Clustering of high density lipoprotein cholesterol levels in premenopausal and postmenopausal female twins.

Journal Article (Journal Article)

Previous family and twin studies indicate that genetic variation makes an important contribution to individual variation in high density lipoprotein cholesterol (HDL) levels, even after adjustment for covariates (such as obesity and alcohol consumption) that also cluster in families. However, most studies assume that genetic mechanisms affecting variation in HDL level are the same in all subgroups of the population (e.g., men versus women, by age). Using data from the Kaiser-Permanente Women Twins Study, we found different patterns of clustering for monozygotic (MZ) and dizygotic (DZ) twins depending on menopausal status. Premenopausal MZ twins were more similar than postmenopausal MZ twins (r(i) = 0.79 and r(i) = 0.61, respectively, after adjustment for age, alcohol consumption, smoking status, degree of obesity, and leisure-time exercise); premenopausal and postmenopausal DZ twins were alike to the same extent (r(i) = 0.31 and r(i) = 0.32, respectively, adjusted as above). These data suggest that either postmenopausal MZ twins have a greater degree of shared environment than postmenopausal DZ twins (e.g., postmenopausal female hormone use) or that genetic mechanisms that affect individual variation in HDL level differ in pre- and postmenopausal women. Data were not available on postmenopausal female hormone use. If genetic mechanisms that influence variation in HDL levels differ between pre- and postmenopausal women, genetic epidemiologic methods that assume that genetic and environmental sources of variation are the same for all groups of individuals may lead to false conclusions.

Full Text

Duke Authors

Cited Authors

  • Harris, EL; Falk, RT; Goldstein, AM; Park, LP

Published Date

  • 1993

Published In

Volume / Issue

  • 10 / 6

Start / End Page

  • 563 - 567

PubMed ID

  • 8314061

International Standard Serial Number (ISSN)

  • 0741-0395

Digital Object Identifier (DOI)

  • 10.1002/gepi.1370100639


  • eng

Conference Location

  • United States