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. 2022 Mar 25:13:780855.
doi: 10.3389/fphar.2022.780855. eCollection 2022.

Defining Molecular Treatment Targets for Bladder Pain Syndrome/Interstitial Cystitis: Uncovering Adhesion Molecules

Guldal Inal-Gultekin  1 , Zeliha Gormez  2 , Naside Mangir  3
Affiliations

Defining Molecular Treatment Targets for Bladder Pain Syndrome/Interstitial Cystitis: Uncovering Adhesion Molecules

Guldal Inal-Gultekin et al. Front Pharmacol. .

Abstract

Bladder pain syndrome/interstitial cystitis (BPS/IC) is a debilitating pain syndrome of unknown etiology that predominantly affects females. Clinically, BPS/IC presents in a wide spectrum where all patients report severe bladder pain together with one or more urinary tract symptoms. On bladder examination, some have normal-appearing bladders on cystoscopy, whereas others may have severely inflamed bladder walls with easily bleeding areas (glomerulations) and ulcerations (Hunner's lesion). Thus, the reported prevalence of BPS/IC is also highly variable, between 0.06% and 30%. Nevertheless, it is rightly defined as a rare disease (ORPHA:37202). The aetiopathogenesis of BPS/IC remains largely unknown. Current treatment is mainly symptomatic and palliative, which certainly adds to the suffering of patients. BPS/IC is known to have a genetic component. However, the genes responsible are not defined yet. In addition to traditional genetic approaches, novel research methodologies involving bioinformatics are evaluated to elucidate the genetic basis of BPS/IC. This article aims to review the current evidence on the genetic basis of BPS/IC to determine the most promising targets for possible novel treatments.

Keywords: adhesion molecules; bioinformatics; gene expression; rare urinary disease; targeted treatment.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Gene Ontology (GO) and putative pathways of common upregulated DEGs in BPS/IC obtained for HLD vs. non-HLD, HLD vs. Ctrl, and non-HLD vs. Ctrl subgroup analysis. The GO terms were extracted from the Enrichr platform in the form of bar graphs for each subgroup analysis, in which the color and length of the bars decrease as the significance decreases. Significant (p-value < 0.05) GO terms were analyzed for (A) biological processes, (B) molecular functions, and (C) cellular components aspects, and (D) top 10 significant putative pathways predicted with the Enrichr platform obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG).
FIGURE 2
FIGURE 2
Gene Ontology (GO) and putative pathways of common downregulated DEGs in BPS/IC obtained for HLD vs. non-HLD, HLD vs. Ctrl, and non-HLD vs. Ctrl subgroup analysis. The GO terms were extracted from the Enrichr platform in the form of bar graphs for each subgroup analysis, in which the color and length of the bars decrease as the significance decreases. Significant (p-value < 0.05) GO terms were analyzed for (A) biological processes, (B) molecular functions, and (C) cellular components aspects, and (D) top 10 significant putative pathways predicted with the Enrichr platform obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG).
FIGURE 3
FIGURE 3
PPI network of common genes and hub genes were identified using Cytoscape and cytoHubba plug-in, respectively, for HLD vs. non-HLD, HLD vs. Ctrl, and non-HLD vs. Ctrl subgroup analysis. (A) Hub genes are colored from yellow to red, with red being the most important. (B) Expanded network with first-stage nodes of hub genes; from yellow to red color indicating higher importance for red hub genes; and blue nodes represent DEGs.
See this image and copyright information in PMC

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