A multiomic approach to examine the molecular signatures differentiating people with obesity alone from those with obesity and metabolic complications

Abstract

Abstract Motivation To examine the hypothesis that obesity with metabolic syndrome, compared to simple obesity, has distinct molecular signatures and metabolic pathways. Methods We analyzed a cohort of 39 patients with obesity that includes 21 subjects with metabolic syndrome, age-matched to 21 subjects with simple obesity. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. Results We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the simple obesity strata from that of obesity with metabolic syndrome. Conclusions The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate the patients with obesity from those with obesity and metabolic complications.