PO.PS01.12 · 人群科学
功能性 I 类、II 类及非经典 HLA 变异在 All of Us 研究项目中驱动淋巴瘤和骨髓瘤风险
Functional Class I, Class II, and nonclassical HLA variation drives lymphoma and myeloma risk in the all of us research program
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摘要 Abstract
中文摘要
背景：HLA 介导的免疫监视涉及经典、非经典和 I 类样通路。由于淋巴瘤和骨髓瘤依赖不同的免疫机制，我们跨祖先群体评估了 HLA I/II 类、非经典及 I 类样基因座，采用等位基因水平氨基酸（AA）、杂合度（HET）、进化分歧度（HED）、IEDB 衍生的肽结合广度（PBW；9 肽结合熵）以及位点氨基酸杂合度（残基错配）等指标。
方法：使用 ICD/SNOMED 在 All of Us 队列中识别霍奇金淋巴瘤（HL）、NHL 及其亚型和多发性骨髓瘤（MM）；对照组无血液系统恶性肿瘤。分析了在 EUR、AFR 和 AMR 中经 HIBAG 填补且 n>20 病例的等位基因。模型校正了年龄、性别、PC 及混合比例，检验 OR、95% CI 和 FDR<0.1。我们使用 PRS-HLA 联合模型检验 HLA 指标是否在淋巴瘤 PRS 之外提供额外的风险信息。
结果：我们在 EUR 中重复验证了 HET 和/或 HED I/II 类与 NHL（N=1668）、DLBCL（N=490）、HL（N=393）和 FL（N=435）的关联，并利用 PBW 和 AA 水平指标扩展了这些模式。在 NHL 中，我们证实 HET-C 降低风险（p=0.027），并发现更大的 PBW 具有保护作用（OR=0.49；p=0.09）。类似地，在 CLL 中，我们重复验证了 HET-A 关联（p=0.027），识别出 PBW-A 效应（OR=0.25；p=.03），以及在 A-163 处的位点信号（OR=.83，p=0.015），该信号也出现于 NHL（p=.015）。两个基因座均未显示 HED 效应。新的 MM 关联与 HET-B 和 -C（OR≈0.74；p<0.03）相关，并得到 B-42 处位点命中（OR=0.77；P=0.033）和 PBW-C 效应（OR≈0.24；p=0.01）的支持，而 HED 仍为阴性。相比之下，DLBCL 在所有 I 类指标以及 MICB（OR=0.75；p=0.006）和 MHC 样 HET（OR=0.73；p=0.084）上均显示出保护作用。在 EUR DLBCL 中，A*01:01（OR=1.23；p=0.076）和 A26:01（OR=1.56；p=0.051）显示出风险效应，与既往部分报告一致，并由多个 A 基因座位点信号（P<0.02）所强化。新的 AFR 特异性发现包括：HL 中的 A*68:02（OR=2.88；p=1.8×10⁻⁵），由 A-30 处的位点命中所印证（OR≈3.0，p=.0004），NHL 中的 B*07:02（OR=1.69；p=0.018），以及 C1 基序等位基因 C07:01（OR=1.51，p=.04）和 C*07:02（OR=2.02，p=.00017），与 KIR-C1 机制一致。DLBCL PRS（其中包含一个 HLA-B 变异）在 EUR 中重复验证（OR=1.25，95% CI 1.15-1.36；p=7.3×10⁻⁷），联合模型显示当与 PRS 结合时 HED（p=0.0028）和 HET（OR=0.86，95% CI 0.80-0.93，p=7.0×10⁻⁵）仍然显著。AIC 确定 HET + PRS 加协变量为最佳模型。该 PRS 在 AFR 或 AMR 中未获重复验证。
结论：我们重复验证了经典 HLA 关联，并识别出跨祖先群体塑造 B 细胞恶性肿瘤风险的新的非经典和功能性 HLA 特征。此外，添加正交 HLA 指标在 PRS 之外提供了大量独立的信息。
查看英文原文 English abstract
Background: HLA-mediated immune surveillance involves classical, non-classical, and class I-like pathways. Because lymphoma and myeloma rely on different immune mechanisms, we evaluated HLA class I/II, non-classical, and class I-like loci across ancestries using allele-level amino acids(AA), heterozygosity (HET), evolutionary divergence (HED), IEDB-derived peptide-binding breadth (PBW; 9-mer binding entropy), and positional amino-acid heterozygosity (residue mismatch).
Methods: Hodgkin lymphoma (HL), NHL and subtypes, and multiple myeloma (MM) in All of Us Cohort were identified using ICD/SNOMED; controls lacked hematologic malignancy. HIBAG-imputed allele with n>20 cases were analyzed in EUR, AFR, and AMR. Models adjusted for age, sex, PCs, and admixture proportions tested ORs, 95% CIs, and FDR<0.1. We used joint PRS-HLA models to test whether HLA metrics contributed risk information beyond the lymphoma PRS.
Results: We replicated EUR HET and/or HED class I/II associations with NHL (N=1668), DLBCL (N=490), HL (N=393), and FL (N=435), and extended these patterns using PBW and AA-level metrics. In NHL, we confirmed that HET-C reduced risk (p=0.027) and found greater PBW was protective (OR=0.49; p=0.09). Similarly, in CLL, we replicated the HET-A association (p=0.027), identified PBW-A effect (OR=0.25; p=.03), and a positional signal at A-163 (OR=.83, p=0.015) that also appeared in NHL(p=.015). Neither locus showed HED effects.Novel MM associations with HET-B and -C (OR≈0.74; p<0.03), were supported by a positional hit at B-42 (OR=0.77; P=0.033) and a PBW-C effect (OR≈0.24; p=0.01), while HED remained null. In contrast, DLBCL showed protection across all class I metrics as well as at MICB (OR=0.75; p=0.006) and MHC-like HET (OR=0.73; p=0.084). In EUR DLBCL, A*01:01 (OR=1.23; p=0.076) and A26:01 (OR=1.56; p=0.051) showed risk effects consistent with some prior reports reinforced by multiple A-locus positional signals (P<0.02).Novel AFR-specific findings included A*68:02 in: HL (OR=2.88; p=1.8×10⁻⁵), mirrored by a positional hit at A-30 (OR≈3.0, p=.0004), NHL at B*07:02 (OR=1.69; p=0.018) and for C1-motif alleles C07:01 (OR=1.51, p=.04) and C*07:02 (OR= 2.02, p=.00017) consistent with a KIR-C1 mechanism.The DLBCL PRS replicated (which includes an HLA-B variant) in EUR (OR=1.25, 95% CI 1.15-1.36; p=7.3×10⁻⁷) and joint models showed HED (p=0.0028) and HET (OR=0.86, 95% CI 0.80-0.93, p=7.0×10⁻ 5 ) remained significant when combined with PRS. AIC identified HET + PRS with covariates as the best model. The PRS did not replicate in AFR or AMR.
Conclusion: We replicated classical HLA associations and identified novel non-classical and functional HLA features that shape B-cell malignancy risk across ancestries. Furthermore, adding orthogonal HLA metrics provided substantial, independent information beyond the PRS.
利益披露 Disclosure
L. Sucheston-Campbell, None..
S. Tambe, None..
L. Zuo, None..
A. Clay-Gilmour, None..
V. Joseph, None..
B. Tycko, None..
W. Cozen, None.