Next steps in the identification of gene targets for type 1 diabetes

被引:15
作者
Grant, Struan F. A. [1 ,2 ,3 ,4 ,5 ]
Wells, Andrew D. [1 ,6 ]
Rich, Stephen S. [7 ,8 ]
机构
[1] Childrens Hosp Philadelphia, Ctr Spatial & Funct Genom, Philadelphia, PA 19104 USA
[2] Univ Penn, Dept Pediat, Perelman Sch Med, Philadelphia, PA 19104 USA
[3] Univ Penn, Dept Genet, Perelman Sch Med, Philadelphia, PA 19104 USA
[4] Childrens Hosp Philadelphia, Div Human Genet, Philadelphia, PA 19104 USA
[5] Childrens Hosp Philadelphia, Div Endocrinol, Philadelphia, PA 19104 USA
[6] Univ Penn, Dept Pathol & Lab Med, Perelman Sch Med, Philadelphia, PA 19104 USA
[7] Univ Virginia, Sch Med, Ctr Publ Hlth Genom, Charlottesville, VA 22908 USA
[8] Univ Virginia, Sch Med, Dept Publ Hlth Sci, Charlottesville, VA 22908 USA
关键词
Chromatin; Enhancers; eQTLs; Genetics; Prediction; Review; Target genes; Type; 1; Diabetes; GENOME-WIDE ASSOCIATION; HIGH-RESOLUTION; VARIANTS; RISK; CHROMATIN; LOCI; EXPRESSION; LANDSCAPE; CELLS;
D O I
10.1007/s00125-020-05248-8
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (similar to 50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment.
引用
收藏
页码:2260 / 2269
页数:10
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