# MiR−33 as a novel diagnostic biomarker for distinguishing cholesterol from adenomatous polyps: a case-control study

## TL;DR

This study explores miR-33 as a potential biomarker to distinguish cholesterol from adenomatous gallbladder polyps, aiming to reduce unnecessary surgeries.

## Contribution

The study identifies miR-33 as a novel diagnostic biomarker for differentiating cholesterol and adenomatous polyps.

## Key findings

- MiR-33a levels and the miR-33a/miR-33b ratio were significantly lower in cholesterol polyps.
- A predictive model using miR-33 achieved 88.5% accuracy in diagnosing adenomatous polyps.
- Decreased miR-33b and elevated miR-33a/miR-33b ratio are independent risk factors for cholesterol polyps.

## Abstract

Cholecystectomy is often excessively utilized in the management of gallbladder polyps. It is crucial to effectively differentiate between adenomatous and cholesterol polyps to reduce unnecessary cholecystectomies. This study aimed to investigate the potential of miR−33 as a novel diagnostic biomarker for distinguishing cholesterol from adenomatous polyps. Gallbladder specimens were retrospectively collected from gallbladder polyp patients who underwent laparoscopic cholecystectomy at the Second Department of General Surgery, Dongzhimen Hospital, Beijing University of Traditional Chinese Medicine, between June 2021 and December 2021. Pathological analysis categorized the specimens into two groups: the cholesterol polyp group (n = 13) and the adenomatous polyp group (n = 12). The expression levels of miR−33a and miR−33b in both groups were assessed using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). MiR-33a level and the miR-33a/miR-33b ratio were significantly lower in cholesterol polyps than in adenomatous polyps (p < 0.05). Spearman correlation analysis showed a strong positive correlation between miR-33a and miR-33b (r = 0.956, p < 0.001). Stepwise logistic regression analysis revealed that decreased miR-33b and elevated miR-33a/miR-33b ratio are independent risk factors for cholesterol polyps (p < 0.05). A predictive model was constructed, with the model’s AUC for diagnosing adenomatous polyps being 0.885 (95% CI: 0.753−1.000, p = 0.001), exhibiting a notable specificity of 84.62% and a sensitivity of 83.33% at a cut-off of 0.424. MiR−33 could serve as a novel diagnostic biomarker for distinguishing cholesterol from adenomatous polyps to facilitate the diagnosis and treatment of clinicians.