A PROTEOMICS COMPUTATIONAL APPROACH TO PRETERM DELIVERY

描述（由申请人提供）：早产是一个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，并不是所有的早产儿都有不好的结局。正确和早期识别有早产和新生儿预后不良风险的妊娠对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通过蛋白质组学工具和用于实验后数据分析的新型数学算法可靠地识别出来。我们的目标是确定预测妊娠并发症的蛋白质组学特征，如早产或早产早破膜（pPROM），以及pPROM是否发生羊膜内炎症。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，将在未来五年内实现三个具体目标：(1)确定可靠的蛋白质组学生物标志物，用于早期诊断PTL或pPROM引起的PTD；(2)鉴定能够可靠诊断pPROM的宫颈阴道生物标志物；(3)鉴定pPROM患者宫颈阴道分泌物中预测羊膜内炎症的蛋白质组学特征。对早产患者的预先识别和分类可以勾勒出患者亚组，在这些患者中可以进行各种干预措施的试验，而不会影响对安慰剂有反应的患者的试验。此外，未来多种生物标志物的鉴定提供了新的方向，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.