Temporally complex inflammatory networks in an animal model reveal signatures for interstitial cystitis and bladder pain syndrome phenotype

Author:

Shah Ashti M.1ORCID,Vodovotz Yoram234,Yoshimura Naoki5ORCID,Chermansky Christopher J.5ORCID,Fitzgerald Jocelyn6,Tyagi Pradeep5

Affiliation:

1. University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA

2. Department of Surgery University of Pittsburgh Pittsburgh Pennsylvania USA

3. Center for Inflammation and Regeneration Modeling McGowan Institute for Regenerative Medicine Pittsburgh Pennsylvania USA

4. Center for Systems Immunology University of Pittsburgh Pittsburgh Pennsylvania USA

5. Department of Urology University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA

6. Department of Obstetrics, Gynecology, and Reproductive Sciences University of Pittsburgh School of Medicine Pittsburgh Pennsylvania USA

Abstract

AbstractIntroduction and ObjectiveInterstitial cystitis and bladder pain syndrome (IC/BPS) presents with symptoms of debilitating bladder pain and is typically a diagnosis of exclusion. The cystoscopic detection of Hunner's lesions increases the likelihood of detecting tissue inflammation on bladder biopsy and increases the odds of therapeutic success with anti‐inflammatory drugs. However, the identification of this subgroup remains challenging with the current lack of surrogate biomarkers of IC/BPS. On the path towards identifying biomarkers of IC/BPS, we modeled the dynamic evolution of inflammation in an experimental IC/BPS rodent model using computational biological network analysis of inflammatory mediators (cytokines and chemokines) released into urine. The use of biological network analysis allows us to identify urinary proteins that could be drivers of inflammation and could therefore serve as therapeutic targets for the treatment of IC/BPS.MethodsRats subjected to cyclophosphamide (CYP) injection (150 mg/kg) were used as an experimental model for acute IC/BPS (n = 8). Urine from each void was collected from the rats over a 12‐h period and was assayed for 13 inflammatory mediators using Luminex™. Time‐interval principal component analysis (TI‐PCA) and dynamic network analysis (DyNA), two biological network algorithms, were used to identify biomarkers of inflammation characteristic of IC/BPS over time.ResultsCompared to vehicle‐treated rats, nearly all inflammatory mediators were elevated significantly (p < 0.05) in the urine of CYP treated rats. TI‐PCA highlighted that GRO‐KC, IL‐5, IL‐18, and MCP‐1 account for the greatest variance in the inflammatory response. At early time points, DyNA indicated a positive correlation between IL‐4 and IL‐1β and between TNF‐α and IL‐1β. Analysis of TI‐PCA and DyNA at later time points showed the emergence of IL‐5, IL‐6, and IFNγ as additional key mediators of inflammation. Furthermore, DyNA network complexity rose and fell before peaking at 9.5 h following CYP treatment. This pattern of inflammation may mimic the fluctuating severity of inflammation associated with IC/BPS flares.ConclusionsComputational analysis of inflammation networks in experimental IC/BPS analysis expands on the previously accepted inflammatory signatures of IC by adding IL‐5, IL‐18, and MCP‐1 to the prior studies implicating IL‐6 and GRO as IC/BPS biomarkers. This analysis supports a complex evolution of inflammatory networks suggestive of the rise and fall of inflammation characteristic of IC/BPS flares.

Funder

National Institute of Diabetes and Digestive and Kidney Diseases

Publisher

Wiley

Subject

Urology,Neurology (clinical)

Reference36 articles.

1. Pathophysiology of interstitial cystitis

2. Epidemiologic Issues in Interstitial Cystitis

3. Clinical guidelines for interstitial cystitis/bladder pain syndrome

4. Interstitial cystitis and endometriosis in patients with chronic pelvic pain: the “Evil Twins” syndrome;Chung MK;JSLS J Soc Laparoendo Surg,2005

5. Stimulated whole blood cytokine/chemokine responses are associated with interstitial cystitis/bladder pain syndrome phenotypes and features of nociplastic pain: a MAPP research network study;Schrepf A;Pain,2022

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