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Am J Obstet Gynecol. 2019 Aug 14. pii: S0002-9378(19)31010-5. doi: 10.1016/j.ajog.2019.08.011. [Epub ahead of print]

Defining the relationship between vaginal and urinary microbiomes.

Author information

1
Obstetrics & Gynecology, University of New Mexico Health Sciences Center, Albuquerque, NM. Electronic address: ykomesu@salud.unm.edu.
2
Pediatrics, Clinical Translational Science Center, University of New Mexico Health Sciences Center, Albuquerque, NM.
3
Obstetrics & Gynecology, University of Alabama at Birmingham, Birmingham, AL.
4
Department of Reproductive Medicine, University of California San Diego, San Diego, CA.
5
Obstetrics & Gynecology, Alpert Medical School of Brown University, Providence, RI.
6
Obstetrics & Gynecology, Duke University, Durham, NC.
7
Obstetrics & Gynecology, University of Pittsburgh School of Medicine, Pittsburgh, PA.
8
Obstetrics & Gynecology, Cleveland Clinic, Cleveland, OH.
9
Obstetrics & Gynecology, Dell Medical School University of Texas Austin, Austin, TX.
10
Obstetrics & Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA.
11
Gynecologic Health and Disease Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH), Bethesda, MD.
12
Social, Statistical & Environmental Sciences, RTI International, Research Triangle Park, NC.

Abstract

BACKGROUND:

Although the vaginal and urinary microbiomes have been increasingly well-characterized in health and disease, few have described the relationship between these neighboring environments. Elucidating this relationship has implications for understanding how manipulation of the vaginal microbiome may affect the urinary microbiome and treatment of common urinary conditions.

OBJECTIVE:

To describe the relationship between urinary and vaginal microbiomes using 16S rRNA gene sequencing. We hypothesized that the composition of the urinary and vaginal microbiomes would be significantly associated, with similarities in predominant taxa.

STUDY DESIGN:

This multicenter study collected vaginal swabs and catheterized urine samples from 186 women with mixed urinary incontinence enrolled in a parent study and 84 similarly aged controls. Investigators decided a priori that if vaginal and/or urinary microbiomes differed between continent and incontinent women, the groups would be analyzed separately; if similar, samples from continent and incontinent women would be pooled and analyzed together. A central laboratory sequenced variable regions 1-3 (v1-3) and characterized bacteria to the genus level. Operational taxonomic unit abundance was described for paired vaginal and urine samples. Pearson's correlation characterized the relationship between individual operational taxonomic units of paired samples. Canonical correlation analysis evaluated the association between clinical variables (including mixed urinary incontinence and control status) and vaginal and urinary operational taxonomic units, using the Canonical correlation analysis function in the Vegan package (R version 3.5). Linear discriminant analysis effect size was used to find taxa that discriminated between vaginal and urinary samples.

RESULTS:

Urinary and vaginal samples were collected from 212 women (mean age 53±11 years) and results from 197 paired samples were available for analysis. As operational taxonomic units in mixed urinary incontinence and control samples were related in canonical correlation analysis and since taxa did not discriminate between mixed urinary incontinence or controls in either vagina or urine, mixed urinary incontinence and control samples were pooled for further analysis. Canonical correlation analysis of vaginal and urinary samples indicated that that 60 of the 100 most abundant operational taxonomic units in the samples largely overlapped. Lactobacillus was the most abundant genus in both urine and vagina (contributing on average 53% to an individual's urine sample and 64% to an individual's vaginal sample) (Pearson correlation r=0.53). Although less abundant than Lactobacillus, other bacteria with high Pearson correlation coefficients also commonly found in vagina and urine included: Gardnerella (r=0.70), Prevotella (r=0.64), and Ureaplasma (r=0.50). Linear discriminant analysis effect size analysis identified Tepidimonas and Flavobacterium as bacteria that distinguished the urinary environment for both mixed urinary incontinence and controls as these bacteria were absent in the vagina (Tepidimonas effect size 2.38, P<.001, Flavobacterium effect size 2.15, P<.001). Although Lactobacillus was the most abundant bacteria in both urine and vagina, it was more abundant in the vagina (linear discriminant analysis effect size effect size 2.72, P<.001).

CONCLUSION:

Significant associations between vaginal and urinary microbiomes were demonstrated, with Lactobacillus being predominant in both urine and vagina. Abundance of other bacteria also correlated highly between the vagina and urine. This inter-relatedness has implications for studying manipulation of the urogenital microbiome in treating conditions such as urgency urinary incontinence and urinary tract infections.

KEYWORDS:

Lactobacillus; mixed urinary incontinence; urinary microbiome; urologic conditions; vaginal microbiome

PMID:
31421123
DOI:
10.1016/j.ajog.2019.08.011

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