The healthy urinary microbiome in asymptomatic participants in the MAPP Network Study: Relation to gender, age, and menopausal status
Bibliographic record
Abstract
INTRODUCTION: To understand the role of the urinary microbiome in disease states and interpret non-culture-based diagnostic urine testing of midstream urine specimens, we must have a better understanding of the urinary microbiome in asymptomatic, healthy individuals. We examined the impact of gender, age, and menopausal status on the healthy human urinary microbiome in asymptomatic control subjects enrolled in the multi-institution National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Multidisciplinary Approach to the Study of Chronic Pelvic Pain Network (MAPP) study. METHODS: Asymptomatic, healthy controls, recruited to be ageand sex-matched to patients in the Trans-MAPP Epidemiology and Phenotyping Study, provided midstream urine collection for polymerase chain reaction (PCR)-electrospray ionization mass spectrometry identification of urinary microbiota. The microbiomes of male and female participants were described and analyzed for differences in composition and diversity at the species and genus level by sex, age, and, in females, by menopausal status. RESULTS: Sixty-six total species were detected with a mean of 1.2 species (standard deviation [SD] 1.1) per male (n=97; mean age=43) and 2.3 (SD 1.3) per female (n=110, mean age=38) in asymptomatic, healthy controls. Species and genera diversity analyses showed significantly greater richness and diversity in females. With regard to species, Bifidobacterium subtile, Lactobacillus crispatus, and Lactobacillus johnsonii were more predominant in females. The genera Bifidobacterium, Staphylococcus, Lactobacillus, and Corynebacterium were more predominant in females, while for males the most prevalent organisms included Staphylococcus and Propionibacterium; only Propionibacterium approached a significant difference between genders. No significant difference in the presence and/or diversity of micro-organisms with menopausal status could be observed. Sex-specific age trends, particularly diversity, were larger for females than males. CONCLUSIONS: These results suggest the urinary microbiome of healthy, asymptomatic subjects differed between genders and age in females, but not menopausal status. Gender differences may be attributable to the detection of urethral/vaginal organisms in females and prostate organisms in males. These findings will better allow us to interpret the results of microbiome reports in the midstream urine specimens of patients with urinary symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".