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Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4)
Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake. Design: We pe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Nutrition
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652928/ https://www.ncbi.nlm.nih.gov/pubmed/23636237 http://dx.doi.org/10.3945/ajcn.112.052183 |
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author | Tanaka, Toshiko Ngwa, Julius S van Rooij, Frank JA Zillikens, M Carola Wojczynski, Mary K Frazier-Wood, Alexis C Houston, Denise K Kanoni, Stavroula Lemaitre, Rozenn N Luan, Jian'an Mikkilä, Vera Renstrom, Frida Sonestedt, Emily Zhao, Jing Hua Chu, Audrey Y Qi, Lu Chasman, Daniel I de Oliveira Otto, Marcia C Dhurandhar, Emily J Feitosa, Mary F Johansson, Ingegerd Khaw, Kay-Tee Lohman, Kurt K Manichaikul, Ani McKeown, Nicola M Mozaffarian, Dariush Singleton, Andrew Stirrups, Kathleen Viikari, Jorma Ye, Zheng Bandinelli, Stefania Barroso, Inês Deloukas, Panos Forouhi, Nita G Hofman, Albert Liu, Yongmei Lyytikäinen, Leo-Pekka North, Kari E Dimitriou, Maria Hallmans, Goran Kähönen, Mika Langenberg, Claudia Ordovas, Jose M Uitterlinden, André G Hu, Frank B Kalafati, Ioanna-Panagiota Raitakari, Olli Franco, Oscar H Johnson, Andrew Emilsson, Valur Schrack, Jennifer A Semba, Richard D Siscovick, David S Arnett, Donna K Borecki, Ingrid B Franks, Paul W Kritchevsky, Stephen B Lehtimäki, Terho Loos, Ruth JF Orho-Melander, Marju Rotter, Jerome I Wareham, Nicholas J Witteman, Jacqueline CM Ferrucci, Luigi Dedoussis, George Cupples, L Adrienne Nettleton, Jennifer A |
author_facet | Tanaka, Toshiko Ngwa, Julius S van Rooij, Frank JA Zillikens, M Carola Wojczynski, Mary K Frazier-Wood, Alexis C Houston, Denise K Kanoni, Stavroula Lemaitre, Rozenn N Luan, Jian'an Mikkilä, Vera Renstrom, Frida Sonestedt, Emily Zhao, Jing Hua Chu, Audrey Y Qi, Lu Chasman, Daniel I de Oliveira Otto, Marcia C Dhurandhar, Emily J Feitosa, Mary F Johansson, Ingegerd Khaw, Kay-Tee Lohman, Kurt K Manichaikul, Ani McKeown, Nicola M Mozaffarian, Dariush Singleton, Andrew Stirrups, Kathleen Viikari, Jorma Ye, Zheng Bandinelli, Stefania Barroso, Inês Deloukas, Panos Forouhi, Nita G Hofman, Albert Liu, Yongmei Lyytikäinen, Leo-Pekka North, Kari E Dimitriou, Maria Hallmans, Goran Kähönen, Mika Langenberg, Claudia Ordovas, Jose M Uitterlinden, André G Hu, Frank B Kalafati, Ioanna-Panagiota Raitakari, Olli Franco, Oscar H Johnson, Andrew Emilsson, Valur Schrack, Jennifer A Semba, Richard D Siscovick, David S Arnett, Donna K Borecki, Ingrid B Franks, Paul W Kritchevsky, Stephen B Lehtimäki, Terho Loos, Ruth JF Orho-Melander, Marju Rotter, Jerome I Wareham, Nicholas J Witteman, Jacqueline CM Ferrucci, Luigi Dedoussis, George Cupples, L Adrienne Nettleton, Jennifer A |
author_sort | Tanaka, Toshiko |
collection | PubMed |
description | Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake. Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(−6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data. Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(−8)) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10(−9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(−10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(−7)). Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis). |
format | Online Article Text |
id | pubmed-3652928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | American Society for Nutrition |
record_format | MEDLINE/PubMed |
