IMPLORE Study: Investigation of Microbiomes of Postmenopausal Women Looking for Outcomes and Response to Estrogen Therapy
Phase: PHASE4
Conditions: Female Urogenital Diseases, Vaginal Atrophy, Postmenopausal Atrophic Vaginitis, Genitourinary Disease, Postmenopausal Symptoms
Sponsor: University of Alabama at Birmingham

 
Investigation of Microbiomes of Postmenopausal Women 
Looking for Outcomes and Response to Estrogen Therapy 
 
Study Protocol & Statistical Analysis Plan 
 
NCT03996603 
 
Date of Last Protocol Approval: 2/24/2021 
 
Kyle P Norris, MD, Principal Investigator 
University of Alabama at Birmingham 
Birmingham, AL 35294 
 

 
 
 
 
 
 
 
IMPLORE Study:  Investigation of Microbiomes of Postmenopausal Women Looking for Outcomes 
and Response to Estrogen Therapy 
 
 
Principal Investigator: 
Kyle P. Norris, MD 
Instructor Fellow 
Division of Urogynecology and Pelvic Reconstructive Surgery 
University of Alabama at Birmingham 
619 19th Street, 176 F  
Suite 10382 
Birmingham, AL 35249 
Phone: (205) 934-1704 
kpnorris@uabmc.edu 
 
Co-Investigators: 
Holly E. Richter, PhD, MD 
Professor 
Research Director, Division of Urogynecology and Pelvic Reconstructive Surgery 
Director, Urogynecology Care and Genitorectal Disorders Clinics 
University of Alabama at Birmingham 
 
Isuzu Meyer, MD 
Assistant Professor 
Division of Urogynecology and Pelvic Reconstructive Surgery 
University of Alabama at Birmingham 
 
Akila Subramaniam, MD 
Assistant Professor 
Division of Maternal Fetal Medicine 
University of Alabama at Birmingham 
 
Casey D. Morrow, PhD 
Professor 
Department of Cell, Developmental and Integrative Biology 
Director, UAB Microbiome Resource 
University of Alabama at Birmingham 
 
 

A. PROPOSAL OVERVIEW 
 
The significant impact of vulvovaginal atrophy (VVA) is well recognized as approximately half of women 
will experience this disorder at some point in the postmenopausal years (1, 2).  Symptoms like vaginal dryness, 
itching, burning, dyspareunia, vaginal bleeding or a combination of these are often encountered.   This 
translates to “sizeable proportions of women who report emotional, lifestyle, and sexual impact from these 
symptoms (3).”  The number of women experiencing this disorder will continue to grow as the older proportion 
of the population is expected to double in the next 30 years (4).  However, the full extent of this impact is 
difficult to estimate as this disorder is multifactorial and often underreported (5).  VVA, as part of a larger 
diagnosis of Genitourinary Syndrome of Menopause (GSM), is associated with concomitant genitourinary 
conditions and women with VVA have a higher incidence of overactive bladder and lower urinary tract 
symptoms (6, 7).  Thus improvement in VVA can have a very real consequence on the functional status and 
quality of life in affected women.   
 
In this proposed pilot study, 16S ribosomal RNA (rRNA) gene sequencing will be used in the analysis of 
microbiomes in postmenopausal women before and after eight weeks of vaginal estrogen use.  We plan to 
characterize the composition and dynamics of the microbiomes of the vagina, bladder, and rectum for 
quantitative and qualitative changes in the distribution of operational taxonomic units (OTUs) before and after 
eight weeks of local vaginal estrogen therapy.  Although the vagina, bladder, and gut microbiomes have been 
increasingly independently studied, less is known about the interactions of the bacterial communities among 
the three environments as well as the dynamic relationship with menopausal status and transvaginal estrogen 
therapy. 
AIM 1:  To assess the quantitative change in relative abundance of Lactobacillus genus and spp 
among the community composition of bacteria in the vagina pre- and post- vaginal estrogen therapy. 
AIM 2:  To evaluate the vaginal maturation index (VMI), vaginal pH, and vaginal inflammatory 
biomarkers: IL-1B, IL-4, IL-6, IL-8, IL-10, TNF-a, MCP-1, GM-CSF and correlate any notable changes with 
changes noted in the vaginal microbiome. 
AIM 3 and 4:  To observe for quantitative and qualitative changes in the distribution of OTUs among 
the bladder microbiome (AIM 3) and the rectal microbiome (AIM 4). 
 
