1型糖尿病遗传风险评分可区分中国人群中的1型糖尿病和2型糖尿病。
A type 1 diabetes genetic risk score discriminates between type 1 diabetes and type 2 diabetes in a Chinese population.
作者信息
Hu Jingyi, Jiang Guozhi, Qin Jiabi, Luo Shuoming, Fan Baoqi, Xie Zhiguo, Wan Raymond, Li Xia, Tam Claudia H T, Wang Zhenqian, Ding Jin, Xia Ying, Yang Yuanqin, Lin Jian, Yu Gechang, Jin Ping, Lim Cadmon K P, Luk Andrea O Y, So Wing Yee, Chan Juliana C N, Wang Congyi, Huang Jiaqi, Weedon Michael N, Hagopian William A, Oram Richard A, Ma Ronald C W, Xiao Yang, Zhou Zhiguang
机构信息
National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, and Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China.
出版信息
Diabetologia. 2025 Jun 26. doi: 10.1007/s00125-025-06455-x.
AIMS/HYPOTHESIS: We aimed to generate a population-specific type 1 diabetes genetic risk score (GRS) and assess whether it could improve discrimination between type 1 diabetes and type 2 diabetes in a Chinese population.
METHODS
We performed a genome-wide association analysis on 1303 individuals with type 1 diabetes and 2236 control individuals. An independent replication cohort of 501 individuals with type 1 diabetes and 853 control individuals was used to validate the top common variant associations. HLA typing data were used to identify tag SNPs for DQA1-DQB1 haplotypes. We integrated significant signals to construct a Chinese type 1 diabetes GRS (C-GRS). The accuracy of the C-GRS was tested in an independent validation cohort consisting of 262 individuals with type 1 diabetes, 1080 individuals with type 2 diabetes and 208 control individuals.
RESULTS
We identified a variant, rs10232170, in BMPER as a possible novel type 1 diabetes locus (p=9.897×10). We identified tag SNPs for 13 DQA1-DQB1 haplotypes and 12 non-DQA1-DQB1 loci. Integrating 33 significant SNPs from HLA and non-HLA regions, C-GRS demonstrated high discriminative power for type 1 diabetes (AUC=0.876). It was tested in an independent validation cohort and showed high discrimination (AUC 0.871 for type 1 diabetes vs control group, 0.869 for type 1 diabetes vs type 2 diabetes). The C-GRS outperformed a European-derived GRS (0.871 vs 0.773, and 0.869 vs 0.793, respectively).
CONCLUSIONS/INTERPRETATION: A type 1 diabetes C-GRS comprising 33 SNPs was highly discriminative of type 1 diabetes risk in the Chinese population and could aid in discriminating between type 1 diabetes and type 2 diabetes. This study highlights the potential of genetic information in improving prediction and precision diagnosis of type 1 diabetes in the Chinese population.
DATA AVAILABILITY
The raw sequencing data and summary statistics of genomic DNA derived from human samples have been deposited at the China National Center for Bioinformation ( https://ngdc.cncb.ac.cn/omix ) under accession number PRJCA023730.
目的/假设：我们旨在生成特定人群的1型糖尿病遗传风险评分（GRS），并评估其是否能改善中国人群中1型糖尿病与2型糖尿病之间的鉴别诊断。
方法
我们对1303例1型糖尿病患者和2236例对照个体进行了全基因组关联分析。使用由501例1型糖尿病患者和853例对照个体组成的独立重复队列来验证最常见的变异关联。HLA分型数据用于识别DQA1-DQB1单倍型的标签单核苷酸多态性（SNP）。我们整合显著信号以构建中国1型糖尿病GRS（C-GRS）。在由262例1型糖尿病患者、1080例2型糖尿病患者和208例对照个体组成的独立验证队列中测试C-GRS的准确性。
结果
我们在BMPER基因中鉴定出一个变异rs10232170，可能是一个新的1型糖尿病位点（p=9.897×10）。我们鉴定出13种DQA1-DQB1单倍型和12个非DQA1-DQB1位点的标签SNP。整合来自HLA和非HLA区域的33个显著SNP，C-GRS对1型糖尿病显示出高鉴别力（曲线下面积[AUC]=0.876）。在独立验证队列中进行测试，显示出高鉴别力（1型糖尿病与对照组相比AUC为0.871，1型糖尿病与2型糖尿病相比AUC为0.869）。C-GRS优于源自欧洲的GRS（分别为0.871对0.773以及0.869对0.793）。
结论/解读：包含33个SNP的1型糖尿病C-GRS对中国人群中的1型糖尿病风险具有高度鉴别力，有助于鉴别1型糖尿病和2型糖尿病。本研究突出了遗传信息在改善中国人群中1型糖尿病预测和精准诊断方面的潜力。
数据可用性
源自人类样本的原始测序数据和基因组DNA的汇总统计信息已保存在中国国家生物信息中心（https://ngdc.cncb.ac.cn/omix），登录号为PRJCA023730。
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