BACKGROUND: Epidemiological investigations have begun to consider gene-environment (GE) interactions as potential risk factors for many diseases, including several different birth defects. However, traditional methodological approaches for the analysis of case-control data tend to have low power for detection of interaction effects. A log-linear approach that can impose the assumption that the genotype and exposure of interest occur independently in the population has been proposed as a potentially more powerful method for assessing GE interactions but has not been widely applied in the published literature. METHODS: The present analyses were undertaken to compare the results obtained when stratified analyses and a log-linear approach were used to assess potential GE interactions. The analyses were conducted using data from a population-based, case-control study conducted in Denmark and considered associations between nonsyndromic cleft lip with or without cleft palate (CL+/-P), infant genotype for variants of RAR-alpha, TGF-alpha, TGF-beta3, and MSX1, and maternal exposure to smoking, alcohol, and multivitamins. RESULTS: Neither the stratified nor the log-linear analyses provided evidence that that risk of CL+/-P is influenced by any of the GE interactions that were evaluated, despite the potential increase in power offered by the latter approach. Further, the analyses highlight concerns regarding the power to reject the assumption of independence of the genetic and environmental factor of interest in the controls and related concerns regarding the validity of results obtained using the log-linear approach when the underlying assumption is violated. CONCLUSIONS: The potential increase in power offered by the log-linear approach is offset by concerns regarding the validity of this approach when the independence assumption is violated. Copyright 2005 Wiley-Liss, Inc.
BACKGROUND: Epidemiological investigations have begun to consider gene-environment (GE) interactions as potential risk factors for many diseases, including several different birth defects. However, traditional methodological approaches for the analysis of case-control data tend to have low power for detection of interaction effects. A log-linear approach that can impose the assumption that the genotype and exposure of interest occur independently in the population has been proposed as a potentially more powerful method for assessing GE interactions but has not been widely applied in the published literature. METHODS: The present analyses were undertaken to compare the results obtained when stratified analyses and a log-linear approach were used to assess potential GE interactions. The analyses were conducted using data from a population-based, case-control study conducted in Denmark and considered associations between nonsyndromic cleft lip with or without cleft palate (CL+/-P), infant genotype for variants of RAR-alpha, TGF-alpha, TGF-beta3, and MSX1, and maternal exposure to smoking, alcohol, and multivitamins. RESULTS: Neither the stratified nor the log-linear analyses provided evidence that that risk of CL+/-P is influenced by any of the GE interactions that were evaluated, despite the potential increase in power offered by the latter approach. Further, the analyses highlight concerns regarding the power to reject the assumption of independence of the genetic and environmental factor of interest in the controls and related concerns regarding the validity of results obtained using the log-linear approach when the underlying assumption is violated. CONCLUSIONS: The potential increase in power offered by the log-linear approach is offset by concerns regarding the validity of this approach when the independence assumption is violated. Copyright 2005 Wiley-Liss, Inc.
Authors: Marie-José H van den Boogaard; Dominique de Costa; Ingrid P C Krapels; Fan Liu; Cock van Duijn; Richard J Sinke; Dick Lindhout; Régine P M Steegers-Theunissen Journal: Hum Genet Date: 2008-10-19 Impact factor: 4.132
Authors: Mary E Swartz; Michael B Wells; Melissa Griffin; Neil McCarthy; Charles B Lovely; Patrick McGurk; Jenna Rozacky; Johann K Eberhart Journal: Alcohol Clin Exp Res Date: 2013-10-24 Impact factor: 3.455