Although obesity is generally associated with lifestyle factors, degree of adiposity is thought to have a significant heritable component(Reference Loos and Bouchard1). SNP in several genes encoding for proteins involved in the hypothalamic control of food intake, energy balance and consequently management of body weight(Reference Rolls2) have been associated with common (non-Mendelian) obesity(Reference Walley, Asher and Froguel3). The fat mass and obesity-associated (FTO), melanocortin-4 receptor (MC4R), leptin (LEP) and leptin receptor (LEPR) genes regulate food intake and energy homeostasis(Reference Grimm and Steinle4) through their actions on the leptin–melanocortin pathway in the hypothalamus(Reference Tung, Ayuso and Shan5), and variants in these loci regions have been identified as genetic risk factors for common obesity.
Genetic variation in FTO was the first common SNP related to BMI, with AA homozygotes for a SNP (rs9939609) in the first intron of the FTO gene having a 1·7-fold increased risk of obesity compared with TT individuals(Reference Loos and Bouchard6). Consistent associations between identified SNP located 188 kb near MC4R and obesity have been found in genome-wide association studies(Reference Speliotes, Willer and Berndt7). Each copy of the rs17782313 C allele in the MC4R gene was associated with a 0·2 kg/m2 increase in BMI. Furthermore, although genetic variation in the LEP gene and that of its receptor LEPR was not identified to be associated with obesity-related traits in genome-wide association studies, a link to obesity has been reported in several candidate gene studies(Reference Portoles, Sorli and Frances8–Reference Boumaiza, Omezzine and Rejeb11).
However, the physiological basis for these genotype–adiposity associations is poorly understood. Given the fact that obesity is a disorder of energy imbalance between energy intake and expenditure, several studies have demonstrated that the SNP (rs9939609) in the FTO gene contributed to variations in energy intake(Reference Cecil, Tavendale and Watt12–Reference Lappalainen, Lindstrom and Paananen17). Yet, most of the studies showing a greater energy intake in individuals carrying the risk allele were conducted in children. In addition, it has been proposed that particular genetic polymorphism in the MC4R, LEP and LEPR genes influences obesity by affecting eating patterns, snacking(Reference de Krom, van der Schouw and Hendriks18, Reference Bienertova-Vasku, Bienert and Forejt19) and energy intake(Reference Qi, Kraft and Hunter20). However, there is a paucity of evidence on whether they affect appetite responses (hunger, desire to eat and prospective food consumption) including satiety (the feeling of fullness that influences the time interval between meals). The aim of the present study was to assess the effect of SNP in the FTO, LEP, LEPR and MC4R genes on postprandial appetite responses and ad libitum energy intake from a lunchtime meal in overweight men. The present analysis was conducted using data from a previously published acute appetite study, the primary aim of which was to examine the effect of consumption of individual dairy products as snacks on appetite(Reference Dougkas, Minihane and Givens21).
Subjects and methods
Study population
A total of forty healthy, non-smoking overweight men, aged 18–50 years with a BMI of 25·0–29·9 kg/m2, were recruited from the local Reading area. Subjects were excluded if they: had food allergies or irregular eating patterns; were athletes who trained >10 h/week; were cognitively dietary restrained eaters (Three-Factor Eating Questionnaire(Reference Stunkard and Messick22), factor 1>11), non-breakfast consumers or non-snack consumers; had any dislike of the ‘study’ foods or had blood pressure and biochemical measurements outside the ‘normal’ range (blood pressure >160/100 mmHg, and plasma total cholesterol >8·0 mmol/l, glucose < 5 or >7 mmol/l, TAG >1·8 mmol/l, alanine transaminase >45 U/l (0.75 μkat/l) or γ-glutamyltransferase >55 U/l (0.92 μkat/l)) after a 12 h overnight fast. The study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the University of Reading Research and Ethics Committee. Subjects gave written informed consent before commencing the study.
