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

项目总结 痛经是一种普遍的疼痛状况，也是发展为其他慢性疼痛状况的危险因素。 痛经经历在不同的女性之间有很大的不同。一些女性没有任何症状，而且 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，以及多种严重症状。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制造障碍。考虑到这个角色 阴道微生物区系在炎症和女性生殖健康中的作用与概念验证数据的联系 阴道微生物区系和痛经表型，阴道微生物区系及其功能的研究是一项 为了解痛经的个体差异提供了一条有希望的途径。我们的中心假设是阴道 微生物区系通过调节生殖器中的宿主炎症反应而导致痛经症状 一条小路。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。在种族方面 不同的女性参与者(年龄14-39岁)将被招募到四组：三种痛经表型 另一组为无症状组。这些人将在月经期和经期提供阴道样本、血液 样本和调查问卷数据。本研究的具体目的是(1)区分阴道微生物类群， 用鸟枪式后基因组和qPCR技术研究痛经表型相关基因和途径 方法：(2)辨别与痛经表型相关的炎性介质和代谢产物 使用细胞因子免疫分析和基于质谱学的代谢组学；以及(3)鉴定分类学 与严重痛经症状相关的阴道代谢体功能改变的驱动因素。网络- 基于系统生物学和预测建模的方法将用于将表型、人口统计学、 行为、后基因组、细胞因子、代谢组学和荷尔蒙数据。这种多组学方法将提供 关于阴道微生物区系和代谢物功能的丰富信息，以揭示 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区系或代谢物(例如，使用药物、益生菌、 和/或行为干预)，(2)揭示阴道微生物区系和/或代谢物作为生物标记物，以及(3) 利用大型微生物元基因组测序、代谢组学分析和详细信息生成丰富的资源 表型、激素和行为数据，以研究痛经和月经健康的机制。在 从长远来看，这项工作有可能导致额外的痛经治疗选择与最终 减少痛苦和提高妇女生活质量的目标。

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.