Identification of diagnostic serum biomarkers for Hunner-type interstitial cystitis

IF 1.5 4区 医学 Q3 UROLOGY & NEPHROLOGY LUTS: Lower Urinary Tract Symptoms Pub Date : 2022-03-20 DOI:10.1111/luts.12439
Kazumasa Torimoto, Tomohiro Ueda, Masato Kasahara, Akihide Hirayama, Chie Matsushita, Yoshihiro Matsumoto, Daisuke Gotoh, Yasushi Nakai, Makito Miyake, Katsuya Aoki, Kiyohide Fujimoto
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引用次数: 1

Abstract

Objectives

Diagnosis of Hunner-type interstitial cystitis (HIC) relies on the ability to identify Hunner lesions endoscopically, which can lead to storage symptom misdiagnosis. Here, we examined serum biomarkers for HIC and verified their utility.

Methods

Based on the previous definition of the Japanese guidelines, which did not distinguish HIC and non-HIC diseases, we searched for serum biomarkers in 25 patients with interstitial cystitis (IC) and 25 control participants using metabolomics during 2013–2014. In 2019, we conducted a validation study in HIC and control groups. Serum samples were analyzed using liquid chromatography–tandem mass spectrometry, and candidate biomarker concentrations were compared between the groups using Mann–Whitney test.

Results

Metabolomics targeted 678 metabolites and revealed that the levels of 14 lysolipids, seven γ-glutamyl amino acids, and two monoacylglycerols were significantly different between the IC and control groups. The following metabolites were selected from each metabolite category as candidates: 1-linoleoylglycerophosphocholine (1-linoleloyl-GPC [18:2]), γ-glutamylisoleucine (γ-Glu-Ile), and 1-arachidonylglycerol (1-AG). The serum concentrations of 1-linoleoyl-GPC (18:2) in the HIC and control groups were 27 920 ± 6261 and 40 360 ± 1514 ng/mL (P = 0.0003), respectively. The serum concentrations of γ-Glu-Ile and 1-AG were not significantly different between the groups. When the cut-off value of 1-linoleoyl-GPC (18:2) was set at 28 400 ng/mL, the sensitivity and specificity were 68% and 84%, respectively.

Conclusions

Serum 1-linoleoyl-GPC (18:2) is a candidate diagnostic biomarker for HIC. Additional studies on whether this biomarker can distinguish HIC from other diseases with high urination frequency are required for its clinical use.

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hunner型间质性膀胱炎诊断血清生物标志物的鉴定
目的Hunner型间质性膀胱炎(HIC)的诊断依赖于Hunner病变的内镜识别能力,而Hunner病变可能导致储存症状的误诊。在这里,我们检查了HIC的血清生物标志物并验证了它们的实用性。方法基于日本指南之前的定义,没有区分HIC和非HIC疾病,我们在2013-2014年期间使用代谢组学方法检索了25例间质性膀胱炎(IC)患者和25名对照参与者的血清生物标志物。2019年,我们在HIC组和对照组中进行了验证研究。采用液相色谱-串联质谱法分析血清样品,采用Mann-Whitney检验比较各组候选生物标志物浓度。结果代谢组学检测了678种代谢物,发现14种溶脂、7种γ-谷氨酰氨基酸和2种单酰基甘油的水平在IC组与对照组之间存在显著差异。从每个代谢物类别中选择以下代谢物作为候选代谢物:1-亚麻油酰甘油酰胆碱(1-亚麻油酰- gpc [18:2]), γ-谷氨酰异亮氨酸(γ-Glu-Ile)和1-花生四烯酰基甘油(1-AG)。HIC组和对照组血清1-亚油酰- gpc(18:2)浓度分别为27 920±6261和40 360±1514 ng/mL (P = 0.0003)。血清γ-Glu-Ile和1-AG浓度各组间无显著差异。当1-亚油基- gpc(18:2)的临界值为28 400 ng/mL时,敏感性为68%,特异性为84%。结论血清1-亚油酰gpc(18:2)是HIC的候选诊断生物标志物。该生物标志物是否能将HIC与其他尿频高的疾病区分开来,尚需进一步研究以供临床使用。
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来源期刊
LUTS: Lower Urinary Tract Symptoms
LUTS: Lower Urinary Tract Symptoms UROLOGY & NEPHROLOGY-
CiteScore
3.00
自引率
7.70%
发文量
52
审稿时长
>12 weeks
期刊介绍: LUTS is designed for the timely communication of peer-reviewed studies which provides new clinical and basic science information to physicians and researchers in the field of neurourology, urodynamics and urogynecology. Contributions are reviewed and selected by a group of distinguished referees from around the world, some of whom constitute the journal''s Editorial Board. The journal covers both basic and clinical research on lower urinary tract dysfunctions (LUTD), such as overactive bladder (OAB), detrusor underactivity, benign prostatic hyperplasia (BPH), bladder outlet obstruction (BOO), urinary incontinence, pelvic organ prolapse (POP), painful bladder syndrome (PBS), as well as on other relevant conditions. Case reports are published only if new findings are provided. LUTS is an official journal of the Japanese Continence Society, the Korean Continence Society, and the Taiwanese Continence Society. Submission of papers from all countries are welcome. LUTS has been accepted into Science Citation Index Expanded (SCIE) with a 2011 Impact Factor.
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