spelling | pubmed-36529282014-06-01 Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) Tanaka, Toshiko Ngwa, Julius S van Rooij, Frank JA Zillikens, M Carola Wojczynski, Mary K Frazier-Wood, Alexis C Houston, Denise K Kanoni, Stavroula Lemaitre, Rozenn N Luan, Jian'an Mikkilä, Vera Renstrom, Frida Sonestedt, Emily Zhao, Jing Hua Chu, Audrey Y Qi, Lu Chasman, Daniel I de Oliveira Otto, Marcia C Dhurandhar, Emily J Feitosa, Mary F Johansson, Ingegerd Khaw, Kay-Tee Lohman, Kurt K Manichaikul, Ani McKeown, Nicola M Mozaffarian, Dariush Singleton, Andrew Stirrups, Kathleen Viikari, Jorma Ye, Zheng Bandinelli, Stefania Barroso, Inês Deloukas, Panos Forouhi, Nita G Hofman, Albert Liu, Yongmei Lyytikäinen, Leo-Pekka North, Kari E Dimitriou, Maria Hallmans, Goran Kähönen, Mika Langenberg, Claudia Ordovas, Jose M Uitterlinden, André G Hu, Frank B Kalafati, Ioanna-Panagiota Raitakari, Olli Franco, Oscar H Johnson, Andrew Emilsson, Valur Schrack, Jennifer A Semba, Richard D Siscovick, David S Arnett, Donna K Borecki, Ingrid B Franks, Paul W Kritchevsky, Stephen B Lehtimäki, Terho Loos, Ruth JF Orho-Melander, Marju Rotter, Jerome I Wareham, Nicholas J Witteman, Jacqueline CM Ferrucci, Luigi Dedoussis, George Cupples, L Adrienne Nettleton, Jennifer A Am J Clin Nutr Nutritional Epidemiology and Public Health Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants. Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake. Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10(−6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data. Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10(−8)) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10(−9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10(−10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10(−7)). Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis). American Society for Nutrition 2013-06 2013-05-01 /pmc/articles/PMC3652928/ /pubmed/23636237 http://dx.doi.org/10.3945/ajcn.112.052183 Text en © 2013 American Society for Nutrition This is a free access article, distributed under terms (http://www.nutrition.org/publications/guidelines-and-policies/license/) which permit unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Nutritional Epidemiology and Public Health Tanaka, Toshiko Ngwa, Julius S van Rooij, Frank JA Zillikens, M Carola Wojczynski, Mary K Frazier-Wood, Alexis C Houston, Denise K Kanoni, Stavroula Lemaitre, Rozenn N Luan, Jian'an Mikkilä, Vera Renstrom, Frida Sonestedt, Emily Zhao, Jing Hua Chu, Audrey Y Qi, Lu Chasman, Daniel I de Oliveira Otto, Marcia C Dhurandhar, Emily J Feitosa, Mary F Johansson, Ingegerd Khaw, Kay-Tee Lohman, Kurt K Manichaikul, Ani McKeown, Nicola M Mozaffarian, Dariush Singleton, Andrew Stirrups, Kathleen Viikari, Jorma Ye, Zheng Bandinelli, Stefania Barroso, Inês Deloukas, Panos Forouhi, Nita G Hofman, Albert Liu, Yongmei Lyytikäinen, Leo-Pekka North, Kari E Dimitriou, Maria Hallmans, Goran Kähönen, Mika Langenberg, Claudia Ordovas, Jose M Uitterlinden, André G Hu, Frank B Kalafati, Ioanna-Panagiota Raitakari, Olli Franco, Oscar H Johnson, Andrew Emilsson, Valur Schrack, Jennifer A Semba, Richard D Siscovick, David S Arnett, Donna K Borecki, Ingrid B Franks, Paul W Kritchevsky, Stephen B Lehtimäki, Terho Loos, Ruth JF Orho-Melander, Marju Rotter, Jerome I Wareham, Nicholas J Witteman, Jacqueline CM Ferrucci, Luigi Dedoussis, George Cupples, L Adrienne Nettleton, Jennifer A Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title | Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title_full | Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title_fullStr | Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title_full_unstemmed | Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title_short | Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
title_sort | genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake(1)(2)(3)(4) |
topic | Nutritional Epidemiology and Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652928/ https://www.ncbi.nlm.nih.gov/pubmed/23636237 http://dx.doi.org/10.3945/ajcn.112.052183 |
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