Human Leucocyte Antigen (HLA) testing is useful in the clinical work-up of coeliac disease (CD) with high negative but low positive predictive value. We construct a genomic risk score (GRS) using HLA risk genotypes to improve CD prediction and guide exclusion criteria. Imputed HLA genotypes for five European CD case-control GWAS (n > 15,000) were used to construct and validate an interpretable HLA-based risk model (HDQ₁₅), which shows statistically significant improvements in predictive performance upon all previous HLA-based risk models. Conditioning on this model, we find two novel associations, HLA-DQ6.2 and HLA-DQ7.3, that interact significantly with HLA-DQ2.5 (p = 2.51 × 10⁻⁹, 1.99 × 10⁻⁷, respectively). Integrating these novel alleles into a new risk model (HDQ₁₇) leads to predictive performance equivalent or better than the strongest reported GRS (GRS₂₂₈) using 228 single nucleotide polymorphisms (SNPs). We also demonstrate that our proposed HLA-based models can be implemented using only six HLA tagging SNPs with statistically equivalent predictive performance. Using insights from our model to guide exclusionary criteria, we find the positive predictive value of CD testing in high-risk populations can be increased by 55%, from 17.5 to 27.1%, while maintaining a negative predictive value above 99%. Our results suggest that HLA typing is currently undervalued in CD assessment.

人类白细胞抗原 (HLA) 检测可用于腹腔疾病 (CD) 的临床检查，具有高阴性但阳性预测值低。我们使用 HLA 风险基因型构建基因组风险评分 (GRS)，以改进 CD 预测并指导排除标准。五个欧洲 CD 病例对照 GWAS ( n  > 15,000) 的估算 HLA 基因型用于构建和验证可解释的基于 HLA 的风险模型 ( HDQ ₁₅ )，该模型显示在统计上显着改善了所有以前基于 HLA 的风险模型的预测性能. 在这个模型的条件下，我们发现两个新的关联，HLA-DQ6.2 和 HLA-DQ7.3，它们与 HLA-DQ2.5 显着相互作用（p  = 2.51 × 10 ^-9 , 1.99 × 10 ^-7， 分别）。将这些新的等位基因整合到新的风险模型 ( HDQ ₁₇ ) 中，预测性能相当于或优于使用 228 个单核苷酸多态性 (SNP)的最强报告 GRS ( GRS ₂₂₈ )。我们还证明了我们提出的基于 HLA 的模型可以仅使用六个具有统计等效预测性能的 HLA 标记 SNP 来实现。使用我们模型中的见解来指导排除标准，我们发现高风险人群中 CD 检测的阳性预测值可以提高 55%，从 17.5% 增加到 27.1%，同时将阴性预测值保持在 99% 以上。我们的结果表明 HLA 分型目前在 CD 评估中被低估了。