Obesity is a complex disease that involves both genetic and environmental perturbations to gene networks in adipose tissue and is proposed as a trigger for metabolic sequelae.

We hypothesized that expression of adipose tissue transcripts in gene networks for adaptive response would correlate with the percent fat mass (PFAT) in healthy nondiabetic subjects to maintain metabolic equilibrium and would overlap with genes modulated in response to elevated fatty acid.

Genome-wide transcript profiles were determined in sc adipose tissue of 136 nondiabetics and in palmitate-induced cells. Genotype information and gene expression data in nondiabetic subjects were integrated to characterize the function of 41 obesity-associated polymorphisms.

Genes involved in inflammation-immune response, endoplasmic reticulum stress, and cell-extracellular matrix interactions were significantly correlated with PFAT. The NRF2 (nuclear factor erythroid 2-related factor-2)-mediated oxidative stress response pathway was strongly enriched among genes correlated with PFAT in adipose and also emerged as the most enriched pathway among genes differentially expressed by palmitate in vitro. Thioredoxin reductase-1 (TXNRD1) was the most strongly correlated gene (ρ = 0.65). Genes coregulated with TXNRD1 expression indicated a significant interaction network of genes involved in thioredoxin-mediated oxidative stress defense mechanisms and angiogenesis. Pro- and antiangiogenic factors were negatively and positively correlated, respectively, with obesity. Eight obesity genome-wide association study single-nucleotide polymorphisms (SNP) were associated with expression of 10 local transcripts. SNP rs6861681 was the strongest cis-eQTL (expression quantitative trait loci) for CPEB4 (P = 3.02 × 10⁻⁹).

Our study suggests a novel interaction of up-regulated TXN-TXNRD1 system-mediated oxidative stress defense mechanisms and down-regulated angiogenesis pathways as an adaptive response in obese nondiabetic subjects. A subset of obesity-associated SNP regulated expression of transcripts as cis-eQTL.