Abstract:

Objective To investigate the correlation between PPARγ and female interstitial cystitis/bladder pain syndrome （IC/BPS） and to establish a predictive model. Methods Clinical data were collected from 89 female IC/BPS patients （observational group） admitted to the hospital from June 2022 to December 2023， and 90 healthy female volunteers undergoing physical examinations during the same period （control group）. Plasma levels of inflammatory factors， total antioxidant capacity （TAC）， total glutathione （GSH）， malondialdehyde （MDA）， and PPARγ levels were measured. Significant clinical features were identified using LASSO regression and fitted into a multivariate logistic regression model. The diagnostic efficacy was assessed through receiver operating characteristic （ROC） curves. Results Compared to the control group， the observation group exhibited significantly elevated age， BMI， NLR， absolute neutrophil count， IFN-α， IL-1β， IL-6， IL-8， TNF-α and CD3⁺CD4⁺T expression levels， while absolute lymphocyte count， IL-10， TAC， GSH and plasma PPARγ expression levels were significantly decreased （all P < 0.05）. LASSO regression identified 8 variables， including NLR， IFN-α， absolute neutrophil count， IL-1β， IL-6， TNF-α， CD3⁺CD4⁺T and PPARγ， which were incorporated into the predictive model. Multivariate binary logistic regression analysis revealed that elevated levels of IL-1β， TNF-α and CD3⁺CD4⁺T cells， along with reduced PPARγ levels， were independent risk factors for IC/BPS. ROC curve analysis indicated that the diagnostic efficacy of the combined PPARγ and clinical parameters （age， IL-1β， TNF-α and CD3⁺CD4⁺T） （AUC = 0.901） was superior to PPARγ alone （AUC = 0.839）. Conclusion Plasma PPARγ levels are significantly reduced in female IC/BPS patients and serve as a potential diagnostic marker， with combined clinical parameters enhancing diagnostic accuracy.

Key words: interstitial cystitis/bladder pain syndrome, PPARγ, diagnostic biomarkers, predictive model