Improving prediction of type 1 diabetes by testing non-HLA genetic variants in addition to HLA markers

Abstract

Objective The purpose of this study was to explore whether non-HLA genetic markers can improve type 1 diabetes (T1D) prediction in a prospective cohort with high-risk HLA-DR,DQ genotypes. Methods The Diabetes Autoimmunity Study in the Young (DAISY) follows prospectively for development of T1D and islet autoimmunity (IA) children at increased genetic risk. A total of 1709 non-Hispanic White DAISY participants have been genotyped for 27 non-HLA single nucleotide polymorphisms and one microsatellite. Results In multivariate analyses adjusting for family history and HLA-DR3/4 genotype, PTPN22 (rs2476601) and two UBASH3A (rs11203203 and rs9976767) SNPs were associated with development of IA (HR=1.87, 1.55 and 1.54 respectively, all p≤0.003), while GLIS3 and IL2RA showed borderline association with development of IA. INS, UBASH3A and IFIH1 were significantly associated with progression from IA to diabetes (HR=1.65, 1.44 and 1.47 respectively, all p≤0.04), while PTPN22 and IL27 showed borderline association with progression from IA to diabetes. In survival analysis, 45% of general population DAISY children with PTPN22 rs2476601 TT or HLA-DR3/4 and UBASH3A rs11203203 AA developed diabetes by age 15, compared to 3% of children with all other genotypes (p<0.0001). Addition of non-HLA markers to HLA-DR3/4,DQ8 did not improve diabetes prediction in first-degree relatives. Conclusion Addition of PTPN22 and UBASH3A SNPs to HLA-DR,DQ genotyping can improve T1D risk prediction.

Non-HLA gene effects on the disease process of type 1 diabetes: From HLA susceptibility to overt disease

“…For the INS SNP rs689 this finding is in line with earlier observations in the DIPP follow-up cohort [21,22], in the observational cohort from Germany [20] and the international TEDDY cohort [17]. In DAISY cohort borderline significance was observed for autoantibody production [19] in the initial report and for the progression rate in the subsequent expanded series published [23]. The present analyses also confirmed the results of our recent study, which demonstrated that the INS gene polymorphism was associated with autoantibody appearance only in those subjects with IAA as the first autoantibody initiating the disease process leading to advanced autoimmunity [15].…”

“…The PTPN22 risk allele has multiple effects in immune cells and effects on different phases of the autoimmune process have been hypothesized [30]. In our cohort IFIH1 exerted its effect on the early phase of the development of b-cell autoimmunity which is in contrast to the finding from the cohorts from Germany and Colorado showing IFIH1 to be associated with enhanced progression rate after the appearance of autoantibodies but not with the appearance of autoantibodies [23,28]. In the recent multi-center TEDDY cohort no effect was observed on the appearance of b-cell autoimmunity [17].…”

“…The finding of an effect of the PTPN22 SNP on autoimmunity initiation is in line with three other reports [17,19,23] whereas no effect of a PTPN22 SNP in close linkage disequilibrium with the one used in the current analysis was observed on the type 1 diabetes pathogenesis in the German cohort [28]. The main difference, which might explain the discrepant findings between the studies is the number of subjects in the analysis.…”

A novel approach for the analysis of longitudinal profiles reveals delayed progression to type 1 diabetes in a subgroup of multiple-islet-autoantibody-positive children

“…It has long been recognised that diabetes risk is related to the number of positive autoantibody specificities [32,33]; more recently, it has been demonstrated that, within a variable time course, multiple-autoantibodypositive children will progress to clinical type 1 diabetes [11]. Progression can be stratified at various degrees by antibody characteristics such as target specificity [14,16,17,34], titre [13,15] or age at seroconversion [35], as well as by genetic [36][37][38][39] and metabolic markers [40][41][42][43]. However, individual sequences of complex autoantibody profiles over time have so far rarely been analysed in prospective studies of type 1 diabetes [21,[44][45][46][47].…”

Emerging roles of GLIS3 in neonatal diabetes, type 1 and type 2 diabetes

“…They found that the combination of GLIS3 rs7020673 and other eight SNPs significantly improved the prediction accuracy of T1D, compared to that provided by HLA alone (Winkler et al 2014). However, GLIS3 rs7020673 alone exhibited nominal association with the development of islet autoimmunity (IA) and failed to predict the progression from IA to T1D (Steck et al 2014).…”