Circadian clock dysfunction in human omental fat links obesity to metabolic inflammation
Abstract
To unravel the pathogenesis of obesity and its complications, we investigate the interplay between circadian clocks and NF-κB pathway in human adipose tissue. The circadian clock function is impaired in omental fat from obese patients. ChIP-seq analyses reveal that the core clock activator, BMAL1 binds to several thousand target genes. NF-κB competes with BMAL1 for transcriptional control of some targets and overall, BMAL1 chromatin binding occurs in close proximity to NF-κB consensus motifs. Obesity relocalizes BMAL1 occupancy genome-wide in human omental fat, thereby altering the transcription of numerous target genes involved in metabolic inflammation and adipose tissue remodeling. Eventually, clock dysfunction appears at early stages of obesity in mice and is corrected, together with impaired metabolism, by NF-κB inhibition. Collectively, our results reveal a relationship between NF-κB and the molecular clock in adipose tissue, which may contribute to obesity-related complications.
How strong is the evidence?
Evidence Hub reads this as a case-control, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.
Read the paper
Related studies
- A Coupled SYSTEM of Intracellular Ca 2+ Clocks and Surface Membrane Voltage Clocks Controls the Timekeeping Mechanism of the Heart’s Pacemaker
- A Comprehensive Review on the Therapeutic Potential of Curcuma longa Linn. in Relation to its Major Active Constituent Curcumin
- Cancer epigenetics: Moving forward
- Current developments in LC-MS for pharmaceutical analysis
- Myricetin: A comprehensive review on its biological potentials
- A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.