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

Author:

Sharp Seth A.1,Rich Stephen S.2ORCID,Wood Andrew R.1,Jones Samuel E.1,Beaumont Robin N.1,Harrison James W.1,Schneider Darius A.34,Locke Jonathan M.1ORCID,Tyrrell Jess1,Weedon Michael N.1,Hagopian William A.3,Oram Richard A.15ORCID

Affiliation:

1. Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, U.K.

2. Center for Public Health Genomics, University of Virginia, Charlottesville, VA

3. Pacific Northwest Diabetes Research Institute, Seattle, WA

4. Department of Medicine, University of Washington, Seattle, WA

5. Academic Renal Unit, Royal Devon and Exeter NHS Foundation Trust, Exeter, U.K.

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.

Funder

Diabetes UK

National Institute of Diabetes and Digestive and Kidney Diseases

Wellcome Trust

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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