作者
Yuqing Liu,Yuanqin Yang,Lemei Zhu,Weijun Peng
摘要
BACKGROUND: Traditional weight-centered models do not fully capture the biological complexity of obesity. Systems biology offers a new framework by integrating molecular, cellular, clinical, and environmental information to reframe obesity as a heterogeneous, multidimensional disease. AIMS: This review aims to reframe obesity as a heterogeneous, multidimensional disease by integrating molecular, cellular, clinical, and environmental information through the lens of systems biology. MATERIALS AND METHODS: This article summarizes findings from recent studies employing systems biology approaches, including single-cell transcriptomics, metabolomics, epigenomics, microbiome profiling, and computational modeling. RESULTS: These approaches have revealed marked heterogeneity in adipose remodeling, inflammatory tone, mitochondrial stress, and inter-organ communication. Such insights help explain why individuals with similar body mass index (BMI) can differ substantially in insulin resistance, organ-specific vulnerability, and treatment response. DISCUSSION: This review focuses on obesity-relevant mechanisms, including adipose tissue heterogeneity, immunometabolic dysfunction, immune aging, and obesity-related multi-system injury. We also discuss emerging precision obesity care strategies such as biomarker-guided subtyping, cell-specific targeting, microbiome-directed intervention, and artificial intelligence-assisted prediction. CONCLUSION: Together, these advances support a shift from BMI-based classification alone toward mechanism-informed obesity prevention and treatment.