Reticulocalbin 3 as a novel biomarker for assessing liver disease severity and identifying decompensated status in cirrhosis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Decompensation in liver cirrhosis reduces survival and is driven by systemic inflammation and vascular dysfunction. Accurately diagnosing decompensated cirrhosis remains challenging due to the inherent subjectivity of traditional tools like the Child-Pugh score. In this prospectivity study conducted at a university-affiliated liver specialty hospital, we aimed to identify circulating biomarkers to refine diagnostic precision and establish an objective clinical framework. Through a rigorous selection pipeline-incorporating univariate analysis, correlation checks, and Least Absolute Shrinkage and Selection Operator (LASSO)-multivariate regression- Reticulocalbin 3 (RCN3), platelet-derived growth factor BB (PDGF-BB), and vascular cell adhesion molecule-1 (VCAM-1) were identified as key diagnostic indicators. Hepatocellular carcinoma (HCC) status was included as a critical covariate in all models to adjust for baseline imbalances as identified during the variable selection process. An integrated model combining these biomarkers with the Child-Pugh score achieved superior discriminative performance (AUC = 0.867), significantly outperforming the clinical baseline. Furthermore, to eliminate the inter-observer variability of clinical assessments, we developed an objective configuration by substituting subjective signs of ascites and encephalopathy with RCN3 alongside laboratory parameters (Total bilirubin, Serum Albumin, and Prothrombin Time) (AUC = 0.852). Our findings suggest that RCN3, PDGF-BB, and VCAM-1 provide critical insights into the pathophysiological state of cirrhosis. The proposed objective framework offers a standardized, reproducible alternative that optimizes cirrhosis staging while maintaining high diagnostic accuracy without clinical subjectivity.
Source: Scientific Reports
Language: English
Subfield: Hepatology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G6378820301
OpenAlex ID: W7165133222
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