Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrence

整合多组学数据：建模生物标志物和机制以减少细菌性阴道病复发

• 批准号: 10625316
• 负责人: Johanna B. Holm
• 金额: $ 9.29万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10625316
• 关键词: Affect; African; Age; American; Anaerobic Bacteria; Antibiotic Therapy; Archives; Atopobium vaginae; Award; Bacteria; Bacterial Vaginosis; Basic Science; Behavioral; Big Data; Bioinformatics; Biological Markers; Biometry; Case/Control Studies; Categories; Clinical; Clinical Research; Communities; Complement; Data; Diagnosis; Ecology; Epidemiologic Methods; Epidemiology; Ethnic Origin; Evaluation; Funding; Future; Genes; Goals; Grant; HIV; Health; Hygiene; Immune Targeting; Immune response; Immunologic Markers; Infection; Infertility; Inflammatory; Intervention; Irrigation; K-Series Research Career Programs; Lactobacillus; Learning; Life Style; Longitudinal Studies; Maryland; Mentors; Metagenomics; Methods; Mission; Modeling; Molecular; Multiomic Data; Outcome; Participant; Pelvic Inflammatory Disease; Predisposition; Premature Birth; Prognostic Factor; Quality of life; Race; Recommendation; Recurrence; Reporting; Reproductive Health; Research; Research Design; Research Personnel; Research Support; Resources; Risk; Sampling; Scientist; Sex Behavior; Sexually Transmitted Diseases; Source; Statistical Models; Symptoms; Training; Translating; United States National Institutes of Health; Universities; Vagina; Visit; Woman; Women' s Health; Work; aged; candidate identification; candidate marker; career development; certificate program; cervicovaginal; clinical diagnosis; clinical translation; complex data; data integration; data modeling; data reduction; epidemiology study; genome sciences; improved; insight; intraamniotic infection; machine learning method; medical schools; metabolome; metabolomics; metagenome; microbial; microbiome; model development; multiple omics; novel; personalized medicine; prognostic indicator; programs; reproductive; research study; screening; supervised learning; targeted treatment; therapeutic target; tool; vaginal microbiome; vaginal microbiota

Bacterial vaginosis (BV) is characterized by a vaginal microbiota with a low abundance of Lactobacillus spp. and higher abundances of anaerobic bacteria and affects nearly 30% of reproductive-age North American women and closer to 50% of sub-Saharan African women. BV is diagnosed by clinical observation of Amsel’s criteria (Amsel-BV), but treatment is only recommended when symptoms are reported, leaving a significant proportion of women untreated. Even with treatment, BV recurrence rates range from 50-70% within 6 months, increasing a woman’s risk of negative sequelae. Regardless of symptoms, BV is associated with serious adverse health outcomes, including preterm birth and HIV, and can seriously impact a woman’s quality of life. Ideal BV treatment would eliminate recurrence. The vaginal microbiome and microenvironment together provide a detailed evaluation of BV states, and hold key functional insights to predict and understand Amsel-BV recurrence. The goal of this proposal is to integrate and operationalize microbiome (metagenomes) and microenvironment (metabolomes and immune markers) data to develop a prognostic indicator of recurrent BV, and identify candidate biomarkers and causal mechanisms which reduce recurrence. Recent work by the PI functionally categorized the vaginal microbiome for use in large clinical research studies (vaginal metagenomic community state types, mgCSTs). The broad hypothesis in this proposal is that not all microbiomes associated with bacterial vaginosis have the same potential for recurrence. Preliminary data suggest that BV recurrence is more frequently observed in only two of the nine mgCSTs containing BV-associated bacteria. This study proposes to utilize archived cervicovaginal samples from the NIH 1999 Longitudinal Study of Vaginal Flora in which participants were followed quarterly for one year. Multi-omic analyses of baseline samples will be assessed to identify microbial (metagenomic and metabolomic) and host (metabolomic and targeted immune markers) signatures of susceptibility to recurrent BV. Specific aims of this proposal are to: (1) conduct an epidemiological analysis to evaluate the demographic and lifestyle correlates of mgCSTs, and (2) employ supervised machine learning and causal inference modeling to identify prognostic factors and drivers of the vaginal microbiome and microenvironment which lead to recurrent BV. Cases are defined as women with Amsel-BV at baseline, then clearance 3 months later, followed by recurrence at six months. Controls are women with Amsel-BV that do not experience recurrence within 9 months. This grant will support the PI’s training in epidemiology and biostatistics with the completion of a Certificate Program in Clinical Research. The PI’s long- term goal is to create an independent research program translating the basic science of the vaginal microbiome to improve women’s reproductive health outcomes. The Institute for Genome Sciences and the University of Maryland School of Medicine uniquely provide the resources and support required for successful completion of this proposal and the PI’s transition to an independent investigator.

细菌性阴道病 (BV) 的特点是阴道微生物群中乳杆菌属和低丰度。 厌氧菌丰度较高，影响近 30% 的北美育龄女性 近 50% 的撒哈拉以南非洲女性 BV 是通过阿姆泽尔氏病的临床观察诊断出来的。 标准（Amsel-BV），但仅在报告症状时才建议治疗，留下显着的 即使接受治疗，6 个月内 BV 复发率仍为 50-70%。 无论症状如何，细菌性阴道炎都会增加女性出现负面后遗症的风险。 健康结果，包括早产和艾滋病毒，并会严重影响女性的生活质量。 治疗可以消除复发。 对 BV 状态进行详细评估，并掌握预测和理解 Amsel-BV 的关键功能见解 该提案的目标是整合和实施微生物组（宏基因组）和 微环境（代谢组和免疫标记）数据，用于制定复发性 BV 的预后指标， 并确定减少复发的候选生物标志物和因果机制。 对阴道微生物组进行功能分类，用于大型临床研究（阴道宏基因组 该提案的广泛假设是并非所有微生物组都如此。 与细菌性阴道病相关的疾病具有相同的复发可能性。 在含有 BV 相关细菌的 9 个 mgCST 中，只有 2 个更常观察到 BV 复发。 本研究建议利用 NIH 1999 年阴道纵向研究中存档的宫颈阴道样本 对参与者进行为期一年的多组学分析。 评估以确定微生物（宏基因组和代谢组）和宿主（代谢组和靶向免疫组） 该提案的具体目标是：(1) 进行一次 BV 易感性标记。 流行病学分析以评估 mgCST 的人口统计和生活方式相关性，以及 (2) 采用 监督机器学习和因果推理模型来识别预后因素和驱动因素 导致 BV 复发的阴道微生物组和微环境的病例被定义为女性。 基线时使用 Amsel-BV，然后在 3 个月后清除，然后在 6 个月时复发。 患有 Amsel-BV 且在 9 个月内未复发的女性 这笔赠款将用于支持 PI 的培训。 完成了 PI 的长期临床研究证书课程，获得流行病学和生物统计学博士学位。 学期目标是创建一个独立的研究项目，转化阴道微生物组的基础科学 改善妇女的生殖健康结果。基因组科学研究所和大学。 马里兰医学院独特地提供成功完成所需的资源和支持 这项提案以及 PI 向独立调查员的转变。