Postprandial study design
A randomised within-subject experimental design was performed, with each subject returning for four separate test sessions in the Hugh Sinclair Nutrition Unit at least 1 week apart. After a 12 h overnight fast, appetite profile was assessed (baseline) using a visual analogue scale rating of hunger (how hungry do you feel?), desire to eat (how strong is your desire to eat?), fullness (how full do you feel?) and prospective food consumption (how much do you think you could eat right now?) anchored by the terms ‘not at all’ and ‘extremely’. These four questions were also reflected in an average appetite score, which was calculated at each time point for each treatment as appetite (mm) = (desire to eat+hunger+(100 − fullness)+prospective consumption)/4(Reference Samra and Anderson23). A standardised light breakfast was provided at 09·00 h (0 min) and appetite was assessed at 10, 60, 115, 125, 145, 165, 185, 205 and 230 min. The light breakfast consisted of two oat cereal bars with strawberry filling (Nutrigrain soft baked bars; Kellogg's) and orange juice (250 ml; Sainsbury's), which together had an energy content of 1456 kJ and provided 60·5 g carbohydrate, 3 g protein and 7 g fat. The breakfast provided 15 % of the energy intake of an average UK male(24). The dairy snacks were semi-skimmed milk (Cravendale; ArlaFoods), a natural set biopot yogurt (Dr Oetker) or a mild Cheddar cheese (Sainsbury's), and provided the same energy (841 kJ) and volume (410 ml). Full details of the macronutrient composition of the dairy snacks have been previously reported(Reference Dougkas, Minihane and Givens21). Briefly, dairy composition was as follows: milk (28, 41 and 31 % of energy from protein, carbohydrate and fat, respectively); yogurt (22, 32 and 46 % of energy from protein, carbohydrate and fat, respectively); cheese (25 and 75 % of energy from protein and fat, respectively). The fourth treatment was an isovolumetric serving (compared with milk) of non-carbonated water. Non-carbonated water was ingested separately with cheese and yogurt in order to equate the volume of milk. Energy intake was assessed by an ad libitum lunch provided 90 min after the dairy snacks or water control. The lunch consisted of one main course composed of pasta, tomato and basil sauce and Parmesan cheese (2811·9 kJ/476·5 g of serving portion). Subjects were instructed to eat only until they felt comfortably satisfied and were given 20 min to consume the meal. Subjects ate individually in the dining room of the Unit for the entire length of time, and ad libitum food intake was monitored by determining total food consumed (g) and energy consumed (kJ).
DNA isolation and SNP genotyping
Genomic DNA was isolated from the leucocyte buffy coat layer, which was taken at screening, using the QIAamp DNA Mini Kit (Qiagen Limited). Genotyping was performed on four SNP (rs9939609 (FTO) in chromosome 16q12.2, rs7799039 (LEP) in 7q31.3, rs1137101 (LEPR) in 1p31 and rs17782313 (MC4R) in 18q21) by conducting allelic discrimination using a TaqMan Genotyping ‘Assay-on-Demand’ (Applied Biosystems). The percentage of replicate quality-control samples used for genotyping was 8 % with a >99 % concordance rate. The call rate was higher than 99·5 % and the genotype distribution obeyed Hardy–Weinberg equilibrium (P>0·05).
Statistical analyses
The agreement of allele frequency with Hardy–Weinberg equilibrium was assessed for all SNP using a χ2 analysis. The genetic model of inheritance was based on the number of copies of an allele needed for increased susceptibility and was described as follows: (1) additive, the susceptibility is increased having 0, 1 and 2 copies of the risk allele with the risk of 0 alleles < 1 allele < 2 alleles; (2) recessive, 2 copies of the risk allele are needed; (3) dominant, 1 or 2 copies of the risk allele are equally related to the likelihood of possessing a trait. The model of inheritance for each SNP that fits the data best was selected when comparisons between the additive, recessive and dominant models for each SNP were made. The genotypic effect of the four SNP on the baseline-adjusted, self-reported appetite scores or energy intake was evaluated by the PROC MIXED procedure (SAS Institute, Inc. 1992). Random effects of subject and subject × time interactions and fixed effects of treatment (dairy snacks or water), visit and SNP on appetite score and energy intake were tested and adjusted for BMI and age. The first-order autoregressive (AR (1)) covariance structure was selected for the appetite scores and variance components were selected for the energy intake based on goodness-of-fit criteria. The number of subjects was insufficient to test SNP interactions for the appetite scores and energy intake. Further backward stepwise analysis was conducted by checking the significance of the fixed effects or their interactions and including in the models only the significant effects. All models were tested for the normality of residuals. Standard diagnostics were used to ensure that all variables meet the normal distribution assumption. Statistical analyses were performed using SAS (release 9.2; SAS Institute, Inc.). Differences were considered statistically significant at P< 0·05 (two-tailed). Data are presented as means with their standard errors, unless otherwise indicated.
Results
All forty men completed the study. The mean age and BMI of the study participants was 32·1 (sd 9·1) years and 26·8 (sd 1·6) kg/m2. The mean average appetite rating of 51·9 (sd 24·9) mm (out of a possible 100 mm) and an ad libitum lunch intake of 3978·7 (sd 1444·0) kJ were evident for the group as a whole (data not shown). The genotype distribution of the four examined SNP all obeyed Hardy–Weinberg equilibrium (P>0·05) and their allele frequencies are provided in Table 1.
