An Integrative Omics Approach to Identify Biomarkers Related to Preeclampsia and Breast Cancer Risks

项目总结 先兆子痫是以孕妇高血压和蛋白尿为特征的医学状况。它 发生在所有怀孕的5%到8%(与乳腺癌一样常见)，是发病率和 母亲和未出生的孩子的死亡率。令人惊讶的是，流行病学研究表明， 有证据表明，与子痫前期妊娠相关的女性乳房发病率降低了近50% 几十年后的癌症。然而，由于伦理和现实的原因，来自长期跟踪的直接证据 在人类人口中是缺乏的。此外，解释其持久影响的潜在机制 先兆子痫仍不清楚。在这里，我们提出了一种替代的和综合的组学方法来研究 先兆子痫和乳腺癌之间的分子联系在以后的生活中有风险。我们将进行嵌套案件 研究胎盘表观基因组、RNA-Seq转录组和蛋白质组学差异的对照研究 以及与先兆子痫有关的孕妇血液DNA样本。未确认的样本将是 通过夏威夷生物库(HiBR)收集，它们反映了夏威夷独特的多民族人口 夏威夷。我们将建设生物信息学管道，分别分析所有三种类型的组学数据，以及 为组学数据集成开发新的计算方法。我们将确定连贯的基因、模块和 生物途径作为子痫前期的生物标志物。此外，我们将把我们的数据与DNA进行比较 乳腺癌标本的甲基组、RNA-Seq转录组和蛋白质组学数据 基因组图谱。通过这样的比较，我们将揭示与癌症相关的基因、模块和生物学 先兆子痫样本中的路径。这将提供直接的分子水平的证据来联系 先兆子痫和乳腺癌的风险在以后的生活中是不可能的，使用 人口跟踪调查。它还将在孩子出生时就确定乳腺癌易感性的生物标记物， 预防癌症的目的。

PROJECT SUMMARY Preeclampsia is the medical condition characterized by hypertension and proteinuria in pregnant women. It occurs in 5 to 8% of all pregnancies (as common as breast cancer) and is the leading cause of morbidity and mortality for both the mother and the unborn child. Surprisingly, epidemiological studies have shown strong evidence that women associated with preeclamptic pregnancies have almost 50% reduced rate of breast cancers decades later. However, due to ethical and practical reasons, direct evidence from long-term follow up in human population is lacking. Moreover, the underlying mechanism to explain the lasting effect of preeclampsia remains unknown. Here we propose an alternative and integrative omics approach to investigate the molecular links between preeclampsia and breast cancer risks later in life. We will conduct a nested case control study to investigate the epigenome, RNA-Seq transcriptome and proteomics differences in the placenta and matched maternal blood DNA samples associated with preeclampsia. The de-identified samples will be collected through the Hawaii Biorepository (HiBR), and they reflect the unique multi-ethnic population of Hawaii. We will construct bioinformatics pipelines to analyze all three types of omics data individually, and develop new computational methods for omics data integration. We will identify coherent genes, modules and biological pathways as the biomarkers of preeclampsia. Moreover, we will compare our data with the DNA methylome, RNA-Seq transcriptome, and proteomics data of the breast cancer samples from The Cancer Genome Atlas. Through such comparison, we will uncover the cancer-related genes, modules and biological pathways within the preeclampsia samples. This will provide direct molecular-level evidence to link preeclampsia and breast cancer risks later in life, which is practically impossible using the approach of population follow-up. It will also identify biomarkers of breast cancer susceptibility as early as a child's birth, for the purpose of cancer prevention.