Value of high-throughput sequencing technology in observation of chromosomal abnormalities in the villus samples of women with missed abortion and risk factors for missed abortion

doi:10.3877/cma.j.issn.1674-0785.2021.12.017

Abstract

Abstract:

Objective

To assess the value of high-throughput sequencing technology in the observation of chromosomal abnormalities in the villus samples of women with missed abortions and identify the risk factors for missed abortion.

Methods

The clinical data of 105 missed abortion women (observation group) admitted to Suzhou Hospital of Anhui Medical University from July 2018 to December 2020 were retrospectively analyzed. Meanwhile, 105 normal pregnant women who were healthy during physical examination during the same period were included as a control group. Patients in the observation group underwent uterine evacuation or drug abortion at our hospital, and villus samples were collected to perform traditional karyotyping and high-throughput sequencing tests. The test results were then compared statistically between the two groups. In addition, basic information [age, area of residence, history of miscarriage, body mass index (BMI), smoking, drinking, radiation exposure, physical exercise, folic acid supplementation, estrogen receptor alpha (ERα) gene polymorphism] was compared between the two groups, and variables with statistical significance were incorporated into multivariate Logistic regression analysis to identify the risk factors for missed abortion.

Results

In the high-throughput sequencing test, 105 cases successfully completed the test, of which 38.10% (40/105) had normal karyotypes, 49.52% (52/105) had abnormal numbers, and 12.38% (13/105) had abnormal structures. In the traditional karyotype analysis, 7 (6.67%) cases failed to be tested due to culture failure, and 98 cases successfully completed the test, of which 45.92% (45/98) had normal karyotypes, 50.00% (49/98) had abnormal numbers, and 4.08% (4/98) had abnormal structures. The detection rate of structural abnormalities by high-throughput sequencing technology was 12.38%, which was significantly higher than that of traditional karyotype analysis (4.08%, P＜0.05). Age (more than 35 years old), smoking, drinking, radiation exposure, ERα gene PvuⅡ polymorphism PP and Pp genotypes differed significantly between the two groups (P＜0.05). Multivariate Logistic regression analysis confirmed that age ≥35 years old, smoking, drinking, radiation exposure, and ERα gene PvuⅡ polymorphism PP and Pp genotypes were risk factors for missed abortion (P＜0.05).

Conclusion

The incidence of missed abortion is affected by many factors, such as age, smoking, drinking, radiation exposure, and ERα gene PvuⅡ polymorphism, and high-throughput sequencing technology can detect small fragments, which can provide assistance for the detection of villus chromosome abnormalities in women with missed abortion.

Key words: Missed abortion, High-throughput sequencing technology, Estrogen receptor α, Chromosome

Zhongyu Chen, Shui Jing. Value of high-throughput sequencing technology in observation of chromosomal abnormalities in the villus samples of women with missed abortion and risk factors for missed abortion[J]. Chinese Journal of Clinicians(Electronic Edition), 2021, 15(12): 1003-1008.

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Figures/Tables 6

检测结果		例数	百分率（%）
标本未见异常		45	45.92
数目异常
三体
	16-三体	8	8.16
	22三体	7	7.14
	9-三体	6	6.12
	18-三体	4	4.08
	20-三体	2	2.04
多倍体
	三倍体	13	13.27
	四倍体	9	9.18
结构异常
染色体部分缺失		2	2.04
染色体部分重复		2	2.04

检测结果		例数	百分率（%）
标本未见异常		40	38.10
数目异常
三体
	16-三体	7	6.67
	22-三体	6	5.71
	9-三体	4	3.81
	18-三体	4	3.81
	20-三体	3	2.86
多倍体
	三倍体	15	14.29
	四倍体	13	12.38
结构异常
染色体部分缺失		8	7.62
染色体部分重复		5	4.76

