• Xuangao Wu, Ting Zhang, and Sunmin Park.
• Korea Department of Bioconvergence, Hoseo University, Asan, South Korea. Electronic address: niyani0@naver.com.
• Nutrition. 2024 Oct 18; 130: 112604112604.

ObjectivesThis study investigated biomarkers in individuals with newly developed metabolic dysfunction-associated steatotic liver disease (ND-MASLD) and examined the interplay between genetic predisposition and environmental factors using a machine learning approach in a large longitudinal study.MethodsParticipants were classified into four groups based on metabolic dysfunction-associated steatotic liver disease (MASLD) status between the first and second measurements with an approximate 5-y gap. A model was developed to identify early-stage biomarkers of ND-MASLD (n = 1603). Nutrient intake, dietary patterns, genetic variants, and psychosocial factors were compared among the no MASLD (n = 60 081), recovered MASLD (n = 3181), persistent MASLD (n = 670), and ND-MASLD (n = 1603) groups. Their association with ND-MASLD was also predicted using a machine learning approach.ResultsThe model incorporating ND-MASLD status, age, sex, dietary inflammatory index, and metabolic syndrome (MetS), especially low high-density lipoprotein cholesterol and hypertriglyceridemia, at the second measurement demonstrated an optimal fit. High carbohydrate intake with a high glycemic index was associated with elevated ND-MADSLD risk. Fatty liver index was lower in persistent MASLD followed by ND-MASLD, recovered MASLD, and no MASLD. Participants in the ND-MASLD group had lower vitamin D and total isoflavonoid intake and a lower modified healthy eating index, indicating unhealthy diets. The XGBoost and deep neural network models identified age, sex, MetS components, dietary antioxidants, self-rated health, psychological well-being indexes, and serum liver enzyme levels at the second measurement as significant predictors of ND-MASLD. However, polygenic risk scores were not included.ConclusionsEarly-stage biomarkers of ND-MASLD were closely linked to MetS incidence. Dietary quality, perceived health status, and psychological stress emerged as potential targets for MASLD prevention strategies, with lifestyle modifications potentially overriding genetic predispositions. The results indicate that preventive strategies about lifestyle modification should be developed for MASLD.Copyright © 2024 Elsevier Inc. All rights reserved.

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