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 (GRSBMI) to...
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Autor*in:	Mirjam Frank [verfasserIn] Nico Dragano [verfasserIn] Marina Arendt [verfasserIn] Andreas J Forstner [verfasserIn] Markus M Nöthen [verfasserIn] Susanne Moebus [verfasserIn] Raimund Erbel [verfasserIn] Karl-Heinz Jöckel [verfasserIn] Börge Schmidt [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 14(2019), 8, p e0221252
Übergeordnetes Werk:	volume:14 ; year:2019 ; number:8, p e0221252

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0221252

Katalog-ID:	DOAJ00600623X

Internformat


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520			\|a 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis.
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allfields	10.1371/journal.pone.0221252 doi (DE-627)DOAJ00600623X (DE-599)DOAJded752c43f44464d980ef7fc5a736d5e DE-627 ger DE-627 rakwb eng Mirjam Frank verfasserin aut A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis. Medicine R Science Q Nico Dragano verfasserin aut Marina Arendt verfasserin aut Andreas J Forstner verfasserin aut Markus M Nöthen verfasserin aut Susanne Moebus verfasserin aut Raimund Erbel verfasserin aut Karl-Heinz Jöckel verfasserin aut Börge Schmidt verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 14(2019), 8, p e0221252 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:14 year:2019 number:8, p e0221252 https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e kostenfrei https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2019 8, p e0221252
spelling	10.1371/journal.pone.0221252 doi (DE-627)DOAJ00600623X (DE-599)DOAJded752c43f44464d980ef7fc5a736d5e DE-627 ger DE-627 rakwb eng Mirjam Frank verfasserin aut A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis. Medicine R Science Q Nico Dragano verfasserin aut Marina Arendt verfasserin aut Andreas J Forstner verfasserin aut Markus M Nöthen verfasserin aut Susanne Moebus verfasserin aut Raimund Erbel verfasserin aut Karl-Heinz Jöckel verfasserin aut Börge Schmidt verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 14(2019), 8, p e0221252 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:14 year:2019 number:8, p e0221252 https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e kostenfrei https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2019 8, p e0221252
allfields_unstemmed	10.1371/journal.pone.0221252 doi (DE-627)DOAJ00600623X (DE-599)DOAJded752c43f44464d980ef7fc5a736d5e DE-627 ger DE-627 rakwb eng Mirjam Frank verfasserin aut A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis. Medicine R Science Q Nico Dragano verfasserin aut Marina Arendt verfasserin aut Andreas J Forstner verfasserin aut Markus M Nöthen verfasserin aut Susanne Moebus verfasserin aut Raimund Erbel verfasserin aut Karl-Heinz Jöckel verfasserin aut Börge Schmidt verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 14(2019), 8, p e0221252 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:14 year:2019 number:8, p e0221252 https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e kostenfrei https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2019 8, p e0221252
allfieldsGer	10.1371/journal.pone.0221252 doi (DE-627)DOAJ00600623X (DE-599)DOAJded752c43f44464d980ef7fc5a736d5e DE-627 ger DE-627 rakwb eng Mirjam Frank verfasserin aut A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis. Medicine R Science Q Nico Dragano verfasserin aut Marina Arendt verfasserin aut Andreas J Forstner verfasserin aut Markus M Nöthen verfasserin aut Susanne Moebus verfasserin aut Raimund Erbel verfasserin aut Karl-Heinz Jöckel verfasserin aut Börge Schmidt verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 14(2019), 8, p e0221252 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:14 year:2019 number:8, p e0221252 https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e kostenfrei https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2019 8, p e0221252
allfieldsSound	10.1371/journal.pone.0221252 doi (DE-627)DOAJ00600623X (DE-599)DOAJded752c43f44464d980ef7fc5a736d5e DE-627 ger DE-627 rakwb eng Mirjam Frank verfasserin aut A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study. 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis. Medicine R Science Q Nico Dragano verfasserin aut Marina Arendt verfasserin aut Andreas J Forstner verfasserin aut Markus M Nöthen verfasserin aut Susanne Moebus verfasserin aut Raimund Erbel verfasserin aut Karl-Heinz Jöckel verfasserin aut Börge Schmidt verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 14(2019), 8, p e0221252 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:14 year:2019 number:8, p e0221252 https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e kostenfrei https://doi.org/10.1371/journal.pone.0221252 kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2019 8, p e0221252
language	English
source	In PLoS ONE 14(2019), 8, p e0221252 volume:14 year:2019 number:8, p e0221252
sourceStr	In PLoS ONE 14(2019), 8, p e0221252 volume:14 year:2019 number:8, p e0221252
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topic_facet	Medicine R Science Q
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container_title	PLoS ONE
authorswithroles_txt_mv	Mirjam Frank @@aut@@ Nico Dragano @@aut@@ Marina Arendt @@aut@@ Andreas J Forstner @@aut@@ Markus M Nöthen @@aut@@ Susanne Moebus @@aut@@ Raimund Erbel @@aut@@ Karl-Heinz Jöckel @@aut@@ Börge Schmidt @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
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author	Mirjam Frank
spellingShingle	Mirjam Frank misc Medicine misc R misc Science misc Q A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study.
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topic_title	A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study
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title	A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study.
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title_full	A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study
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author_browse	Mirjam Frank Nico Dragano Marina Arendt Andreas J Forstner Markus M Nöthen Susanne Moebus Raimund Erbel Karl-Heinz Jöckel Börge Schmidt
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title_sort	genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the heinz nixdorf recall study
title_auth	A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study.
abstract	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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis.
abstractGer	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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis.
abstract_unstemmed	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 (GRSBMI) to affect BMI in a population-based cohort. SEP-related health behaviors and a GRS associated with educational attainment (GRSEdu) were included in the analysis to explore potential interactions underlying the GRSBMIxSEP 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/m2 higher BMI (95%CI: 0.16; 0.31) and in the lowest income quartile with a 0.14 kg/m2 higher BMI (95%CI: 0.09; 0.18) per additional risk allele. Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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 GRSBMIxSEP interaction was affected by other SEP-related factors included in the analysis.
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title_short	A genetic sum score of risk alleles associated with body mass index interacts with socioeconomic position in the Heinz Nixdorf Recall Study.
url	https://doi.org/10.1371/journal.pone.0221252 https://doaj.org/article/ded752c43f44464d980ef7fc5a736d5e https://doaj.org/toc/1932-6203
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Indication for a GRSBMIxSEP interaction was observed for education (ßGRSbmixeducation = -0.02 [95%CI:-0.03; -0.01]) and income (ßGRSbmixincome = -0.05 [95%CI: -0.08; -0.02]). When adjusting for interactions with the GRSEdu and SEP-related health behaviors, effect size estimates of the GRSBMIxSEP 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. 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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.

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