Abstract

Introduction

Several studies have recently described association between variation at the FTO gene locus and body mass index (BMI), the risk of obesity and adiposity(1, 2). FTO had been identified as one of several loci involved in a knockout murine model resulting in a fused toe phenotype (Ft)(3), however had not been noted for other biological associations. Recently, work focusing on the nature of this locus has shown there to be ubiquitous expression of this protein in foetal and adult tissues, with a preferential hypothalamic mRNA profile. This and evidence for possible links between FTO and dietary consumption in mice (4) have prompted investigation into the FTO locus as one potentially influencing appetite and this being a possible mechanism contributing to the known association between FTO and BMI/fat mass. Of particular interest is the notion that BMI associated variation at the FTO locus may not only be associated with appetite as a result of elevated energy demand (coincident with weight increase), but also may independently influence appetite.

Recognizing fto as a demethylation catalyst, Gerken et al examined fto mRNA levels in the hypothalamic nuclei of mice grouped by feeding behavior(4). This work explored whether hypothalamic fto expression is nutritionally regulated and noted that fto mRNA levels are indeed reduced in fasted mice. This, along with similar patterns of hypothalamic expression and a fasting effect shown by Stratigopoulos et al (5), has formed part of the first functional evidence available on the human FTO gene and provided possible links to the control of energy balance. Furthermore, the existence of variation at this locus within predicted cut like homeobox (CUTL1) binding sites which have demonstrable regulatory effects on the expression of FTO (and the related FTM/RPGRIP1-like locus) has suggested a route between observed genetic variation at this locus and altered hypothalamic activity (5).

Assessing the relationship between BMI associated features and appetite/dietary intake is a difficult procedure for two reasons. First, people with higher BMI may have higher total energy intakes since these are required to maintain their greater adiposity(6). Second, their may be systematic under-reporting of dietary intake by people with higher BMI levels(7). A key component of this investigation is the incorporation of methodology designed to correct for this effect and to provide estimates of the effect of FTO gene variation that are not biased by these issues. In most cases, the relationship between genetic variation and such anomalies are essentially randomized as a result of the Mendelian allocation of alleles at meiosis and conception(8, 9). However, in this case, this may not be the case owing to the known association between variation at the FTO locus and BMI; with the BMI elevating effect of the FTO risk allele possibly influencing energy intake or influencing reporting tendency.

We examine the first issue through adjusting the association between FTO and dietary intake for BMI. This may, of course, represent over-adjustment, but the unconfounded effect should lie between the unadjusted and adjusted effect estimates. With regard to under-reporting we approached this by assessing the relationship between genotypes and reporting accuracy and also by repeating the analyses after excluding children flagged as being under-reporters utilizing standard methods(6).

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective study of pregnancy and childhood where detailed dietary records have been used to assess childhood consumption of food and drinks (10, 11). Considering that the FTO locus may exert an effect on adiposity through an alteration of appetite and dietary consumption, we aimed to examine the relationship between genotypes at the single nucleotide polymorphism (SNP) rs9939609 and a series of variables relating to the daily intake of dietary components. We hypothesised that the FTO allele associated with higher BMI would be related to greater energy intake, but also carried out exploratory analyses of other dietary measures. The availability of measures of BMI and the accuracy of dietary reporting allowed us to assess whether appetite effects may be considered independent of BMI related energy demand and also to avoid potential bias generated by BMI related misreporting.

Subjects and Methods

Genotyping and numbers included

Genotyping of rs9939609 was undertaken in 8,480 children(1). Genotyping was performed by KBiosciences (Hoddesdon, UK) using their own system of fluorescence-based competitive allele-specific PCR (KASPar). Details of assay design are available from the KBiosciences website (http://www.kbioscience.co.uk). After accounting for missing data and exclusion for under-reporting, accurate information on dietary intake was available for 3641 children with FTO genotypes, 3589 of whom also had measurements for BMI (Figure 1). Results for the overall sample, without exclusion, are reported in supplementary table (Table S1). The exclusion for under-reporting yielded substantial reduction in the effective sample size, however was considered important as a result of the potentially distorting effects misreporting individuals may have on our findings.

