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MALDI–TOF–MS for Rapid Screening and Typing of β-Globin Variants and β-Thalassemia

Yan Li, PhD. Key Laboratory of Interdisciplinary Research, Institute of Biophysics of Chinese Academy of Sciences, College of Life Sciences, University of Chinese Academy of Sciences; Department of Biomedicine, Bioland Laboratory;

Xiangmin Xu, PhD. Department of Medical Genetics, School of Basic Medical Sciences and Innovation Center for Diagnostics and Treatment of Thalassemia, Nanfang Hospital, Southern Medical University

Dr. Yan Li Xiangming Xu


Beta-globin disorders are the most pervasive monogenic disorder worldwide. Traditional phenotype-based screening for β-globin variants and β-thalassemia using hematological parameters is time-consuming with low-resolution detection.

The authors constructed a MALDI–TOF–MS approach for identifying various β-globin disorders and classifying thalassemia major (TM) and thalassemia intermedia (TI) patients based on δ- to β-globin, γ- to α-globin, γ- to β-globin ratios, and/or the abnormal globin-chain patterns.

The study consists of 3 phases. First, a QuanTOF I (Intelligene Biosystems, Qingdao, China) MALDI–TOF mass spectrometer was used to analyze the intact globin chains. These processed spectra were mass-calibrated using the known masses of Hb α, β, γ, and δ subunits, respectively.

Second, the training set of 901 samples (598 normal controls and 303 samples with various β-globin disorders) was used to develop a model for testing β-globin variant and β-thalassemia and determining fetal hemoglobin (Hb F) concentration. The training samples were categorized into 3 groups. 1: abnormal Hb variants (16 cases); 2: β-thalassemia traits (152 cases), coinheritance of β- and α-thalassemia (34 cases), and deletional hereditary persistence of fetal hemoglobin (HPFH)/δβ-thalassemia (11 cases); and 3: β-thalassemia (90 cases).

Third, the MALDI–TOF–MS prediction model was validated in two separate cohorts, 16,172 healthy individuals in the general population, and 201 patients with β-thalassemia.

The validation study yielded comparable results of clinical specificity (99.89% vs. 99.71%), and accuracy (99.78% vs. 99.16%) between the new assay and traditional methods but higher clinical sensitivity for the new method (97.52% vs 88.01%). The new assay identified 22 additional abnormal hemoglobin variants in 69 individuals including 9 novel ones, and accurately screened for 9 carriers of deletional hereditary persistence of fetal hemoglobin or δβ-thalassemia. TM and TI were well classified in 178 samples out of 201 β-thalassemia patients.


This study demonstrated this MALDI–TOF–MS approach is a highly accurate, predictive tool that could be suitable for large-scale population screening and clinical classification of β-globin disorders.


基质辅助激光解吸电离飞行时间质谱用于快速筛查和鉴定β-珠蛋白变异和β地中海贫血

作者:

李岩,博士,研究员,中国科学院生物物理研究所跨学科研究重点实验室;中国科学院大学生命科学学院生物医学系

徐湘明,博士,教授,南方医科大学南方医院遗传学系;基础医学学院及地中海贫血诊断与治疗创新中心


β-珠蛋白疾病是全球最普遍的单基因疾病。传统的基于表型的β-珠蛋白变异和β地中海贫血的筛查方法使用血液学参数,耗时且分辨率低。


本文作者构建了一种基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS)方法,用于鉴定各种β-珠蛋白疾病,并根据δ-对β-珠蛋白、γ-对α-珠蛋白、γ-对β-珠蛋白比例和/或异常珠蛋白链模式对地中海贫血重型(TM)和中度型(TI)患者进行分类。


该研究分为3个阶段。首先,使用QuanTOF I(Intelligene Biosystems,中国青岛)MALDI-TOF质谱仪分析完整的珠蛋白链。然后,使用已知的Hb α、β、γ和δ亚基的质量校准这些处理过的光谱。


其次,使用901个样本的训练集(598个正常对照组和303个具有各种β-珠蛋白疾病的样本)来开发测试β-珠蛋白变异和β地中海贫血以及确定胎儿血红蛋白(Hb F)浓度的模型。训练样本分为3组:1:异常Hb变异(16例);2:β地中海贫血特征(152例)、β-和α-地中海贫血的共同遗传(34例)以及删除性遗传性胎儿血红蛋白持续存在(HPFH)/δβ-地中海贫血(11例);3:β地中海贫血(90例)。


第三,MALDI-TOF-MS预测模型在两个不同的队列中进行了验证,其中一个队列包括16,172名一般人口的健康个体,另一个队列包括201名患有β-地中海贫血的患者。


验证研究结果显示,新方法与传统方法相比,在临床特异性(99.89%对99.71%)和准确性(99.78%对99.16%)方面取得了可比较的结果,但新方法的临床敏感性更高(97.52%对88.01%)。新方法在69名个体中鉴定出22种额外的异常血红蛋白,其中包括9种新型异常血红蛋白,并准确筛查出9名携带删除性遗传性胎儿血红蛋白或δβ-地中海贫血的携带者。在201名β-地中海贫血患者中,178名样本成功分类为TM和TI。


该研究表明,这种MALDI-TOF-MS方法是一种高度准确的预测工具,适用于大规模人群筛查和β-珠蛋白疾病的临床分类。


Reference

Zhang Q, Wang G, Sun D, Lin W, Yan T, Wu Y, Wu M, Chen J, Zou S, Xie W, Zhou Y, Wang Y, He L, Liu Y, Qiu Z, Hu L, Lin B, Zhou X, Li Y, Xu X. MALDI-TOF-MS for Rapid Screening and Typing of β-Globin Variant and β-Thalassemia through Direct Measurements of Intact Globin Chains. Clin Chem. 2022 Dec 6;68(12):1541-1551. DOI: 10.1093/clinchem/hvac151


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