How Sleep Loss May Contribute to Adverse Weight Gain

Epidemiological studies have shown that the risk for obesity and type 2 diabetes is elevated in those who suffer from chronic sleep loss or who carry out shift work. Other studies have shown an association between disrupted sleep and adverse weight gain, in which fat accumulation is increased at the same time as the muscle mass is reduced – a combination that in and of itself has been associated with numerous adverse health consequences. Researchers from Uppsala and other groups have in earlier studies shown that metabolic functions that are regulated by e.g. skeletal muscle and adipose tissue are adversely affected by disrupted sleep and circadian rhythms. However, until now it has remained unknown whether sleep loss per se can cause molecular changes at the tissue level that can confer an increased risk of adverse weight gain. “In the present study we observed molecular signatures of increased inflammation across tissues in response to sleep loss. However, we also saw specific molecular signatures that indicate that the adipose tissue is attempting to increase its capacity to store fat following sleep loss, whereas we instead observed signs indicating concomitant breakdown of skeletal muscle proteins in the skeletal muscle, in what’s also known as catabolism. We also noted changes in skeletal muscle levels of proteins involved handling blood glucose, and this could help explain why the participants’ glucose sensitivity was impaired following sleep loss. Taken together, these observations may provide at least partial mechanistic insight as to why chronic sleep loss and shift work can increase the risk of adverse weight gain as well as the risk of type 2 diabetes,” says Jonathan Cedernaes. https://www.technologynetworks.com/proteomics/news/how-sleep-loss-may-contribute-to-adverse-weight-gain-308058?utm_campaign=Newsletter_TN_BreakingScienceNews&utm_source=hs_email&utm_medium=email&utm_content=65428939&_hsenc=p2ANqtz-9WyhRtqicw4bmD0I8BnMG6h5ZQSWiwNRAUv2VKEUSfHgTRXLu_s2F7cEoGIm0UxJrTEGPZrU55CmgCRH91nJtc0DNaFA&_hsmi=65428940