Dietary Intake, FTO Genetic Variants, and Adiposity

A Combined Analysis of Over 16,000 Children and Adolescents

Qibin Qi; Mary K. Downer; Tuomas O. Kilpeläinen; H. Rob Taal; Sheila J. Barton; Ioanna Ntalla; Marie Standl; Vesna Boraska; Ville Huikari; Jessica C. Kiefte-de Jong; Antje Körner; Timo A. Lakka; Gaifen Liu; Jessica Magnusson; Masayuki Okuda; Olli Raitakari; Rebecca Richmond; Robert A. Scott; Mark E.S. Bailey; Kathrin Scheuermann; John W. Holloway; Hazel Inskip; Carmen R. Isasi; Yasmin Mossavar-Rahmani; Vincent W.V. Jaddoe; Jaana Laitinen; Virpi Lindi; Erik Melén; Yannis Pitsiladis; Niina Pitkänen; Harold Snieder; Joachim Heinrich; Nicholas J. Timpson; Tao Wang; Hinoda Yuji; Eleftheria Zeggini; George V. Dedoussis; Robert C. Kaplan; Judith Wylie-Rosett; Ruth J.F. Loos; Frank B. Hu; Lu Qi

Disclosures

Diabetes. 2015;64(7):2467-2476. 

In This Article

Results

FTO Variants and BMI

We found a significant association between the minor allele (A-allele) of the FTO SNP rs9939609 (or its proxies) and a higher BMI in all participants combined (effect per allele = 0.07 SD [95% CI 0.05, 0.09 SDs], P = 4.7 × 10−10) (Table 1). The association was significant in 15,352 whites (effect per allele = 0.08 SD [0.05, 0.10 SDs], P = 2.9 × 10−11), but not in 478 African Americans (effect per allele = −0.12 SD [−0.26, 0.02 SDs], P = 0.08) or 267 Asians (effect per allele = 0.11 SD [−0.12, 0.09 SDs], P = 0.87), separately.

FTO Variants and Dietary Intake

The minor allele of the FTO variant was significantly associated with higher total energy intake in all participants combined (effect per allele = 14.6 kcal/day [6.3, 23.1 kcal/day], P = 6.5 × 10−4), with no heterogeneity among studies (I 2 = 0%) (Table 1). This association was unchanged after further adjustment for BMI (effect per allele = 14.7 kcal/day [6.3, 23.1 kcal/day], P = 6.5 × 10−4). The association between FTO variant and total energy intake was found in whites (P = 0.001) and Asians (P = 0.01), but not in African Americans (P = 0.80), although directions of associations were consistent across ethnicities (P for heterogeneity = 0.07) (Fig. 1). In stratified meta-analyses according to sex, age group, geographic region, study design, dietary intake assessment method, and adjustment for physical activity (Supplementary Fig. 1 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1), the directions of the associations between FTO variant and total energy intake were consistent across subgroups. Of note, the association was stronger in studies with a mean age for participants of ≥10 years than in studies with a mean age of <10 years (effect per allele = 25.3 vs. 4.2 kcal/day, P for heterogeneity = 0.014). Since most studies had a mean age for participants of >7.5 years and three studies had a mean age between 1.0 and 3.5 years, we further examined the association between FTO variant and total energy intake according to the following three categories of age: studies with a mean age for participants between 1.0 and 3.5 years (effect per allele = 2.4 kcal/day); studies with a mean age for participants between 7.5 and 10 years (effect per allele = 10.6 kcal/day); and studies with a mean age for participants of ≥10 years old (effect per allele = 25.3 kcal/day).

Figure 1.

Forest plot of the association between FTO SNP rs9939609 and total energy intake in a fixed-effects meta-analysis of 16,097 children and adolescents. The studies are shown in boys (_B), girls (_G), or mixed case patients (_Case) and control subjects (_Control) for case-control studies and whites (_White) and African Americans (_AA) for studies with multiple ethnicities separately, sorted by sample size (smallest to largest). The β represents the difference in total energy intake per minor allele of SNP rs9939609 or a proxy (r 2 = 1), adjusted for age, pubertal status (if available), physical activity (if available), region (if available), and eigenvectors (GWAS data only).

