Development and Standardization of an Improved Type 1 Diabetes Genetic Risk Score for Use in Newborn Screening and Incident Diagnosis

Abstract

Objective: Previously generated genetic risk scores (GRSs) for type 1 diabetes (T1D) have not captured all known information at non-HLA loci or, particularly, at HLA risk loci. We aimed to more completely incorporate HLA alleles, their interactions, and recently discovered non-HLA loci into an improved T1D GRS (termed the "T1D GRS2") to better discriminate diabetes subtypes and to predict T1D in newborn screening studies.

Research design and methods: In 6,481 case and 9,247 control subjects from the Type 1 Diabetes Genetics Consortium, we analyzed variants associated with T1D both in the HLA region and across the genome. We modeled interactions between variants marking strongly associated HLA haplotypes and generated odds ratios to create the improved GRS, the T1D GRS2. We validated our findings in UK Biobank. We assessed the impact of the T1D GRS2 in newborn screening and diabetes classification and sought to provide a framework for comparison with previous scores.

Results: The T1D GRS2 used 67 single nucleotide polymorphisms (SNPs) and accounted for interactions between 18 HLA DR-DQ haplotype combinations. The T1D GRS2 was highly discriminative for all T1D (area under the curve [AUC] 0.92; P < 0.0001 vs. older scores) and even more discriminative for early-onset T1D (AUC 0.96). In simulated newborn screening, the T1D GRS2 was nearly twice as efficient as HLA genotyping alone and 50% better than current genetic scores in general population T1D prediction.

Conclusions: An improved T1D GRS, the T1D GRS2, is highly useful for classifying adult incident diabetes type and improving newborn screening. Given the cost-effectiveness of SNP genotyping, this approach has great clinical and research potential in T1D.

© 2019 by the American Diabetes Association.

Figures

Figure 1

Manhattan plots of GWAS before and after adjustment for GRSs. Top row, GWAS: unadjusted (A), after adjustment for GRS1 (B), and after adjustment for GRS2 (C). Bottom row, high-resolution plot of association scores for the full HLA region on chromosome 6q: unadjusted (D), after adjustment for GRS1 (E), and after adjustment for GRS2 (F). MB, megabases.

Figure 2

ROC curves comparing the ability of GRS1 and GRS2, and their components, to discriminate T1D. For each pair of curves in a panel, ROC AUCs are shown as well as the P value for their comparison by the DeLong algorithm. A: HLA DR-DQ haplotypes and interaction terms for GRS1 vs. GRS2 in the T1DGC. B: Both non–DR-DQ HLA and non-HLA loci for GRS1 vs. GRS2 in the T1DGC. C: Full GRS1 vs. full GRS2 in the T1DGC discovery data set. D: HLA DR-DQ haplotypes and interaction terms, for GRS1 vs. GRS2, in the UK Biobank (UKB). E: Both non–DR-DQ HLA and non-HLA loci, for GRS1 vs. GRS2, in UK Biobank. F: Full GRS1 vs. full GRS2 in UK Biobank.

Figure 3

A and B: Comparison of how well GRS1 (A) and GRS2 (B) discriminate those with T1D from control subjects. C and D: Comparison of how well GRS1 (C) and GRS2 (D) discriminate those with T1D from those with T2D. Note the similar distribution of T1D GRS2 scores in the background population and in those with T2D.