Association between mental health and MASLD molecular insights through metabolomics

通过代谢组学揭示心理健康与MASLD之间的分子关联

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Abstract

BACKGROUND: Mental health disorders and metabolic dysfunction-associated steatotic liver disease (MASLD) represent substantial global public health challenges. The precise relationship between mental health parameters and MASLD development remains poorly characterized. METHODS: Using data from the UK Biobank cohort, we conducted a prospective cohort study to evaluate participants' anxiety, depression, mania, and trauma exposure scores using standardized psychometric instruments. Metabolic signatures were derived through elastic net regularization coupled with Cox proportional hazards modeling. Mediation analyses quantified the proportion of mental health-MASLD associations attributable to metabolic pathway alterations. RESULTS: The analytical cohort comprises 55,012 participants with trauma assessments, 15,318 with mania evaluations, 30,798 with depression metrics, and 17,596 with anxiety profiles. Multivariable-adjusted analyses reveal significant dose-response relationships between mental health burden and MASLD incidence: anxiety (HR = 1.13, 95%CI 1.08-1.18, P < 0.05), depression (HR = 1.06, 95%CI 1.03-1.10, P < 0.05), mania (HR = 1.15, 95%CI 1.06-1.24, P < 0.05), and trauma (HR = 1.22, 95%CI 1.11-1.34, P < 0.05). Metabolic analyses indicate that creatinine, glutamine, and the triglyceride fraction of very low-density lipoprotein (VLDL-triglyceride%) serve as key mediators in the pathway through which mental health influences MASLD incidence. The derived metabolic signature demonstrates significant mediation effects across all psychological domains (anxiety: 12.7%, depression: 15.7%, mania: 11.5%, trauma: 11.2%). CONCLUSIONS: This large-scale cohort study establishes clinically significant mental health conditions as risk factors for MASLD development, with metabolic dysregulation serving as a partial mediator of this association. The identified metabolite panel, particularly perturbations in nitrogen metabolism and lipid partitioning, provides mechanistic insights into psychosomatic pathways influencing hepatic steatosis, suggesting potential targets for interdisciplinary intervention strategies.

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