Institute of Biomedical and Clinical Science, University of Exeter Medical School, Exeter, UK.
Pacific Northwest Research Institute, Seattle, WA, USA.
Curr Opin Genet Dev. 2018 Jun;50:96-102. doi: 10.1016/j.gde.2018.03.009. Epub 2018 Apr 24.
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.
1 型糖尿病(T1D)是一种由自身免疫破坏胰岛β细胞导致的慢性高血糖疾病,最终导致严重的胰岛素缺乏。T1D 具有显著的遗传风险。在 HLA Ⅱ类区域发现的遗传关联特别强,但 T1D 是一种多基因疾病,与基因组中 60 多个位点相关。多基因风险评分是将这些遗传风险因素作为单一连续变量进行汇总的一种方法。本综述讨论了遗传风险评分在 T1D 中的临床和研究应用,特别是在疾病预测和进展方面。我们还探讨了遗传风险评分在大数据中的创造性应用以及使用遗传风险评分的局限性。随着公共遗传数据的增加和基因分型成本的快速下降,T1D 遗传风险评分(T1D GRS)很可能在疾病预测、鉴别、异常队列研究以及在有遗传数据的大型数据集的生物学研究中证明有用。