基于胎盘基因表达谱研究孕期烟草暴露对孕妇和胎儿的影响

刘玄石; 郝婵娟; 徐立新; 李巍

doi:10.16766/j.cnki.issn.1674-4152.002593

基于胎盘基因表达谱研究孕期烟草暴露对孕妇和胎儿的影响

doi: 10.16766/j.cnki.issn.1674-4152.002593

1.
国家儿童医学中心，首都医科大学附属北京儿童医院遗传与出生缺陷防治中心，北京市儿科研究所，出生缺陷遗传学研究北京市重点实验室，儿科重大疾病研究教育部重点实验室，北京 100045
2.
首都医科大学宣武医院神经外科，北京 100054

基金项目:

国家重点研发计划项目 2016YFC1000306

北京市自然科学基金项目 5222007

详细信息

通讯作者:
李巍, E-mail: liwei@bch.com.cn

中图分类号: R446.7 R714.5 R714.14
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出版历程
- 收稿日期: 2021-12-15

Effects of tobacco exposure during pregnancy on pregnant women and foetuses based on placental gene expression profiling

1.
Beijing Key Laboratory for Genetics of Birth Defects, Beijing Paediatric Research Institute; MOE Key Laboratory of Major Diseases in Children; Genetics and Birth Defects Control Centre, Beijing Children' s Hospital, Capital Medical University, National Centre for Children' s Health, Beijing 100045, China

摘要

摘要: 目的扩展孕期烟草暴露对孕妇和胎儿造成影响的分子机制的认识。方法首先系统检索NCBI GEO和EBI ArrayExpress数据库，挑选符合条件的吸烟和不吸烟2组孕妇胎盘组织的基因表达谱数据集。然后整合并校正了数据集间的差异，采用差异表达、功能注释、富集分析、回归分析等多种生物信息方法和模型研究烟草暴露对孕妇和胎儿的影响。结果通过合并后的表达谱数据找到476条差异表达的基因(FDR < 0.5, |log₂FC|>0.3)，其中上调的基因317条，下调的基因159条。随后通过KEGG、GO以及Reactome、MSigDb对显著差异表达的基因进行功能注释和富集分析，发现这些基因主要出现在细胞外结构组织(P=1.10×10^-28)、细胞外基质组织(P=3.44×10^-25)以及间充质发育(P=2.60×10^-13)等通路上。进一步针对烟草暴露标志物研究，采用回归分析发现CDCA7L基因在校正了母亲年龄等混杂因素后，与母亲血清中的可的宁含量最相关(FDR=0.046)。结论通过系统研究，探讨了孕妇和胎儿在烟草暴露环境中可能受到影响的通路，烟草暴露影响胎盘功能和胎儿生长的机制，对后续深入的分子机制研究提出思路。
- 孕期 /
- 表达谱 /
- 烟草暴露 /
- 胎盘 /
- 差异表达 /
- 富集分析 /
- 回归分析
Abstract: Objective To expand the understanding of the molecular mechanisms underlying tobacco exposure during pregnancy on pregnant women and their foetuses. Methods Firstly, the NCBI GEO database and EBI ArrayExpress database were systematically searched, and two gene expression profile datasets from placental tissues of smoking and non-smoking pregnant women were selected. After integrating and correcting these datasets, various bioinformatics methods and models including differential expression, functional annotation, enrichment analysis and regression analysis were applied to study the effects of tobacco exposure on pregnant women and foetuses. Results Amongst 476 significantly differentially expressed genes (FDR < 0.5, |log₂FC|>0.3), 317 were up-regulated and 159 were down-regulated. After functional annotations and enrichment analyses using KEGG, GO, Reactome and MSigDb, these genes mainly appeared in extracellular structure (P=1.10×10^-28), extracellular matrix (P=3.44×10^-25) and mesenchymal development (P=2.60×10^-13). Regression analysis was conducted to study molecular markers of tobacco exposure. CDCA7L was the most significant gene correlated with cotinine level after adjusting for confounding factors (FDR=0.046). Conclusion The pathways and the possible molecular mechanisms that pregnant women and foetuses may be affected by tobacco exposure are explored and discussed, and the ideas for future molecular mechanism research are proposed.
- Pregnancy /
- Gene expression profiles /
- Tobacco exposure /
- Placenta /
- Differential expression /
- Enrichment analysis /
- Regression analysis
利益冲突 无

