Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects

Abstract

Multiple mechanisms have been suggested to confer to the pathophysiology of metabolic syndrome (MetS), however despite great interest from the scientific community, the exact contribution of each of MetS risk factors still remains unclear. The present study aimed to investigate molecular signatures in peripheral blood of individuals affected by MetS and different degrees of obesity. Metabolic health of 1204 individuals from 1000PLUS cohort was assessed, and 32 subjects were recruited to four study groups: MetS lean, MetS obese, “healthy obese”, and healthy lean. Whole-blood transcriptome next generation sequencing with functional data analysis were carried out. MetS obese and MetS lean study participants showed the upregulation of genes involved in inflammation and coagulation processes: granulocyte adhesion and diapedesis (p < 0.0001, p = 0.0063), prothrombin activation pathway (p = 0.0032, p = 0.0091), coagulation system (p = 0.0010, p = 0.0155). The results for “healthy obese” indicate enrichment in molecules associated with protein synthesis (p < 0.0001), mitochondrial dysfunction (p < 0.0001), and oxidative phosphorylation (p < 0.0001). Our results suggest that MetS is related to the state of inflammation and vascular system changes independent of excess body weight. Furthermore, “healthy obese”, despite not fulfilling the criteria for MetS diagnosis, seems to display an intermediate state with a lower degree of metabolic abnormalities, before they proceed to a full blown MetS.

Use of human PBMC to analyse the impact of obesity on lipid metabolism and metabolic status: a proof-of-concept pilot study

“…In future studies it would of interest to perform more global approaches to obtain further insights of the usefulness of PBMC to understand the impact of increased adiposity on metabolism and health. For example, the relevance of transcriptome next generation sequencing applied to whole blood for the study of overweight/obesity and metabolic syndrome has been already established 43 . Moreover, lipidomics has been shown to detect changes in plasma lipidome with obesity and metabolic risk 44 , 45 .…”

Obesity, metabolic health and omics: Current status and future directions

“…We found that similar pathways were enriched in our recent transcriptomic study of different metabolic health phenotypes[ 35 ]. The IPA core analysis of differentially expressed genes between MHO and MHNW subjects revealed significant enrichment in EIF2 signaling, regulation of eIF4 and p70S6K signaling, oxidative phosphorylation, mitochondrial dysfunction, and mTOR signaling canonical pathways.…”

Metabolic Inflammation in Obesity—At the Crossroads between Fatty Acid and Cholesterol Metabolism

“…[ 141 ] Finally, transcriptomics has also reflected the chronic inflammatory state present within the MetS with upregulation of inflammatory genes in MUO patients while MHO patients displayed upregulation of genes involved in oxidative phosphorylation and protein synthesis. [ 142 ] The potential to use these more advanced technologies combined with advances in machine learning will no doubt lead to a greater understanding of obesity sub‐types, their specific risk clusters, and indeed better biomarkers of low‐grade metabolic inflammation.…”