Mou Xiaoqin, Nie Pengxing, Chen Renrui, Cheng Yang, Wang Guang-Zhong
CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
Heliyon. 2025 Jan 7;11(2):e41774. doi: 10.1016/j.heliyon.2025.e41774. eCollection 2025 Jan 30.
Feeding disruption is closely linked to numerous diseases, yet the underlying molecular mechanisms remain an important but unresolved issue at the molecular level. We hypothesize that, at the network level, dietary disruptions can alter gene co-expression patterns, leading to an increase in disease-associated modules, and thereby elevating the likelihood of disease occurrence. Here, we investigate this hypothesis using transcriptomic data from a large cohort of adult mice subjected to feeding disruptions. Our computational analysis indicates that altered feeding schedules significantly increase disease-related modules in adult mouse livers, well before aging and disease onset. Conversely, calorie restriction significantly reduces these disease modules. This provides a critical missing link between feeding disruption and the molecular mechanisms of disease.
进食紊乱与多种疾病密切相关,但其潜在的分子机制在分子层面仍是一个重要但尚未解决的问题。我们假设,在网络层面,饮食紊乱会改变基因共表达模式,导致与疾病相关的模块增加,从而增加疾病发生的可能性。在此,我们使用来自大量遭受进食紊乱的成年小鼠队列的转录组数据来研究这一假设。我们的计算分析表明,改变进食时间表会在成年小鼠肝脏中显著增加与疾病相关的模块,且远在衰老和疾病发作之前。相反,热量限制会显著减少这些疾病模块。这为进食紊乱与疾病的分子机制之间提供了一个关键的缺失环节。