 
Sub Aims 3 and 4:  To assess for quantitative changes in bladder and rectal inflammatory 
biomarkers and correlate these findings both with any notable changes in the bladder and rectal 
microbiomes as well as with the data yielded from vaginal sampling. 
 
Based on limited prior research from Shen J, et al. we hypothesize that transvaginal estrogen therapy 
will result in significant increases in Lactobacillus species with corresponding decreases in gram negative and 
anaerobic species.  Therefore, vaginal estrogen therapy will also yield a decrease in overall bacterial diversity 
with an expected Lactobacillus predominance.  Our hypothesis is currently unstudied and to our knowledge 
there has not been a study of 16S rRNA gene sequencing of the vaginal microbiome with local vaginal 
estrogen therapy in any manner. 
 
This proposed research is critical to evaluating the relationship between VVA and these dynamic site-
specific microbiomes.  Furthermore, this proposal allows us to evaluate the microbiome response to vaginal 
estrogen therapy – a widely used treatment approach to patients with VVA.  This information will also inform 
future studies, and serve to guide estimations of power and necessary cohort numbers.  Currently the baseline 
and post treatment compositions of these microbiomes are unclear in our study population of interest and this 
pilot study will help to define that.  If our hypotheses are confirmed, future studies from samples collected in 
this pilot study will allow us to investigate the relationships of rectal, urinary, and vaginal metabolites in VVA 
and its associated physiologic and inflammatory changes.  Furthermore, alternative prophylactic uses of 
vaginal estrogen for prevention of lower genitourinary tract conditions may also be explored. 
This study will utilize multidisciplinary expertise from the University of Alabama at Birmingham among 
the departments of Urogynecology, UAB Microbiome Resource, Pathology, Maternal Fetal Medicine, the 
Center for Clinical and Translational Science, and the Center for Women’s Reproductive Health. 
 
B. SIGNIFICANCE 
B.1. Significance of Vulvovaginal Atrophy:  The significant impact of vulvovaginal atrophy (VVA) is well 
recognized as approximately half of women will experience this disorder at some point in the postmenopausal 
years (1, 2).  Symptoms like vaginal dryness, itching, burning, dyspareunia, vaginal bleeding or a combination 
of these are often encountered.   This translates to “sizeable proportions of women who report emotional, 
lifestyle, and sexual impact from these symptoms (3).”  The number of women experiencing this disorder will 
continue to grow as the elderly proportion of the population is expected to double in the next 30 years (4).  

