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Gene-diet interaction effects on BMI levels in the Singapore Chinese population

BACKGROUND: Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. METHODS: We utilized GWAS information from six data subsets from two...

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Autores principales: Chang, Xuling, Dorajoo, Rajkumar, Sun, Ye, Han, Yi, Wang, Ling, Khor, Chiea-Chuen, Sim, Xueling, Tai, E-Shyong, Liu, Jianjun, Yuan, Jian-Min, Koh, Woon-Puay, van Dam, Rob M., Friedlander, Yechiel, Heng, Chew-Kiat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389173/
https://www.ncbi.nlm.nih.gov/pubmed/29477148
http://dx.doi.org/10.1186/s12937-018-0340-3
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author Chang, Xuling
Dorajoo, Rajkumar
Sun, Ye
Han, Yi
Wang, Ling
Khor, Chiea-Chuen
Sim, Xueling
Tai, E-Shyong
Liu, Jianjun
Yuan, Jian-Min
Koh, Woon-Puay
van Dam, Rob M.
Friedlander, Yechiel
Heng, Chew-Kiat
author_facet Chang, Xuling
Dorajoo, Rajkumar
Sun, Ye
Han, Yi
Wang, Ling
Khor, Chiea-Chuen
Sim, Xueling
Tai, E-Shyong
Liu, Jianjun
Yuan, Jian-Min
Koh, Woon-Puay
van Dam, Rob M.
Friedlander, Yechiel
Heng, Chew-Kiat
author_sort Chang, Xuling
collection PubMed
description BACKGROUND: Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. METHODS: We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. RESULTS: Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10(− 15)) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP(interaction) = 0.043). CONCLUSIONS: The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12937-018-0340-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-63891732019-03-19 Gene-diet interaction effects on BMI levels in the Singapore Chinese population Chang, Xuling Dorajoo, Rajkumar Sun, Ye Han, Yi Wang, Ling Khor, Chiea-Chuen Sim, Xueling Tai, E-Shyong Liu, Jianjun Yuan, Jian-Min Koh, Woon-Puay van Dam, Rob M. Friedlander, Yechiel Heng, Chew-Kiat Nutr J Research BACKGROUND: Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. METHODS: We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. RESULTS: Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10(− 15)) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP(interaction) = 0.043). CONCLUSIONS: The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12937-018-0340-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-24 /pmc/articles/PMC6389173/ /pubmed/29477148 http://dx.doi.org/10.1186/s12937-018-0340-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Chang, Xuling
Dorajoo, Rajkumar
Sun, Ye
Han, Yi
Wang, Ling
Khor, Chiea-Chuen
Sim, Xueling
Tai, E-Shyong
Liu, Jianjun
Yuan, Jian-Min
Koh, Woon-Puay
van Dam, Rob M.
Friedlander, Yechiel
Heng, Chew-Kiat
Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title_full Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title_fullStr Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title_full_unstemmed Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title_short Gene-diet interaction effects on BMI levels in the Singapore Chinese population
title_sort gene-diet interaction effects on bmi levels in the singapore chinese population
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389173/
https://www.ncbi.nlm.nih.gov/pubmed/29477148
http://dx.doi.org/10.1186/s12937-018-0340-3
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