摘要
目的应用染色体微阵列技术(chromosomal microarray analysis,CMA)检测自然流产组织的染色体数目和结构异常,探讨该技术的临床应用价值。方法选取自然流产组织112例,行CMA检测,分析其染色体畸变的类型。结果 CMA成功检测了103例(91.96%)流产组织,检出异常结果 57例,检出率为55.34%(57/103)。异常结果包括染色体数目异常51例,占89.47%(51/57),结构异常5例,占8.77%(5/57),父源性全基因组单亲二倍体(UPD)1例,占1.75%(1/57)。染色体数目异常以45,X最常见,其次为16-三体。≥35岁组的流产组织染色体异常检出率显著高于<35岁组(P<0.05)。结论染色体异常是导致自然流产的重要因素,而高龄是导致流产组织染色体异常发生率增加的高危因素。CMA是一种快速、有效的染色体畸变检测方法,有助于阐明自然流产的遗传学病因。
Objective To explore the numerical chromosomal abnormalities and structural chromosomal abnormalities of spontaneous abortion tissues by chromosomal microarray analysis(CMA), and to discuss the clinical application value of CMA. Methods A total of 112 cases of spontaneous abortion were recruited, and the abortion tissues were analyzed by CMA detection to search the types of chromosome aberrations. Results 103 cases(91.96%) of abortion tissues were detected successfully. The abnormal detection rate was 55.34%(57/103). Among the results, 51 cases(89.47%) were numerical abnormalities, 5 cases(8.77%) were structural abnormalities, and 1 case(1.75%) was paternal uniparental disomy(UPD). 45, X was the most common chromosome numerical aberration, followed by 16 trisomy. The detection rate of chromosomal abnormalities in abortion tissues in the ≥35 years old group was significantly higher than that in the <35 years old group(P<0.05). Conclusion Chromosomal abnormality was an important factor leading to spontaneous abortion. Advanced age pregnancy was a high risk factor leading to the increase of chromosomal abnormalities in abortion tissues. CMA was a rapid and effective technique for detecting chromosome aberration, which helped to clarify the genetic causes of spontaneous abortion.
作者
陈伟萍
潘海滔
张涛
CHEN Weiping;PAN Haitao;ZHANG Tao(Department of Genetics,Shaoxing Maternity and Child Health Care Hospital,Shaoxing,Zhejiang 312000,China)
出处
《中国优生与遗传杂志》
2021年第3期392-394,共3页
Chinese Journal of Birth Health & Heredity
基金
国家自然科学基金青年科学基金(81701522)
浙江省医药卫生科研基金(2019KY230)。
关键词
流产组织
染色体微阵列分析
染色体数目异常
染色体结构异常
abortion tissue
chromosomal microarray analysis
numerical abnormality
chromosome structural abnormality