AIMS/HYPOTHESIS: The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. METHODS: Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. RESULTS: Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. CONCLUSIONS/ INTERPRETATION: Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.
AIMS/HYPOTHESIS: The common genetic and environmental effects on endophenotypes related to the metabolic syndrome have been investigated using bivariate and multivariate twin models. This paper extends the pairwise analysis approach by introducing independent and common pathway models to Chinese twin data. The aim was to explore the common genetic architecture in the development of these phenotypes in the Chinese population. METHODS: Three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted to 695 pairs of Chinese twins representing six phenotypes including BMI, total cholesterol, total triacylglycerol, fasting glucose, HDL and LDL. Performances of the nested models were compared with that of the full Cholesky model. RESULTS: Cross-phenotype correlation coefficients gave clear indication of common genetic or environmental backgrounds in the phenotypes. Decomposition of phenotypic correlation by the Cholesky model revealed that the observed phenotypic correlation among lipid phenotypes had genetic and unique environmental backgrounds. Both pathway models suggest a common genetic architecture for lipid phenotypes, which is distinct from that of the non-lipid phenotypes. The declining performance with model restriction indicates biological heterogeneity in development among some of these phenotypes. CONCLUSIONS/ INTERPRETATION: Our multivariate analyses revealed common genetic and environmental backgrounds for the studied lipid phenotypes in Chinese twins. Model performance showed that physiologically distinct endophenotypes may follow different genetic regulations.
Authors: Khytam Dawood; Katherine M Kirk; J Michael Bailey; Paul W Andrews; Nicholas G Martin Journal: Twin Res Hum Genet Date: 2005-02 Impact factor: 1.587
Authors: Ann L Hasselbalch; Beben Benyamin; Peter M Visscher; Berit L Heitmann; Kirsten O Kyvik; Thorkild I A Sørensen Journal: Obesity (Silver Spring) Date: 2008-10-16 Impact factor: 5.002
Authors: Yurii S Aulchenko; Samuli Ripatti; Ida Lindqvist; Dorret Boomsma; Iris M Heid; Peter P Pramstaller; Brenda W J H Penninx; A Cecile J W Janssens; James F Wilson; Tim Spector; Nicholas G Martin; Nancy L Pedersen; Kirsten Ohm Kyvik; Jaakko Kaprio; Albert Hofman; Nelson B Freimer; Marjo-Riitta Jarvelin; Ulf Gyllensten; Harry Campbell; Igor Rudan; Asa Johansson; Fabio Marroni; Caroline Hayward; Veronique Vitart; Inger Jonasson; Cristian Pattaro; Alan Wright; Nick Hastie; Irene Pichler; Andrew A Hicks; Mario Falchi; Gonneke Willemsen; Jouke-Jan Hottenga; Eco J C de Geus; Grant W Montgomery; John Whitfield; Patrik Magnusson; Juha Saharinen; Markus Perola; Kaisa Silander; Aaron Isaacs; Eric J G Sijbrands; Andre G Uitterlinden; Jacqueline C M Witteman; Ben A Oostra; Paul Elliott; Aimo Ruokonen; Chiara Sabatti; Christian Gieger; Thomas Meitinger; Florian Kronenberg; Angela Döring; H-Erich Wichmann; Johannes H Smit; Mark I McCarthy; Cornelia M van Duijn; Leena Peltonen Journal: Nat Genet Date: 2008-12-07 Impact factor: 38.330