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图 1 研究设计的工作流程

注：从NCBI GEO数据库中筛选出GSE18044和GSE27272两项包含胎盘表达谱的研究，分别进行差异表达分析、功能注释、富集和回归分析。

Figure 1. Study the design workflow

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图 2 校正前后数据分布特点

注：主成分分析反映Combat校正前后数据的分布情况。形状代表数据集，颜色代表吸烟或者非吸烟者。

Figure 2. Data distribution characteristics before and after correction

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图 3 差异表达基因火山图

注：蓝色点表示了显著差异的基因，显著阈值为|log₂FC|>0.3和FDR=0.5。

Figure 3. Volcano map of differentially expressed genes

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表 1 数据集表型的分布情况[M(P₂₅, P₇₅)]

Table 1. The distribution of phenotypes in the dataset [M(P₂₅, P₇₅)]

数据集	例数	样本类型	年龄(岁)	BMI	胎盘体积(cm³)	孕周(周)
GSE18044	76	胎盘	33.0(28.5, 35.0)	23.0(20.4, 25.4)	1 023(765, 1 335)	39.0(38.5, 40.0)
GSE27272	54	胎盘, 外周血, 脐带血	31.0(28.0, 33.0)	22.5(21.0, 25.0)	520(465, 600)	40.0(39.0, 40.0)

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表 2 前5位显著差异表达基因

Table 2. The top five significantly differentially expressed genes

方式	基因符号	倍数变化	FDR
上调	CYP1A1	1.039	0.007
	CYP1B1	1.034	0.007
	TBC1D16	0.486	0.008
	CYP1A2	0.522	0.015
	ANGPTL6	0.386	0.042
下调	C1orf71	-0.395	0.049
	LITAF	-0.332	0.049
	TNFAIP8L1	-0.487	0.066
	CCDC69	-0.411	0.079
	C14orf37	-0.881	0.086

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表 3 显著差异的基因富集结果

Table 3. Significantly different gene enrichment results

方式	通路	数据库来源	P值
显著差异的上调基因所富集的通路	extracellular structure organization	GO_BP	1.10×10^-28
	extracellular matrix organization	GO_BP	3.44×10^-25
	mesenchyme development	GO_BP	2.60×10^-13
	extracellular matrix structural constituent	GO_MF	3.31×10^-27
	extracellular matrix structural constituent conferring tensile strength	GO_MF	5.11×10^-12
	growth factor binding	GO_MF	3.14×10^-10
	collagen-containing extracellular matrix	GO_CC	1.19×10^-35
	extracellular matrix	GO_CC	1.38×10^-29
	collagen trimer	GO_CC	4.88×10^-19
	Extracellular matrix organization	REACTOME	4.52×10^-17
	ECM proteoglycans	REACTOME	3.20×10^-13
	Collagen chain trimerization	REACTOME	2.46×10^-10
	LIM_MAMMARY_STEM_CELL_UP	MsigDB_C2CGP	2.60×10^-32
	SCHUETZ_BREAST_CANCER_DUCTAL_INVASIVE_UP	MsigDB_C2CGP	1.32×10^-30
	LINDGREN_BLADDER_CANCER_CLUSTER_2B	MsigDB_C2CGP	1.46×10^-29
	Steroid hormone biosynthesis	KEGG	3.59×10^-4
	PI3K-Akt signaling pathway	KEGG	4.22×10^-4
	cGMP-PKG signaling pathway	KEGG	1.10×10^-3
显著差异的下调基因所富集的通路	Cell surface interactions at the vascular wall	REACTOME	1.04×10^-5
	Dectin-2 family	REACTOME	5.18×10^-5
	Defective GALNT3 causes familial hyperphosphatemic tumoral calcinosis (HFTC)	REACTOME	2.84×10^-4
	HAHTOLA_CTCL_PATHOGENESIS	MsigDB_C2CGP	2.67×10^-6
	SENESE_HDAC1_TARGETS_UP	MsigDB_C2CGP	3.56×10^-5
	MCLACHLAN_DENTAL_CARIES_UP	MsigDB_C2CGP	3.62×10^-5

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