However, the full extent of this impact is difficult to estimate as this disorder is multifactorial and often 
underreported (5). 
B.2. Relationship of VVA to Other Genitourinary Conditions:  VVA, as part of a larger diagnosis of 
Genitourinary Syndrome of Menopause (GSM), is highly associated with concomitant genitourinary conditions 
and women with VVA have a higher incidence of overactive bladder and lower urinary tract symptoms (6, 7). 
Some women have been shown to have increased episodes of urgency urinary incontinence (UUI) despite no 
clinical or culture evidence of bacterial UTI but with positive urinary bacteria detected by quantitative PCR (8).  
B.3. Pathophysiology of VVA and Hypoestrogenemic State:  The pathophysiology of the relationship 
between a hypoestrogenemic state and changes in the vulvovaginal area have been described.   Significant 
changes in vaginal pH, cellular glycogen stores and integrity, adipose tissue and vaginal secretions have been 
observed (9-11).   Decreased levels of estrogen have also been shown to impact the local cellular immunity of 
the vagina leading to increased levels of neutrophils, cellular destruction and inflammation (9). 
B.4. Relevance of Interest in Microbiome Niches:  Symbiotic and dysbiotic relationships have been 
described as they pertain to protective and pathogenic effects on the host.  Vaginal microbiomes of 
postmenopausal women have been shown to have increased rates of anaerobic, mixed flora communities and 
decreased predominance of lactobacillus species (13).  This has been associated with increased alkaline pH 
values of the vagina that make for a less suitable environment to the lactobacillus spp.  Interest in human 
microbiomes has existed for more than a century.  From microscopy to Gram stains and cultures, the analysis 
of microbiomes has evolved to culture independent next-generation gene sequencing (14).  These molecular 
techniques for analysis of human microbiomes have developed over decades and 16S rRNA gene sequencing 
for analysis has been shown to be a valid tool for analyzing distributions of OTUs (14-16). 
B.5. Effect of Microbiome Niches on Host Well-being:  In addition to the microbiomes of the vagina and 
bladder in post-menopause, which have been increasingly studied, there is great interest in the relationship of 
the microbiomes of the gastrointestinal tract and rectum and how it relates to the genitourinary environments.  
A study concluded that Lactobacilli colonizing the rectum may be a reservoir for vaginal lactobacilli (17).  A 
study found significant associations between menopause, hypoestrogenemia, disorders of the GI tract and oral 
cavity as well as alterations of both the oral and gut microbiomes that lead to dysbyosis and loss of health 
integrity (18).  Inflammatory states of the gut and autoimmune conditions have been associated with gut 
microbial dysbyosis.  Bone homeostasis has also been implicated in the sphere of influence of gut microbiota 
(18). 
B.6. Standard Treatment of VVA:  In women without contraindications, vaginal estrogen therapy, among 
other treatment options, is considered a standard of care for treatment of vulvovaginal disorders including 
vaginal atrophy, dyspareunia, and some lower urinary tract symptoms (19-21).  Vaginal estrogen therapy has 
been shown to yield a statistically significant increase in the VMI and decreases in both the vaginal pH and 
severity of the reported most bothersome symptom (MBS) (23).  This study, however, did not concurrently 
evaluate any effect of estrogen therapy on vaginal bacterial communities and questions still remain regarding 
how vaginal estrogen therapy specifically affects the composition of the microbiome and how these 
compositional changes affect physiologic change. 
B.7. Limitations of Current Knowledge:  Our current knowledge is based on assumptions from other limited 
studies as well as extrapolated from research evaluating the vagina both in pre- and post-menopausal states 
or with other methods of estrogen delivery (24).  The prevailing theory is that with decreasing estrogen levels in 
the aging woman, we see decreasing levels of glycogen stores in the vagina (both intra and extracellular) 
which leads to decreases in Lactobacillus species, decreased H202 presence in the vagina, increases in 
vaginal pH, and increased biodiversity including various gram negative, coliform and anaerobic species (25).  
While aspects of these theories are documented in the literature other associations have been noted as well, 
some reporting different results.  A recent study assessing correlations between levels of vaginal glycogen did 
not support an association with quantities of lactobacillus dominant microbiomes (26).  This same study also 
did not note an association between documented Lactobacillus predominant microbiomes and fewer VVA 
symptoms.  With this in mind, the findings from our study will be pertinent to further interpreting these varied 
pathophysiologic associations. 
 
C. INNOVATION 
 
16S rRNA gene sequencing is a well validated and increasingly predominant mode of evaluating 
bacterial communities among locations of interest (14-16).  To our knowledge, there has not been a study of 
the vaginal microbiome and any assessment of its relationship to therapy with intravaginal estrogen cream 
utilized prospectively.  Further, there are limited studies that evaluate changes in the vaginal microbiome in a 

Figure 1.  Flow Diagram of Enrollment and Study Design
N=25  Total 
Patients; 150 
Total Samples 
to be Obtained
N=20 Receive 
Treatment
Baseline Sampling 
of Vagina, Bladder, 
Rectum
Vaginal Estrogen 
Therapy for Eight 
Weeks
Repeat Sampling of 
Vagina, Bladder, 
Rectum
Comparison of Pre-
and Post-
Treatment Data
N=5 Control (No 
Treatment)
Baseline Sampling 
of Vagina, Bladder, 
Rectum
Repeat Sampling of 
Vagina, Bladder, 
Rectum
Comparison of Pre-
and Post-Treatment 
Data
pre- and post- manner after any of the other routes estrogen therapy.  The same holds true for evaluation of 
the bladder and gut microbiomes in response to vaginal estrogen therapy.  Additionally, there is limited data 
combining efforts to assess the dynamic relationships of these microbiomes with local inflammatory biomarkers 
and standard clinical tools to evaluate vaginal health.   
 
