下一代测序(NGS)小组的效用可以在遗传性周围神经病变中增加,鉴于PMP22的重复是一个主要的异常。在本研究中,评估了从NGS组数据中检测PMP22拷贝数变异(CNV)的算法的分析性能.NGS小组涵盖了141个基因,包括PMP22和在17p11.2的1.5-Mb重复区域内的五个基因。使用实验室开发的算法进行CNV调用。在2018年3月至2021年1月接受NGS目标小组的92例病例中,有26例可疑PMP22CNV。58例进行MLPA分析,结果与NGS数据100%一致(23次重复,2个删除,和33个否定)。通过包括14个阳性和20个阴性样品的另一个盲数据集进一步验证了管道的分析性能。通过不仅分析PMP22,而且分析17p11.2的1.5Mb区域内的相邻基因,可以可靠地检测PMP22CNV。基于要求PMP22的CNV的高精度,可以通过减少对MLPA的需求来简化诊断周围多发性神经病的测试策略。
The utility of the next-generation sequencing (NGS) panel could be increased in hereditary peripheral neuropathies, given that the duplication of
PMP22 is a major abnormality. In the present study, the analytical performance of an algorithm for detecting
PMP22 copy number variation (CNV) from the NGS panel data was evaluated. The NGS panel covers 141 genes, including
PMP22 and five genes within 1.5-megabase duplicated region at 17p11.2. CNV calling was performed using a laboratory-developed algorithm. Among the 92 cases subjected to targeted NGS panel from March 2018 to January 2021, 26 were suggestive of
PMP22 CNV. Multiplex ligation-dependent probe amplification analysis was performed in 58 cases, and the results were 100% concordant with the NGS data (23 duplications, 2 deletions, and 33 negatives). Analytical performance of the pipeline was further validated by another blind data set, including 14 positive and 20 negative samples. Reliable detection of
PMP22 CNV was possible by analyzing not only
PMP22 but also the adjacent genes within the 1.5-megabase region of 17p11.2. On the basis of the high accuracy of CNV calling for PMP22, the testing strategy for diagnosis of peripheral polyneuropathies could be simplified by reducing the need for multiplex ligation-dependent probe amplification.