OBJECTIVES: The aim of the present study was to examine the role of genetic and environmental factors in the phenotypic variance of bruxism in a large population-based cohort of young adult twins in Finland. METHODS: The material of the present study derives from the FinnTwin16 cohort study consisting of five birth cohorts of twin pairs born in 1975-1979 who completed a questionnaire (at mean age 24, range 23-27 years) with data on frequency of sleep-related bruxism in 2000-2002. We used quantitative genetic modeling, based on the genetic similarity of monozygotic and dizygotic twins, to estimate the most probable genetic model for bruxism, based on decomposition of phenotypic variance into components:additive genetic effects (A), dominant genetic effects (D), and non-shared environmental effects (E). RESULTS: On average, 8.7% experienced bruxism weekly, 23.4% rarely, and 67.9% never, with no significant gender difference (p = .052). The best fitting genetic model for bruxism was the AE-model. Additive genetic effects accounted for 52% (95% Cl 0.41--0.62) of the total phenotypic variance. Sex-limitation model revealed no gender differences. CONCLUSIONS: Genetic factors account for a substantial proportion of the phenotypic variation of the liability to sleep-related bruxism, with no gender difference in its genetic architecture.
OBJECTIVES: The aim of the present study was to examine the role of genetic and environmental factors in the phenotypic variance of bruxism in a large population-based cohort of young adult twins in Finland. METHODS: The material of the present study derives from the FinnTwin16 cohort study consisting of five birth cohorts of twin pairs born in 1975-1979 who completed a questionnaire (at mean age 24, range 23-27 years) with data on frequency of sleep-related bruxism in 2000-2002. We used quantitative genetic modeling, based on the genetic similarity of monozygotic and dizygotic twins, to estimate the most probable genetic model for bruxism, based on decomposition of phenotypic variance into components:additive genetic effects (A), dominant genetic effects (D), and non-shared environmental effects (E). RESULTS: On average, 8.7% experienced bruxism weekly, 23.4% rarely, and 67.9% never, with no significant gender difference (p = .052). The best fitting genetic model for bruxism was the AE-model. Additive genetic effects accounted for 52% (95% Cl 0.41--0.62) of the total phenotypic variance. Sex-limitation model revealed no gender differences. CONCLUSIONS: Genetic factors account for a substantial proportion of the phenotypic variation of the liability to sleep-related bruxism, with no gender difference in its genetic architecture.
Authors: Norma Cruz-Fierro; Margarita Martínez-Fierro; Ricardo M Cerda-Flores; Mayra A Gómez-Govea; Iván Delgado-Enciso; Laura E Martínez-De-Villarreal; Mónica T González-Ramírez; Irám Pablo Rodríguez-Sánchez Journal: Biomed Rep Date: 2018-01-15