Review | