Decreased protein levels of key insulin signalling molecules in adipose tissue from young men with a low birthweight: potential link to increased risk of diabetes?
- PMID: 17063325
- DOI: 10.1007/s00125-006-0466-2
Decreased protein levels of key insulin signalling molecules in adipose tissue from young men with a low birthweight: potential link to increased risk of diabetes?
Abstract
Aims/hypothesis: Individuals with low birthweight are at increased risk of type 2 diabetes mellitus. However, the underlying molecular mechanisms are unknown. Previously we have shown that low birthweight is associated with changes in muscle insulin signalling proteins. Here we determined whether low birthweight is associated with changes in insulin signalling proteins in adipose tissue.
Methods: Men (age 23 years) with either a low (bottom 10th percentile) (n = 17) or a normal (50th-90th percentile) (n = 17) birthweight were recruited from the Danish Medical Birth Registry and subcutaneous adipose biopsies were taken.
Results: Between the two groups there was no difference in protein level of the insulin receptor, protein kinase C zeta, glycogen synthase kinase-3 (GSK3) alpha, GSK3 beta, protein kinase B alpha and beta, peroxisome proliferative activated receptor gamma coactivator 1 or Src-homology-2-containing protein. However, the levels of GLUT4 (also known as solute carrier family 2 [facilitated glucose transporter], member 4 [SLC2A4]) (52 +/- 10.9% reduction, p < 0.01), p85alpha subunit of phosphoinositide 3-kinase (PI3K) (45 +/- 9% reduction, p < 0.01), p110ss subunit of PI3K (48 +/- 17% reduction, p = 0.06) and IRS1 (59 +/- 24% reduction, p < 0.05) were reduced in men of low birthweight.
Conclusions/interpretation: These findings show that low birthweight is associated with reduced levels of adipose insulin signalling proteins, thus providing a potential molecular framework to explain why people with low birthweight are at increased risk of developing type 2 diabetes. These differences precede the development of diabetes and thus may help predict disease risk.
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