Genetic and environmental architecture of the features of the insulin-resistance syndrome

Am J Hum Genet. 1997 Jan;60(1):143-52.


The contribution of genetic and environmental effects to the clustering of metabolic factors contained in insulin-resistance syndrome (IRS) is still unclear. To explore the genetic architecture of IRS, we examined a population of elderly twins from the Swedish Adoption/Twin Study of Aging. A sample of 289 pairs of twins (mean age 65.5 years; range 52-86 years), of whom 140 pairs had been reared apart, was studied. The features contained in the IRS consisted of body-mass index (BMI), insulin resistance, triglycerides, HDL cholesterol, and systolic blood pressure. Intraclass correlations, cross-twin correlations, and model-fitting analyses were used to evaluate the relative importance of genetic and environmental influences for variation in and covariation among the components of the syndrome. All of the five principal metabolic components contained in IRS are more or less influenced by a single latent genetic factor, whereas only three of the components (triglycerides, insulin resistance, and HDL cholesterol) are influenced by a latent individual-specific environmental factor. The genetic factor reflected influences of importance to BMI and insulin resistance and to a lesser degree to triglycerides, HDL cholesterol, and systolic blood pressure, whereas the individual-specific environmental factor reflected influences in common to triglycerides and HDL cholesterol and to a lesser degree to insulin resistance. Systolic blood pressure was related to IRS, albeit weakly, only through genetic effects. In conclusion, IRS appears to be influenced by different sets of genetic and environmental mechanisms. The set of genetic influences in common to all the components may initiate the abnormalities underlying IRS.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.
  • Twin Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Diseases in Twins / genetics*
  • Environment
  • Female
  • Humans
  • Insulin Resistance / genetics*
  • Male
  • Middle Aged
  • Models, Genetic
  • Multivariate Analysis
  • Sweden