OBJECTIVE: Plasma adiponectin and high-density lipoprotein cholesterol (HDL-C) exhibit a well-known positive metabolic correlation. Neither heritability nor genome-wide linkage analysis for the high-molecular weight (HMW) adiponectin is available. This work estimates the genetic and environmental determinants and the heritabilities of the adiponectins and lipid traits in Finnish families with early onset coronary heart disease (CHD) and low HDL-C. METHODS: Heritability and genome-wide univariate linkage analysis was performed for total and HMW adiponectin in extended families from Northern Finland with early onset CHD and low HDL-C using a variance components approach. The genetic and environmental correlations between the plasma adiponectins and various lipid traits were also studied and a bivariate analysis for HDL-C and the adiponectins carried out. RESULTS: In the partial correlation analysis (adjusted for sex, age, BMI and statin use) the adiponectins showed a stronger correlation with HDL-C (total 0.57, p=0.001, HMW 0.51, p<0.005) than with any other lipid trait in unrelated subjects. Our estimates detected strong heritability for total (0.53+/-0.10), HMW (0.51+/-0.10) and the HMW/total adiponectin ratio (0.68+/-0.11). Univariate linkage analysis showed suggestive evidence of linkage on chromosome 11p15 for total adiponectin and on 3q13.2-q24 and 6p21 for the HMW adiponectin. The strongest environmental cross-correlation between the adiponectins and lipids was seen between HDL-C and total adiponectin (rhoe=0.64, p<0.05), whereas the strongest genetic correlation was detected between low-density lipoprotein cholesterol and the HMW adiponectin (rhog=-0.48, p<0.05). CONCLUSION: No significant genetic correlations between HDL-C and the adiponectins were observed. Therefore, the metabolic association between HDL-C and adiponectin is most likely regulated by complex genetic pathways and environmental factors. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.
OBJECTIVE: Plasma adiponectin and high-density lipoprotein cholesterol (HDL-C) exhibit a well-known positive metabolic correlation. Neither heritability nor genome-wide linkage analysis for the high-molecular weight (HMW) adiponectin is available. This work estimates the genetic and environmental determinants and the heritabilities of the adiponectins and lipid traits in Finnish families with early onset coronary heart disease (CHD) and low HDL-C. METHODS: Heritability and genome-wide univariate linkage analysis was performed for total and HMW adiponectin in extended families from Northern Finland with early onset CHD and low HDL-C using a variance components approach. The genetic and environmental correlations between the plasma adiponectins and various lipid traits were also studied and a bivariate analysis for HDL-C and the adiponectins carried out. RESULTS: In the partial correlation analysis (adjusted for sex, age, BMI and statin use) the adiponectins showed a stronger correlation with HDL-C (total 0.57, p=0.001, HMW 0.51, p<0.005) than with any other lipid trait in unrelated subjects. Our estimates detected strong heritability for total (0.53+/-0.10), HMW (0.51+/-0.10) and the HMW/total adiponectin ratio (0.68+/-0.11). Univariate linkage analysis showed suggestive evidence of linkage on chromosome 11p15 for total adiponectin and on 3q13.2-q24 and 6p21 for the HMW adiponectin. The strongest environmental cross-correlation between the adiponectins and lipids was seen between HDL-C and total adiponectin (rhoe=0.64, p<0.05), whereas the strongest genetic correlation was detected between low-density lipoprotein cholesterol and the HMW adiponectin (rhog=-0.48, p<0.05). CONCLUSION: No significant genetic correlations between HDL-C and the adiponectins were observed. Therefore, the metabolic association between HDL-C and adiponectin is most likely regulated by complex genetic pathways and environmental factors. Copyright (c) 2009 Elsevier Ireland Ltd. All rights reserved.
Authors: Krasimira Aleksandrova; Mazda Jenab; H Bas Bueno-de-Mesquita; Veronika Fedirko; Rudolf Kaaks; Annekatrin Lukanova; Fränzel J B van Duijnhoven; Eugene Jansen; Sabina Rinaldi; Isabelle Romieu; Pietro Ferrari; Neil Murphy; Marc J Gunter; Elio Riboli; Sabine Westhpal; Kim Overvad; Anne Tjønneland; Jytte Halkjær; Marie-Christine Boutron-Ruault; Laure Dossus; Antoine Racine; Antonia Trichopoulou; Christina Bamia; Philippos Orfanos; Claudia Agnoli; Domenico Palli; Salvatore Panico; Rosario Tumino; Paolo Vineis; Petra H Peeters; Eric J Duell; Esther Molina-Montes; J Ramón Quirós; Miren Dorronsoro; Maria-Dolores Chirlaque; Aurelio Barricarte; Ingrid Ljuslinder; Richard Palmqvist; Ruth C Travis; Kay-Tee Khaw; Nicholas Wareham; Tobias Pischon; Heiner Boeing Journal: Eur J Epidemiol Date: 2014-05-04 Impact factor: 8.082
Authors: Lu Qi; Claudia Menzaghi; Lucia Salvemini; Concetta De Bonis; Vincenzo Trischitta; Frank B Hu Journal: Diabetes Date: 2011-06-23 Impact factor: 9.461