Genome-wide Association Study of Different Types of Diabetes and Construction of Genetic Risk Score

Type 1 diabetes (T1D) is caused by autoimmune destruction of pancreatic beta cells, leading to severe insulin deficiency and requires life-long insulin therapy. Although traditionally viewed as a disease primarily affecting children and adolescents, recent epidemiological studies have demonstrated that over half of all new-onset T1D cases worldwide occur in adults. At present, methods to differentiate adult-onset T1D from T2D rely on the clinical phenotypes such as onset age and pattern, body mass index (BMI), C-peptide levels, and islet autoantibodies. However, the increasing rates of obesity in T1D, the presence of ketosis-prone T2D and idiopathic T1D, as well as unavailable autoantibody detection in some districts make it an increasing difficult challenge to accurately classify between adult-onset T1D and T2D. The discrimination of diabetes types is more challenging in the Chinese population due to the higher prevalence of early-onset T2D at a lower BMI than in European populations. Incorrectly identifying T1D as T2D can result in inadequate control of blood glucose levels, an elevated risk of ketoacidosis, and potentially severe and life-endangering complications. Therefore, it is crucial to search for new discriminative methods for different types of diabetes. The genetic pathogenesis of T1D and T2D differ significantly, allowing for the differentiation of diabetes types based on genetic information. A T1D genetic risk score (GRS), comprising 31 HLA and non-HLA T1D-associated single nucleotide polymorphisms (SNPs), can be a useful tool to aid the discrimination between T1D and T2D. GRS2, which improved SNP capture of HLA DR-DQ risk including haplotype interactions and added non-DR-DQ loci, showed better discriminative power for the classification of diabetes type among multiethnic youth. In this study, we employed GWAS to enhance the genetic profile of T1D patients in China. Additionally, our aim was to identify SNP tags for the HLA DR-DQ risk in the Chinese population, which could capture HLA DR-DQ risk and the interactions between these haplotypes. Using this information, we constructed a Chinese-specific GRS and evaluated its ability to differentiate between T1D and controls, as well as between T1D and T2D.