The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department
Older adults suffer from a high rate of asymptomatic bacteriuria (ASB), in which urinalysis may appear positive (presence of bacteria, white blood cells, and nitrates), often triggering initiation of antibiotics in acute care settings, without actual urinary tract infection (UTI) present. To investi...
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| Format: | Article |
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Taylor & Francis Group
2025-12-01
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| Series: | Virulence |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21505594.2025.2546063 |
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| author | Evan S. Bradley Celina Stansky Abigail L. Zeamer Ziyuan Huang Lindsey Cincotta Abigail Lopes Linda Potter Theresa Fontes Doyle V. Ward Vanni Bucci Beth A. McCormick John P. Haran |
| author_facet | Evan S. Bradley Celina Stansky Abigail L. Zeamer Ziyuan Huang Lindsey Cincotta Abigail Lopes Linda Potter Theresa Fontes Doyle V. Ward Vanni Bucci Beth A. McCormick John P. Haran |
| author_sort | Evan S. Bradley |
| collection | DOAJ |
| description | Older adults suffer from a high rate of asymptomatic bacteriuria (ASB), in which urinalysis may appear positive (presence of bacteria, white blood cells, and nitrates), often triggering initiation of antibiotics in acute care settings, without actual urinary tract infection (UTI) present. To investigate the urinary microbiome of older adults being tested for UTI, we enrolled a convenience sample of 250 older adult Emergency Department patients who had microscopic urinalysis ordered as part of their routine clinical care. Urinalysis results were classified as positive or negative, and patients were classified as being symptomatic or asymptomatic based on established diagnostic guidelines. We sought to determine if features of the urinary microbiome differed between positive and negative urinalysis (UAs) and symptomatic and asymptomatic patients with positive UAs. The same urine sample used for clinical testing was sequenced and analyzed for bacterial taxa, metabolic pathways, and known bacterial virulence factors. After exclusion of anatomical abnormalities and filtering for sequencing quality, 152 samples were analyzed (5 negative UAs, 147 positive UAs, among which 68 were asymptomatic, and 79 symptomatic). Positive UA samples showed significantly lower alpha diversity (2.29 versus 0.086, p < 0.01) and distinct community composition based on beta-diversity (PERMANOVA on Bray-Curtis distance p < 0.01). Alpha and beta diversity did not significantly differ between asymptomatic and symptomatic patients. Machine learning classifiers combining clinical covariates other than specific signs and symptoms and microbiome features (taxa, metabolic pathways, or virulence factors) revealed mostly microbiome features as predictive of symptomatic UTI over clinical features. |
| format | Article |
| id | doaj-art-2192bbc72aca4a7b8b8c20d11d87037c |
| institution | Kabale University |
| issn | 2150-5594 2150-5608 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Virulence |
| spelling | doaj-art-2192bbc72aca4a7b8b8c20d11d87037c2025-08-20T03:36:26ZengTaylor & Francis GroupVirulence2150-55942150-56082025-12-0116110.1080/21505594.2025.2546063The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency departmentEvan S. Bradley0Celina Stansky1Abigail L. Zeamer2Ziyuan Huang3Lindsey Cincotta4Abigail Lopes5Linda Potter6Theresa Fontes7Doyle V. Ward8Vanni Bucci9Beth A. McCormick10John P. Haran11Department of Emergency Medicine, UMass Memorial Medical Center, Worcester, MA, USADepartment of Emergency Medicine, UMass Memorial Medical Center, Worcester, MA, USAProgram in Microbiome Dynamics, UMass Chan Medical School, Worcester, MA, USAProgram in Microbiome Dynamics, UMass Chan Medical School, Worcester, MA, USADepartment of Emergency Medicine, UMass Memorial Medical Center, Worcester, MA, USADepartment of Emergency Medicine, UMass Memorial Medical Center, Worcester, MA, USAClinical Renal Laboratory, UMass Memorial Medical Center, Worcester, MA, USAClinical Renal Laboratory, UMass Memorial Medical Center, Worcester, MA, USAProgram in Microbiome Dynamics, UMass Chan Medical School, Worcester, MA, USAProgram in Microbiome Dynamics, UMass Chan Medical School, Worcester, MA, USAProgram in Microbiome Dynamics, UMass Chan Medical School, Worcester, MA, USADepartment of Emergency Medicine, UMass Memorial Medical Center, Worcester, MA, USAOlder adults suffer from a high rate of asymptomatic bacteriuria (ASB), in which urinalysis may appear positive (presence of bacteria, white blood cells, and nitrates), often triggering initiation of antibiotics in acute care settings, without actual urinary tract infection (UTI) present. To investigate the urinary microbiome of older adults being tested for UTI, we enrolled a convenience sample of 250 older adult Emergency Department patients who had microscopic urinalysis ordered as part of their routine clinical care. Urinalysis results were classified as positive or negative, and patients were classified as being symptomatic or asymptomatic based on established diagnostic guidelines. We sought to determine if features of the urinary microbiome differed between positive and negative urinalysis (UAs) and symptomatic and asymptomatic patients with positive UAs. The same urine sample used for clinical testing was sequenced and analyzed for bacterial taxa, metabolic pathways, and known bacterial virulence factors. After exclusion of anatomical abnormalities and filtering for sequencing quality, 152 samples were analyzed (5 negative UAs, 147 positive UAs, among which 68 were asymptomatic, and 79 symptomatic). Positive UA samples showed significantly lower alpha diversity (2.29 versus 0.086, p < 0.01) and distinct community composition based on beta-diversity (PERMANOVA on Bray-Curtis distance p < 0.01). Alpha and beta diversity did not significantly differ between asymptomatic and symptomatic patients. Machine learning classifiers combining clinical covariates other than specific signs and symptoms and microbiome features (taxa, metabolic pathways, or virulence factors) revealed mostly microbiome features as predictive of symptomatic UTI over clinical features.https://www.tandfonline.com/doi/10.1080/21505594.2025.2546063Urinary tract infectionmetagenomic analysismachine learningolder adultsemergency departmentasymptomatic bacteriuria |
| spellingShingle | Evan S. Bradley Celina Stansky Abigail L. Zeamer Ziyuan Huang Lindsey Cincotta Abigail Lopes Linda Potter Theresa Fontes Doyle V. Ward Vanni Bucci Beth A. McCormick John P. Haran The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department Virulence Urinary tract infection metagenomic analysis machine learning older adults emergency department asymptomatic bacteriuria |
| title | The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| title_full | The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| title_fullStr | The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| title_full_unstemmed | The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| title_short | The urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| title_sort | urinary microbiome distinguishes symptomatic urinary tract infection from asymptomatic older adult patients presenting to the emergency department |
| topic | Urinary tract infection metagenomic analysis machine learning older adults emergency department asymptomatic bacteriuria |
| url | https://www.tandfonline.com/doi/10.1080/21505594.2025.2546063 |
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