# Methods to Test the Role of Age-related Lifestyle and Vaginal Microenvironment Changes and the Prevention, Treatment, and Progression of Genitourinary Syndrome of Menopause

> **NIH NIH R01** · UNIVERSITY OF MARYLAND BALTIMORE · 2022 · $640,205

## Abstract

Over 50% of postmenopausal women are affected by the genitourinary syndrome of menopause (GSM), a
progressive, chronic condition related to estrogen decline that includes vaginal atrophy, vaginal dryness,
reduced sexual desire, and other signs and symptoms. GSM symptoms are a costly public health concern and
worsen if untreated. Estrogen decline in menopause is thought to lead to reduced accumulation of vaginal
glycogen and shifts in vaginal microbiota. These include low vaginal Lactobacillus spp. levels in 50-80% of
postmenopausal women. Lactobacillus spp. protect the urogenital tract from pathogens in part by lactic acid
production and hypothesized anti-inflammatory properties, but whether lactobacilli 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 about side effects. While vaginal lubricants provide
some relief, many are toxic to the vaginal epithelium, reduce lactobacilli, and raise urogenital infection risk.
Thus, new ways to treat and prevent GSM are needed. Because lactobacilli are often reduced in menopause,
vaginal microbiota are plausible treatment targets; however, probiotics alone have not been proven effective.
Also, age-related changes in vaginal microbiota co-vary with metabolite and immune profiles; but, the cross-
talk between these molecular features and their role in GSM is unknown. We hypothesize that core vaginal
micro-environment biomarkers (VMB; e.g., microbial, metabolite, and immune profiles) reflect vaginal biological
aging (V-BA) that increases in menopause but may be modifiable by lifestyle factors. Prospective studies are
needed to identify core age-related VMB and determine how they affect GSM. To achieve this goal, we will
leverage 2,301 archived cervicovaginal samples collected from 812 women aged 35-60 years with clinical
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). We will
quantify concentrations of 70 immune markers (cytokines, chemokines, growth factors) and metabolites
(GC/LC-MS) in cervicovaginal samples. A novelty of this proposed project is that we will develop, validate, and
apply new statistical methods for complex longitudinal data that refine and adapt modern structural modeling
and compositional microbiome data analyses. These methods will provide a rigorous framework to handle
missing data and confounding that has been a major limitation in many microbiome studies. The ultimate public
health impact is that findings from this project have potential to inform development of new therapy to prevent
or treat GSM to pr...

## Key facts

- **NIH application ID:** 10475571
- **Project number:** 5R01AG069915-02
- **Recipient organization:** UNIVERSITY OF MARYLAND BALTIMORE
- **Principal Investigator:** REBECCA M. BROTMAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $640,205
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475571

## Citation

> US National Institutes of Health, RePORTER application 10475571, Methods to Test the Role of Age-related Lifestyle and Vaginal Microenvironment Changes and the Prevention, Treatment, and Progression of Genitourinary Syndrome of Menopause (5R01AG069915-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10475571. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*