Table 1 Distribution of genotypes and alleles (Number of subjects and percentages)
FTO, fat mass and obesity-associated gene; LEP, leptin gene; LEPR, leptin receptor gene; MC4R, melanocortin-4 receptor gene.
* P value for the χ2 analysis of Hardy–Weinberg equilibrium.
† Wild type.
‡ Homozygote for the risk allele.
Effect of SNP on responses of hunger, desire to eat, fullness, prospective food consumption and energy intake at lunch
Mean postprandial responses of appetite according to SNP using backward stepwise analyses are presented in Table 2. There was no detectable difference between the genotype groups for the LEPR or MC4R SNP with respect to postprandial appetite responses. The mean ratings of hunger and desire to eat over the full experiment following intake of the different snacks were 23·9 % (P= 0·019) and 21·8 % (P= 0·046) higher in A carriers compared with TT homozygotes for FTO (dominant model), respectively. The fullness score was 17·2 % (P= 0·026) lower in A carriers compared with TT homozygotes for FTO (dominant model) and 18·6 % (P= 0·020) lower in G carriers compared with AA homozygotes for LEP (dominant model). The most notable effect was a genotype difference in prospective food consumption, with A and G carriers displaying 26·0 % (P= 0·008) and 19·1 % (P= 0·028) higher prospective food consumption compared with TT individuals in FTO and AA individuals in LEP, respectively. The average appetite, as a summary measure of the four specific appetite responses, was 11·0 (se 4·5) mm (P= 0·015) higher in A carriers compared with TT homozygotes for FTO (dominant model) and 8·0 (se 4·2) mm lower in G carriers compared with AA homozygotes for LEP (dominant model) without reaching significance (P= 0·057). The four individual SNP did not have an effect on ad libitum energy intake at lunch (Table 2).
Table 2 Mean appetite responses, using repeated 100 mm visual analogue scale ratings, over the whole study and mean energy intake (kJ) following intake of dairy snacks or water according to gene variants (Mean values with their standard errors)
FTO, fat mass and obesity-associated gene; LEP, leptin gene; LEPR, leptin receptor gene; MC4R, melanocortin-4 receptor gene.
* Appetite responses (hunger, desire to eat, fullness and prospective consumption) were assessed using a visual analogue scale and energy intake at the lunchtime meal.
† The genetic model of inheritance that fits the data best.
‡ P value for the difference between the genotypes after adjustment for baseline appetite scores, visit, treatment, BMI, age, and FTO, LEP, LEPR and MC4R SNP.
§ How hungry do you feel?
∥ How strong is your desire to eat?
¶ How full do you feel?
** How much do you think you could eat right now?
†† Average appetite calculated as (desire to eat+hunger+(100 − fullness)+prospective consumption)/4.
Similar results on the phenotypes were observed in the backward stepwise analysis by checking the significance of the fixed effects or their interactions and including in the models only the significant effects (data not shown).
Discussion
A heritable component for the regulation of appetite and eating behaviour has been reported, although the individual polymorphisms, their ‘effect size’ and the molecular mechanisms underlying genotype–phenotype associations are not fully elucidated(Reference Grimm and Steinle4). The present study investigated for the first time the effect of FTO, LEP, LEPR and MC4R variants on measurements of appetite and energy intake at an ad libitum lunch, in a ‘fit for purpose’ appetite research laboratory setting. The main finding was that primarily a FTO and to a lesser extent LEP polymorphisms were associated with an overall reduced appetite (based on the four phenotypes) and more specifically with perceptions of fullness and prospective food consumption.
While numerous studies, largely conducted in children, have examined the effect of the FTO rs9939609 SNP on food intake, dietary energy density and macronutrient selection(Reference Cecil, Tavendale and Watt12, Reference Timpson, Emmett and Frayling14, Reference McCaffery, Papandonatos and Peter25), very few have examined its impact on appetite(Reference Wardle, Llewellyn and Sanderson16, Reference den Hoed, Westerterp-Plantenga and Bouwman26). Wardle et al. (Reference Wardle, Llewellyn and Sanderson16) showed that children homozygous for the purported risk allele (AA) had reduced satiety scores, and these results have recently been replicated in adults by den Hoed et al. (Reference den Hoed, Westerterp-Plantenga and Bouwman26). Carriers of the risk allele (TA/AA) had increased hunger (OR 3·02, 95 % CI 1·26, 7·24) and decreased satiety (OR 2·02, 95 % CI 1·26, 7·24) relative to TT homozygotes(Reference den Hoed, Westerterp-Plantenga and Bouwman26). This is in agreement with the present results, since TT homozygotes had higher fullness and lower hunger and prospective food consumption scores compared with A carriers.
