Matched serum- and urine-derived biomarkers of interstitial cystitis/bladder pain syndrome

Abstract

Setting up the correct diagnosis of interstitial cystitis/bladder pain syndrome (IC/BPS), a chronic inflammatory disease of the bladder, is a challenge, as there are neither diagnostic criteria nor reliable and non-invasive disease biomarkers available. The aim of the present study was to simultaneously determine matched serum- and urine-derived biomarkers of IC/BPS, which would provide additional insights into disease mechanisms and set the basis for further biomarker validation. Our study included 12 female patients with IC/BPS and 12 healthy controls. A total of 33 different biomarkers were measured, including cytokines and chemokines, proteins involved in extracellular matrix remodeling, adhesion molecules, growth factors, and markers of oxidative stress using enzyme linked immunoassays and multiplex technology. Heatmaps and principal component analysis based on significantly altered biomarkers, revealed urine- and serum-associated IC/BPS signatures that clearly differentiated IC/BPS patients from controls. Four biomarkers, including CCL11, BAFF, HGF and MMP9, were significantly upregulated in both serum and urine of patients with IC/BPS compared to controls. Serum levels of MMP9 were associated with disease severity and could distinguish well between IC/BPS patients with and without Hunner's lesions. Systemic levels of MMP9 can therefore mirror the local pathology within the bladders of IC/BPS patients, and MMP9 may prove to be a useful target for the development of novel therapeutic interventions. Utilizing a comprehensive panel of both urine and serum biomarkers, identified here, holds promise for disease detection in IC/BPS patients.

Fig 1

Heatmaps (a, b) and principal component analysis (c, d) for IC/BPS patients and HC in urine (a, c) and serum (b, d) based on significantly deregulated biomarkers. (a, b) Heatmaps with unsupervised hierarchical clustering based on significantly deregulated biomarkers in urine (a) and serum (b) showing a distinction between IC/BPS (pink; n = 12, a1-a12) and HC (blue; n = 12, b1-b12). Both rows and columns are clustered using Euclidean distance and complete linkage. (c, d) Principal component analysis based on significantly deregulated biomarkers in urine (c) and serum (d) showing a distinction between IC/BPS (blue; n = 12) and HC (pink; n = 12). Unit variance scaling was applied to rows and singular value decomposition (SVD) with imputation was used to calculate principal components. Prediction ellipses are such that with probability 0.68, a new observation from the same group will fall inside the ellipse. IC/BPS, interstitial cystitis/bladder pain syndrome; HC, healthy control; PC, principal component.

Fig 2. Correlation between serum and urine levels of selected biomarkers in IC/BPS patients.

Shown is linear regression fitting line where applicable. IC/BPS, interstitial cystitis/bladder pain syndrome; CCL11 (eotaxin1), C-C motif chemokine 1; BAFF, B-cell activating factor; HGF, hepatocyte growth factor; MMP9, matrix metalloproteinase 9.

Fig 3. Correlation of ICSI score with serum MMP9 in IC/BPS patients.

Shown is linear regression fitting line. IC/BPS, interstitial cystitis/bladder pain syndrome; ICSI, interstitial cystitis symptom index; MMP9, matrix metalloproteinase 9.

Fig 4. Differences in serum MMP and ICSI score between Hunner (HIC/BPS) and non Hunner (NHIC/BPS) type of IC/BPS.

Shown are violin plots with median and Q₂₅-Q₇₅ for serum MMP (a), ICSI score (b) in HIC/BPS (blue) and NHIC/BPS (green) and ROC curves for serum MMP9 (blue circles) and ICSI score (orange squares) (c). *p<0.005; HIC/BPS, Hunner type of interstitial cystitis/bladder pain syndrome; NHIC/BPS, non Hunner type of interstitial cystitis/bladder pain syndrome; ICSI, interstitial cystitis symptom index; MMP9, matrix metalloproteinase 9.