Are ALT and AST released into the blood with hepatocellular injury and commonly elevated in MASLD?

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health burden, frequently heralded by changes in circulating liver enzymes.

Mechanistic explanations

• Membrane leakage: Hepatocytes highly concentrate alanine aminotransferase (ALT) and aspartate aminotransferase (AST) intracellularly. Hepatocellular injury from oxidative stress, lipotoxicity, or inflammation compromises membrane integrity, leading to enzyme leakage into the sinusoidal blood.
• Subcellular origins: ALT is predominantly cytosolic and highly liver-specific. AST exists in both the cytosol and mitochondria; its mitochondrial isoform is released during more severe, necrotic, or mitochondrial-targeting injuries.
• Lytic and non-lytic release: While frank necrosis and necroptosis cause rapid, passive diffusion via membrane rupture, sublethal injury and membrane blebbing can also permit transaminase leakage without immediate cell death.

Clinical evidence and implications

• Association with MASLD: Large-scale cohorts show elevated ALT and AST are common markers of hepatic necro-inflammatory activity. Reductions in transaminases (e.g., following weight loss or bariatric surgery) closely parallel MASH resolution and histological improvement.
• Diagnostic limitations: Elevated transaminases are not universal; a substantial portion of MASLD patients—even those with advanced fibrosis—present with normal ALT and AST. Isolated transaminase cutoffs show poor screening sensitivity.
• Risk stratification: International guidelines advise against using these enzymes as stand-alone diagnostic tools. Instead, ALT and AST are validated as essential inputs in multi-variable risk scores like the FIB-4 index or FAST score to assess fibrosis risk.

Bottom line

• ALT and AST are intracellular transaminases released into circulation via hepatocyte membrane disruption, acting as common but non-universal markers of injury in MASLD that are best utilized within composite, non-invasive risk algorithms rather than as stand-alone diagnostic tests.