Evidence map›Paper›PMID 42116030›Full record

ArticleBMC urology2026

Urinary adhesion molecules with ERK signaling as predictive biomarkers for kidney stones: a pilot study.

Yi-Shiou Tseng, Hsing-I Tseng, Shang-Jen Chang, Po-Wen Ku, Jiann-Ming Wu, Huei-Pin Lai, Ting-Hui Chang, Yuan-Ju Lee

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Article in BMC urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yi-Shiou Tseng *Division of Urology, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan. femh87004@femh.org.tw.
Hsing-I Tseng *Division of Urology, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Shang-Jen ChangDepartment of Urology, National Taiwan University Hospital, Taipei, Taiwan.
Po-Wen KuDivision of Urology, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Jiann-Ming WuDivision of General Surgery, Department of Surgery, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Huei-Pin LaiDivision of Endocrinology and Metabolism, Department of Internal Medicine, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Ting-Hui ChangDivision of Allergy Immunology and Rheumatology, Department of Internal Medicine, Far Eastern Memorial Hospital, New Taipei, Taiwan.
Yuan-Ju LeeDepartment of Urology, National Taiwan University Hospital, Taipei, Taiwan. leeyuanju@ntuh.gov.tw.

Funding

Far Eastern Memorial Hospital and National Taiwan University Hospital 113-FTN0014
6 · The paper itself

Abstract

backgroundNoninvasive diagnostic biomarkers should be researched to reduce the need for imaging and radiation exposure in patients with kidney stone disease. This pilot study aimed to evaluate the diagnostic potential of urinary p-ERK/t-ERK (inflammatory signaling), osteopontin, CD44, and annexin II (adhesion molecule) levels in predicting kidney stone disease.

methodsThirty-seven participants were enrolled: 20 with and 17 without the disease. Spot urine samples were collected for crystal count and biochemical analyses. Enzyme-linked immunosorbent assay was performed to measure p-ERK/t-ERK in urine sediment and urinary osteopontin, CD44, and annexin II levels. Pearson's correlation and receiver operating characteristic curve analyses were used to assess the correlations and diagnostic values of these biomarkers.

resultsThe stone group showed significantly higher levels of p-ERK1/2 activity and urinary adhesion proteins (osteopontin, CD44, and annexin II) compared with those in the non-stone group. Receiver operating characteristic curve analysis revealed that these biomarkers could moderately distinguish between stone and non-stone groups. A multivariable logistic model combining CD44², ERK/CD44, and CD44/annexin II demonstrated enhanced discriminatory potential, achieving an AUC-ROC of 0.88. Additionally, annexin II levels showed a weak positive correlation with stone number and could distinguish patients with three or more stones from those with fewer.

conclusionsThis is the first study to reveal the concurrent elevation of ERK-related inflammatory signaling and urinary adhesion molecules in association with kidney stone disease. These markers could serve as potential candidate biomarkers for non-invasive diagnosis and disease monitoring. Our findings offer preliminary insights into the pathophysiology of kidney stones and may aid in future diagnostic development.

Indexed as

Annexin A2Cell Adhesion MoleculesHyaluronan ReceptorsKidney CalculiMAP Kinase Signaling SystemOsteopontinAdultBiomarkersFemaleHumansMaleMiddle AgedPilot ProjectsPredictive Value of TestsAnnexin A2BiomarkersCD44 protein, humanCell Adhesion MoleculesHyaluronan ReceptorsOsteopontinBiomarkersCell adhesion moleculesExtracellular Signal-Regulated MAP KinasesUrinalysisUrolithiasis

Identifiers

PMID42116030
PMCPMC13371508

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.