目的 对甘肃地区新生儿遗传代谢病（inherited metabolic disorder, IMD）的疾病谱和致病基因变异进行分析。 方法 回顾性分析2018年1月—2021年12月甘肃省妇幼保健院286 682例新生儿IMD筛查的串联质谱数据，对串联质谱初筛及复查阳性的患儿进行基因分析。 结果 286 682例新生儿中共发现28个致病基因导致的23种IMD，IMD总患病率为0.63‰（1/1 593），其中苯丙酮尿症患病率最高（0.32‰，1/3 083），其次为甲基丙二酸血症（0.11‰，1/8 959）及四氢生物蝶呤缺乏症（0.06‰，1/15 927）。在28个致病基因中共鉴定出166种变异，其中9个基因中存在13种新变异。根据美国医学遗传学与基因组学学会指南，5种新变异为致病变异，7种为可能致病变异，1种为临床意义未明。 结论 该研究丰富了IMD相关致病基因变异数据库，为该地区IMD精准筛查与诊断体系的建立提供基础性数据。
Abstract
Objective To investigate the disease spectrum and pathogenic genes of inherited metabolic disorder (IMD) among neonates in Gansu Province of China. Methods A retrospective analysis was conducted on the tandem mass spectrometry data of 286 682 neonates who received IMD screening in Gansu Provincial Maternal and Child Health Hospital from January 2018 to December 2021. A genetic analysis was conducted on the neonates with positive results in tandem mass spectrometry during primary screening and reexamination. Results A total of 23 types of IMD caused by 28 pathogenic genes were found in the 286 682 neonates, and the overall prevalence rate of IMD was 0.63‰ (1/1 593), among which phenylketonuria showed the highest prevalence rate of 0.32‰ (1/3 083), followed by methylmalonic acidemia (0.11‰, 1/8 959) and tetrahydrobiopterin deficiency (0.06‰, 1/15 927). In this study, 166 variants were identified in the 28 pathogenic genes, with 13 novel variants found in 9 genes. According to American College of Medical Genetics and Genomics guidelines, 5 novel variants were classified as pathogenic variants, 7 were classified as likely pathogenic variants, and 1 was classified as the variant of uncertain significance. Conclusions This study enriches the database of pathogenic gene variants for IMD and provides basic data for establishing an accurate screening and diagnosis system for IMD in this region.
关键词
遗传代谢病 /
基因变异 /
精准筛查与诊断 /
新生儿
Key words
Inherited metabolic disorder /
Genetic variation /
Accurate screening and diagnosis /
Neonate
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参考文献
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基金
甘肃省科技计划资助项目（22YF7FA094）；兰州市科技计划项目（2021-1-182）；甘肃省卫生行业计划项目（GSWSKY2022-33）；甘肃省科技厅创新基地及人才计划（21JR7RA680）；甘肃省自然科学基金（23JRRA1378）；国家科技资源共享服务平台（2005DKA21300）。
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