High-resolution MHC sequencing reveals novel genetic risk variants underlying antithyroid drug-induced agranulocytosis

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ID: 337462
2026
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Abstract
Abstract Background Antithyroid drug-induced agranulocytosis (TIA) is a rare and severe complication Graves disease (GD) treatment. Previous genome-wide association studies (GWAS) have identified ethnicity-specific human leukocyte antigen (HLA) risk alleles for TIA, but limitations persist in major histocompatibility complex (MHC) region coverage, variant resolution, and population generalizability. Methods We conducted the first comprehensive MHC probe-capture sequencing (138× depth, covering 4.97 Mb) using a 2-stage study (Stage 1: 40 TIA cases, 93 GD controls; Stage 2: 20 TIA cases, 49 GD controls), with 1200 healthy controls as background references. High-resolution HLA typing, single-nucleotide polymorphism (SNP) association analysis, meta-analysis, and logistic regression were employed to identify TIA-related genetic variants, and a clinical nomogram was constructed for TIA risk prediction. Results A total of 5661 MHC variants were detected, among which 133 TIA-risk SNPs were identified and grouped into 12 linkage disequilibrium blocks. The lead SNP rs9270003 (HLA-DRB1) was the most strongly associated variant (odds ratio, 10.19; Padj = 5.99 × 10−7). The C4A missense variant rs201016130 (Ser1286Ala) was correlated with milder TIA and lower serum C4 levels, revealing a novel link between complement system variation and TIA severity. Four human leukocyte antigen (HLA) alleles (HLA-B*38:02:01:02, HLA-B*39:01:01:02L, HLA-C*07:02:01:01, DRB1*08:03:02:01) were associated with TIA and validated in the Stage 2. Notably, homozygosity of HLA-C*07:02:01:01 was linked to more severe TIA phenotypes. A preliminary risk-stratification nomogram was developed (C-index = 0.792), necessitating prospective validation for further confirmation. Conclusion Targeted MHC sequencing with high-resolution HLA typing identified novel genetic markers associated with TIA susceptibility and severity. Our findings may help lay a foundation for further investigation into individualized risk assessment in GD management.
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Authors Xinyao Miao, Yiqi Jiang, 明晶 趙, Yuanlin Luo, Xiaojuan Gong, Xin Guo, Bowen Tan, Chunxia Yan, Bao Zhang, Shuai Cheng Li, Yayi He
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Journal the journal of clinical endocrinology & metabolism
Year 2026
DOI
10.1210/clinem/dgag359
URL
https://doi.org/10.1210/clinem/dgag359
Keywords Keywords not found

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