Assessing the interrelationships of these microbiomes and local inflammatory biomarkers is crucial to 
understanding how pathologic or therapeutic changes in these markers affect the other microbiome niches.  
Given that the microbiomes of these three environments are conceivably modifiable, the understanding of the 
correlative relationship between the microbiomes and inflammatory biomarkers as well as objective 
improvement of the vagina can provide important clarity and guidance for future research and potential 
therapies.  Results from this study will also serve to guide estimations of power and necessary cohort 
numbers.  Currently the baseline and post treatment compositions of these microbiomes are unclear in our 
study population of interest and this pilot study will help to define that.  If our hypotheses are confirmed, future 
studies from samples collected in this pilot study will allow us to investigate the relationships of rectal, urinary, 
and vaginal metabolites in VVA and its associated physiologic and inflammatory changes.  Furthermore, 
alternative prophylactic uses of vaginal estrogen for prevention of lower genitourinary tract conditions may also 
be explored. 
 
D. METHODS 
D.1 Study Population 
D.1.1. Cohort Identification:  Postmenopausal women ≥55 years old with clinically diagnosed vulvovaginal 
atrophy.  Twenty volunteer patients will be placed in the intervention arm.  The primary aim is to compare the 
change in the data points of interest over the eight week study period in a pre- and post-treatment comparison 
manner.  The five patients meeting the same inclusion/exclusion criteria will serve as a control cohort, not to 
receive treatment, and are included in this study to demonstrate microbiome stability across the eight week 
time period.  We anticipate interest and participation in this study from planned advertisements and women 
seen in the UAB Urogynecology and Women’s Reproductive Health Clinics. 
 
 
Screening/Eligibility:  During screening, eligibility will be determined using scripted questions: 
Inclusion/Exclusion Criteria.  Potential subjects will be invited to participate in the study, demographics will be 
recorded.  Inclusion Criteria:  Postmenopausal women with clinically diagnosed vulvovaginal atrophy, age 
≥55 years old and a screening vaginal pH of ≥5, without menses for ≥12 months, no uterovaginal or vaginal 
vault prolapse beyond the hymen.  Exclusionary Criteria:  1) Patients with BMI ≥35kg/m2.  2) Any patients 
with infections requiring antibiotic or antifungal therapy during the study period or within the last month or 
during the study period.  3) Study patients may not use any vaginal suppositories, douches, or vaginal hygiene 
wipes within the month preceding enrollment.  4) Patients receiving ongoing hormone replacement therapy.  
Patients already on hormone therapy, will be allowed to undergo a “wash out” period of estrogen or 
progesterone products for one month prior to enrollment.  5) Patients requiring concurrent use of steroid 
creams for other indications (e.g. lichen sclerosis).  6) Additional exclusions included patients with systemic 
conditions requiring immunosuppressive drugs, currently receiving chemotherapy, or history of pelvic radiation.  
7) Any patients with contraindications to vaginal estrogen therapy including vaginal bleeding of unknown 
etiology.  8) Any patients with history of connective tissue disease.  9) Current tobacco use. 
 
D.2. Study Design 
The intention of this study is for each of the subjects to serve as her own control.  Twenty patients will receive 
the treatment intervention.  Five will not receive the treatment intervention.  The five subjects not receiving 

