Multivariate analysis of lipoprotein cholesterol fractions

George P. Vogler, D. C. Rao, P. M. Laskarzewski, C. J. Glueck, J. M. Russell

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Intervention and prevention of multifactorial diseases such as coronary heart disease can be effective only when the joint effects of multiple risk factors are known. This process is facilitated by multivariate analysis of correlated risk factors, such as the serum cholesterol fractions, high density lipoprotein (HDL), low density lipoprotein (LDL), and very low density lipoprotein (VLDL). Whereas evidence for genetic covariation provides focus for further refined biochemical analysis, covariation among environmental factors can point to efficacious intervention strategies. To assess sources of variation and covariation among HDL, LDL, and VLDL, a multivariate path model was developed and applied to family data. Phenotypic variance is due primarily to specific environmental influences with substantial genetic influences, with the common family environment contributing less than 10% of the variance. There are genetic correlations of (-0.22 for HDL-VLDL and 0.35 for VLDL-LDL, consistent with the known inverse associations of HDL and VLDL and the precursor-product relationship between VLDL and LDL, whereas there is no evidence for a direct HDL-LDL genetic relationship. Strong specific environmental correlations are found between HDL and VLDL (-0.35 in children and (-0.50 in adults). Thus, intervention focused primarily on one fraction (e.g., triglycerides and VLDL) might beneficially affect levels of both lipoproteins (e.g., lowering VLDL cholesterol and elevating HDL cholesterol). Multivariate analysis can facilitate understanding of the linked effects of intervention on lipoprotein cholesterols, and, hence, should benefit approaches to maximize the effects of lipoprotein cholesterol intervention on coronary heart disease morbidity and mortality.

Original languageEnglish
Pages (from-to)706-719
Number of pages14
JournalAmerican journal of epidemiology
Volume125
Issue number4
DOIs
StatePublished - Apr 1987

Keywords

  • Genetic
  • Genetics
  • Lipoproteins
  • Models
  • Statistics

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