Yuko M Komesu1, Holly E Richter2, Benjamin Carper3, Darrell L Dinwiddie4, Emily S Lukacz5, Nazema Y Siddiqui6, Vivian W Sung7, Halina M Zyczynski8, Beri Ridgeway9, Rebecca G Rogers10,11, Lily A Arya12, Donna Mazloomdoost13, Marie G Gantz3. 1. Department of Obstetrics and Gynecology, University of New Mexico Health Sciences Center, MSC 10 5580 1 University of New Mexico, Albuquerque, NM, 87131-0001, USA. ykomesu@salud.unm.edu. 2. Obstetrics & Gynecology, University of Alabama at Birmingham, Birmingham, AL, USA. 3. Social, Statistical & Environmental Sciences, RTI International, Research Triangle Park, NC, USA. 4. Pediatrics and Clinical Translational Science Center, University of New Mexico Health Sciences Center, Albuquerque, NM, USA. 5. Department of Reproductive Medicine, University of California San Diego, San Diego, CA, USA. 6. Obstetrics & Gynecology, Duke University, Durham, NC, USA. 7. Obstetrics & Gynecology, Alpert Medical School of Brown University, Providence, RI, USA. 8. Obstetrics, Gynecology and Reproductive Sciences, Magee-Womens Research Institute, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 9. Obstetrics & Gynecology, Cleveland Clinic, Cleveland, OH, USA. 10. Department of Obstetrics and Gynecology, University of New Mexico Health Sciences Center, MSC 10 5580 1 University of New Mexico, Albuquerque, NM, 87131-0001, USA. 11. Obstetrics & Gynecology, Dell Medical School University of Texas Austin, Austin, TX, USA. 12. Obstetrics & Gynecology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. 13. Gynecologic Health and Disease Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) National Institutes of Health (NIH), Bethesda, MD, USA.
Abstract
INTRODUCTION & HYPOTHESIS: Previous studies have suggested that women with urinary incontinence have an altered urinary microbiome. We hypothesized that the microbiome in women with mixed urinary incontinence (MUI) differed from controls and tested this hypothesis using bacterial gene sequencing techniques. METHODS: This multicenter study compared the urinary microbiome in women with MUI and similarly aged controls. Catheterized urine samples were obtained; v4-6 regions of the 16S rRNA gene were sequenced to identify bacteria. Bacterial predominance (> 50% of an individual's genera) was compared between MUI and controls. Bacterial sequences were categorized into "community types" using Dirichlet multinomial mixture (DMM) methods. Generalized linear mixed models predicted MUI/control status based on clinical characteristics and community type. Post-hoc analyses were performed in women < 51 and ≥ 51 years. Sample size estimates required 200 samples to detect a 20% difference in Lactobacillus predominance with P < 0.05. RESULTS: Of 212 samples, 97.6% were analyzed (123 MUI/84 controls, mean age 53 ± 11 years). Overall Lactobacillus predominance did not differ between MUI and controls (45/123 = 36.6% vs. 36/84 = 42.9%, P = 0.36). DMM analyses revealed six community types; communities differed by age (P = 0.001). A High-Lactobacillus (89.2% Lactobacillus) community had a greater proportion of controls (19/84 = 22.6%, MUI 11/123 = 8.9%). Overall, bacterial community types did not differ in MUI and controls. However, post-hoc analysis of women < 51 years found that bacterial community types distinguished MUI from controls (P = 0.041); Moderate-Lactobacillus (aOR 7.78, CI 1.85-32.62) and Mixed (aOR 7.10, CI 1.32-38.10) community types were associated with MUI. Community types did not differentiate MUI and controls in women ≥ 51 years (P = 0.94). CONCLUSIONS: Women with MUI and controls did not differ in overall Lactobacillus predominance. In younger women, urinary bacterial community types differentiated MUI from controls.
INTRODUCTION & HYPOTHESIS: Previous studies have suggested that women with urinary incontinence have an altered urinary microbiome. We hypothesized that the microbiome in women with mixed urinary incontinence (MUI) differed from controls and tested this hypothesis using bacterial gene sequencing techniques. METHODS: This multicenter study compared the urinary microbiome in women with MUI and similarly aged controls. Catheterized urine samples were obtained; v4-6 regions of the 16S rRNA gene were sequenced to identify bacteria. Bacterial predominance (> 50% of an individual's genera) was compared between MUI and controls. Bacterial sequences were categorized into "community types" using Dirichlet multinomial mixture (DMM) methods. Generalized linear mixed models predicted MUI/control status based on clinical characteristics and community type. Post-hoc analyses were performed in women < 51 and ≥ 51 years. Sample size estimates required 200 samples to detect a 20% difference in Lactobacillus predominance with P < 0.05. RESULTS: Of 212 samples, 97.6% were analyzed (123 MUI/84 controls, mean age 53 ± 11 years). Overall Lactobacillus predominance did not differ between MUI and controls (45/123 = 36.6% vs. 36/84 = 42.9%, P = 0.36). DMM analyses revealed six community types; communities differed by age (P = 0.001). A High-Lactobacillus (89.2% Lactobacillus) community had a greater proportion of controls (19/84 = 22.6%, MUI 11/123 = 8.9%). Overall, bacterial community types did not differ in MUI and controls. However, post-hoc analysis of women < 51 years found that bacterial community types distinguished MUI from controls (P = 0.041); Moderate-Lactobacillus (aOR 7.78, CI 1.85-32.62) and Mixed (aOR 7.10, CI 1.32-38.10) community types were associated with MUI. Community types did not differentiate MUI and controls in women ≥ 51 years (P = 0.94). CONCLUSIONS: Women with MUI and controls did not differ in overall Lactobacillus predominance. In younger women, urinary bacterial community types differentiated MUI from controls.
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