A PROTEOMICS COMPUTATIONAL APPROACH TO PRETERM DELIVERY

描述(申请人提供)：早产是一个多因素和不同的临床实体，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、脑瘫和慢性肺部疾病。然而，并不是所有早产儿的结局都很差。正确和早期地识别有早产风险和不良新生儿结局的妊娠对于开发有教育意义的治疗方法至关重要。我们假设，注定要早产的女性在临床表现前几周或几个月表达宫颈阴道生物标记物，可以使用蛋白质组学工具结合新的数学算法进行实验后数据分析，从而可靠地识别这些生物标记物。我们的目标是确定预测妊娠并发症的蛋白质组学特征，如早产或早产胎膜早破(PPROM)，以及PPROM是否发生羊膜内炎症。这种方法可能会在未来指导临床实践，以防止早产，因此不良妊娠结局。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记物，用于PTL或pPROM所致即将发生的PTD的早期诊断；(2)确定可靠诊断pPROM的宫颈阴道生物标记物；(3)确定pPROM患者宫颈阴道分泌物中可预测羊膜内炎症的蛋白质组图谱。提前识别和分类预定早产的患者可以勾勒出可能进行各种干预试验的患者亚群，而不会污染对安慰剂有反应的患者的试验。此外，未来识别多个生物标记物提供的新方向可能导致病理特异性治疗。

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.