EXPOSOME BIOCHEMICAL ANALYSIS FOR BIRTH WEIGHT/OBESITY

NICHD的墙内人口健康研究司处于暴露组研究的前沿，因为它的墙内名称与高风险研究的进行是一致的，许多预期怀孕队列产生了丰富的数据库，在人类发育的敏感时期纵向收集(在不同程度上)生物标本，该司拥有开发适当分析方法所需的专业知识水平的生物统计学家。这些资源使该司的调查员有机会在曝光组范例内设计研究举措。 也许最早和最关键的敏感窗口之一发生在人类生殖和发育期间。目前，该司正在进行一项概念验证研究，以利用现有的妊娠队列研究确定和量化妊娠暴露的特征和数量，结果正常。这项研究的目的是在我们以前的工作的基础上，通过将同样的方法扩展到婴儿出生时出生体重极端的“正常”孕妇，将同样的方法扩展到“正常”孕妇身上，将出生体重定义为出生体重第10百分位数的小于胎龄(SGA)和定义为出生体重第90百分位数(Brenner，1976)的后代排除在先前的分析之外。[20]低出生体重和高出生体重都与短期发病率和死亡率的增加有关，也一再与晚年患慢性疾病的风险增加有关，如心血管疾病和2型糖尿病。[21]对出生体重相关暴露的全面调查可能会提高我们对慢性病的了解或早期生命决定因素，并有助于制定终生慢性病的早期预防策略。也有证据表明，暴露于母亲肥胖的长期影响会增加肥胖风险和心脏代谢风险。[22]另外值得注意的是，我们努力确保这两个群体的抽样框架具有可比性，因为所有符合条件的妇女都在怀孕13周和每三个月期间收集了初次生物检验剂。由于妊娠会在受孕和植入后引起许多生理变化，因此限制在妊娠早期采集生物样品是评估妊娠期间纵向变化的关键。因此，随机选择两组只在婴儿出生体重方面存在差异的正常孕妇，将使我们能够对这两个样本中的每一个孕妇在怀孕期间的暴露进行表征和量化。这一战略是我们在2013财年向该司提交的初步工作的一部分，但后来仅限于前一组，因为对用于研究目的的生物标本的完整性感到担忧。我们现在证明了样本的完整性是存在的，并且变化是可以量化的。我们的第二个目标是对第三组肥胖的“正常”孕妇进行抽样，鉴于当代产科人群中肥胖率的上升，她们是最相关的。

The Division of Intramural Population Health Research, NICHD, is uniquely positioned to be on the forefront of exposome research, in that its intramural designation is consistent with the conduct of high risk research, many prospective pregnancy cohorts that have generated rich databases with longitudinally collected (in varying degrees) biospecimens during sensitive windows of human development are available, and the Division has biostatisticians with the level of expertise needed to develop appropriate analytical methods. These resources afford Division investigators an opportunity to design research initiatives within the exposome paradigm. Perhaps one of the earliest and most critical sensitive windows occurs during human reproduction and development. Currently the Division has a proof-of-concept study underway to characterize and quantify the pregnancy exposome using an existing pregnancy cohort study with normal outcomes. The goal of the present study is to build upon our previous work that focuses on the characterization of the normal pregnancy exposome by extending the same methodology to 'normal' pregnant women whose infants were born at the extremes of birth weight, as women with offspring small for gestational age (SGA) defined as birth weight < 10th percentile and large for gestational age (LGA) defined as birth weight > 90th percentile (Brenner, 1976) were excluded from the prior analysis. [20] Both low and high birth weight are associated with increased short term morbidity and mortality,and also have been repeatedly related to Increased risk of chronic diseases in later life, such as cardiovascular disease and type 2 diabetes. [21] Comprehensive Investigation of the exposome related to birth weight would potentially improve our understanding or early life determinants of the chronic diseases and help develop early preventive strategies of life long chronic diseases. Evidence has also linked the long-term impact of exposure to maternal obesity to increase risk of obesity and cardiometabolic risk. [22] Of added note is our effort to ensure comparable sampling frameworks for both groups in that all eligible women have their Initial biospecimens collected <13 weeks gestation and during each trimester. Restricting to women with a first trimester biospecimen collection is critical for assessing longitudinal changes during pregnancy, as pregnancy induces many physiologic changes following conception and implantation. Thus, having two randomly selected groups of 'normal’ pregnant women who differ only in terms of infants' birth weight will allow us to characterize and quantify the exposome during pregnancy for each of these two samples of pregnant women. This strategy was a part of our initial work presented to the Division for FY13, but later restricted to only the former group in light of concerns about the integrity of the biospecimens for research purposes. We now demonstrate that the sample integrity is there, and variation can be quantified. Our second objective is to sample a third group of 'normal' pregnant women who are obese and who are most relevant given the increasing prevalence of obesity in contemporary obstetric populations.