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Figure 1

Numbers of individuals included in analyses for association between rs9939609 and dietary intake.

Results

General characteristics for the major dietary components (macronutrients) can be seen in Table 1. Energy and nutrient intakes were at levels expected for children aged 10-11 years(20) with higher intakes for all nutrients in males compared to females. However, whilst consistent differences were observed between the sexes, there were no consistent differences between the dietary intakes of those with and without genotypic data (747 children) that would withstand correction for multiple testing. Thus it appears that the children with genotypic data were representative of the whole population with regard to diet.

The FTO locus showed a minor allele frequency of 0.39 (SE 0.004) in this study. This sample showed no departure from Hardy Weinberg Equilibrium (p^exact=0.5). On removal of individuals flagged for under-reporting (2322), the remaining sample of 3741 individuals with dietary data and required covariates showed a minor allele frequency of 0.40 (SE 0.006) and again did not show departure from Hardy Weinberg equilibrium (p^exact=0.9). A simple test of the difference in the proportion of genotypes by inclusion and exclusion for under-reporting showed no difference in distribution by exclusion criteria (p^chi=0.6).

In an extension to this, despite under-reporters having consistently higher BMI values than the remaining sample (19.96 [19.81, 20.11] versus 17.36 [17.29, 17.44], p=<0.001), this study did not demonstrate the relationship between under-reporting and the FTO SNP rs9939609 that might be predicted by the influence of FTO variation on BMI (OR under-reporter by ‘A’ allele at rs9939609 = 1.01 (0.93, 1.09) p=0.85.

Within this sample, tests of association between rs9939609 and daily dietary consumption indicated detectable, positive, relationships between genetic variation and the daily consumption of total energy, energy from food, saturated fat, monounsaturated fat, polyunsaturated fat (all p<=0.009) and trans-fatty acid (p=0.01) at age 10-11 (Table 2). The effect sizes are very similar in the whole sample (Table S1) and in the sample with exclusions for under-reporting, although the significance values are greater for the whole sample as would be expected given the greater amount of data.​data.

Although we excluded those flagged for reporting bias, these data may reflect co-association between BMI, basal metabolic rate and intake. We therefore adjusted analyses for BMI and found that associations remained (and were of similar magnitude to that before adjustment) for total energy from all food (ratio of geometric means 1.008, SE 0.0037, p=0.03), total fat (ratio of geometric means 1.012, SE 0.005, p=0.02) and saturated fat (ratio of geometric means 1.012 SE 0.007, p=0.05) (Table 2). Conversely, adjustment of the known FTO-BMI association for dietary components was seen to attenuate the relationship between genotype and BMI (Table 4).

We observed a considerable effect of energy intake on BMI of children within this sample when under-reporting had been taken into account. Per-tertile of energy intake, the effect on BMI was a 0.34 SD [SE 0.017] increase, or approximately 0.84kg/m². Without exclusions for under-reporting, the BMI/energy association was 0.03 SD [SE 0.015] (approximately 0.097kg/m²) per tertile of energy intake. This comparison of data before and after correction for reporting bias confirmed a relationship between energy intake and BMI and also that reporting bias has a substantial impact on this association.

There was no difference by genotype in the percentage of total energy (kcal) consumed as fat, carbohydrate and protein (BMI adjusted - fat: mean 35.6% (35.5, 35.7), per allele effect on percentage 0.07[SE 0.09], protein: mean 13.6% (13.5, 13.6), per allele effect on percentage 0.06[0.05], carbohydrate: mean 50.9% (50.7, 51.0), per allele effect on percentage 0.004[SE 0.1]).

Discussion

We observed associations between rs9939609 and the daily intake of energy and fat in a large, representative, sample of children aged 10-11 both before and after adjustment for BMI. Frayling et al (1) report that by this age, the adiposity effect of this locus is stable (approximately 0.1 standard deviations of BMI), however the mechanism(s) of this relationship is as yet unclear.