The role of leptin and its receptor in the regulation of energy homeostasis is well established, with studies demonstrating that functional mutations in the LEP and LEPR genes underlie a proportion of severe early-onset obesity cases(Reference Montague, Farooqi and Whitehead27, Reference Baicy, London and Monterosso28). However, the current epidemic of obesity cannot be explained by these rare monogenic mutations, and data in the literature considering the associations between common polymorphisms in the rs7799039 (LEP) or rs1137101 (LEPR) genes and polygenic obesity phenotypes are inconsistent(Reference Boumaiza, Omezzine and Rejeb11, Reference Hinuy, Hirata and Sampaio29–Reference Yu, Han and Cao31). The present study is one of the few that have examined the impact of leptin and its receptor gene variants on appetite responsiveness. Ratings of fullness and prospective food consumption were found to be different between the genotype groups for LEP with a significant increase in feelings of fullness and suppressed prospective food consumption in AA homozygotes relative to G carriers. This is in contrast with the two studies by den Hoed et al. (Reference den Hoed, Westerterp-Plantenga and Bouwman26, Reference den Hoed, Smeets and Veldhorst32), in which LEP was not associated with hunger and satiety(Reference den Hoed, Westerterp-Plantenga and Bouwman26) and where GG homozygotes felt more hungry compared with GA, but not AA individuals(Reference den Hoed, Smeets and Veldhorst32). Additionally, den Hoed et al. (Reference den Hoed, Westerterp-Plantenga and Bouwman26) showed that AA individuals had lower hunger ratings compared with carriers of the risk allele in LEPR, while in the present study, there was no effect of LEPR on appetite. It has been proposed that LEPR variants may affect the transcription of leptin depending on the circulating concentration of leptin(Reference Ben Ali, Kallel and Sediri10). However, circulating leptin concentration is influenced by BMI, body fat mass, sex and hormonal status(Reference Ben Ali, Kallel and Sediri10, Reference Gregoor, van der Weide and Mulder33). Thus, this discrepancy among the studies, although hard to explain, might be due to the relatively small homogeneous sample size in the present study (overweight men) compared with the larger more heterogeneous populations with respect to BMI distribution (from 19 to 31 kg/m2), sex (both sexes) and body fat mass in the other two studies.
Both LEP and MC4R genes are involved in the regulation of appetite and food intake through the leptin–melanocortin pathway(Reference Tung, Ayuso and Shan5). Despite the role of the MC4R in the regulation of energy intake and its association with obesity(Reference Loos, Lindgren and Li34), there are controversial results regarding the association between the rs17782313 (MC4R) variant and intakes of total dietary energy and fat in human subjects(Reference Qi, Kraft and Hunter20, Reference Hasselbalch, Angquist and Christiansen35, Reference Loos36). In most studies, dietary energy intake was assessed using self-reported FFQ, which are prone to a number of limitations and errors. However, even with more valid and accurate measurement of intake in the present study, the MC4R genotype did not emerge as a significant determinant of ad libitum energy consumption.
There are a limited number of studies examining the impact of genotype on appetite responsiveness, with no data available to base valid power calculations. Although the strength of the present study is the careful phenotypic characterisation of our volunteers with respect to appetite regulation, a limitation is the relatively small number of subjects, which may result in limited power to detect more subtle effects of the minor allele relative to the wild-type genotype.
In conclusion, the present preliminary investigations have shown that FTO and LEP polymorphisms are related to a feeling of fullness and decreased prospective food consumption. Further research is warranted to validate these novel findings, to investigate the interactions between individual gene variants and the interactions between variants and dietary nutrients, to identify the best-fitting model of inheritance, to provide an insight into the underlying physiological mechanisms for the genotype–phenotype associations and to investigate the ‘penetrance’ of these genotypes in additional population subgroups.
Acknowledgements
The present study was funded by the Barham Benevolent Trust Studentship, DairyCo UK and The Dairy Council UK. The authors thank Paul Chatfield for his valuable statistical help and advice. A. D. conducted the study, the data analysis and drafted the manuscript. All authors contributed to the design of the study and manuscript, and approved the final version of the manuscript. The authors declare no conflict of interest.
