IRS1 DNA promoter methylation and expression in human adipose tissue are related to fat distribution and metabolic traits.
Kerstin RohdeMatthias KlösLydia HoppXuanshi LiuMaria KellerMichael StumvollArne DietrichMichael R SchönDaniel GärtnerTobias LohmannMiriam DreßlerPeter KovacsHans BinderMatthias BlüherYvonne BöttcherPublished in: Scientific reports (2017)
The SNP variant rs2943650 near IRS1 gene locus was previously associated with decreased body fat and IRS1 gene expression as well as an adverse metabolic profile in humans. Here, we hypothesize that these effects may be mediated by an interplay with epigenetic alterations. We measured IRS1 promoter DNA methylation and mRNA expression in paired human subcutaneous and omental visceral adipose tissue samples (SAT and OVAT) from 146 and 41 individuals, respectively. Genotyping of rs2943650 was performed in all individuals (N = 146). We observed a significantly higher IRS1 promoter DNA methylation in OVAT compared to SAT (N = 146, P = 8.0 × 10-6), while expression levels show the opposite effect direction (N = 41, P = 0.011). OVAT and SAT methylation correlated negatively with IRS1 gene expression in obese subjects (N = 16, P = 0.007 and P = 0.010). The major T-allele is related to increased DNA methylation in OVAT (N = 146, P = 0.019). Finally, DNA methylation and gene expression in OVAT correlated with anthropometric traits (waist- circumference waist-to-hip ratio) and parameters of glucose metabolism in obese individuals. Our data suggest that the association between rs2943650 near the IRS1 gene locus with clinically relevant variables may at least be modulated by changes in DNA methylation that translates into altered IRS1 gene expression.
Keyphrases
- dna methylation
- genome wide
- gene expression
- adipose tissue
- copy number
- body mass index
- insulin resistance
- endothelial cells
- poor prognosis
- high fat diet
- metabolic syndrome
- weight loss
- type diabetes
- induced pluripotent stem cells
- pluripotent stem cells
- skeletal muscle
- emergency department
- high throughput
- electronic health record
- obese patients
- long non coding rna
- single molecule
- binding protein
- bariatric surgery
- transcription factor
- physical activity
- single cell
- artificial intelligence