Table 1.  Description of Sample Numbers and Locations. 
treatment are intended to serve as a control cohort to demonstrate stability of the microbiome over the study 
period.  It is anticipated that unlike premenopausal subjects, the postmenopausal subjects not undergoing 
treatment (control group) will have 
little variation of the microbiome over 
the eight weeks.  Each of the 
twenty-five subjects will be sampled 
for microbiome and inflammatory 
biomarker analysis at three different 
locations (vagina, bladder, rectum) 
at two separate time points 
(Baseline Visit 1 and after eight 
weeks of vaginal estrogen therapy, 
Visit 2).  This will yield a total of 300 
samples for the study.  The treated 
subjects (20) and untreated (5) 
subjects may be compared to each 
other but that is not the primary aim 
of this study. 
 Intervention:  1g conjugated estrogen (CE) cream given nightly for 2 weeks then twice-weekly to complete 
planned eight weeks therapy.  This specific dose and frequency has been shown to improve objective and 
subjective measures of vaginal epithelium in previous studies (23, 27).  It has also been shown to achieve 
objective improvements in as little as three to four weeks (23).  Additionally, this dose and regimen is already 
commonly used and will provide excellent external generalizability.   
D.3. Specific Aims 
D.3.1. Specific Aim – 1:  To assess the quantitative change in relative abundance of Lactobacillus among the 
community composition of bacteria in the vagina pre- and post- vaginal estrogen therapy.  Hypothesis:  A 
statistically significant quantitative increase in the relative abundance of Lactobacillus will be seen. 
Approach:  The vaginal microbiome will be analyzed using 16S rRNA gene sequencing techniques evaluating 
specimens of mid-vaginal secretions to compare samples from each subject prior to initiation of vaginal 
estrogen cream and then again after eight weeks of therapy.  This will yield 50 vaginal specimens in total for 
this specific aim (V1 = 25, V2 = 25; Treatment Group V1 = 20 vs. V2 = 20; Control Group V1 = 5 vs. V2 = 5).  
Baseline characteristics will be recorded and compared among the total cohort to identify covariates for 
adjusted analyses.  Whole genome DNA (gDNA) will be extracted from specimens using DNA extraction kits 
(Zymo Research Corp, Irvine, CA) and PCR primers targeting the V4 rRNA gene will be used to prepare an 
amplicon library sequenced by the MiSeq platform (Illumina: San Diego, CA) and analyzed using the 
Quantitative Insight into Microbial Ecology (QIIME) suite.  These raw data sequences will then be cross-
validated and additional quality control measure will be applied.  Analysis using QIIME will be supplemented 
with the use of the program DADA2 for more robust methods of sequence read de-noising and clustering to 
yield a higher degree of species-level identification (28).  To better detect species of organisms known to be 
present in vaginal samples, taxonomy will be assigned using appropriately modified and validated databases 
(29-31)  Microbiome Analysis Statement of Rigor:  Several quality controls are performed: 1) removing 
sequences with low quality scores, those matching human databases and low-duplicates and 2) merging 
paired reads and discarding sequences with substantial differences. Results from the UAB Microbiome 
Resource pipeline showed that duplicate samples had significant co-clustering on Principal Coordinate 
Analysis (PCoA) plots.  Using 16S rRNA gene and whole genome DNA sequences from 20 known species, we 
are able to correctly identify organisms with unique 16S rRNA V4 genes to the genus and even species level 
and predict genetic pathways.   Sample Size and Power Rationale:  Our sample size calculation is based 
upon our primary aim to evaluate the expected quantitative change in relative abundance of Lactobacillus 
genus and spp among the community composition of bacteria in the vagina.  There’s an abundance of 
research reporting the normalization of the vagina by objective measures by various routes of estrogen 
therapy, specifically by serving to facilitate the increase of the relative Lactobacillus presence.  However, it is 
difficult to define how much of an increase in Lactobacillus is needed to be clinically relevant.  As previously 
stated there is no previous study by which to reference in predicting what the expected change in Lactobacillus 
may be in the setting of vaginal estrogen therapy.  A previous study (22) has compared a cohort of atrophic 
vaginitis (AV) patients who received low dose oral estrogen therapy to a healthy control (not receiving therapy); 
all patients were postmenopausal meeting strict criteria.  Vaginal sampling took place at baseline, two weeks, 
 
Pre-Treatment 
Post-Treatment 
SAMPLE LOCATION 
 
 
VAGINA 
 
 
Inflammatory Biomarkers 
25 
25 
Microbiome 
25 
25 
BLADDER 
 
 
Inflammatory Biomarkers 
25 
25 
Microbiome 
25 
25 
RECTUM 
 
 
Inflammatory Biomarkers 
25 
25 
Microbiome 
25 
25 

and at four weeks after treatment initiation.  Among the AV group the relative abundance of Lactobacillus 
pretreatment was 0.112 ±0.164.  At 4 weeks of oral estrogen therapy the Lactobacillus abundance rose 
dramatically to 0.71 ±0.375.  The baseline abundance among the “healthy” untreated postmenopausal cohort 
was 0.532 ±0.403 and virtually without change over the four week period.   
 
