BACKGROUND: A poor diet is a risk factor for chronic diseases such as obesity, cardiovascular disease, hypertension, and some cancers. Twin and family studies suggest that genetic factors potentially influence energy and nutrient intakes. OBJECTIVE: We sought to identify genomic regions harboring genes affecting total energy, carbohydrate, protein, and fat intakes. DESIGN: We performed a genomic scan in 347 white sibling pairs and 99 black sibling pairs. Dietary energy and nutrient intakes were assessed by using Willett's food-frequency questionnaire. Single-point and multipoint Haseman-Elston regression techniques were used to test for linkage. These subjects were part of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a multicenter project undertaken by 5 laboratories. RESULTS: In the whites, the strongest evidence of linkage appeared for dietary energy and nutrient intakes on chromosomes 1p21.2 (P = 0.0002) and 20q13.13 (P = 0.00007), and that for fat intake appeared on chromosome 12q14.1 (P = 0.0013). The linkage evidence on chromosomes 1 and 20 related to total energy intake rather than to the intake of specific macronutrients. In the blacks, promising linkages for macronutrient intakes occurred on chromosomes 12q23-q24.21, 1q32.1, and 7q11.1. Several potential candidate genes are encoded in and around the linkage regions on chromosomes 1p21.2, 12q14.1, and 20q13.13. CONCLUSIONS: These are the first reported human quantitative trait loci for dietary energy and macronutrient intakes. Further study may refine these quantitative trait loci to identify potential candidate genes for energy and specific macronutrient intakes that would be amenable to more detailed molecular studies.
BACKGROUND: A poor diet is a risk factor for chronic diseases such as obesity, cardiovascular disease, hypertension, and some cancers. Twin and family studies suggest that genetic factors potentially influence energy and nutrient intakes. OBJECTIVE: We sought to identify genomic regions harboring genes affecting total energy, carbohydrate, protein, and fat intakes. DESIGN: We performed a genomic scan in 347 white sibling pairs and 99 black sibling pairs. Dietary energy and nutrient intakes were assessed by using Willett's food-frequency questionnaire. Single-point and multipoint Haseman-Elston regression techniques were used to test for linkage. These subjects were part of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a multicenter project undertaken by 5 laboratories. RESULTS: In the whites, the strongest evidence of linkage appeared for dietary energy and nutrient intakes on chromosomes 1p21.2 (P = 0.0002) and 20q13.13 (P = 0.00007), and that for fat intake appeared on chromosome 12q14.1 (P = 0.0013). The linkage evidence on chromosomes 1 and 20 related to total energy intake rather than to the intake of specific macronutrients. In the blacks, promising linkages for macronutrient intakes occurred on chromosomes 12q23-q24.21, 1q32.1, and 7q11.1. Several potential candidate genes are encoded in and around the linkage regions on chromosomes 1p21.2, 12q14.1, and 20q13.13. CONCLUSIONS: These are the first reported human quantitative trait loci for dietary energy and macronutrient intakes. Further study may refine these quantitative trait loci to identify potential candidate genes for energy and specific macronutrient intakes that would be amenable to more detailed molecular studies.
Authors: Kathleen L Keller; Lisa C H Liang; Johannah Sakimura; Daniel May; Christopher van Belle; Cameron Breen; Elissa Driggin; Beverly J Tepper; Patricia C Lanzano; Liyong Deng; Wendy K Chung Journal: Obesity (Silver Spring) Date: 2012-01-12 Impact factor: 5.002
Authors: Jun Wu; James S Pankow; Russell P Tracy; Kari E North; Richard H Myers; Mary E Feitosa; Michael A Province; Ingrid B Borecki Journal: Obesity (Silver Spring) Date: 2008-12-25 Impact factor: 5.002
Authors: A Haghighi; M G Melka; M Bernard; M Abrahamowicz; G T Leonard; L Richer; M Perron; S Veillette; C J Xu; C M T Greenwood; A Dias; A El-Sohemy; D Gaudet; T Paus; Z Pausova Journal: Mol Psychiatry Date: 2013-01-22 Impact factor: 15.992
Authors: Chi Bun Chan; Xia Liu; Dae Young Jung; John Y Jun; Hongbo R Luo; Jason K Kim; Keqiang Ye Journal: Diabetes Date: 2010-01-12 Impact factor: 9.461