journal article·2025-12Open access

Liver-bone organoids reveal senescence-driven interorgan crosstalk

Yingting Zhang, Yue Li, Fuxiao Wang, Zhenglin Dong, Jian Wang, Yi Chen, Yinkun Fu, Yuheng Lu, Xinyu Bao, Yuxiao Lai, Yingying Jing, Jianhua Wang, Jianping Peng, Chao-Po Lin, Jiacan Su, Ming He

Abstract

The liver-bone axis plays a critical role in age-related diseases. However, current models inadequately capture its complex inter-organ communication. Here, we established novel, physiologically relevant senescent liver and bone organoid models using engineered bionic hydrogels combined with doxorubicin (DOX)-induced senescence. These models successfully recapitulated hallmark aging characteristics: bone organoids exhibited reduced mineralization accompanied by elevated senescence markers, and liver organoids demonstrated DNA damage along with structural deterioration. Notably, aged mouse serum effectively induced senescence in both organoid types, confirming the existence of systemic aging regulators. The platform demonstrated robust bidirectional crosstalk, with senescent liver organoid-conditioned medium potently driving degradation in bone organoids and senescent bone organoid-conditioned medium aggravating dysfunction in liver organoids. Mechanistically, we identified 27-hydroxycholesterol (27-OHC) as a novel hepatocyte-derived factor mediating liver-to-bone communication. 27-OHC not only induced bone organoids senescence but also synergized with DOX treatment to exacerbate bone loss, a finding corroborated by in vivo mouse studies that validated the relevance of our platform in the context of pathological damage. This study pioneers the first organoid-based platform that elucidates multi-organ aging mechanisms, uncovering 27-OHC as a pivotal regulator of liver-bone axis dysfunction and proposing novel treatment strategies for age-related systemic disorders.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Liver physiology and pathology · Genetic and Kidney Cyst Diseases · Medical Imaging and Pathology Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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