We did not find evidence for associations between FTO variant and intake of protein (P = 0.10), carbohydrate (P = 0.96), or fat (P = 0.40), and there was a low or moderate heterogeneity among studies (I 2 = 0%, 24%, and 34%, respectively) (Table 1 and Supplementary Figs. 2, 3, and 4 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1). Further adjustment for BMI did not notably change the results.

We also performed meta-analyses for FTO variant and dietary intake using the random-effects method, resulting in similar findings (Supplementary Table 5 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1).

Dietary Intake and BMI

Higher total energy and protein intake were significantly associated with higher BMI (Supplementary Table 6 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1). Difference in BMI between the high and low energy intake groups was 0.04 SD (95% CI 0.01, 0.02 SDs, P = 0.004), and difference in BMI between the high–protein intake and low–protein intake groups was 0.09 SD (0.07, 0.12 SDs, P = 5.0 × 10−10). There was no significant difference in BMI between the high–carbohydrate intake and low–carbohydrate intake groups (difference in BMI = −0.02 SD [−0.05, 0.01 SDs], P = 0.12), and a nominally significant difference in BMI between the high–fat intake and low–fat intake groups (difference in BMI = −0.03 SD [−0.06, −0.001 SDs], P = 0.04).

Interaction Between FTO Variants and Dietary Intake on BMI

We observed a significant interaction between FTO variant and dietary protein intake on BMI in all participants combined (effect per allele for interaction = 0.08 SD [95% CI 0.03, 0.12 SDs], P for interaction = 7.2 × 10−4), showing that lower protein intake attenuated the association between the FTO variant and BMI, with no heterogeneity among studies (I 2 = 0%) (Table 2). In stratified analysis by low–protein intake and high–protein intake groups (dichotomized at medians of protein intake in each study: ranging from 12.9% to 16.8% across studies). The association between FTO variant and BMI among participants in the low–protein intake group (effect per allele = 0.04 SD [95% CI 0.01, 0.07 SDs], P = 0.02) was significantly weaker than that in the high–protein intake group (effect per allele = 0.10 SD [0.07, 0.13 SDs], P = 8.2 × 10−10) (Table 2). Although the interaction was found in whites (P for interaction = 0.001) but not in African Americans (P = 0.84) or Asians (P = 0.11) separately, there was no significant heterogeneity among these ethnic groups (P for heterogeneity = 0.53) (Fig. 2). In stratified meta-analyses (Supplementary Fig. 5 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1), we found similar interaction patterns between FTO variant and protein intake on BMI across subgroups divided by sex, age group, geographic region, study design, dietary intake assessment method, and adjustment for physical activity (all P for heterogeneity > 0.11).

Figure 2.

Forest plot of the interaction between FTO SNP rs9939609 and dietary protein intake on BMI in a fixed-effects meta-analysis of 16,097 children and adolescents. The studies are shown in boys (_B), girls (_G), or mixed case patients (_Case) and control subjects (_Control) for case-control studies and whites (_White) and African Americans (_AA) for studies with multiple ethnicities separately, sorted by sample size (smallest to largest). The β represents the difference in BMI per minor allele of SNP rs9939609 or a proxy (r 2 = 1) comparing participants in the high–protein intake group to those in the low–protein intake group, adjusted for age, pubertal status (if available), physical activity (if available), region (if available), and eigenvectors (GWAS data only).

We did not find substantive evidence for interactions between FTO variant and total energy intake (P for interaction = 0.20), carbohydrate intake (P for interaction = 0.98), or fat intake (P for interaction = 0.89) on BMI (Table 2 and Supplementary Figs. 6, 7, and 8 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1). The heterogeneity among studies was low (I 2 = 0%, 15%, and 5%, respectively). In analyses stratified by levels of dietary intake, associations between FTO variant and BMI were similar in high- and low-intake groups (Table 2).

In addition, since there was little or no heterogeneity in interactions between FTO variant and dietary intake on BMI across studies, the results were similar when we performed meta-analyses using the random-effects method (Supplementary Table 7 http://diabetes.diabetesjournals.org/content/64/7/2467/suppl/DC1).

processing....