Clinical and research uses of genetic risk scores in type 1 diabetes

Abstract

Type 1 diabetes (T1D) is a chronic disease of high blood glucose caused by autoimmune destruction of pancreatic beta cells eventually resulting in severe insulin deficiency. T1D has a significant heritable risk. Genetic associations found are particularly strong in the HLA class II region but T1D is a polygenic disease associated with over 60 loci across the genome. Polygenic risk scores are one method of summing these genetic risk elements as a single continuous variable. This review discusses the clinical and research utility of genetic risk scores in T1D particularly in disease prediction and progression. We also explore creative uses of genetic risk scores in big data and the limitations of using a genetic risk score. The increase in publically available genetic data and rapid fall in costs of genotyping mean that a T1D genetic risk score (T1D GRS) is likely to prove useful for disease prediction, discrimination, investigation of unusual cohorts, and investigation of biology in large datasets where genetic data are available.

Figure 1. Manhattan plot of variants associated with T1D [19]

Manhattan plot showing associations of genotyped and imputed variants across the autosome in T1DGC. As the logarithmic scale demonstrates the HLA signal is the most dominant association.

Figure 2. ROC-AUC Comparisons [46]

A series of ROC analyses demonstrating that the T1D GRS is an additive and independent predictor of insulin deficiency in young adults with diabetes when compared with known biomarker and clinical discriminators. AAD, age at diagnosis; ABS, autoantibody status for GAD and IA-2; ALL, T1D GRS, BMI, age at diagnosis, and autoantibodies as predictors.

Figure 3. Dot plots of T1D GRS stratified by disease [47]

Those without diabetes, with T2D, and those with maturity onset diabetes of the young (MODY) all have similar and significantly lower T1D GRS than people with T1D.