Dear Editor,
We thanked Kim et al. for their insightful editorial entitled “Rethinking lean metabolic dysfunction-associated steatotic liver disease: unrecognized risk in lean populations” [1,2]. Their work clarifies the complexity of the “lean phenotype” and highlights potential bias in disease burden estimates during the conceptual shift from nonalcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated steatotic liver disease (MASLD). This underscores our conclusion that caution is required when applying historical data based on lean NAFLD to the current lean MASLD, as the transition results in incomplete overlap between the two populations, especially in community settings. We fully acknowledge the authors’ critical concerns regarding the lean phenotype within the steatotic liver disease (SLD) spectrum and would like to take this opportunity to respond.
The editorial correctly notes that lean NAFLD actually comprises distinct subgroups, including metabolically healthy individuals with incidental SLD (cryptogenic SLD), centrally obese but normal-body mass index (BMI) patients at high cardiometabolic risk, and severely ill individuals who lost weight. To accurately estimate the risk of all-cause mortality in this heterogeneous population, we adjusted for confounding factors such as age and extrahepatic diseases in our analyses. Nevertheless, unmeasured confounders could still exist and multivariable adjustment could not account for the impact of residual confounding. Nevertheless, our results align with other studies [3], indicating the “obesity paradox” phenomenon as observed in other chronic diseases [4].
We appreciate the authors’ insights extending from this phenomenon. Specifically, there is a subset within the normal-weight MASLD population who present with central obesity, sarcopenia, or systemic illness. This distinct phenotype is intrinsically linked to insulin resistance and metabolic dysfunction [5] that significantly elevates mortality risk. Therefore, the validation of non-invasive tests for fibrosis detection and risk stratification is crucial in this specific subgroup. Given that transient elastography is likely to be accurate in lean individuals due to the absence of excess percutaneous fat [6], the observed discrepancy between FIB-4 and fibrosis by histology or transient elastography may be more attributable to the limited accuracy of FIB-4 for this unique cohort.
Furthermore, BMI alone may be an inadequate triage tool to differentiate MASLD phenotypes, as it is unable to distinguish between percutaneous and abdominal adiposity. Acknowledging this, the Lancet Diabetes & Endocrinology Commission defined “clinical obesity” as a chronic, systemic illness due to excess adiposity, requiring confirmation either via direct body fat measurement or anthropometric waist-centered criteria in addition to BMI [7]. Evidence from nationwide cohorts suggests waist-based measures correlate more closely with hepatic steatosis and fibrosis, providing a superior prognostic value in MASLD.8 Future studies are warranted to characterize the long-term impact of body composition on outcomes, and appropriate measurements to establish objective phenotype classifications for MASLD.
In summary, the editorial by Kim et al. effectively summarizes our major findings while raising critical points regarding the distinct subgroups embedded in the lean NAFLD, the potentially limited utility of non-invasive tests, and the significance of waist-based measures in defining lean and non-lean phenotypes. Lean MASLD should be treated as a distinct clinical target requiring optimized definition strategies and potentially, phenotype-specific management.
Abbreviations
- BMI
body mass index
- MASLD
metabolic dysfunction-associated steatotic liver disease
- NAFLD
non-alcoholic fatty liver disease
- SLD
steatotic liver disease
Footnotes
Authors’ contribution
The authors contributed equally to the literature review and drafting of the manuscript. They all approved the final version of the manuscript.
Conflicts of Interest
Song SJ and Jun DW had no conflicts of interest to declare. Terry Yip has served as an advisory committee member for Gilead Sciences and GSK, and a speaker for Gilead Sciences. He has received a research grant from Gilead Sciences. Vincent Wong served as a consultant or advisor for AbbVie, AstraZeneca, Boehringer Ingelheim, Echosens, Eli Lilly, Gilead Sciences, Merck, Novartis, Novo Nordisk, Pfizer, Roche Diagnostics, and TARGET PharmaSolutions; a speaker for Abbott, AbbVie, AstraZeneca, Echosens, Gilead Sciences, and Novo Nordisk; an independent non-executive director for Furui; and a co-founder of Illuminatio Medical Technology. He has received a research grant from Gilead Sciences.
REFERENCES
- 1.Song SJ, Yoon EL, Wong VW, Jo AJ, Wong GL, Lai JC, et al. Normal-weight metabolic dysfunction-associated steatotic liver disease: reclassification, characteristics, and adverse liver outcomes across diverse populations. Clin Mol Hepatol. 2026;32:646–660. doi: 10.3350/cmh.2025.0851. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Kim D, Shenoy A, Ahmed A. Rethinking lean metabolic dysfunction-associated steatotic liver disease: Unrecognized risk in lean populations: Editorial on “Normal-weight metabolic dysfunction-associated steatotic liver disease: Reclassification, characteristics, and adverse liver outcomes across diverse populations”. Clin Mol Hepatol. 2026;32:1441–1443. doi: 10.3350/cmh.2026.0056. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Danpanichkul P, Suparan K, Prasitsumrit V, Ahmed A, Wijarnpreecha K, Kim D, et al. Long-term outcomes and risk modifiers of metabolic dysfunction-associated steatotic liver disease between lean and non-lean populations. Clin Mol Hepatol. 2025;31:74–89. doi: 10.3350/cmh.2024.0631. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Elsabaawy M. Liver at crossroads: unraveling the links between obesity, chronic liver diseases, and the mysterious obesity paradox. Clin Exp Med. 2024;24:240. doi: 10.1007/s10238-024-01493-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Vesković M, Šutulović N, Hrnčić D, Stanojlović O, Macut D, Mladenović D, et al. The interconnection between hepatic insulin resistance and metabolic dysfunction-associated steatotic liver disease-the transition from an adipocentric to liver-centric approach. Curr Issues Mol Biol. 2023;45:9084–9102. doi: 10.3390/cimb45110570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Wong VW, Irles M, Wong GL, Shili S, Chan AW, Merrouche W, et al. Unified interpretation of liver stiffness measurement by M and XL probes in non-alcoholic fatty liver disease. Gut. 2019;68:2057–2064. doi: 10.1136/gutjnl-2018-317334. [DOI] [PubMed] [Google Scholar]
- 7.Rubino F, Cummings DE, Eckel RH, Cohen RV, Wilding JPH, Brown WA, et al. Definition and diagnostic criteria of clinical obesity. Lancet Diabetes Endocrinol. 2025;13:221–262. doi: 10.1016/S2213-8587(24)00316-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yeo YH, Zhu Y, Gao J, Liu S, Ni W, Rui F, et al. Anthropometric measures and mortality risk in individuals with metabolic dysfunction-associated steatotic liver disease (MASLD): A population-based cohort study. Aliment Pharmacol Ther. 2025;62:168–179. doi: 10.1111/apt.70174. [DOI] [PubMed] [Google Scholar]