Institute for Systems Biology, Seattle, Washington, USA.
Division of Human Genetics, Center for Prevention of Preterm Birth, Cincinnati Children's, Hospital Medical Center, Cincinnati, Ohio, USA.
Biol Reprod. 2018 Jan 1;98(1):89-101. doi: 10.1093/biolre/iox163.
Preterm birth affects 1 out of every 10 infants in the United States, resulting in substantial neonatal morbidity and mortality. Currently, there are few predictive markers and few treatment options to prevent preterm birth. A healthy, functioning placenta is essential to positive pregnancy outcomes. Previous studies have suggested that placental pathology may play a role in preterm birth etiology. Therefore, we tested the hypothesis that preterm placentae may exhibit unique transcriptomic signatures compared to term samples reflective of their abnormal biology leading to this adverse outcome. We aggregated publicly available placental villous microarray data to generate a preterm and term sample dataset (n = 133, 55 preterm placentae and 78 normal term placentae). We identified differentially expressed genes using the linear regression for microarray (LIMMA) package and identified perturbations in known biological networks using Differential Rank Conservation (DIRAC). We identified 129 significantly differentially expressed genes between term and preterm placenta with 96 genes upregulated and 33 genes downregulated (P-value <0.05). Significant changes in gene expression in molecular networks related to Tumor Protein 53 and phosphatidylinositol signaling were identified using DIRAC. We have aggregated a uniformly normalized transcriptomic dataset and have identified novel and established genes and pathways associated with developmental regulation of the placenta and potential preterm birth pathology. These analyses provide a community resource to integrate with other high-dimensional datasets for additional insights in normal placental development and its disruption.
早产影响了美国每 10 个婴儿中的 1 个,导致新生儿发病率和死亡率显著增加。目前,预测早产的标志物和治疗方法很少。健康、功能正常的胎盘对良好的妊娠结局至关重要。先前的研究表明,胎盘病理可能在早产病因学中起作用。因此,我们假设早产胎盘与足月样本相比可能具有独特的转录组特征,反映了导致这种不良后果的异常生物学。我们汇总了公开的胎盘绒毛微阵列数据,生成了早产和足月样本数据集(n=133,55 例早产胎盘和 78 例正常足月胎盘)。我们使用微阵列线性回归(LIMMA)包识别差异表达基因,并使用差异秩守恒(DIRAC)识别已知生物学网络中的扰动。我们在足月和早产胎盘中鉴定出 129 个差异表达基因,其中 96 个基因上调,33 个基因下调(P 值<0.05)。使用 DIRAC 鉴定了与肿瘤蛋白 53 和磷脂酰肌醇信号相关的分子网络中基因表达的显著变化。我们已经汇总了一个统一标准化的转录组数据集,并鉴定了与胎盘发育和潜在早产病理相关的新的和已建立的基因和途径。这些分析为整合其他高维数据集以获得正常胎盘发育及其破坏的更多见解提供了一个社区资源。