孟德尔随机化
遗传关联
全基因组关联研究
遗传力
连锁不平衡
遗传变异
遗传建筑学
2型糖尿病
医学
遗传学
进化生物学
候选基因
多效性
计算生物学
遗传变异
遗传相关
遗传倾向
生物
遗传模型
遗传力缺失问题
生物信息学
遗传异质性
等位基因
遗传连锁
表达数量性状基因座
加性遗传效应
遗传变异
基因组学
遗传分析
单核苷酸多态性
联动装置(软件)
数量性状位点
孟德尔遗传
作者
Ben Niu,M Xia,Jia-Xin Wu,Fei‐Yan Deng,Haiying Wu,Shu‐Feng Lei
摘要
AIMS: Type 2 diabetes (T2D) is a heterogeneous disorder with substantial variation in age at onset (AAO). This study aimed to characterize the distinct genetic architectures and biological mechanisms underlying extreme AAO-defined T2D subtypes. MATERIALS AND METHODS: Using 74 795 European-ancestry participants from the UK Biobank, we performed genome-wide association studies (GWAS) of relatively early-onset T2D (eoT2D; AAO < 55 years) and late-onset T2D (loT2D; AAO ≥ 70 years). We investigated subtype-specific genetic loci, SNP-based heritability, genetic correlations, Mendelian randomization (MR)-based relationships, polygenic risk scores (PRS) and phenome-wide association studies (PheWAS). Single-cell transcriptomic data from human pancreatic tissues were further used to evaluate cell-type-specific expression patterns of candidate genes. RESULTS: SNP-based heritability was substantially higher for eoT2D than loT2D (11.2% vs. 6.4%), with eoT2D displaying distinct genetic loci related to β-cell function and insulin regulation, including SLC30A8 and IRS1. By contrast, loT2D showed a comparatively lipid-related genetic profile, featuring APOE-associated signals and expression patterns in immune-related cell populations. Linkage disequilibrium score regression (LDSC) and MR analyses further underscored this divergence: eoT2D exhibited broader genetic overlap with cardiometabolic traits, whereas loT2D showed stronger relationships with traditional metabolic risk factors. Finally, subtype-specific PRSs improved risk discrimination beyond conventional covariates, although their clinical utility warrants further evaluation. CONCLUSIONS: Extreme AAO-defined T2D subtypes exhibit partially distinct genetic architectures, highlighting AAO as an important dimension of T2D heterogeneity and providing a framework for future age-stratified genetic risk assessment.
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