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A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study

Body mass index (BMI) is influenced by genetic, behavioral and environmental factors, while interactions between genetic and socioeconomic factors have been suggested. Aim of the study was to investigate whether socioeconomic position (SEP) interacts with a BMI-related genetic sum score (GRS(BMI)) t...

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Detalles Bibliográficos
Autores principales: Frank, Mirjam, Dragano, Nico, Arendt, Marina, Forstner, Andreas J., Nöthen, Markus M., Moebus, Susanne, Erbel, Raimund, Jöckel, Karl-Heinz, Schmidt, Börge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707579/
https://www.ncbi.nlm.nih.gov/pubmed/31442235
http://dx.doi.org/10.1371/journal.pone.0221252
Descripción
Sumario:Body mass index (BMI) is influenced by genetic, behavioral and environmental factors, while interactions between genetic and socioeconomic factors have been suggested. Aim of the study was to investigate whether socioeconomic position (SEP) interacts with a BMI-related genetic sum score (GRS(BMI)) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRS(Edu)) were included in the analysis to explore potential interactions underlying the GRS(BMI)xSEP effect. Baseline information on SEP indicators (education, income), BMI, smoking, physical activity, alcohol consumption and genetic risk factors were available for 4,493 participants of the Heinz Nixdorf Recall Study. Interaction analysis was based on linear regression as well as on stratified analyses. In SEP-stratified analyses, the highest genetic effects were observed in the lowest educational group with a 0.24 kg/m(2) higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m(2) higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRS(BMI)xSEP interaction was observed for education (ß(GRSbmixeducation) = -0.02 [95%CI:-0.03; -0.01]) and income (ß(GRSbmixincome) = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRS(Edu) and SEP-related health behaviors, effect size estimates of the GRS(BMI)xSEP interaction remained virtually unchanged. Results gave indication for an interaction of BMI-related genetic risk factors with SEP indicators, showing substantially stronger genetic effects in low SEP groups. This supports the hypothesis that expression of genetic risks is higher in socioeconomically disadvantaged environments. No indication was observed that the GRS(BMI)xSEP interaction was affected by other SEP-related factors included in the analysis.