Synergistic impact of serum uric acid and ferritin on MAFLD risk: A comprehensive cohort analysis

血清尿酸和铁蛋白对代谢相关脂肪性肝病风险的协同作用:一项综合队列分析

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Abstract

The characterization of Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) underscores metabolic anomalies as critical in fatty liver disease progression. Serum uric acid is increasingly recognized as a determinant for fatty liver diseases due to its association with metabolic disorders. Ferritin, in parallel, serves as an inflammatory marker closely tied to metabolic syndrome and insulin resistance. Our study explores the combined influence of serum uric acid and ferritin on MAFLD prevalence. We conducted a retrospective cohort analysis at Samsung Changwon Hospital's Health Screening Center (2011-2018), encompassing 7,818 individuals post-exclusion criteria. Participants were stratified into gender-specific quartiles based on serum uric acid and ferritin levels. Utilizing multivariable Cox proportional hazard models alongside Kaplan-Meier analysis, we assessed the incidence of MAFLD and its relationship with these serum biomarkers, also performing subgroup assessments by gender, age, and BMI. Over 41,819 person-years with an average observation period of 5.35 ± 2.06 years, 1,073 incident cases of MAFLD were recorded. The risk of MAFLD was notably higher within the upper quartiles of serum uric acid (HR: 2.17, 95% CI: 1.70-2.78). Each increment in natural logarithmic serum uric acid level correlated with an increased risk (HR: 3.65, 95% CI: 2.32-5.74). Serum ferritin also indicated an enhanced risk, albeit less pronounced. The simultaneous presence of elevated levels of both uric acid and ferritin correlated with the highest MAFLD risk (HR: 3.89, 95% CI: 2.41-6.28). Our findings affirm that high serum uric acid levels significantly escalate the risk of MAFLD, with serum ferritin levels contributing to a lesser yet substantial degree. The concurrent elevation of both biomarkers magnifies MAFLD risk, reinforcing the need for their combined assessment in MAFLD risk evaluation.

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