Skip to content
DraconiticResearch
Search Sources API
224,303 studies31 sourcesUpdated 29 min ago
Peer-reviewedCC BY-NC 4.0Journal of Obesity & Metabolic Syndrome

Comparison of Data-Driven Phenotyping Systems for Metabolic Dysfunction-Associated Steatotic Liver Disease: Implications for Treatment Response

  • Ling Luo1
  • Congxiang Shao1
  • Tingfeng Wu2
  • Long Teng1
  • Jiaming Lai1
  • Shuyu Zhuo3
  • Zhi Dong4
  • Wei Wang5
  • Junzhao Ye1
  • Bihui Zhong1
5 affiliations
  1. 1Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  2. 2Department of Gastroenterology, Guangzhou University of Traditional Chinese Medicine Affiliated Foshan Hospital of Traditional Chinese Medicine, Foshan, China
  3. 3Department of Nutrition, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  4. 4Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  5. 5Department of Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
Read full textPDFDOICite

Abstract

Background: Although emerging classification systems address the pathophysiological heterogeneity of metabolic dysfunction-associated steatotic liver disease (MASLD), the implications of these subtypes for treatment responses remain unclear. We systematically evaluated three phenotyping frameworks for stratifying responses to lifestyle management.

Methods: This prospective observational cohort study included 618 patients with MASLD who received 48 weeks of guideline-based lifestyle management. The classification systems assessed were metabolic clusters—mild obesity/dyslipidemia-associated MASLD (MODM), age-related MASLD (AM), severe insulin resistance-associated MASLD, high lipoprotein(a)-associated MASLD (HLPAM), and severe mixed hyperlipidemia-associated MASLD (SMHLM); hepatic and cardiometabolic traits (control, liver-specific, and cardiometabolic); and biochemical patterns (hepatocellular, mixed, and cholestatic). The primary endpoints were responses in magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) (≥30% relative liver fat reduction), alanine aminotransferase (ALT) (≥17 IU/L decrease), and liver stiffness measurements (LSM) (≥1-stage improvement in the LSM-defined fibrosis stage).

Results: Metabolic clusters demonstrated significantly greater temporal stability than the hepatic and cardiometabolic trait and biochemical pattern systems (62.8% vs. 56.6% vs. 53.4%, P=0.003). The HLPAM cluster demonstrated an attenuated MRI-PDFF response (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.15 to 0.79), while the AM cluster showed a lower ALT response (OR, 0.33; 95% CI, 0.18 to 0.62), and the MODM cluster displayed a superior LSM response compared to the others (all P<0.05). Moreover, the liver-specific cluster showed better MRI-PDFF, ALT, and LSM responses than the control cluster. However, biochemical patterns selectively stratified ALT responses, with the hepatocellular pattern demonstrating a greater response than the mixed and cholestatic patterns.

Conclusion: Metabolic cluster-based MASLD subtypes exhibited differential responses to lifestyle management, supporting the integration of metabolic subtyping into clinical algorithms to optimize management.

Related

  1. The liver–muscle axis in metabolic dysfunction-associated steatotic liver disease: a narrative review and conceptual framework for body-composition phenotyping
    Zhendong Ma, Xinri Zhang, Yan Leng +1
    Frontiers in medicinePeer-reviewedCC BYFull textGeneral medicineEurope PMC
  2. Comparison of Metabolic Dysfunction‐Associated Steatotic Liver Disease Between Individuals With Werner Syndrome and Those With Insulin‐Resistant Type 2 Diabetes: Hepatic Steatosis and Fibrosis Indices
    Makoto Miyabayashi, Masaya Koshizaka, Mayumi Shoji +29
    Geriatrics & gerontology internationalPeer-reviewedCC BY-NC-NDFull textGeneral medicineEurope PMC
  3. Metabolic dysfunction-associated steatotic liver disease and neurocognitive and reward circuit dysfunction: implications for mental disorders
    Nina Sachi Mollin, Gia Han Le, Christine E. Dri +10
    CNS SpectrumsPeer-reviewedCC BY 4.0Full textGeneral medicinePMC
  4. Emerging insights into PPARα's role in lean metabolic dysfunction-associated steatotic liver disease: Implications for targeted therapies.
    Yafei Yang, Furong Zhang, Zhuang Peng +6
    Acta pharmaceutica Sinica. BPeer-reviewedCC BY-NC-NDFull textEpidemiology & public healthEurope PMCPMC
  5. Thyroid dysfunction in aging and cardiovascular-kidney-metabolic syndrome: metabolic regulation and clinical implications
    Hui Li, Na Wang, Xianhui Ran +3
    Frontiers in EndocrinologyPeer-reviewedCC BY 4.0Full textEndocrinology & metabolismCrossrefPMC

