دورية أكاديمية
A MALDI-TOF mass spectrometry-based haemoglobin chain quantification method for rapid screen of thalassaemia
| العنوان: | A MALDI-TOF mass spectrometry-based haemoglobin chain quantification method for rapid screen of thalassaemia |
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| المؤلفون: | Jian Zhang, Zhizhong Liu, Ribing Chen, Qingwei Ma, Qian Lyu, Shuhui Fu, Yufei He, Zijie Xiao, Zhi Luo, Jianming Luo, Xingyu Wang, Xiangyi Liu, Peng An, Wei Sun |
| المصدر: | Annals of Medicine, Vol 54, Iss 1, Pp 293-301 (2022) |
| بيانات النشر: | Taylor & Francis Group, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Medicine |
| مصطلحات موضوعية: | maldi-tof, haemoglobin, molecular diagnostics, Medicine |
| الوصف: | Background Thalassaemia is one of the most common inherited monogenic diseases worldwide with a heavy global health burden. Considering its high prevalence in low and middle-income countries, a cheap, accurate and high-throughput screening test of thalassaemia prior to a more expensive confirmatory diagnostic test is urgently needed. Methods In this study, we constructed a machine learning model based on MALDI-TOF mass spectrometry quantification of haemoglobin chains in blood, and for the first time, evaluated its diagnostic efficacy in 674 thalassaemia (including both asymptomatic carriers and symptomatic patients) and control samples collected in three hospitals. Parameters related to haemoglobin imbalance (α-globin, β-globin, γ-globin, α/β and α-β) were used for feature selection before classification model construction with 8 machine learning methods in cohort 1 and further model efficiency validation in cohort 2. Results The logistic regression model with 5 haemoglobin peak features achieved good classification performance in validation cohort 2 (AUC 0.99, 95% CI 0.98–1, sensitivity 98.7%, specificity 95.5%). Furthermore, the logistic regression model with 6 haemoglobin peak features was also constructed to specifically identify β-thalassaemia (AUC 0.94, 95% CI 0.91–0.97, sensitivity 96.5%, specificity 87.8% in validation cohort 2). Conclusions For the first time, we constructed an inexpensive, accurate and high-throughput classification model based on MALDI-TOF mass spectrometry quantification of haemoglobin chains and demonstrated its great potential in rapid screening of thalassaemia in large populations.Key messages Thalassaemia is one of the most common inherited monogenic diseases worldwide with a heavy global health burden. We constructed a machine learning model based on MALDI-TOF mass spectrometry quantification of haemoglobin chains to screen for thalassaemia. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 0785-3890 1365-2060 07853890 |
| Relation: | https://doaj.org/toc/0785-3890; https://doaj.org/toc/1365-2060 |
| DOI: | 10.1080/07853890.2022.2028002 |
| URL الوصول: | https://doaj.org/article/ef2c92ab740d4a93a6b907f4c074916d |
| رقم الأكسشن: | edsdoj.f2c92ab740d4a93a6b907f4c074916d |
| قاعدة البيانات: | Directory of Open Access Journals |
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Full Text Finder | تدمد: | 07853890 13652060 |
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| DOI: | 10.1080/07853890.2022.2028002 |