Circadian regulation in human white adipose tissue revealed by transcriptome and metabolic network analysis.
Skevoulla ChristouSophie M T WehrensCheryl IsherwoodCarla Sofia Möller-LevetHuihai WuVictoria L RevellGiselda BuccaDebra Jean SkeneEmma E LaingSimon N ArcherJonathan D JohnstonPublished in: Scientific reports (2019)
Studying circadian rhythms in most human tissues is hampered by difficulty in collecting serial samples. Here we reveal circadian rhythms in the transcriptome and metabolic pathways of human white adipose tissue. Subcutaneous adipose tissue was taken from seven healthy males under highly controlled 'constant routine' conditions. Five biopsies per participant were taken at six-hourly intervals for microarray analysis and in silico integrative metabolic modelling. We identified 837 transcripts exhibiting circadian expression profiles (2% of 41619 transcript targeting probes on the array), with clear separation of transcripts peaking in the morning (258 probes) and evening (579 probes). There was only partial overlap of our rhythmic transcripts with published animal adipose and human blood transcriptome data. Morning-peaking transcripts associated with regulation of gene expression, nitrogen compound metabolism, and nucleic acid biology; evening-peaking transcripts associated with organic acid metabolism, cofactor metabolism and redox activity. In silico pathway analysis further indicated circadian regulation of lipid and nucleic acid metabolism; it also predicted circadian variation in key metabolic pathways such as the citric acid cycle and branched chain amino acid degradation. In summary, in vivo circadian rhythms exist in multiple adipose metabolic pathways, including those involved in lipid metabolism, and core aspects of cellular biochemistry.
Keyphrases
- adipose tissue
- nucleic acid
- gene expression
- endothelial cells
- insulin resistance
- network analysis
- induced pluripotent stem cells
- rna seq
- pluripotent stem cells
- single cell
- small molecule
- high fat diet
- dna methylation
- single molecule
- systematic review
- high resolution
- electronic health record
- high throughput
- fatty acid
- artificial intelligence