A large scale investigation of the vaginal metagenome and metabolome and their role in spontaneous preterm birth

摘要：家长奖 自然早产(SPTB)是新生儿发病率和死亡率的主要原因。尽管广泛 研究和医学努力，我们既缺乏及早发现它的手段，也缺乏预防它的治疗选择 一旦辨认出来。阴道微生物群被认为在相当一部分sPTB中起到了因果作用，并且 多项研究表明，即使在怀孕早期测量，微生物组也与 不良妊娠结局。尽管有这个巨大的希望，基于微生物组的强大的sPTB预测指标已经 还没有被开发出来，我们对它参与的机制缺乏详细的了解 SPTB。我们将其归因于当前研究中的样本量较小；将sPTB定义为二进制 变量，忽略其异质性表现和病因；关注微生物分类学，而不是 更具功能性和机械性的数据。我们计划利用世界上最大和最大的 到目前为止收集的最好的表型妊娠队列，nuMoM2B研究。这是一次全国性、多中心的试验。 他们在三个时间点收集了不同地理和人口统计的女性的阴道拭子 背景。这项研究调查了近500名患有肺结核的女性，几乎比任何一位女性都多一个数量级 以前的微生物组研究。我们已经组建了一支跨学科的团队，对 NuMoM2B研究，在编制、剖析和分析大规模微生物组和 代谢组队列，以及在微生物组分析及其临床应用方面的创新记录。我们 将执行深度元基因组测序、纵向样本测序和匹配的代谢组 对来自近1500名孕妇的近6000份样本进行了分析，产生了最大规模的此类 到目前为止的数据集。这一数据集将推进微生物群落，推动野外发现，并使 美国和其他研究人员在一般和具体的背景下研究宿主-微生物组相互作用 SPTB，具有前所未有的深度。我们建议的数据分析提供了一个细致入微的高分辨率视图 包括临床和生物学数据。我们将研究sPTB，同时说明其各种临床表现， 病因和重要的母体协变量。我们将从多个角度研究阴道生态系统， 研究微生物基因组的适应性、生态系统中代谢物的水平以及 微生物群组的特征。我们将设计一个聚合计算框架，基于最先进的 方法和算法，提供基于微生物组相关特征的sPTB的早期预测。我们会 使用参数和非参数方法的组合来获得对宿主的机械性洞察- 可能导致肺结核和其他不良妊娠结局的微生物组相互作用。总而言之， 这项研究将改变我们对不良妊娠结局中阴道微生物群的理解。 以及宿主-微生物群相互作用的影响。

ABSTRACT : PARENT AWARD Spontaneous preterm birth (sPTB) is a leading cause of neonatal morbidity and mortality. Despite extensive research and medical efforts, we lack both the means to identify it early and the therapeutic options to prevent it when identified. The vaginal microbiome is believed to have a causal role in a substantial fraction of sPTBs, and multiple studies have shown that even when measured early in pregnancy, the microbiome is associated with adverse pregnancy outcomes. Despite this great promise, robust microbiome-based predictors for sPTB have not been developed yet, and we lack a detailed understanding of the mechanisms underlying its involvement in sPTB. We attribute this to a small sample size in current studies; the aggregative definition of sPTB as a binary variable, ignoring its heterogeneous presentations and etiologies; and a focus on microbial taxonomy instead of data that is more functionally and mechanistically oriented. We propose to capitalize on one of the largest and best-phenotyped pregnancy cohorts collected to date, the nuMoM2b study. This was a national, multi-center trial that collected vaginal swabs at three time-points from women with diverse geographic and demographic backgrounds. This study profiled nearly 500 women with sPTB, almost an order of magnitude more than any previous microbiome study. We have compiled an interdisciplinary team with intimate knowledge of the nuMoM2b study, ample experience in compiling, profiling, and analyzing large-scale microbiome and metabolomic cohorts, and a track record of innovation in microbiome analysis and its clinical applications. We will perform deep metagenomic sequencing, longitudinal sample sequencing, and matched metabolomic analysis of a total of almost 6,000 samples from nearly 1,500 pregnant women, generating the largest such dataset to date. This dataset would advance the microbiome community, drive discovery in the field, and enable us and other researchers to study host-microbiome interactions, in general and specifically in the context of sPTB, with an unprecedented depth. Our proposed data analysis offers a nuanced and high-resolution view of both clinical and biological data. We will study sPTB while accounting for its various clinical presentations, etiologies, and important maternal covariates. We will study the vaginal ecosystem from multiple angles, investigating microbial genomic adaptations, levels of metabolites in the ecosystem, and dynamic changes to the microbiome profile. We will devise an aggregative computational framework, based on state-of-the-art methods and algorithms, that provides early prediction of sPTB based on microbiome-related features. We will employ a combination of parametric and non-parametric methods to obtain mechanistic insights into host- microbiome interactions that potentially contribute to sPTB and other adverse pregnancy outcomes. Altogether, this study will be transformative to our understanding of the vaginal microbiome in adverse pregnancy outcomes and of host-microbiome interactions in general.