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基于中国炎症性肠病患者DNA-硫鸟嘌呤核苷酸代谢途径多态性建立硫唑嘌呤诱导白细胞减少的新型预测模型。

Establishment of a novel predictive model for thiopurine-induced leucopenia based on the polymorphisms in the DNA-thioguanine nucleotide metabolite pathway in Chinese patients with inflammatory bowel disease.

作者信息

Zhu Xia, Wang Xue-Ding, Xuan Qiao-Lan, Guan Shao-Xing, Guan Yan-Pin, Gao Xiang, Chao Kang, Huang Min

机构信息

Department of Pharmacy, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; Department of Gastroenterology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.

Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.

出版信息

Drug Metab Dispos. 2025 Aug;53(8):100119. doi: 10.1016/j.dmd.2025.100119. Epub 2025 Jul 7.

Abstract

Thiopurine-induced leucopenia (TIL) affects more than 20% of Asians despite dose optimization via NUDT15 and TPMT genotyping. Elevated levels of DNA-thioguanine nucleotide (DNA-TG) have been implicated in the development of TIL. This study aimed to identify genetic polymorphisms influencing TIL through the DNA-TG metabolic pathway and construct a predictive model in Chinese inflammatory bowel disease patients. A prospective cohort of inflammatory bowel disease patients receiving thiopurines from December 2018 to December 2019 was analyzed. A total of 294 single-nucleotide polymorphisms across 29 genes were screened using the MassARRAY system. Candidate single-nucleotide polymorphisms associated with DNA-TG exposure or TIL (P < .1) were selected for validation. Independent risk factors were identified through multivariate logistic regression and incorporated into a predictive nomogram. Thiopurine metabolites, including DNA-TG and 6TGN, were quantified. DNA-TG, but not 6TGN, exposure was significantly associated with TIL (P = 8.3 × 10, P = .41). Sex, along with variants in NUDT15 (rs116855232 c.415C > T), TPMT (rs9465102), MOCOS (rs73430958), and RRM1 (rs1735053), were identified as independent predictors of TIL. The resulting nomogram demonstrated good discriminative performance (area under the curve = 0.72, 95% confidence interval: 0.65-0.78). Individuals stratified into low-, medium-, and high-risk groups based on total point thresholds (25.0 and 196.8), showed significant differences in TIL incidence in both NUDT15 variants and nonvariants (P = 1.8×10, P = .045). Our findings indicate that in addition to NUDT15, novel genetic variants in TPMT, MOCOS, and RRM1 are potential predictive markers of TIL. The new nomogram enables more accurate identification of individuals at high risk of TIL, allowing for the proactive adjustment of thiopurine therapy. SIGNIFICANCE STATEMENT: Compared with prior studies limited to NUDT15 and TPMT variants, it was the first pharmacogenomic study to investigate genetic polymorphisms affecting thiopurine-induced leucopenia (TIL) and DNA-thioguanine nucleotide metabolism, constructing a clinically actionable TIL prediction model. We identified novel associations of TPMT, MOCOS, and RRM1 variants with TIL risk, offering key insights for precision dosing in Asian populations. The validated nomogram integrates these biomarkers to stratify patients into distinct risk groups, facilitating tailored thiopurine therapy.

摘要

尽管通过NUDT15和TPMT基因分型进行了剂量优化,但硫嘌呤诱导的白细胞减少症(TIL)在超过20%的亚洲人中出现。DNA硫鸟嘌呤核苷酸(DNA-TG)水平升高与TIL的发生有关。本研究旨在通过DNA-TG代谢途径鉴定影响TIL的基因多态性,并在中国炎症性肠病患者中构建预测模型。对2018年12月至2019年12月接受硫嘌呤治疗的炎症性肠病患者的前瞻性队列进行了分析。使用MassARRAY系统筛选了29个基因中的294个单核苷酸多态性。选择与DNA-TG暴露或TIL相关的候选单核苷酸多态性(P < 0.1)进行验证。通过多因素逻辑回归确定独立危险因素,并将其纳入预测列线图。对包括DNA-TG和6TGN在内的硫嘌呤代谢物进行了定量。DNA-TG而非6TGN暴露与TIL显著相关(P = 8.3 × 10,P = 0.41)。性别以及NUDT15(rs116855232 c.415C > T)、TPMT(rs9465102)、MOCOS(rs73430958)和RRM1(rs1735053)的变异被确定为TIL的独立预测因素。所得列线图显示出良好的判别性能(曲线下面积 = 0.72,95%置信区间:0.65 - 0.78)。根据总分阈值(25.0和196.8)分为低、中、高风险组的个体,在NUDT15变异和非变异个体中TIL发生率均有显著差异(P = 1.8×10,P = 0.045)。我们的研究结果表明,除了NUDT15外,TPMT、MOCOS和RRM1中的新基因变异是TIL的潜在预测标志物。新的列线图能够更准确地识别TIL高风险个体,从而主动调整硫嘌呤治疗。意义声明:与之前仅限于NUDT15和TPMT变异的研究相比,这是第一项药物基因组学研究,旨在调查影响硫嘌呤诱导的白细胞减少症(TIL)和DNA硫鸟嘌呤核苷酸代谢的基因多态性,构建一个具有临床可操作性的TIL预测模型。我们确定了TPMT、MOCOS和RRM1变异与TIL风险的新关联,为亚洲人群的精准给药提供了关键见解。经过验证的列线图整合了这些生物标志物,将患者分为不同的风险组,便于进行个性化的硫嘌呤治疗。

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