Metabolic effects of sleep loss in humans




Principal Investigator:

Jonathan Cedernaes


Uppsala universitet

Start Date:


End Date:


Primary Classification:

30205: Endocrinology and Diabetes



  • Castor /proj/nobackup at UPPMAX: 10000 GiB
  • Cygnus /proj/nobackup at UPPMAX: 10000 GiB
  • Castor /proj at UPPMAX: 8000 GiB
  • Cygnus /proj at UPPMAX: 8000 GiB
  • Bianca at UPPMAX: 2 x 1000 core-h/month


We are requesting transfer of files from project b2015398, as milou is shutting down, and we would like to transfer the files to Bianca as the project is largely based on analyses of human genomic data. The current (applying) PI was co-investigator on the previous project, but also proxy, and has technical linux knowledge, and has secured almost all of the funding for the completed and ongoing analyses (from Åke Wiberg, VR, Selanders stiftelse, Swedish Brain Foundation and Svenska Läkaresällskapet). Abstract: Sleep loss and circadian misalignment increase the risk of obesity and type 2 diabetes through unknown mechanisms. Our previous data indicates that acute sleep loss induces tissue-specific alterations (Cedernaes et al., J Clin Endocrinol Metab. 2015 Sep;100(9):E1255-61), but more unbiased approaches are lacking. To determine the effects of one and several nights of sleep loss on peripheral metabolic tissues in healthy humans, we are utilizing a range of state-of-the art omic approaches (such as RNA-seq and methylation arrays) on skeletal muscle and adipose tissue samples obtained under standardized conditions in healthy participants after sleep loss compared with after sleep. We have also obtained samples before and after exercise under normal sleep and sleep loss conditions, and thus have ongoing two of the most comprehensive intra-tissue analyses to date of how sleep loss impacts metabolic integrity at the molecular and genomic level in healthy humans. Resources: We are requesting to move data from Milou (project b2015398) to Bianca. - We are currently using 1.0 Tb of data for previous data files (mostly RNA-seq), and have 0.5 Tb of data that is not backed up. - We will soon receive additional data (~80 RNA-seq / fastq samples of ~36 M reads/sample), i.e. up to 400 Gb more data, and therefore request 0.5 Tb more storage than what we currently have - We therefore request 2 Tb of storage for this continuation project - The project is assisted by WABI support (with Sergiu Netotea and Jakub Westholm) We will use the NGI pipeline for RNA-seq and combine the data with 450K data that we have also obtained via SciLifeLab at Uppsala, in both skeletal muscle and adipose tissue samples after two types of sleep loss (in total samples from >30 individuals), compared with normal sleep conditions. - The goal is to compare genome-wide methylation changes with - transcriptomic changes, as well as with - proteomic (SciLifeLab collaboration) and - metabolomic (UMEÅ metabolomics centre) analyses, and with targeted validation analyses (e.g. western blotting, including of phosphorylation events, and qPCR) in the same tissue samples. We will also - perform eQTL analyses and utilize R packages and - motif and pathway analysis tools (such as HOMER and ENRICHR) to discover biological pathways that are altered in the investigated tissues after sleep loss. As we also have deep sequence coverage (>30 M reads/sample in our new project), we also aim to do - isoform analysis and possibly to discover tissue-specific lncRNAs that contribute to inter- and intra-tissue adverse effects of sleep loss in humans.