Based on these results, we expect the relative abundance of Lactobacillus in our cohort to be 
somewhere between 0.112-0.532 at baseline.  As the selection criteria of our cohort does not include VVA 
symptomatology, we expect the relative abundance of Lactobacillus spp to be approximately 0.4 ±0.3.With a 
Type-1 error of 0.05, we estimate with 80% power that we can detect an effect size of 0.2 increase 
(0.4à0.6) in the relative abundance of Lactobacillus spp with a treatment sample size of 20 patients. 
Biostatistical Analysis Plan: The following microbial community-level analyses will be performed to 
investigate the overall microbiome differences between the pre-treatment and post-treatments groups using 
the R package phyloseq (Table 2)(32). 
Table 2. Overview of Community-Level Microbiome Analysis 
Outcome 
Measurements 
Two-group comparisons 
Alpha diversity (diversity within a sample) 
Shannon, Chao, Simpson indices 
t-tests, Mann-Whitney U 
Beta diversity (diversity between samples, 
overall microbiota composition) 
Bray-Curtis, unweighted UniFrac, weighted UniFrac 
(represented by PCoA to visualize clustering) 
PERMANOVA or Dirichlet-multinomial 
distribution with Wald-type test 
To identify individual taxa significantly associated with vaginal estrogen treatment, taxa-specific analyses will 
be performed. Given the distinct properties of microbiome data (compositional counts/proportions, varying total 
sequence reads across samples, over-dispersion), microbiome counts, transformations of microbiome counts, 
and beta regression for relative abundance will be used (33-39) To deal with zero-inflation of microbiome data, 
we will employ zero-inflated models: negative binomial (for count data), Gaussian (for logarithm or arcsine 
square root transformations), beta regression (for relative abundance) – which allow analysis of multiple 
covariates which may vary between treatment and non-treatment groups (38, 40-43).  An R package bmzim for 
these models will be used.  Standard procedures (e.g. Holm’s, Hochberg’s, Hommel's, Benjamini and 
Hochberg’s methods) will be used to calculate p-values adjusted for multiple comparisons. 
D.3.2. Specific Aim – 2:  To evaluate the VMI, vaginal pH, and vaginal inflammatory biomarkers: IL-1B, IL-4, 
IL-6, IL-8, IL-10, TNF-a, MCP-1, GM-CSF and correlate any notable changes with changes noted in the 
vaginal microbiome.  Hypothesis:  An overall measured decrease in the levels of vaginal inflammatory 
biomarkers in response to therapy as well as an increase of the VMI with concomitant lowering of the vaginal 
pH, all signifying a return of the vaginal environment to a healthier state will occur.  These changes will be 
highly correlated with increased Lactobacillus predominance. 
Approach:  The VMI, vaginal pH, and vaginal inflammatory biomarkers: IL-1B, IL-4, IL-6, IL-8, IL-10, TNF-a, 
MCP-1, GM-CSF will be collected at the same time points (V1 and V2). Changes in these data points will be 
correlated with changes noted in the vaginal microbiome (see below).  As was used in a previous study (27), 
the VMI served as a tool for measure of adherence to vaginal estrogen application but also as an objective 
standard by which to correlate changes in the vaginal microbiome. 
Biostatistical Analysis Plan:  Mean inflammatory marker concentrations and VMI scores will be compared by 
Student t-test or robust non-parametric tests between pre- and post-treatment samples.  Normal linear 
regression will also be used to test the difference of the two cohorts (cytokine concentrations as response, 
cohort indicator as covariate). Similar methods will be used to analyze the difference in cytokine levels from V1 
and V2 between groups. We will use three methods to investigate the relationship between bacterial taxa and 
cytokine levels: 1) Pearson’s correlation coefficients will be calculated between cytokine levels and bacteria 
taxa (measured by percentage of reads) with a heat map showing correlations that are significantly different 
between pre- and post-treatment groups. To determine if cytokine levels and microbiota contribute to the 
clustering of women pre- and post-treatment, PCoA will be used to determine if these groups separate in 
space.  Clusters will be examined for potential novel subsets of samples - with clinical data used to identify the 
cause of the clustering with linear and discrete data methods. 2) We will treat counts of each taxa as response, 
inflammatory cytokine levels as covariates and use negative binomial models (or zero-inflated versions). 3) We 
will treat cytokine levels as response, relative abundance of each taxa as covariates and use linear models. In 
these regressions, a pre-treatment indicator and an interaction term between pre-treatment and the covariates 
will be included.  Similar methods will be used to analyze VMI and vaginal pH.  Sample Size and Power 
Rationale: Cytokine levels are continuous variables and even given this small sample size, should allow for 
more than adequate power to detect large differences in mean concentrations between pre- and post-
treatment groups. 
D.3.3. Specific Aims – 3 and 4:  To observe for quantitative and qualitative changes in the distribution of 
OTUs among the bladder and rectal microbiomes.  Hypothesis:  Alterations in the bladder and rectal 

