Integration of PNPLA3 and TM6SF2 genotypes provides incremental improvement in advanced fibrosis prediction among MASLD patients with type 2 diabetes mellitus

作者：Dong Yun Kim, Hyun‐Soo Zhang, Jae Seung Lee, Hye Won Lee, Hye Won Lee, Beom Kyung Kim, Beom Kyung Kim, Seung Up Kim, Do Young Kim, Sang Hoon Ahn, Heon Yung Gee, Heon Yung Gee, Jung Il Lee, Jung Il Lee, Jun Yong Park · 发表于：JHEP Reports · 年份：2025 · DOI：10.1016/j.jhepr.2025.101713 · 被引用次数：2 · 研究领域：Liver Disease Diagnosis and Treatment、Diabetes, Cardiovascular Risks, and Lipoproteins、Genetic Associations and Epidemiology

Background & Aims Genetic information is not yet used for the clinical diagnosis of advanced fibrosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Here we investigated whether incorporating genetic information regarding PNPLA3 and TM6SF2 into existing non-invasive fibrosis scoring systems could enhance the predictive accuracy, particularly in patients with type 2 diabetes mellitus (T2DM), a high-risk population for MASLD-related complications. Methods Data were collected from a cohort of 637 patients with biopsy-proven MASLD. All participants underwent liver stiffness measurement (LSM), serum marker analysis, and genotyping for PNPLA3 (rs738409), TM6SF2 (rs58542926), and other relevant SNPs. We evaluated the benefit of adding genetic information to existing non-invasive tests (NITs)—including the Agile 3+, Fibrosis-4 (FIB-4) index, and NAFLD fibrosis score (NFS). Results Decision curve analysis in the validation cohort (n=238) demonstrated that incorporating PNPLA3 and TM6SF2 genetic information marginally enhanced net clinical benefit across all three models over a range of threshold probabilities (10-50%). At a 30% threshold probability, the net benefit of genotype-enhanced models increased from 22.0 to 22.8 per 100 patients for Agile 3+, from 17.0 to 18.4 for NFS, and from 13.0 to 16.9 for FIB-4. In the T2DM subgroup (n=121), genotype incorporation led to small but statistically significant improvements in discrimination for NFS (AUROC...