HLA class I genes modulate disease risk and age at onset together with DR-DQ in Chinese patients with insulin-requiring type 1 diabetes.

ABSTRACT

AIMS/HYPOTHESIS: The study aimed to investigate the effects of HLA class I genes on susceptibility to type 1 diabetes with different onset ages, in addition to the well-established effects of HLA class II genes. METHODS: A total of 361 patients with type 1 diabetes (192 patients with onset <18 years and 169 patients with onset ≥18 years) and 500 healthy control participants from China were enrolled and genotyped for the HLA-A, -B, -C, -DQA1, -DQB1 and -DRB1 genes using next-generation sequencing. RESULTS: The susceptible DR3 (ß = -0.09, p = 0.0009) and DR4-DQ8 (ß = -0.13, p = 0.0059) haplotypes were negatively associated with onset age, while the protective DR11 (ß = 0.21, p = 0.0314) and DR12 (ß = 0.27, p < 0.0001) haplotypes were positively associated with onset age. After adjustment for linkage disequilibrium with DR-DQ haplotypes, A*110101 was positively associated with onset age (ß = 0.06, p = 0.0370), while the susceptible C*150201 was negatively associated with onset age (ß = -0.21, p = 0.0050). The unit for ß was double square-root (fourth root) transformed years of change in onset age associated with per copy of the HLA haplotype/allele. In addition, B*460101 was protective (OR 0.41, 0.46; pc [corrected for multiple comparisons] = 0.0044, 0.0040), whereas A*240201 (OR 2.71, 2.25; pc = 0.0003, 0.0002) and B*540101 (OR 3.96, 3.79; pc = 0.0018, 0.0004) were predisposing in both the <18 group and the ≥18 group compared with healthy control participants. In the context of DR4-DQ4, A*110101 (61.29% vs 28.26%, pc = 0.0144) was increased while the predisposing A*240201 (19.35% vs 47.83%, pc = 0.0403) was decreased in patients with onset ≥18 years when compared with patients with onset <18 years. CONCLUSIONS/INTERPRETATION: In addition to DR-DQ haplotypes, novel HLA class I alleles were detected to play a role in susceptibility to type 1 diabetes with different onset ages, which could improve the understanding of disease heterogeneity and has implications for the design of future studies.