基于多重RNA-seq研究的胎儿生长受限生物标志物筛选。

IF 1.5 Q3 OBSTETRICS & GYNECOLOGY European Journal of Obstetrics and Gynecology and Reproductive Biology: X Pub Date : 2023-10-31 DOI:10.1016/j.eurox.2023.100259

Xiaohui Li , Xin He , Zhengpeng Li , Yi Chen

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引用次数: 0

摘要

目的:胎儿生长受限(FGR)是一种与胎儿发育受损相关的严重病理并发症。FGR的早期诊断和预测仍不清楚。测序技术为鉴定新的生物标志物提供了巨大的机会。然而，个体研究的局限性(例如，失调基因的长列表，小样本量和相互矛盾的结果)阻碍了选择最匹配的基因。研究设计:进行多步骤生物信息学分析。我们分别重新分析了来自四项公开RNA-seq研究的数据，然后对单个结果进行了综合分析。基于DESeq2鉴定差异表达基因(DEGs)。然后通过功能富集分析和蛋白相互作用网络(PPI)筛选枢纽基因。利用外部微阵列数据进一步验证了结果。结果:与对照组相比，FGR中共鉴定出65个失调基因(50个下调，15个上调)。功能富集和PPI分析揭示了10个与FGR密切相关的枢纽基因。验证分析发现了FGR的四个下调候选生物标志物(CEACAM6, SCUBE2, DEFA4和MPO)。结论:使用组学工具探索妊娠障碍的机制有助于改善产科临床实践。

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Biomarker screening in fetal growth restriction based on multiple RNA-seq studies

Objective

Fetal growth restriction (FGR) is a severe pathological complication associated with compromised fetal development. The early diagnosis and prediction for FGR are still unclear. Sequencing technologies present a huge opportunity to identify novel biomarkers. However, limitation of individual studies (e.g., long lists of dysregulated genes, small sample size and conflicting results) hinders the selection of the best-matched ones.

Study design

A multi-step bioinformatics analysis was performed. We separately reanalyzed data from four public RNA-seq studies, followed by a combined analysis of individual results. The differentially expressed genes (DEGs) were identified based on DESeq2. Then, function enrichment analyses and protein-protein interaction network (PPI) were conducted to screen for hub genes. The results were further verified by using external microarray data.

Results

A total of 65 dysregulated genes (50 down and 15 upregulated) were identified in FGR compared to controls. Function enrichment and PPI analysis revealed ten hub genes closely related to FGR. Validation analysis found four downregulated candidate biomarkers (CEACAM6, SCUBE2, DEFA4, and MPO) for FGR.