type approach (136.31)

Abstract

Abstract Immunogeneticists have found significant associations between specific HLA alleles and a variety of medical conditions, including autoimmune diseases. Current disease association studies treat each HLA allele as a single complete unit, which does not illuminate the parts of the molecule associated with disease. We have developed a novel approach for genetic association analysis in which HLA genes and proteins are broken down into smaller sequence features. Sequence features are defined based on structural or functional information, and can be overlapping and continuous or discontinuous in the linear sequence. The extent of sequence variation is then assessed for each HLA sequence feature to define all variant types found in the human population. This allows for the independent analysis of disease association with any sequence feature variant type (SFVT). We tested this approach in the analysis of systemic sclerosis patients using HLA-DRB1 and HLA-DQB1 typing data. We identified a region of the HLA-DRB1 protein centered around peptide-binding pocket 7 that appears to be associated with disease risk; aromatic amino acids found in HLA-DRB1*1104 at positions 26, 28, 37 and 67 were associated with increased risk. The SFVT approach is a novel method for identifying the molecular determinants of disease association in highly polymorphic genes like the HLA. For DAIT-DISC; supported by NIAID N01AI40076