医学
标准化
糖尿病
2型糖尿病
1型糖尿病
风险评估
内科学
儿科
内分泌学
政治学
计算机安全
计算机科学
法学
作者
Seth A. Sharp,Stephen S. Rich,Andrew R. Wood,Samuel E. Jones,Robin N. Beaumont,Jamie Harrison,Darius Schneider,Jonathan M. Locke,Jessica Tyrrell,Michael N. Weedon,William Hagopian,Richard A. Oram
出处
期刊:Diabetes Care
[American Diabetes Association]
日期:2019-01-11
卷期号:42 (2): 200-207
被引量:373
摘要
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: < 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.
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