Science· 2016Q1· Review
Circadian physiology of metabolism
- 1,080citations
- Q1SCImago
- 2016year
Short summary
Circadian rhythms, driven by daily light-dark and feeding-fasting cycles, regulate the expression of most mammalian genes and optimize physiology by managing energy use and separating incompatible processes.
AI-generated from the title and abstract; the full text is not read.
Key points
- Circadian rhythms regulate the expression of most mammalian genes.
- These rhythms optimize physiology by managing energy and separating processes.
- Chronic circadian disruption increases metabolic disease risk.
- Time-restricted feeding can alleviate metabolic diseases by sustaining diurnal rhythms.
AI-generated from the title and abstract; the full text is not read.
Abstract
A majority of mammalian genes exhibit daily fluctuations in expression levels, making circadian expression rhythms the largest known regulatory network in normal physiology. Cell-autonomous circadian clocks interact with daily light-dark and feeding-fasting cycles to generate approximately 24-hour oscillations in the function of thousands of genes. Circadian expression of secreted molecules and signaling components transmits timing information between cells and tissues. Such intra- and intercellular daily rhythms optimize physiology both by managing energy use and by temporally segregating incompatible processes. Experimental animal models and epidemiological data indicate that chronic circadian rhythm disruption increases the risk of metabolic diseases. Conversely, time-restricted feeding, which imposes daily cycles of feeding and fasting without caloric reduction, sustains robust diurnal rhythms and can alleviate metabolic diseases. These findings highlight an integrative role of circadian rhythms in physiology and offer a new perspective for treating chronic diseases in which metabolic disruption is a hallmark.
The authors' abstract, as published at the source. Science, 2016 · DOI ↗
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Field: Endocrine and Autonomic Systems
Endocrine and Autonomic SystemsNeuroscience