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Randomized trial investigates selenium biomarker dynamics in rats and humans, suggesting new prevention strategies for Keshan disease.
BACKGROUND: Selenium deficiency is an established etiological risk factor for Keshan disease, yet conventional biomarkers and linear modeling approaches remain insufficient for capturing its complex metabolic dynamics. This study aims to elucidate the nonlinear dynamics of selenium biomarkers for precision prevention of Keshan disease. METHODS: This study employed a human-rat dual-system design and a multi-model analytical framework. The human cohort included 6987 adults from 29 Chinese provinces, stratified by endemicity. The animal experiment utilized 100 specific-pathogen-free male Wistar rats, randomly allocated into a control group and a sodium selenite intervention group (200 μg/L), with samples collected across five sequential stages. Biospecimens including blood, hair, and myocardial tissue were systematically analyzed for selenium content, selenoprotein P, and glutathione peroxidase activity. In statistical analyses, we employed a multi-model comparison strategy incorporating generalized additive models, polynomial regression, restricted cubic splines, and linear regression to identify the optimal approach for analyzing selenium biomarker dynamics. Myocardial selenium rose rapidly and then plateaued relative to serum glutathione peroxidase activity, but remained inversely correlated with serum selenoprotein P. Generalized additive models outperformed other approaches in describing myocardial-peripheral biomarker associations. CONCLUSIONS: Selenium biomarkers exhibit dynamic, non-linear associations. Erythrocyte selenium reflects myocardial status, whereas serum selenoprotein P and glutathione peroxidase activity respectively serve as long-term and short-term indicators. Keshan disease involves threshold-saturation-driven systemic selenium dysregulation, not mere deficiency. Non-linear myocardial selenium accumulation favors continuous, moderate over short-term, high-dose supplementation, supporting precision assessment and prevention in endemic areas.
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Hao et al. (2026) studied this question.
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