Phenotyping and validating central sensitization in painful and non-painful benign urologic disease using machine learning - interstitial cystitis/bladder pain syndrome (IC/BPS) and overactive bladder…

The National Institute of Neurological Disorders and Stroke awarded Fairleigh Dickinson University $560,491 on August 17, 2026, under the Drug Use and Addiction Research Programs (CFDA 93.279) to phenotype and validate central sensitization in interstitial cystitis/bladder pain syndrome and overactive bladder using machine learning and secondary data analysis.

The project applies latent growth mixture modeling to existing quantitative sensory testing data from approximately 500 urologic patients collected at Vanderbilt University Medical Center to identify a central sensitization phenotype characterized by temporal summation of pain. The research characterizes the identified phenotype using objective sensation meter metrics, ecological momentary assessment via daily surveys, and treatment response data. The work tests whether central sensitization phenotype predicts bladder sensation outcomes, lower urinary tract symptom variability and anxiety in overactive bladder populations, and differential response to cognitive behavioral therapy versus physical therapy in interstitial cystitis/bladder pain syndrome patients.

The award establishes an undergraduate-centered collaborative research infrastructure at Fairleigh Dickinson University, the recipient, with place of performance at Teaneck, New Jersey. The period of performance runs through July 31, 2029. This is a Project Grant assistance type, a standard three-to-five-year NIH research award mechanism supporting investigator-initiated projects with peer-reviewed scientific merit.

Phenotyping and validating central sensitization in painful and non-painful benign urologic disease using machine learning - interstitial cystitis/bladder pain syndrome (IC/BPS) and overactive bladder (OAB) are prevalent, debilitating urologic disorders marked by lower urinary tract symptoms-including pain, urgency, and frequency-but lack mechanistically informed treatments. Evidence implicates central sensitization (CS)-heightened central nervous system responsiveness-in persistent urologic symptoms, yet no validated CS phenotype exists. We aim to extend the putative CS framework by employing mechanism-based phenotyping to inform precision interventions for urologic disorders. The project uses secondary analyses of existing NIH-R01-funded datasets collected at vanderbilt university medical center (vumc) to clarify the role of CS in urinary hypersensitivity, and establishes a sustainable undergraduate-centered collaborative research infrastructure at fairleigh dickinson university (FDU). Aim 1: apply machine learning to existing datasets to identify a CS phenotype (or dimension) of urologic patients using quantitative sensory testing (QST). We will apply latent growth mixture modeling to ten-trial pain ratings from a thermal QST paradigm across OAB and IC/BPS participants (n ≈ 500) to identify a CS subgroup via positive temporal summation of pain (TSP) slopes. Aim 2: harness interdisciplinary expertise across research sites to characterize CS through objective, ecological, and treatment data. We will characterize the CS phenotype/dimension with objective (sensation meter), ecological (daily surveys), and treatment response data. H2A: CS phenotype/dimension will predict bladder sensation meter metrics. H2B: in OAB, CS will predict average and variability in momentary lower urinary symptoms and anxiety/stress. H2C: in IC/BPS, baseline CS will enhance benefit of cognitive behavioral therapy (compared to physical therapy) for urinary and psychological outcomes. Aim 3: establish a sustainable, interdisciplinary pain-science environment and professional research pipeline advancing research skills and grant-funded, biomedical science engagement for students at FDU. Paid interns will be trained with emphasis on education, immersion, and dissemination of research . Faculty and graduate mentors at FDU and vumc will facilitate research training. Impact. This project will yield the first QST-based CS phenotype in urologic disorders, characterize CS in objective and real-world cases, clarify treatment moderators with precision medicine implications, and expand FDU's undergraduate translational research ecosystem.