Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Nov:157:85-92.
doi: 10.1016/j.urology.2021.05.005. Epub 2021 May 17.

Diagnostic Utility of Serum and Urinary Metabolite Analysis in Patients with Interstitial Cystitis/Painful Bladder Syndrome

Jayoung Kim  1 , Amanda De Hoedt  2 , Emily Wiggins  2 , Kelsey Haywood  2 , Peng Jin  1 , Bennett Greenwood  3 , Niven R Narain  3 , Vladimir Tolstikov  3 , Valerie Bussberg  3 , Kamil E Barbour  4 , Michael A Kiebish  3 , Stephen J Freedland  1 , Jennifer T Anger  5
Affiliations

Diagnostic Utility of Serum and Urinary Metabolite Analysis in Patients with Interstitial Cystitis/Painful Bladder Syndrome

Jayoung Kim et al. Urology. 2021 Nov.

Abstract

Objective: To identify the potential biomarkers of interstitial cystitis/painful bladder syndrome (IC), a chronic syndrome of bladder-centric pain with unknown etiology that has an adverse impact on quality of life, we analyzed the urine and serum metabolomes of a cohort of IC patients and non-disease controls (NC).

Methods: Home collection of serum and urine samples was obtained from 19 IC and 20 NC females in the Veterans Affairs (VA) Health Care System. IC was diagnosed independently by thorough review of medical records using established criteria. Biostatistics and bioinformatics analyses, including univariate analysis, unsupervised clustering, random forest analysis, and metabolite set enrichment analysis (MSEA), were then utilized to identify potential IC biomarkers.

Results: Metabolomics profiling revealed distinct expression patterns between NC and IC. Random forest analysis of urine samples suggested discriminators specific to IC; these include phenylalanine, purine, 5-oxoproline, and 5-hydroxyindoleacetic acid. When these urinary metabolomics-based analytes were combined into a single model, the AUC was 0.92, suggesting strong potential clinical value as a diagnostic signature. Serum-based metabolomics did not provide potential IC discriminators.

Conclusion: Analysis of serum and urine revealed that women with IC have distinct metabolomes, highlighting key metabolic pathways that may provide insight into the pathophysiology of IC. The findings from this pilot study suggest that integrated analyses of urinary metabolites, purine, phenylalanine, 5-oxoproline, and 5-HIAA, can lead to promising IC biomarkers for pathophysiology of IC. Validation of these results using a larger dataset is currently underway.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest.

Some of authors declare conflict of interest. B.G., N.N., V.B., V.T., and M.K. are employees of BERG Health. The other authors have nothing to disclose.

Figures

Figure 1.
Figure 1.. Metabolic Biomarker Analysis of Serum Samples.
(A) A volcano plot shows differentially expressed metabolites (DEMs) between IC and NC samples. Univariate analysis was performed. (C) Top 15 discriminators by random forest analysis. (B) Enrichment overview of the top 50 DEMs in IC samples compared to NC, and the metabolic pathways associated with the metabolite sets.
Figure 2.
Figure 2.. Metabolomic Biomarker Analysis of Urine Samples.
(A) A volcano plot showing DEMs between IC and NC samples. Univariate analysis was performed. (B) Enrichment overview of the top 50 DEMs in IC compared to NC, and the metabolic pathways associated with the metabolite sets.
Figure 3.
Figure 3.. Statistical Consideration of Potential Urinary Biomarkers.
(A) Top 4 ranked differentially expressed analytes. (B) Area under the curve (AUC) analysis of the top 4 analytes. Y-axis shows AUC. X-axis illustrates either the NC or IC groups. (C) AUC of the potential biomarker panel, true positive rate (TPR) vs false positive rate (FPR). (D) AUC sensitivity and specificity calculations of the biomarker panel.
See this image and copyright information in PMC

Comment in

References

    1. Hanno PM, Erickson D, Moldwin R et al. : Diagnosis and treatment of interstitial cystitis/bladder pain syndrome: AUA guideline amendment. J Urol, 193: 1545, 2015 - PubMed
    1. Bogart LM, Berry SH, Clemens JQ: Symptoms of interstitial cystitis, painful bladder syndrome and similar diseases in women: a systematic review. J Urol, 177: 450, 2007 - PubMed
    1. Suskind AM, Berry SH, Ewing BA et al. : The prevalence and overlap of interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome in men: results of the RAND Interstitial Cystitis Epidemiology male study. J Urol, 189: 141, 2013 - PMC - PubMed
    1. Buffington CA: Re: Symptoms of interstitial cystitis, painful bladder syndrome and similar diseases in women: a systematic review: L. M. Bogart, S. H. Berry and J. Q. Clemens. J Urol 2007; 177: 450–456. J Urol, 178: 1121, 2007 - PubMed
    1. Hanno PM, Burks DA, Clemens JQ et al. : AUA guideline for the diagnosis and treatment of interstitial cystitis/bladder pain syndrome. J Urol, 185: 2162, 2011 - PMC - PubMed