Temporally complex inflammatory networks in an animal model reveal signatures for interstitial cystitis and bladder pain syndrome phenotype.
Temporally complex inflammatory networks in an animal model reveal signatures for interstitial cystitis and bladder pain syndrome phenotype.
复制标题
动物模型中的时间复杂炎症网络揭示了间质性膀胱炎和膀胱疼痛综合征表型的特征。
DOI：
10.1002/nau.25267
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发表时间：
2023
影响因子：
2
通讯作者：
Tyagi,Pradeep
中科院分区：
文献类型：
--
作者：
Shah,AshtiM;Vodovotz,Yoram;Yoshimura,Naoki;Chermansky,ChristopherJ;Fitzgerald,Jocelyn;Tyagi,Pradeep
简介和目的间质性膀胱炎和膀胱疼痛综合征 (IC/BPS) 表现为使膀胱疼痛衰弱的症状，通常是排除性诊断。膀胱镜检测亨纳病灶增加了膀胱活检中检测组织炎症的可能性，并增加了抗炎药物治疗成功的几率。然而，由于目前缺乏 IC/BPS 替代生物标志物，该亚组的识别仍然具有挑战性。在识别 IC/BPS 生物标志物的过程中，我们利用释放到尿液中的炎症介质（细胞因子和趋化因子）的计算生物网络分析，在实验性 IC/BPS 啮齿动物模型中模拟了炎症的动态演变。生物网络分析的使用使我们能够识别可能是炎症驱动因素的尿蛋白，因此可以作为 IC/BPS 治疗的治疗靶点。 方法将接受环磷酰胺 (CYP) 注射 (150mg/kg) 的大鼠用作急性 IC/BPS 的实验模型 (n=≥8)。在 12 小时内收集大鼠每次排尿的尿液，并使用 Luminex™ 检测 13 种炎症介质。时间间隔主成分分析（TI-PCA）和动态网络分析（DyNA）这两种生物网络算法被用来识别IC/BPS随时间变化的炎症特征生物标志物。结果与载体治疗的大鼠相比，CYP治疗的大鼠尿液中几乎所有炎症介质均显着升高（p<0.05）。 TI-PCA 强调 GRO-KC、IL-5、IL-18 和 MCP-1 是炎症反应中最大差异的原因。在早期时间点，DyNA 表明 IL-4 和 IL-1β 之间以及 TNF-α 和 IL-1β 之间呈正相关。稍后时间点的 TI-PCA 和 DyNA 分析显示，IL-5、IL-6 和 IFNγ 出现作为炎症的额外关键介质。此外，DyNA 网络复杂性在 CYP 处理后 9.5 小时达到峰值之前有所上升和下降。这种炎症模式可能模仿与 IC/BPS 耀斑相关的炎症严重程度的波动。结论实验性 IC/BPS 分析中炎症网络的计算分析通过将 IL-5、IL-18 和 MCP-1 添加到先前将 IL-6 和 GRO 作为 IC/BPS 生物标志物的研究中，扩展了先前接受的 IC 炎症特征。该分析支持炎症网络的复杂演化，表明 IC/BPS 耀斑炎症特征的升降。
Introduction 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.