Variation in urobiome composition over time in asymptomatic individuals with spinal cord injury and disease using intermittent catheterization

Abstract Urinary tract infection (UTI) remains the most common infectious complication among individuals with neurogenic lower urinary tract dysfunction (NLUTD) due to spinal cord injury or disease (SCI/D). Despite widespread reliance on microbiological and symptom-based criteria for UTI diagnosis, significant ambiguity persists—especially in distinguishing clinically meaningful change from normal variability in urinary analysis results. This uncertainty contributes to overdiagnosis, inappropriate antibiotic use, and antimicrobial resistance. The present study seeks to operationalize “normal variability” of the urinary microbiome (urobiome) among adults with SCI/D. Using repeated samples collected from asymptomatic individuals over time, we analyzed inter- and intra-individual microbial composition to determine stability and fluctuation under baseline conditions. We observed wide intra- and inter-individual variability, substantial overlap between asymptomatic and pre-symptomatic states, and a consistent predominance of genera conventionally labeled as “uropathogens” even in the absence of symptoms. These findings suggest that assumptions drawn from cross-sectional studies—linking particular taxa or diversity values to health or disease—are not supported within individuals over time, at least in people with NLUTD. This study provides a foundation for distinguishing expected variation from those potentially related to infection, supporting development of precision-based diagnostic thresholds. Results offer critical insight into the ecological dynamics of the urobiome among people with NLUTD who are asymptomatic, establishes a methodological precedent for urobiome-informed clinical decision-making in SCI/D populations, and provides a foundation for distinguishing expected variation from those potentially related to infection, supporting development of precision-based diagnostic thresholds. By identifying personalized baselines and patterns of change, we aim to support research designed to obtain actionable information from the urobiome to enhance the accuracy and stewardship of UTI diagnosis and treatment in this high-risk population.