title: Familial clustering for features of the metabolic syndrome: the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study.
abstract: OBJECTIVE
  Metabolic syndrome-related traits (obesity, glucose intolerance/insulin resistance, dyslipidemia, and hypertension) have been shown to be genetically correlated. It is less clear, however, if the genetic correlation extends to novel risk factors associated with inflammation, impaired fibrinolytic activity, and hyperuricemia. We present a bivariate genetic analysis of MetS-related traits including both traditional and novel risk factors.
  
  
  METHODS
  Genetic correlations were estimated using a variance components procedure in 1,940 nondiabetic white individuals from 445 families in the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study. Twelve MetS-related traits, including BMI, waist circumference, blood pressure, white blood cell count, fasting serum triglycerides, HDL cholesterol, insulin, glucose, plasminogen activator inhibitor-1 antigen, uric acid, and C-reactive protein, were measured and adjusted for covariates, including lifestyle variables.
  
  
  RESULTS
  Significant genetic correlations were detected among BMI, waist circumference, HDL cholesterol, triglycerides, insulin, and plasminogen activator inhibitor-1 antigen and between uric acid and all of the above variables except insulin. C-reactive protein and white blood cell count were genetically correlated with each other, and both showed significant genetic correlations with waist circumference and insulin. Fasting glucose was not significantly genetically correlated with any of the other traits.
  
  
  CONCLUSIONS
  These results suggest that pleiotropic effects of genes or shared family environment contribute to the familial clustering of MetS-related traits.
authors.affiliation: Division of Epidemiology and Community Health, University of Minnesota, 1300 South Second St., Suite 300, Minneapolis, MN 55454, USA. tang0097@tc.umn.edu
authors.forename: Weihong
authors.initials: W
authors.lastname: Tang
authors.forename: Yuling
authors.initials: Y
authors.lastname: Hong
authors.forename: Michael A
authors.initials: MA
authors.lastname: Province
authors.forename: Stephen S
authors.initials: SS
authors.lastname: Rich
authors.forename: Paul N
authors.initials: PN
authors.lastname: Hopkins
authors.forename: Donna K
authors.initials: DK
authors.lastname: Arnett
authors.forename: James S
authors.initials: JS
authors.lastname: Pankow
authors.forename: Michael B
authors.initials: MB
authors.lastname: Miller
authors.forename: John H
authors.initials: JH
authors.lastname: Eckfeldt
mesh_terms: D000328:Adult; D015992:Body Mass Index; D002097:C-Reactive Protein / Q000032:analysis; D008076:Cholesterol, HDL / Q000097:blood; D016000:Cluster Analysis; D005192:Family Health; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D007958:Leukocyte Count; D008297:Male; D024821:Metabolic Syndrome / Q000235:genetics*; D008875:Middle Aged; D010641:Phenotype; D017395:Plasminogen Activator Inhibitor 1 / Q000097:blood; D014280:Triglycerides / Q000097:blood; D014527:Uric Acid / Q000097:blood; D049629:Waist-Hip Ratio
chemical_list: D008076:Cholesterol, HDL; D007328:Insulin; D017395:Plasminogen Activator Inhibitor 1; D014280:Triglycerides; D014527:Uric Acid; D002097:C-Reactive Protein