Methods to Test Lifestyle, Vaginal Microenvironment, and Genitourinary Symptoms across Menopause Transition

超过50%的绝经后妇女受到绝经后生殖道综合征(GSM)的影响，这种疾病 包括阴道萎缩、阴道干燥和性功能障碍。如果不治疗，症状会恶化 与压力和抑郁有关。更年期雌激素水平下降被认为会导致糖原减少 在阴道上皮中堆积，并与阴道低乳杆菌属有关。50%-80%的水平 对女人来说。乳杆菌属保护泌尿生殖道免受病原体侵袭部分是通过产生乳酸和 它们的抗炎特性，但乳酸菌是雌激素水平的标志物还是起作用的 GSM中的角色尚不清楚。现有的治疗外阴阴道GSM症状的方法都有局限性。一些女人 是荷尔蒙治疗的禁忌，或与副作用有关。阴道润滑剂提供了一些 缓解，但它们可能对阴道上皮有毒，减少乳杆菌，并增加泌尿生殖系统感染的风险。 需要新的治疗方法。然而，阴道微生物区系是一种看似合理的治疗方法。 单靠这一点并不能证明是有效的。阴道微生物区系与代谢物和免疫特征共同变化，它是 未知这些分子特征如何与GSM相关。我们假设核心阴道微环境 生物标志物(VMB；例如微生物、代谢物和免疫图谱)反映阴道生物老化(V-BA)， 更年期会增加，但也可能会受到其他因素的影响，比如生活方式。纵向研究 需要识别与年龄相关的核心VMB，并确定它们与GSM的关系。为了完成这项任务， 我们将开发新的统计方法，将复杂的纵向流行病学数据与高风险数据相结合。 维度组成数据。我们将利用收集的2,301个存档的宫颈阴道样本作为 812名年龄在35-60岁之间的女性，每六个月就诊一次，为期两年(R01-CA123467)。特定的 目的是1)利用VMB对V-BA进行量化；2)评估V-BA与GSM的纵向关系；3) 纵向评估生活方式因素对V-BA和VMB的影响；4)量化纵向中介 在Lifestyle和GSM之间由V-BA和VMB提供。微生物区系已被16S rRNA基因扩增子分析 测序(R21-AI107224)。与临床、人口统计学和行为调查一起，我们将1)使用颈椎病 分泌物和多重珠状免疫分析法定量测定70种免疫标记物的浓度 (细胞因子、趋化因子、生长因子)；2)阴道拭子代谢物(GC/LC-MS)。这项建议 专注于开发和验证新的统计方法，以改进和适应现代结构 建模和微生物区系组成分析。新的统计方法将允许识别 阴道微环境特征，可能导致新的和有效的GSM治疗方法的开发。 这些方法还将提供一个新的框架来处理丢失的数据和有限的混淆 以前的微生物组研究。我们的团队在生物统计学、流行病学、老龄化、 对GSM采取新的系统生物学方法所需的妇科学、基因组学、微生物学和免疫学。

Over 50% of postmenopausal women are affected by the genitourinary syndrome of menopause (GSM), which includes vaginal atrophy, vaginal dryness, and sexual dysfunction. Symptoms worsen if untreated and are associated with stress and depression. Estrogen decline in menopause is thought to lead to reduced glycogen accumulation in the vaginal epithelium and is associated with low vaginal Lactobacillus spp. levels in 50-80% of women. Lactobacillus spp. protect the urogenital tract from pathogens in part by producing lactic acid and for their anti-inflammatory properties, but whether lactobacilli are a marker for estrogen levels or play a functional role in GSM is unknown. Available treatments for vulvovaginal GSM symptoms have limitations. Some women are contraindicated for hormonal therapy or are concerned with side effects. Vaginal lubricants provide some relief, but they may be toxic to the vaginal epithelium, reduce lactobacilli, and raise urogenital infection risk. New therapies are needed. Vaginal microbiota are a plausible approach to treatment, however, probiotics alone have not proven effective. Vaginal microbiota co-vary with metabolite and immune profiles, and it is unknown how these molecular features relate to GSM. We hypothesize that core vaginal microenvironment biomarkers (VMB; e.g., microbial, metabolite, and immune profiles) reflect vaginal biological aging (V-BA) that is increased by menopause but may also be modifiable by other factors, such as lifestyle. Longitudinal studies are needed to identify core age-related VMB and determine how they relate to GSM. To accomplish this task, we will develop new statistical methods to combine complex longitudinal epidemiologic data with high- dimensional compositional data. We will leverage 2,301 archived cervicovaginal samples collected as part of a cohort of 812 women aged 35-60 years with visits every six months for two years (R01-CA123467). Specific Aims are to 1) quantify V-BA using VMB; 2) evaluate the longitudinal relationship between V-BA and GSM; 3) longitudinally assess the relationship of lifestyle factors on V-BA and VMB; 4) quantify longitudinal mediation by V-BA and VMB between lifestyle and GSM. Microbiota are already profiled by 16S rRNA gene amplicon sequencing (R21-AI107224). Along with clinical, demographic, and behavioral surveys, we will 1) use cervical secretions and multiplexed bead-based immune-assays to quantify concentrations of 70 immune markers (cytokines, chemokines, growth factors); 2) profile metabolites from vaginal swabs (GC/LC-MS). This proposal is focused on developing and validating new statistical methods that refine and adapt modern structural modeling and microbiota compositional analyses. The novel statistical approaches will allow identification of vaginal microenvironment features which may lead to development of new and effective GSM treatments. These methods will also provide a new framework to handle missing data and confounding that has limited prior microbiome studies. Our team has the multidisciplinary expertise in biostatistics, epidemiology, aging, gynecology, genomics, microbiology, and immunology required for a new systems-biology approach to GSM.