Dried blood spot proteomics analysis of newborn screening cards to identify prognostic markers of SIDS risk

项目总结 尽管安全睡眠运动减少了死亡人数，但婴儿猝死综合症(SID)仍然存在 美国新生儿后死亡的主要原因(每1000名活产儿中有0.33人死亡)。我们的研究 这与脑干内的生物异常密切相关，这些异常是婴儿易患小岛屿发展中国家的原因。 我们还在小岛屿发展中国家患者的血清和血小板中发现了与小岛屿发展中国家相关的异常 在验尸时。总而言之，这些数据表明，小岛屿发展中国家婴儿死亡时血液和大脑中存在分子异常。 然而，未知的是，在尸检中观察到的异常在多大程度上也存在于出生时，以及 无论是这些还是其他尚未发现的异常，都可以确定新生儿期的小岛屿发展中国家风险， 从而为干预提供了机会。尽管目前还没有已知的小岛屿发展中国家风险的生物标志物，但报告 呼吸暂停、心率异常和随后死于小岛屿发展中国家的婴儿的唤醒缺陷支持 潜在的脆弱性可能存在于婴儿中。这样的亚临床异常 当婴儿在关键的发育期受到足够的压力时，他们就会表现出来。我们的实验室 现在已经从新生儿筛查卡中获得了一个独特的干血点(DBS)数据集，这些卡来自 后来死于小岛屿发展中国家(n=109)，死于已知死因(死亡对照，n=34)，年龄和性别匹配 对照婴儿，根据新生儿代谢紊乱筛查确定为出生时健康的婴儿(健康对照 (n=60)。此外，我们在大约50%的小岛屿发展中国家和死亡病例的尸检中发现了相应的脑干组织 控制婴儿。利用这个数据集，我们假设死于SID的婴儿在出生时表现出异常蛋白质 DBS中的配置文件与对照的比较。利用液-质联用(LC/MS)，我们将测试 这一假设是通过对来自小岛屿发展中国家和对照组婴儿的DBS进行无偏见的蛋白质组学分析(特定的 目标1)。使用匹配的脑干组织，我们将使用有针对性的方法，例如Western blotting， 免疫组织化学和/或RNAScope来解决假定的血液蛋白是否 出生时的异常表现在尸检时收集的脑组织中(特定目标2)。新生儿的使用 用于小岛屿发展中国家无偏倚蛋白质组学的数据库是新颖的，从这个史无前例的样本中产生的数据 收集有可能识别在小岛屿发展中国家发病机制中起作用的未知蛋白质和/或途径。 此外，这些数据将使我们能够评估已确定的异常情况，以预测它们对小岛屿发展中国家的预测潜力 因此，它们有可能成为小岛屿发展中国家风险的新生儿生物标志物。鉴于我们的总体目标，此应用程序 与NICHD最近特别关注的通知(非HD-21-032)完全一致，重点是确定根源 减少与小岛屿发展中国家有关的死亡人数。从该R21生成的数据将提供 关于小岛屿发展中国家婴儿出生时的新的预后信息，这些信息将被用作先导数据进行扩展 在具有新假设、更大的新生儿数据集和动物模型的R01中。

PROJECT SUMMARY Despite fewer deaths as a result of the Safe Sleep campaign, the Sudden Infant Death Syndrome (SIDS) remains the leading cause of post-neonatal infant mortality in the United States (0.33/1000 live births). Our research strongly implicates biological abnormalities within the brainstem that underlie an infant's vulnerability to SIDS. We have also identified SIDS-associated abnormalities within the serum and platelets taken from SIDS victims at autopsy. Together, these data suggest molecular abnormalities in the blood and brain of SIDS infants at death. What is unknown, however, is to what extent abnormalities observed at autopsy are also present at birth, and whether these or other, yet to be discovered, abnormalities can identify SIDS risk during the neonatal period, thereby providing the opportunity for intervention. Although there are no known biomarkers for SIDS risk, reports of apnea, cardiac rate abnormalities, and arousal deficits in infants who subsequently die of SIDS support the possibility that an underlying vulnerability may exist in the infant subclinically. Such subclinical abnormalities then manifest themselves when the infant is sufficiently stressed during a critical developmental period. Our laboratory has now acquired a unique dataset of dried blood spots (DBS) from neonatal screening cards from infants who later died of SIDS (n=109), died of known causes of death (demise controls, n=34), and age- and sex-matched control infants, identified as healthy at birth based on newborn screening for metabolic disorders (healthy controls (n=60)). In addition, we have corresponding brainstem tissue from autopsy in ~50% of these SIDS and demise control infants. Utilizing this dataset, we hypothesize that infants dying of SIDS display at birth abnormal protein profiles in DBSs compared to controls. Using liquid chromatography/mass spectrometry (LC/MS), we will test this hypothesis by performing an unbiased proteomic analysis of DBSs from SIDS and control infants (Specific Aim 1). Using the matching brainstem tissue we will use targeted methodologies, such as Western blotting, immunohistochemistry, and/or RNAscope to address the question of whether putative blood protein abnormalities at birth are represented in brain tissue collected at autopsy (Specific Aim 2). The use of neonatal DBSs for unbiased proteomics in SIDS is novel and the data generated from this unprecedented sample collection has potential to identify yet unknown proteins and/or pathways that play a role in SIDS pathogenesis. Furthermore, these data will allow us to assess identified abnormalities for their predictive potential for SIDS death and therefore their potential as neonatal biomarkers of SIDS risk. Given our overall goal, this application is fully aligned with NICHD's recent notice of special interest (NOT-HD-21-032) focused on identifying the root cause of SIDS with the aim to reduce SIDS-related deaths. The data to be generated from this R21 will provide novel prognostic information about SIDS infants at birth which will then be utilized as pilot data to expand upon in an R01 with new hypotheses, larger newborn datasets, and animal models.