1.
Acute sleep loss results in tissue-specific alterations in genome-wide DNA methylation state and metabolic fuel utilization in humans.
Cedernaes, J, Schönke, M, Westholm, JO, Mi, J, Chibalin, A, Voisin, S, Osler, M, Vogel, H, Hörnaeus, K, Dickson, SL, et al
Science advances. 2018;(8):eaar8590
Abstract
Curtailed sleep promotes weight gain and loss of lean mass in humans, although the underlying molecular mechanisms are poorly understood. We investigated the genomic and physiological impact of acute sleep loss in peripheral tissues by obtaining adipose tissue and skeletal muscle after one night of sleep loss and after one full night of sleep. We find that acute sleep loss alters genome-wide DNA methylation in adipose tissue, and unbiased transcriptome-, protein-, and metabolite-level analyses also reveal highly tissue-specific changes that are partially reflected by altered metabolite levels in blood. We observe transcriptomic signatures of inflammation in both tissues following acute sleep loss, but changes involving the circadian clock are evident only in skeletal muscle, and we uncover molecular signatures suggestive of muscle breakdown that contrast with an anabolic adipose tissue signature. Our findings provide insight into how disruption of sleep and circadian rhythms may promote weight gain and sarcopenia.
2.
Transcriptomic coordination in the human metabolic network reveals links between n-3 fat intake, adipose tissue gene expression and metabolic health.
Morine, MJ, Tierney, AC, van Ommen, B, Daniel, H, Toomey, S, Gjelstad, IM, Gormley, IC, Pérez-Martinez, P, Drevon, CA, López-Miranda, J, et al
PLoS computational biology. 2011;(11):e1002223
Abstract
Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF(2α). These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress.