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Yining Xie

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Review Open access Sep 2026

Decoding SUMOylation as a metabolic stress sensor in aging and age-related disorders: mechanisms, tissue specificity and therapeutic potential.

SUMOylation is a reversible post-translational modification increasingly recognized for its role in coordinating cellular responses to metabolic stress during aging. Emerging evidence indicates that it functions beyond a conventional modification, representing an adaptive stress‑responsive regulatory network that integrates metabolic, oxidative, inflammatory, and proteotoxic signals. Rather than acting on isolated pathways, this network finely tunes mitochondrial function, proteostasis, genome maintenance, immune balance, and epigenetic regulation. Accumulating evidence indicates that SUMO-dependent regulation exhibits remarkable tissue specificity, supporting mitochondrial adaptation and contractile integrity in skeletal muscle, shaping lipid and glucose metabolism in the liver, modulating proteotoxic stress and neuronal resilience in the brain, and contributing to immune cell differentiation and chronic low-grade inflammation during aging. In this review, we summarize current mechanistic insights into SUMO signaling across aging-relevant tissues, with particular emphasis on its functional interplay with other post-translational modifications, including ubiquitination and acetylation. We discuss how SUMOylation operates as a shared regulatory layer while enabling context-dependent outcomes that underlie diverse aging phenotypes and age-related disorders. Finally, we evaluate emerging translational approaches-ranging from pharmacological modulation of SUMO enzymes to lifestyle interventions such as caloric restriction and exercise-that highlight both the opportunities and challenges of targeting SUMO-regulated stress responses in aging. Together, this synthesis provides a framework for understanding how SUMOylation links metabolic stress to tissue-specific aging trajectories and therapeutic potential.

Xin-Yue Liu, Shuang Chen, Dong-Can Liu et al. · 0 citations
Review Open access Jul 2026

Endocrine-metabolic imbalance drives osteoarthritis: From whole-joint pathobiology to precision therapy (Review)

Osteoarthritis (OA) is a chronic degenerative joint disease closely associated with aging and metabolic dysfunction, characterized by cartilage degeneration, synovial inflammation, aberrant subchondral bone remodeling, pain and progressive functional impairment. Beyond mechanical loading, accumulating evidence indicates that OA is increasingly recognized as a whole-joint disorder shaped by the interplay between local tissue damage and systemic endocrine-metabolic imbalance. Endocrine factors, including sex hormones, thyroid hormone, melatonin, parathyroid hormone and vitamin D, together with metabolic disturbances, such as obesity, insulin resistance, dysregulated glucose and lipid metabolism and gut microbiota imbalances, can cooperatively remodel the joint microenvironment. Mechanistically, these alterations converge on immuno-inflammatory amplification, mitochondrial dysfunction, oxidative stress, cellular senescence, metabolic reprogramming and regulated cell death, thereby promoting extracellular matrix degradation, persistent synovitis and uncoupled bone-cartilage remodeling. The present review systematically summarizes the molecular basis of endocrine-metabolic crosstalk in OA and discusses emerging therapeutic opportunities targeting hormonal signaling, metabolic pathways, circadian regulation, nutritional support and lifestyle interventions. Nevertheless, the reciprocal interactions among endocrine signals, systemic metabolic abnormalities and local joint pathology remain incompletely understood, and their translation into mechanism-based clinical stratification remains at an early stage. Thus, targeting endocrine-metabolic crosstalk may support mechanism-based phenotyping and subtype-informed precision therapy for OA, provided that candidate biomarkers and interventions are validated in prospective clinical studies.

Ruhui Yang, Haimin Zeng, Qi Xiao et al. · 1 citation

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