Rethinking FIB-4: The hidden zonal bias in alpha-1 antitrypsin deficiency

INTRODUCTION Noninvasive fibrosis scores, particularly Fibrosis-4 (FIB-4), are widely used in hepatology due to their accessibility and simplicity.1 The FIB-4 index combines age, AST, platelet count, and ALT into a formula validated primarily in hepatitis C and metabolic dysfunction–associated steatotic liver disease, which typically cause zone III (centrilobular) hepatocyte injury and transaminase elevation.1,2 In contrast, alpha-1 antitrypsin deficiency (AATD) represents a distinct pattern of injury, with fibrosis originating in zone I (periportal) hepatocytes due to intracellular retention of Z-type alpha-1 antitrypsin polymers.3 This pathogenesis is often not associated with overt hepatocyte necrosis, and consequently, serum ALT levels may remain within or near normal limits even in the presence of significant fibrosis. This short communication highlights a systematic underestimation of fibrosis in AATD when using FIB-4, due to a zonal mismatch between disease biology and biomarker dynamics. ZONAL MISMATCH AND DIAGNOSTIC LIMITATIONS While ALT is most abundant in zone I hepatocytes, its serum elevation depends on membrane disruption or necrosis. In AATD, the hepatocytes may be dysfunctional but intact—leading to a disconnect between tissue injury and ALT levels.4 This creates a double-layered flaw in the FIB-4 model: Biological mismatch: Fibrosis is present, but ALT does not reflect it. Mathematical suppression: Since ALT appears in the denominator, even mildly elevated or normal values will artificially depress the score. FIB-4=(Age×AST)/(Plateletcount×√ALT). Thus, in AATD—a zone I-dominant disease—ALT remains low not due to lack of injury, but because affected hepatocytes retain membrane integrity. This, coupled with ALT’s position in the denominator, systematically depresses FIB-4 scores.4,5 CLINICAL AND RESEARCH IMPLICATIONS Clinicians should be cautious when using FIB-4 in AATD and consider integrating elastography-based methods such as transient elastography or shear-wave elastography for fibrosis assessment.5 Additionally, fibrosis scores should be revalidated or modified in diseases with nonclassical zonation, where ALT and AST release do not reflect the extent of underlying fibrosis. CONCLUSIONS The assumption that ALT reliably mirrors fibrosis—embedded in formulas like FIB-4—fails in AATD. Here, the disease’s zone I injury profile, coupled with ALT’s denominator role, leads to an intrinsic diagnostic blind spot. Addressing this requires recalibrating our fibrosis tools to align with the spatial biology of liver disease. Zonal awareness may be the next frontier in refining noninvasive diagnostics for genetic and atypical hepatopathies in diseases with atypical spatial patterns of injury.