microbiomes will occur before and after transvaginal therapy (similar to the changes seen in the vaginal 
microbiome).  These specific aims are exploratory. 
D.3.3.1 Sub Aims – 3.1 and 4.1 (Exploratory):  To assess for quantitative changes in the bladder and 
rectal inflammatory biomarkers (IL-1B, IL-4, IL-6, IL-8, IL-10, TNF-a, MCP-1, GM-CSF) and correlate 
these findings both with any notable changes in the bladder and rectal microbiomes.  Furthermore, 
changes in these biomarkers will be compared with the data (inflammatory and microbial) yielded from 
vaginal sampling.  Hypothesis:  We hypothesize that an overall measured decrease in the levels of 
bladder and rectal inflammatory biomarkers in response to therapy will occur. 
Approach:  The bladder and rectal microbiome samples will be obtained and analyzed at the same time points 
as Specific Aim 1.  Bladder sampling will be via straight catheterization and rectal sampling will be via rectal 
swabbing (swab placed high into the rectum).  Urine dipstick point of care testing will be performed for each 
baseline assessment and results suspicious for acute infection will be excluded from the study.  Inflammatory 
biomarker testing will be performed and analyzed in the same manner as Specific Aim 2 from the bladder and 
rectal samples at the same time points and changes will be statistically correlated with bladder and rectal 
sampling, as well as the vaginal sampling.  The biostatistical analysis plan will follow the plan outlined 
independently for Aims 1 and 2. 
 
D.4  Potential Problems/Alternative Strategies and Benchmarks for Success:  The main problem we may 
encounter during this investigation is that not all taxonomic differences can be resolved to the genus or species 
level.  Therefore, it is possible to find statistically significant differences in certain taxa for which there is no 
identification in the taxonomic databases.  However, these data can be continuously reanalyzed with 
expanding taxonomic databases in the future to add to our findings. 
 
Our benchmarks for this study are presented in the timeline shown below.  These benchmarks are 
dependent on the streamlined process for microbiome analysis that has been established.  DNA extraction will 
be done by Dr. Elena Lobashevsky, who has previously extracted DNA for our department’s microbiome 
studies; DNA amplification and sequencing will be done by Dr. Morrow and colleagues; statistical analysis will 
be performed by the UAB Microbiome Bioinformatics and Biostatics division (led by Dr. Elliot Lefkowitz with Dr. 
Nengjun Yi as the lead biostatistician.)  This collaboration allows all sequencing and analysis to be performed 
at one site in a timely fashion.  
 
E.  TIMELINE:  As noted in the separate document describing the institutional and departmental environment, 
the University of Alabama at Birmingham has a long track record of successfully completing clinical and 
translational trials.  As such, the proposed study is feasible within the predicted time frame.  The estimated 
time frame to accomplish these aims is illustrated below. 
 
 
 
 
 
 
 
 
 
Subject Recruitment & 
Sample Acquisition 
(Months 1-6)
DNA Extraction / 
Inflammatory 
Biomarker 
Processing 
300 Samples
(Months 7-9)
DNA 
Amplification & 
Sequencing 
(Months 10-11)
DNA Analysis 
(Months 12-13)
Statistical & 
Bioinformatic 
Analysis 
(Month 14-15)
Manuscript 
Preparation 
& Submission 
(Month 16)

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