Vaginal Microbiome, Inflammatory Mediators, Metabolome, and Dysmenorrhea Symptom-based Phenotypes

阴道微生物组、炎症介质、代谢组和基于痛经症状的表型

• 批准号: 10586875
• 负责人: Xiaochen Chen
• 金额: $ 69.22万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10586875
• 关键词: 16S ribosomal RNA sequencing; Affect; Age; Anti-Inflammatory Agents; Arachidonic Acids; Bacteria; Behavior Therapy; Behavioral; Biological Markers; Biological Response Modifiers; Blood specimen; Data; Drug usage; Dysmenorrhea; Endometritis; Female; Funding; Gardnerella; Genes; Goals; Gonadal Steroid Hormones; Gynecologic; Health; Hormonal; Hormones; Hour; Hysterectomy; Immunoassay; Individual; Individual Differences; Inflammation; Inflammation Mediators; Inflammatory; Inflammatory Response; Lactobacillus; Link; Mass Spectrum Analysis; Menstruation; Metagenomics; Methods; Network-based; Pain; Participant; Pathway interactions; Persons; Pharmaceutical Preparations; Phenotype; Pilot Projects; Prevotella; Probiotics; Prostaglandins; Quality of life; Questionnaires; Reproductive Health; Research; Resources; Risk; Risk Factors; Role; Sampling; Schools; Shotguns; Swab; Symptoms; Systems Biology; Taxonomy; Testing; United States National Institutes of Health; Vagina; Volatile Fatty Acids; Woman; Work; aged; chronic painful condition; cytokine; experience; falls; girls; improved; individual variation; inflammatory marker; longitudinal, prospective study; metabolome; metabolomics; metagenomic sequencing; microbial; microbiome composition; multiple omics; opioid use; pain reduction; personalized medicine; predictive modeling; racial diversity; recruit; reproductive; reproductive tract; standard care; vaginal lactobacilli; vaginal microbiome; vaginal microbiota

PROJECT SUMMARY Dysmenorrhea is a prevalent pain condition and a risk factor for developing other chronic pain conditions. Dysmenorrhea experiences vary significantly among individual women. Some women are symptom-free, and those with symptoms fall into three dysmenorrhea symptom phenotypes: mild localized pain, severe localized pain, and multiple severe symptoms. The mechanisms underlying this individual variation remain incompletely understood, creating barriers for expanding and personalizing dysmenorrhea treatment options. Given the role of the vaginal microbiota in inflammation and female reproductive health and the proof-of-concept data linking vaginal microbiota and dysmenorrhea phenotypes, the study of vaginal microbiota and their function is a promising avenue to understand individual differences in dysmenorrhea. Our central hypothesis is that vaginal microbiota contributes to dysmenorrhea symptoms by modulating the host inflammatory response in the genital tract. The purpose of this proposed, prospective, longitudinal study is to examine relationships among vaginal microbiome, inflammatory mediators, sex hormones, metabolome, and dysmenorrhea phenotypes. Racially diverse female participants (aged 14-39) will be recruited into four groups: three dysmenorrhea phenotype groups and one symptom-free group. These individuals will provide vaginal samples off- and on-menses, blood samples, and questionnaire data. The specific aims of the study are to (1) differentiate vaginal microbial taxa, genes, and pathways associated with dysmenorrhea phenotypes using shotgun metagenomic and qPCR methods; (2) differentiate inflammatory mediators and metabolites associated with dysmenorrhea phenotypes using immunoassays of cytokines and mass spectrometry-based metabolomics; and (3) identify taxonomic drivers of functional shifts in vaginal metabolome associated with severe dysmenorrhea symptoms. Network- based systems biology and predictive modeling approaches will be used to integrate phenotypic, demographic, behavioral, metagenomic, cytokine, metabolomic, and hormonal data. This multi-omics approach will provide rich information on the function of vaginal microbiota and metabolites to uncover mechanisms underlying individual differences in dysmenorrhea. The expected impact of this research is to (1) suggest new avenues for treating dysmenorrhea through modifying the vaginal microbiota or metabolites (e.g., using drugs, probiotics, and/or behavioral interventions), (2) reveal vaginal microbiota and/or metabolites as biomarkers, and (3) generate a rich resource with large microbial metagenomic sequencing, metabolomic profiling, and detailed phenotype, hormonal, and behavioral data to study mechanisms of dysmenorrhea and menstrual health. In the long term, this work has the potential to lead to additional dysmenorrhea treatment options with the ultimate goals of reducing pain and improving women's quality of life.

项目概要 痛经是一种常见的疼痛病症，也是发生其他慢性疼痛病症的危险因素。 不同女性的痛经经历差异很大。有些女性没有任何症状，并且 有症状者可分为三种痛经症状表型：轻度局部疼痛、重度局部疼痛 疼痛和多种严重症状。这种个体差异背后的机制仍然不完全 理解，为扩大和个性化痛经治疗选择创造了障碍。鉴于角色 阴道微生物群在炎症和女性生殖健康中的作用以及概念验证数据链接 阴道微生物群和痛经表型，阴道微生物群及其功能的研究是 了解痛经个体差异的有希望的途径。我们的中心假设是阴道 微生物群通过调节宿主生殖器炎症反应而导致痛经症状 道。这项拟议的前瞻性纵向研究的目的是检查阴道之间的关系 微生物组、炎症介质、性激素、代谢组和痛经表型。种族上 不同的女性参与者（14-39岁）将被分为四组：三种痛经表型 组和一组无症状组。这些人将提供经期和经期的阴道样本、血液样本 样本和问卷数据。该研究的具体目的是（1）区分阴道微生物类群， 使用鸟枪法宏基因组和 qPCR 分析与痛经表型相关的基因和通路 方法; (2)区分与痛经表型相关的炎症介质和代谢物 使用细胞因子免疫分析和基于质谱的代谢组学； (3) 确定分类学 与严重痛经症状相关的阴道代谢组功能变化的驱动因素。网络- 基于系统生物学和预测建模方法将用于整合表型、人口统计、 行为、宏基因组、细胞因子、代谢组和激素数据。这种多组学方法将提供 有关阴道微生物群和代谢物功能的丰富信息，以揭示潜在机制 痛经的个体差异。这项研究的预期影响是（1）提出新的途径 通过改变阴道微生物群或代谢物来治疗痛经（例如使用药物、益生菌、 和/或行为干预），（2）揭示阴道微生物群和/或代谢物作为生物标志物，以及（3） 生成丰富的资源，包括大型微生物宏基因组测序、代谢组分析和详细信息 表型、激素和行为数据来研究痛经和月经健康的机制。在 从长远来看，这项工作有可能带来更多的痛经治疗选择，并最终实现 减少疼痛和提高妇女生活质量的目标。