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We sincerely appreciate the thoughtful editorial by Dr. Nam and Lee and are grateful for their insightful comments on our study evaluating a steatosis-related polygenic risk score (PRS) for hepatocellular carcinoma (HCC) risk following sustained virological response (SVR) to direct-acting antiviral therapy [1]. In the post-SVR setting, the risk of HCC is not completely eliminated [2, 3], and our study is the first to report the potential utility of PRS-5 for HCC risk stratification. Dr. Nam and Lee appropriately highlighted important considerations regarding the translation of genetic associations into clinical practice [4], and we appreciate the opportunity to address these issues. PRS aggregates the effects of multiple genetic variants into a single quantitative measure of inherited susceptibility and may be useful for population-level risk stratification. Because germline variants remain constant throughout life, PRS reflects lifelong susceptibility and provides a stable baseline risk that is not influenced by disease progression, treatment response or fluctuations in clinical biomarkers. However, several barriers must be addressed before PRS can be widely implemented in practice. These include heterogeneity in PRS reporting, challenges in selecting appropriate models, limited generalizability across populations and the lack of established clinical workflows or practice guidelines for PRS integration [5]. Accordingly, although our findings suggest that PRS-5 may contribute to HCC risk stratification after HCV eradication, several steps are needed before clinical translation. These include the definition of actionable risk thresholds, integration of PRS with established clinical predictors to generate absolute risk estimates, and external validation in multicentre cohorts. Ultimately, prospective studies are needed to determine whether PRS-informed surveillance improves early HCC detection and increases opportunities for curative treatment. Defining actionable risk thresholds for HCC surveillance is essential before clinical implementation. For example, in the development of the REACH-B score for chronic hepatitis B, viral load thresholds were rigorously defined and validated before being translated into clinically applicable risk scores [6]. Similar strategies have been proposed for PRS, including percentile-based classification, relative risk estimation and absolute risk modelling [7]. These approaches have also begun to inform clinical decision-making in other fields, such as cardiovascular prevention [8]. However, due to limited event numbers, many PRS studies rely on cohort-specific percentile stratification, which may limit generalizability [9]. A similar challenge exists in HCC risk prediction, as no universal PRS cut-off has been established in prior studies or current guidelines. In our study, restricted cubic spline analysis suggested a potential inflection point that may help identify a higher-risk subgroup; however, larger cohorts are required to determine optimal thresholds more precisely. Our study was conducted in a single-centre cohort; therefore, future studies should prioritise external validation in multicentre cohorts with diverse ancestral backgrounds, as genetic susceptibility may vary by ancestry and environmental exposures [10]. Furthermore, validation may be particularly valuable in clinically ambiguous subgroups. For example, our subgroup analyses indicated that PRS-5 retains predictive value in patients with FIB-4 < 3.25 or without cirrhosis, populations in whom optimal HCC surveillance strategies remain uncertain. Ensuring appropriate calibration and transportability across populations will be essential before broader clinical implementation. The authors' declarations of personal and financial interests are unchanged from those in the original article [1]. Yu-Sheng Lin: conceptualization, writing – original draft. Hwai-I Yang: conceptualization, supervision. Teng-Yu Lee: conceptualization, supervision, writing – original draft, writing – review and editing. The authors have nothing to report. T.Y. Lee: research support from Gilead, Merck and Roche diagnostics; consultant of BMS, Gilead and AstraZeneca; and speaker of Abbvie, BMS, Eisai, Gilead, Roche and AstraZeneca. This article is linked to Lin et al papers. To view these articles, visit https://doi.org/10.1111/apt.70566 and https://doi.org/10.1111/apt.70606. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.