Research Project 1 - The pregnancy ImmunOME

研究项目 1 - 妊娠 ImmunOME

• 批准号: 10611526
• 负责人: Andrea Goldberg Edlow
• 金额: $ 74.79万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-19 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10611526
• 关键词: Address; Adenoviruses; Adjuvant; Age; Antigens; Area; Atlases; Biological Assay; Body mass index; COVID-19 pandemic; COVID-19 vaccination; COVID-19 vaccine; Cell Separation; Cells; Cellular Assay; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Characteristics; Child; Chromatin; Clinical; Collaborations; Complex; Data; Data Analyses; Disease; Enrollment; Ensure; Equilibrium; Fc Receptor; Feces; Future; Goals; High-Throughput Nucleotide Sequencing; Human; Immune; Immune Tolerance; Immune response; Immune system; Immunity; Immunologics; Immunology; In Vitro; Infant; Infection; Inflammation; Influenza; Infrastructure; Innate Immune Response; Knowledge; Maps; Maternal Mortality; Maternally-Acquired Immunity; Messenger RNA; Metabolic Diseases; Metagenomics; Mothers; Peripheral Blood Mononuclear Cell; Pertussis; Pertussis Vaccine; Plasma; Population; Pregnancy; Pregnancy Trimesters; Pregnant Women; Proliferating; Proteins; Proteome; Proteomics; Recording of previous events; Research Project Grants; Resolution; Risk; SARS-CoV-2 negative; Sampling; Shapes; Shotguns; Systems Biology; Therapeutic; Time; Transposase; Vaccinated; Vaccination; Vaccine Design; Vaccines; Woman; Work; adaptive immune response; antibody transfer; booster vaccine; cell type; cohort; data integration; data management; early pregnancy; emerging pathogen; experimental study; fetal; gut microbiome; healthy pregnancy; high dimensionality; in vivo; influenza virus vaccine; insight; maternal immune system; maternal vaccination; metabolome; metabolomics; metagenomic sequencing; microbial; microbiome; multidisciplinary; neonate; next generation; novel; pandemic disease; pathogen; placental transfer; prospective; receptor expression; response; sex; single-cell RNA sequencing; therapeutic development; transcriptome; vaccine development; vaccine platform; vaccine response; vaccine strategy

Project 1: Summary The COVID-19 pandemic has revolutionized our ability to decode the rules of maternal immunity. There is a significant gap in knowledge regarding innate and adaptive immune responses over the course of pregnancy and how trimester-specific perturbations in the maternal immunological signature might manifest in attributable risk or benefit to the maternal-fetal dyad. The COVID-19 vaccines and their real-world use by pregnant women present a unique opportunity to define the baseline, trimester-specific immune signature, and to examine the maternal immune response after in vivo perturbation with both de novo (never before seen by the immune system) and recall (boosted responses such as influenza and pertussis) vaccines across the trimesters of pregnancy. In Project 1 in the Maternal ‘Omics to Maximize Immunity (MOMi) consortium, we propose to apply a multi-‘OMICs approach to deeply and comprehensively capture shifts in the maternal immune response before and after maternal immunization across pregnancy. We will profile maternal peripheral blood mononuclear cells, plasma, placental cell isolates, and stool from pre- and post-maternal vaccination, using single cell RNA-Seq (scRNA-Seq), Assay for Transposase-Accessible Chromatin with high-throughput sequencing (scATAC-Seq), Cellular Indexing of Transcriptomes and Epitopes by Sequencing (scCITE-Seq), proteomics, metabolomics, and metagenomics, and integrate all data through the Data Management and Analysis Core (DMAC). In collaboration with Project 2, the ultimate goal is to define maternal immunity longitudinally across pregnancy trimesters in the normal baseline and vaccinated state, in order to build the most comprehensive Pregnancy Immune Atlas of innate and adaptive immune profiling across the maternal-fetal dyad. We will examine how the cellular transcriptome, microbiome, metabolome, and proteome shifts over the course of pregnancy, and how they are modified in response to different vaccine platforms (mRNA, adenovirus, adjuvanted protein) and types (de novo versus recall), providing a unique opportunity to profile the maternal immune response with unprecedented resolution. This detailed map of pregnancy immunity will generate critical data to open previously unrecognized therapeutic windows in this unusual and understudied area of human immunology.

项目1：总结 新冠肺炎疫情彻底改变了我们破译母体免疫规则的能力。有一个 关于怀孕期间先天免疫反应和获得性免疫反应的知识存在显著差距 以及孕妇免疫特征中的三个月特有的扰动如何在可归因性中表现出来 对母体-胎儿二体的风险或益处。新冠肺炎疫苗及其孕妇的实际使用 提供一个独特的机会来定义基线、特定于三个月的免疫签名，并检查 体内扰动后的母体免疫反应与从头开始(以前从未见过的免疫 系统)和召回(加强反应，如流感和百日咳)疫苗 怀孕了。在母体免疫力最大化(MOMI)联盟的项目1中，我们建议 应用多组学方法深入全面地捕捉母体免疫的变化 孕期母体免疫前后的反应。我们将分析母体外周 孕妇接种前后的血液单个核细胞、血浆、胎盘细胞分离株和粪便， 利用单细胞RNA-Seq(scRNA-Seq)高通量检测转座酶可及染色质 测序(scATAC-Seq)，通过测序对转录本和表位进行细胞索引(scCITE-Seq)， 蛋白质组学、代谢组学和元基因组学，并通过数据管理和 分析核心(DMAC)。在与项目2的合作中，最终目标是界定产妇免疫 在正常基线和接种疫苗状态下纵向跨越怀孕三个月，以便建立最 孕妇-胎儿先天免疫和获得性免疫图谱的综合妊娠免疫图谱 二元组。我们将研究细胞转录组、微生物组、代谢组和蛋白质组如何在 怀孕过程，以及它们如何被修改以响应不同的疫苗平台(mRNA，腺病毒， 佐剂蛋白)和类型(从新与召回)，提供了一个独特的机会来描述母体 以前所未有的分辨率做出免疫反应。这张详细的怀孕免疫图将产生关键的 在人类这一不寻常和未被研究的领域打开以前未被识别的治疗窗口的数据 免疫学。