检测方式	例数	正常核型	数目异常	结构异常
传统染色体核型分析	98	45（45.92）	49（50.00）	4（4.08）
高通量测序技术	105	40（38.10）	52（49.52）	13（12.38）
χ²值		1.275	0.005	4.550
P值		0.259	0.946	0.033

影响因素	观察组（105例）	对照组（105例）	t/χ²值	P值
年龄［例（%）］			4.311	0.038
≥35岁	64（60.95）	49（46.67）
＜35岁	41（39.05）	56（53.33）
居住地区［例（%）］			0.172	0.679
城镇	52（49.52）	55（52.38）
农村	53（50.48）	50（47.62）	0.108	0.914
BMI（kg/m²， $x ¯$ ±s）	21.43±1.33	21.45±1.35
流产史［例（%）］			0.177	0.674
有	60（57.14）	63（60.00）
无	45（42.86）	42（40.00）
吸烟［例（%）］			5.926	0.015
是	47（44.76）	30（28.57）
否	58（55.24）	75（71.43）
饮酒［例（%）］			10.109	0.001
是	61（58.10）	38（36.19）
否	44（41.90）	67（63.81）
辐射暴露［例（%）］			10.135	0.001
是	60（57.14）	37（35.24）
否	45（42.86）	68（64.76）
体育锻炼［例（%）］			0.514	0.473
是	88（83.81）	84（80.00）
否	17（16.19）	21（20.00）
补充叶酸［例（%）］			0.085	0.771
是	35（33.33）	37（35.24）
否	70（66.67）	68（64.76）
ERα基因PvuⅡ多态性［例（%）］			7.149	0.028
PP	15（14.29）	10（9.52）
Pp	56（53.33）	42（40.00）
pp	34（32.38）	53（5.048）

影响因素	观察组（105例）	对照组（105例）	t/χ²值	P值
年龄［例（%）］			4.311	0.038
≥35岁	64（60.95）	49（46.67）
＜35岁	41（39.05）	56（53.33）
居住地区［例（%）］			0.172	0.679
城镇	52（49.52）	55（52.38）
农村	53（50.48）	50（47.62）	0.108	0.914
BMI（kg/m²， $x ¯$ ±s）	21.43±1.33	21.45±1.35
流产史［例（%）］			0.177	0.674
有	60（57.14）	63（60.00）
无	45（42.86）	42（40.00）
吸烟［例（%）］			5.926	0.015
是	47（44.76）	30（28.57）
否	58（55.24）	75（71.43）
饮酒［例（%）］			10.109	0.001
是	61（58.10）	38（36.19）
否	44（41.90）	67（63.81）
辐射暴露［例（%）］			10.135	0.001
是	60（57.14）	37（35.24）
否	45（42.86）	68（64.76）
体育锻炼［例（%）］			0.514	0.473
是	88（83.81）	84（80.00）
否	17（16.19）	21（20.00）
补充叶酸［例（%）］			0.085	0.771
是	35（33.33）	37（35.24）
否	70（66.67）	68（64.76）
ERα基因PvuⅡ多态性［例（%）］			7.149	0.028
PP	15（14.29）	10（9.52）
Pp	56（53.33）	42（40.00）
pp	34（32.38）	53（5.048）

影响因素	量化赋值
年龄	≥35岁=1，＜35岁=0
吸烟	是=1，否=0
饮酒	是=1，否=0
辐射暴露	是=1，否=0
ERα基因PvuⅡ多态性	PP或Pp=1，pp=0
发生稽留流产	是=1，否=0

影响因素	β值	SE	Wald值	P值	OR值	95%CI
年龄≥35岁	0.453	0.180	6.354	0.012	1.573	1.106~2.237
吸烟	1.349	0.576	5.484	0.019	3.853	1.246~11.915
饮酒	1.062	0.312	11.604	0.001	2.893	1.570~5.331
辐射暴露	0.628	0.184	11.587	0.001	1.873	1.305~2.688
ERα基因PvuⅡ多态性	0.363	0.136	7.070	0.007	1.437	1.100~1.877

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