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Weight changes differentially impact MASLD incidence, progression and outcomes based on genetic and metabolic risk
Lanlan Chen1, Alfred Wei Chieh Kow2, Guoyue Lv3
1Department of Hepatology & Gastroenterology, Charité - Universitätsmedizin Berlin, Campus Virchow-Klinikum and Campus Charité Mitte, 13353 Berlin, Germany; Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, the First Hospital of Jilin University, Changchun, Jilin, China; China-Singapore Belt and Road Joint Laboratory on Liver Disease Research, the First Hospital of Jilin University, Changchun, Jilin, China.
Background & Aims:
Metabolic dysfunction-associated steatotic liver disease (MASLD) comprises heterogeneous subgroups with liver- vs. cardiovascular-related adverse outcomes. Weight management is crucial in MASLD prevention and treatment, but its effect on MASLD subgroups is unclear.
Methods:
We assessed the impact of body weight dynamics on incident MASLD, steatosis resolution, fibrosis risk regression and related cardiovascular diseases (CVD) from the UK biobank. Genetic subgroups (i.e., hepatic and systemic) were defined by polygenic risk scores, a metabolic risk group by lipid accumulation product. A Cox proportional model evaluated impacts across the general population and sex-stratified subgroups.
Results:
Among 11,882 participants without MASLD, 1,350 developed MASLD during a median follow-up of 4 years. Each 1% reduction in body weight was associated with a 10% lower risk of MASLD (HR = 0.90 [0.89-0.91]). Among 6,013 participants with MASLD, 753 achieved MASLD resolution; each 1% weight reduction was associated with a 9% higher rate of resolution (HR = 1.09 [1.08-1.10]). Weight loss was also associated with a lower risk of MASLD-related CVD (HR = 0.98 [0.97-0.99]). Recommended weight loss for MASLD prevention (male/female) differed across hepatic (8.7%/13.1%), systemic (8.0%/11.8%), and metabolic-risk (10.9%/14.4%) groups. Estimated lower weight-loss thresholds associated with MASLD resolution were 5.3%/13.3% in hepatic-risk, 10.2%/10.7% in systemic-risk, and 5.7%/5.8% in metabolic-risk participants (male/female). For fibrosis-risk regression, no robust threshold was identified in hepatic-risk participants, but 7.7%/5.6% in metabolic-risk participants (male/female).
Conclusion:
Individualized weight management should be recommended according to the genetic and metabolic risk profiles of individuals.
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