Hassan Syahzuwan, Bahar Rosnah, Johan Muhammad Farid, Mohamed Hashim Ezzeddin Kamil, Abdullah Wan Zaidah, Esa Ezalia, Abdul Hamid Faidatul Syazlin, Zulkafli Zefarina
Department of Hematology, School of Medical Sciences, Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia.
Institute for Medical Research, Shah Alam 40170, Malaysia.
Diagnostics (Basel). 2023 Jan 19;13(3):373. doi: 10.3390/diagnostics13030373.
Thalassemia is one of the most heterogeneous diseases, with more than a thousand mutation types recorded worldwide. Molecular diagnosis of thalassemia by conventional PCR-based DNA analysis is time- and resource-consuming owing to the phenotype variability, disease complexity, and molecular diagnostic test limitations. Moreover, genetic counseling must be backed-up by an extensive diagnosis of the thalassemia-causing phenotype and the possible genetic modifiers. Data coming from advanced molecular techniques such as targeted sequencing by next-generation sequencing (NGS) and third-generation sequencing (TGS) are more appropriate and valuable for DNA analysis of thalassemia. While NGS is superior at variant calling to TGS thanks to its lower error rates, the longer reads nature of the TGS permits haplotype-phasing that is superior for variant discovery on the homologous genes and CNV calling. The emergence of many cutting-edge machine learning-based bioinformatics tools has improved the accuracy of variant and CNV calling. Constant improvement of these sequencing and bioinformatics will enable precise thalassemia detections, especially for the CNV and the homologous and genes. In conclusion, laboratory transiting from conventional DNA analysis to NGS or TGS and following the guidelines towards a single assay will contribute to a better diagnostics approach of thalassemia.
地中海贫血是最具异质性的疾病之一，全球记录的突变类型超过一千种。由于表型变异性、疾病复杂性和分子诊断测试的局限性，通过传统的基于聚合酶链反应（PCR）的DNA分析对地中海贫血进行分子诊断既耗时又耗费资源。此外，遗传咨询必须以对导致地中海贫血的表型和可能的遗传修饰因子进行广泛诊断为依据。来自先进分子技术的数据，如下一代测序（NGS）和第三代测序（TGS）的靶向测序，对于地中海贫血的DNA分析更合适且有价值。虽然由于错误率较低，NGS在变异检测方面优于TGS，但TGS较长的读长特性允许进行单倍型分型，这在同源基因上的变异发现和拷贝数变异（CNV）检测方面更具优势。许多基于机器学习的前沿生物信息学工具的出现提高了变异和CNV检测的准确性。这些测序和生物信息学的不断改进将使地中海贫血的精确检测成为可能，特别是对于CNV以及同源基因。总之，实验室从传统DNA分析转向NGS或TGS并遵循指南采用单一检测方法，将有助于改善地中海贫血的诊断方法。
