Noninvasive Detection of Occult yet Significant Liver Pathology in Alanine Aminotransferase-Normal Chronic Hepatitis

Xinjie Li1, Meijie Shi2, Xiaozhong Wang3

  • 1Department of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University, Beijing, China.

PubMed

Insights

New biomarkers like CK18-M65 can detect significant liver disease in chronic hepatitis B patients with normal ALT levels. These non-invasive tools aid in risk stratification and may reduce the need for liver biopsies.

Area of Science:

  • Hepatology
  • Biomarker Discovery
  • Diagnostic Technologies

Background:

  • Chronic hepatitis B (CHB) poses diagnostic challenges due to potential occult liver pathology despite normal alanine aminotransferase (ALT) levels.
  • Accurate detection of significant liver pathology in these patients is crucial for timely intervention.

Purpose of the Study:

  • To identify and validate non-invasive biomarkers for detecting significant liver pathology in CHB patients with normal ALT.
  • To evaluate the diagnostic performance of novel biomarkers and their combinations.

Main Methods:

  • A multicenter study enrolled 390 treatment-naïve CHB patients (137 HBeAg+, 253 HBeAg-) with normal ALT (≤40 U/L).
  • Liver biopsy was performed as the gold standard; novel biomarkers (CK18-M30, CK18-M65, GP73, IL-10, IL-2R) were measured.
  • Machine learning algorithms evaluated 16 biomarker combinations for detecting significant liver pathology (inflammation/fibrosis grade/stage ≥2).

Main Results:

  • Significant liver pathology was found in 45.2% of HBeAg+ and 46% of HBeAg- CHB cases.
  • CK18-M65, CK18-M30, and GP73 strongly correlated with liver pathology severity, independent of ALT.
  • The optimal biomarker combination (CK18-M65+CK18-M30+GP73) achieved superior diagnostic accuracy (AUROC=0.942) compared to existing non-invasive scores.

Conclusions:

  • CK18-M65-centered biomarker models show promise as non-invasive tools for detecting occult liver pathology in ALT-normal CHB patients.
  • These models can aid in risk stratification and potentially reduce unnecessary liver biopsies.
  • Further validation in larger cohorts is warranted to confirm clinical utility.
Abstract