Gene-environment “amplification” of liver stiffness requires more clinically meaningful analytic approaches

Gene-environment "amplification" of liver stiffness requires more clinically meaningful analytic approachesTo the Editor:We read with great interest the recent work by Gensluckner et al., who sought to address a clinically important question as to whether common risk variants in PNPLA3 and TM6SF2 amplify the fibrotic impact of alcohol and metabolic dysfunction. 1 The biological premise is compelling, and the authors use interaction models to show larger increases in liver stiffness with worsening metabolic injury or alcohol use among risk-allele carriers.However, two analytical issues reduce the clinical interpretability of the current results and, in our view, are fixable.First, the endpoint.Liver stiffness measurement (LSM) was modeled as a log-transformed continuous variable without anchoring effects to validated fibrosis stages.Because care pathways are stage-driven, readers need to know whether gene-environment interactions translate into crossing actionable thresholds (e.g.> -8 kPa to rule in suspected advanced fibrosis and > -12 kPa to rule in likely advanced fibrosis 2 ).Reexpressing the interactions between gene and environment effects as absolute/relative differences in the probability of clinically meaningful thresholds of LSM would better align the results with clinical practice.Second, a major confounding factor of LSM was overlooked: the status of hepatic inflammation or surrogate markers, namely aminotransferases.Omitting aminotransferases from multivariable models and interaction terms risks attributing inflammation-related stiffness to genetic amplification.We suggest adding clinically accessible lab values, such as ALT and AST to the covariate set, modeling potential nonlinearity, and conducting sensitivity analyses that exclude marked transaminase spikes.In sum, the study's central message -that PNPLA3/ TM6SF2 act as amplifiers rather than independent drivers -is biologically plausible and clinically relevant.Tethering LSM changes to stage-linked thresholds and accounting for inflammation would move the findings from statistically interesting to clinically directive, clarifying when adding genetics meaningfully changes risk communication or management.