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

Authors
 Kim, Dong Yun  ;  Zhang, Hyun-Soo  ;  Lee, Jae Seung  ;  Lee, Hye Won  ;  Kim, Mi Na  ;  Kim, Beom Kyung  ;  Kim, Seung Up  ;  Kim, Do Young  ;  Ahn, Sang Hoon  ;  Lee, Hyun Woong  ;  Gee, Heon Yung  ;  Lee, Jung Il  ;  Park, Jun Yong 
Citation
 JHEP REPORTS, Vol.8(2), 2026-02 
Article Number
 101713 
Journal Title
JHEP REPORTS
ISSN
 2589-5559 
Issue Date
2026-02
Keywords
Metabolic Dysfunction-Associated Steatotic Liver Disease ; Genotypes ; Advanced Fibrosis ; Non-Invasive Tests ; Decision Curve Analysis ; Type 2 diabetes mellitus
Abstract
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). Herein, we investigated whether incorporating genetic information regarding PNPLA3 and TM6SF2 into existing non-invasive fibrosis scoring systems could improve their 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 single nucleotide polymorphisms. 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 increase: 0.053, p = 0.001) and FIB-4 (AUROC increase: 0.058, p = 0.010), while Agile 3+ showed a favorable trend (AUROC increase: 0.016, p = 0.058). Conclusions: Incorporating PNPLA3 and TM6SF2 genetic information into non-invasive fibrosis scoring systems for MASLD provides limited but measurable improvements, with statistically significant AUROC gains for NFS and FIB-4, particularly among patients with T2DM. Further validation is required before routine clinical implementation can be recommended. (c) 2025 The Authors. Published by Elsevier B.V. on behalf of European Association for the Study of the Liver (EASL). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Files in This Item:
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DOI
10.1016/j.jhepr.2025.101713
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Pharmacology (약리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
Yonsei Authors
Kim, Do Young(김도영)
Kim, Dong Yun(김동윤) ORCID logo https://orcid.org/0000-0002-2471-3385
Kim, Mi Na(김미나)
Kim, Beom Kyung(김범경) ORCID logo https://orcid.org/0000-0002-5363-2496
Kim, Seung Up(김승업) ORCID logo https://orcid.org/0000-0002-9658-8050
Park, Jun Yong(박준용) ORCID logo https://orcid.org/0000-0001-6324-2224
Ahn, Sang Hoon(안상훈) ORCID logo https://orcid.org/0000-0002-3629-4624
Lee, Jae Seung(이재승) ORCID logo https://orcid.org/0000-0002-2371-0967
Lee, Jung Il(이정일) ORCID logo https://orcid.org/0000-0002-0142-1398
Lee, Hyun Woong(이현웅) ORCID logo https://orcid.org/0000-0002-6958-3035
Lee, Hye Won(이혜원) ORCID logo https://orcid.org/0000-0002-3552-3560
Zhang, Hyun-Soo(장현수)
Gee, Heon Yung(지헌영) ORCID logo https://orcid.org/0000-0002-8741-6177
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/211195
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