A PROTEOMICS COMPUTATIONAL APPROACH TO PRETERM DELIVERY

描述（由申请人提供）：早产是一种多因素和异质性的临床实体，占全球450万早产儿的出生。早产占所有婴儿死亡率的75%，占长期神经障碍的50%，包括失明，耳聋，发育迟缓，脑瘫和慢性肺病。然而，并非所有早产儿的结局都不好。正确和早期识别有早产风险的妊娠和不良新生儿结局对于开发有教育意义的治疗至关重要。我们假设，注定要早产的妇女在临床表现前几周或几个月表达宫颈阴道生物标志物，这些生物标志物可以使用蛋白质组学工具结合新的数学算法进行可靠的鉴定，用于实验后数据分析。我们的目标是确定蛋白质组学特征，预测妊娠并发症，如早产或早产胎膜早破（pPROM），如果pPROM发生羊膜内炎症。这种方法可能在未来指导临床实践，以防止早产，从而不良妊娠结局。为了实现这些目标，将在五年内追求三个具体目标：（1）确定可靠的蛋白质组生物标志物，用于早期诊断由于PTL或pPROM引起的即将发生的PTD;（2）确定宫颈阴道生物标志物，以可靠地诊断pPROM;（3）确定pPROM妇女宫颈阴道分泌物中的蛋白质组谱，预测羊膜内炎症。提前识别和分类注定早产的患者可以概述可能进行各种干预试验的患者亚组，而不会污染对安慰剂有反应的患者的试验。此外，未来鉴定多种生物标志物提供的新方向可能导致病理学特异性治疗。

DESCRIPTION (provided by applicant): Preterm birth is a multifactorial and heterogeneous clinical entity that accounts for the birth of 4.5 million premature infants worldwide. Prematurity accounts for 75% of all infant mortality and 50% of long-term neurological handicaps, including blindness, deafness, developmental delay, cerebral palsy, and chronic lung disease. However, not all premature infants have a poor outcome. Correct and early identification of the pregnancy at risk for preterm delivery and poor neonatal outcome is critical for development of educated therapies. We hypothesize that women who are destined to deliver preterm express cervicovaginal biomarkers several weeks or months prior to their clinical presentation that can be reliably identified using proteomics tools coupled with novel mathematical algorithms for post-experimental data analysis. Our goals are to identify proteomic profiles that are predictive for pregnancy complications such as preterm labor or preterm premature rupture of the membranes (pPROM) and should pPROM occur of intra-amniotic inflammation. This approach may in the future guide clinical practice in preventing prematurity and hence adverse pregnancy outcome. To accomplish these objectives, three specific aims over five years will be pursued: (1) To identify reliable proteomic biomarkers for early diagnosis of impending PTD due to PTL or pPROM; (2) To identify cervicovaginal biomarkers that will reliably diagnose pPROM; (3) To identify a proteomic profile in the cervicovaginal secretions of women with pPROM that is predictive of intra-amniotic inflammation. The identification and classification in advance of patients destined to deliver preterm may outline subgroups of patients in whom trials of various interventions might be undertaken without the contamination of the trial with patients who will respond to placebo. Further, the new directions provided by future identification of multiple biomarkers are likely to lead to pathology specific treatments.