Back

Circadian reprogramming of adipose progenitor cells regulates intermittent fasting-mediated adipose tissue remodeling and metabolic improvement

Lee, J. H.; Patel, Y.; Yeung, J. L.-H.; Pickel, L.; Ealey, K. N.; Togo, J.; Kim, Y.-H.; Kim, K.-H.; Park, J.-G.; Jackson, T.; Okrainec, A.; Kim, J.-R.; Park, S.-Y.; Dash, S.; Sung, H.-K.

2022-12-11 molecular biology
10.1101/2022.12.10.519916 bioRxiv
Show abstract

White adipose tissue (WAT) fibrosis is a hallmark of dysfunctional WAT that is directly linked to metabolic abnormalities. Recent studies have highlighted the role of dysfunctional adipose progenitor cells (APCs) in WAT fibrosis and impaired adaptive tissue plasticity, leading to systemic insulin resistance. However, therapeutic options for WAT fibrosis are limited. Intermittent fasting (IF) is an effective dietary regimen for weight control and metabolic improvement through various mechanisms, including healthy remodeling of WAT. However, whether IF is effective in improving age-associated WAT fibrosis and metabolic homeostasis is unknown. Here, we show that IF confers therapeutic benefits in aged and obese mice through reduction of WAT fibrosis. Single-cell analyses revealed that IF significantly reduces pro-fibrotic signatures within APCs along with upregulation of the circadian pathways, suggesting that the circadian clock of APCs mediates IF-induced WAT remodeling. Importantly, mice lacking core circadian gene exhibited increased fibrotic signatures in WAT and diminished beneficial response to IF, further supporting the importance of circadian rhythm in IF-mediated metabolic benefits. Lastly, insulin resistance in humans also presented with dysregulated circadian rhythm signatures in APC populations. Collectively, our findings highlight the novel role of the APC circadian rhythm in plasticity of WAT and metabolic response to IF.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.