Familial correlations in the Quebec family study: Cross-trait familial resemblance for body fat with plasma glucose and insulin

T. Rice, A. Nadeau, L. Pérusse, C. Bouchard, D. C. Rao

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40 Scopus citations

Abstract

This study represents one component in our investigation of the familial factors underlying the insulin resistance (or metabolic) syndrome involving obesity, hyperinsulinaemia, glucose intolerance, dyslipidaemia, and hypertension Here we examine the cross-trait familial resemblance between four measures of body size (two assessing total fat [body mass index and sum of: six skinfolds] and two assessing fat patterning [ratio of trunk skinfold sum to extremity skinfold sum, adjusted and unadjusted for total subcutaneous fat]) with fasting plasma levels of glucose, insulin, and the ratio of insulin to glucose (IGR) in non-diabetic families participating in phase 1 of the Quebec Family Study. A bivariate familial correlation model assessed both intraindividual (e. g. father's body size with father's insulin) and interindividual (e.g. father's body size with son's insulin) cross-trait associations. Intraindividual correlations suggested a greater degree of cross-trait associations for body fat (rather than fat distribution) measures with insulin and the IGR (rather than with glucose) levels. While the intraindividual correlations were significant for most cross-trait comparisons, only the sum of six skinfolds evidenced any familial association (i.e. interindividual resemblance) with insulin and the IGR. Specifically, cross-trait parent-offspring (but not sibling or spouse) correlations were significant, with a bivariate familiality estimate (i.e. polygenic and/or common familial environment) of about 8%. While the lack of sibling correlations does not suggest a simple familial hypothesis, a more complex genetic effect underlying the common covariation between total body fat with insulin and IGR cannot be ruled out.

Original languageEnglish
Pages (from-to)1357-1364
Number of pages8
JournalDiabetologia
Volume39
Issue number11
DOIs
StatePublished - 1996

Keywords

  • Bivariate
  • Environmental
  • Genetic
  • Pleiotropy

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