Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn
Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn
复制标题
DOI：
10.1016/j.jpeds.2014.10.065
复制
发表时间：
2015-02-01
影响因子：
5.1
通讯作者：
Alterovitz, Gil
中科院分区：
文献类型：
--
作者：
Maron, Jill L.;Hwang, Jooyeon S.;Alterovitz, Gil
目的 将唾液基因表达微阵列数据的数学模型和系统生物学注释与逆转录定量聚合酶链式反应扩增相结合，以识别（第一阶段）和验证（第二阶段）唾液生物标志物分析，以预测早产儿的口腔喂养准备情况。研究设计对 12 名早产儿喂养成功前后的全转录组微阵列进行比较分析，用于计算建模和系统生物学分析，以确定与口腔喂养成功（阶段）相关的潜在唾液转录本。我）。通过逆转录定量聚合酶链式反应扩增对来自成功 (n = 200) 和不成功 (n = 200) 口服喂养者的 400 份唾液样本 (II 期) 评估选定的基因表达生物标志物 (15 个来自计算模型；6 个基于证据；3 个参考)。通过控制性别和怀孕后年龄 (PCA) 的多变量分析来评估单独和组合的基因，以确定新生儿成功经口喂养的概率。结果 PCA (P < .001) 和女性 (P = .05) 的提高可积极预测婴儿经口喂养的能力。除了 PCA 和性别之外，神经肽 Y2 受体（饥饿信号）、腺苷一磷酸激活蛋白激酶（能量稳态）、丛蛋白 A1（嗅觉神经发生）、肾痨 4（视觉行为）和无翼型 MMTV 整合位点家族成员 3（面部发育）等 5 个基因的组合，在确定喂养成功方面表现出良好的准确性（接收者算子特征曲线下的面积 = 0.78).结论我们已经确定了客观且生物学相关的唾液生物标志物，可以无创地评估新生儿的大脑发育、感觉和面部发育，因为它们与口腔喂养的成功有关。通过翻译和计算方法了解口腔喂养准备发展的机制可以改善临床决策，同时降低发病率和医疗保健成本。
Objective To combine mathematical modeling of salivary gene expression microarray data and systems biology annotation with reverse-transcription quantitative polymerase chain reaction amplification to identify (phase I) and validate (phase II) salivary biomarker analysis for the prediction of oral feeding readiness in preterm infants.Study design Comparative whole-transcriptome microarray analysis from 12 preterm newborns pre- and postoral feeding success was used for computational modeling and systems biology analysis to identify potential salivary transcripts associated with oral feeding success (phase I). Selected gene expression biomarkers (15 from computational modeling; 6 evidence-based; and 3 reference) were evaluated by reverse-transcription quantitative polymerase chain reaction amplification on 400 salivary samples from successful (n = 200) and unsuccessful (n = 200) oral feeders (phase II). Genes, alone and in combination, were evaluated by a multivariate analysis controlling for sex and postconceptional age (PCA) to determine the probability that newborns achieved successful oral feeding.Results Advancing PCA (P < .001) and female sex (P = .05) positively predicted an infant's ability to feed orally. A combination of 5 genes, neuropeptide Y2 receptor (hunger signaling), adneosine-monophosphate-activated protein kinase (energy homeostasis), plexin A1 (olfactory neurogenesis), nephronophthisis 4 (visual behavior), and wingless-type MMTV integration site family, member 3 (facial development), in addition to PCA and sex, demonstrated good accuracy for determining feeding success (area under the receiver operator characteristic curve = 0.78).Conclusions We have identified objective and biologically relevant salivary biomarkers that noninvasively assess a newborn's developing brain, sensory, and facial development as they relate to oral feeding success. Understanding the mechanisms that underlie the development of oral feeding readiness through translational and computational methods may improve clinical decision making while decreasing morbidities and health care costs.