In our analysis, we were also able to explore the possible effects of misreporting of dietary intake data. Removal of individuals flagged for under-reporting appeared not to influence the distribution of genotypes at rs9939609 and as such genotype was not associated with the likelihood of an individual being either an accurate or inaccurate reporter. Together, this suggests that the relatively small variance in BMI attributable to the FTO locus has not generated an association between dietary under-reporting and genotype and that, when analyses are adjusted for BMI, genotype may indeed give insight into the relationship between this locus and appetite.

Despite this, we performed analyses after excluding individuals with evidence for marked reporting bias and showed that the SNP rs9939609 was nominally associated with the daily intake of both fat and energy. Whilst these findings were of small effects, it was of interest that after BMI adjustment, both our raw data and that corrected for reporting accuracy, yielded evidence of relationships between FTO and dietary intake of a magnitude that is likely to be important over the lifecourse (30, 31). These relationships include total energy, total fat and saturated fat intake and suggest that appetite may be co-associated with variation at this locus, although these results are likely to reflect portions of the variance in dietary intake explained by both basal energy demands (which vary by BMI) and a possible direct effect of the FTO locus on food intake.

An important consideration in the interpretation of these results is that of the possibility of over-adjustment as a result of the incorporation of BMI into models of the association between variation at rs9939609 and appetite. BMI was incorporated into the analysis of relationships between variation at the FTO locus and dietary intake in an effort to remove the effects of the known correlation between metabolic requirements and BMI in accurate dietary reporters. However, as BMI is in part an outcome of dietary intake, such adjustment may attenuate appetite effects. We consider it likely that the actual point estimates of FTO effect on dietary intake will lie between those presented before and after this adjustment.

Importantly, the association between rs9939609 variation and the intake of energy/fat may also be attenuated by the known imprecision of dietary intake measurement and the limited extent to which short-term dietary measures reflect long-term patterns. Whilst this is a limitation, observations here still add to the weight of evidence for a BMI independent relationship between FTO and appetite.

Analysis by effect on the percentage of total energy derived from specific food types indicated that, if the observed appetite effect is real, then is not restricted to any particular dietary component. This would therefore suggest that the observed relationship is one of a generic effect on food intake.

This analysis makes use of the best available evidence to date for the assessment of a possible, direct, role of the FTO locus in regulating dietary intake. In the case of total energy and fat, we have observed nominal evidence for a BMI independent association between this locus and intake even after considerable reduction in sample size as a result of the removal of apparently under-reporting individuals, which did not change the magnitude of the association although it necessarily reduced statistical precision. The independent appetite effect is small, but is of the magnitude that over the lifecourse would be likely to lead to the differences in BMI at least approaching those according to FTO genotype (32-34).

Greater numbers of participants and/or more accurate assessments of dietary intake are required for more comprehensive assessment of this relationship. However, our data are consistent with data from other sources (35) in suggesting that small changes in energy intake will, as they accumulate over time, lead to substantial changes in BMI.

Supplementary Material

Acknowledgements

Ethics

All aspects of the study are reviewed and approved by the ALSPAC Law and Ethics Committee, which is registered as an Institutional Review Board. Approval was also obtained from the Local Research Ethics Committees, which are governed by the Department of Health. More detailed information on the ALSPAC study is available on the web site: http://www.alspac.bris.ac.uk. Parents gave written consent for children in this study.

Contributions

NJT - coordinated and undertook the analysis and writing of the paper. PE - assisted in the writing of the paper. IR - assisted in the organisation of data and in writing of the paper. TMF - was integral to the initial analysis team for FTO and important in the development of hypotheses for this paper. ATH - was integral to the initial analysis team for FTO and important in the development of hypotheses for this paper. MIM - was integral to the initial analysis team for FTO and important in the development of hypotheses and assisted in the writing of this paper. GDS - is the PI responsible for the ALSPAC cohort, helped with the hypothesis generation for this paper and assisted in the writing stages.

Footnotes

References