Cite

BibTeXRIS
BibTeX
@article{luo2026comparison,
  title = {{Comparison of Data-Driven Phenotyping Systems for Metabolic Dysfunction-Associated Steatotic Liver Disease: Implications for Treatment Response}},
  author = {Ling Luo and Congxiang Shao and Tingfeng Wu and Long Teng and Jiaming Lai and Shuyu Zhuo and Zhi Dong and Wei Wang and Junzhao Ye and Bihui Zhong},
  journal = {Journal of Obesity \& Metabolic Syndrome},
  year = {2026},
  month = oct,
  doi = {10.7570/jomes25076},
  url = {https://doi.org/10.7570/jomes25076},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - Comparison of Data-Driven Phenotyping Systems for Metabolic Dysfunction-Associated Steatotic Liver Disease: Implications for Treatment Response
AU  - Ling Luo
AU  - Congxiang Shao
AU  - Tingfeng Wu
AU  - Long Teng
AU  - Jiaming Lai
AU  - Shuyu Zhuo
AU  - Zhi Dong
AU  - Wei Wang
AU  - Junzhao Ye
AU  - Bihui Zhong
PY  - 2026
DA  - 2026/10/23
JO  - Journal of Obesity & Metabolic Syndrome
DO  - 10.7570/jomes25076
UR  - https://doi.org/10.7570/jomes25076
AB  - Background: Although emerging classification systems address the pathophysiological heterogeneity of metabolic dysfunction-associated steatotic liver disease (MASLD), the implications of these subtypes for treatment responses remain unclear. We systematically evaluated three phenotyping frameworks for stratifying responses to lifestyle management.  Methods: This prospective observational cohort study included 618 patients with MASLD who received 48 weeks of guideline-based lifestyle management. The classification systems assessed were metabolic clusters—mild obesity/dyslipidemia-associated MASLD (MODM), age-related MASLD (AM), severe insulin resistance-associated MASLD, high lipoprotein(a)-associated MASLD (HLPAM), and severe mixed hyperlipidemia-associated MASLD (SMHLM); hepatic and cardiometabolic traits (control, liver-specific, and cardiometabolic); and biochemical patterns (hepatocellular, mixed, and cholestatic). The primary endpoints were responses in magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) (≥30% relative liver fat reduction), alanine aminotransferase (ALT) (≥17 IU/L decrease), and liver stiffness measurements (LSM) (≥1-stage improvement in the LSM-defined fibrosis stage).  Results: Metabolic clusters demonstrated significantly greater temporal stability than the hepatic and cardiometabolic trait and biochemical pattern systems (62.8% vs. 56.6% vs. 53.4%, P=0.003). The HLPAM cluster demonstrated an attenuated MRI-PDFF response (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.15 to 0.79), while the AM cluster showed a lower ALT response (OR, 0.33; 95% CI, 0.18 to 0.62), and the MODM cluster displayed a superior LSM response compared to the others (all P<0.05). Moreover, the liver-specific cluster showed better MRI-PDFF, ALT, and LSM responses than the control cluster. However, biochemical patterns selectively stratified ALT responses, with the hepatocellular pattern demonstrating a greater response than the mixed and cholestatic patterns.  Conclusion: Metabolic cluster-based MASLD subtypes exhibited differential responses to lifestyle management, supporting the integration of metabolic subtyping into clinical algorithms to optimize management.
SN  - 2508-6235
SN  - 2508-7576
ER  -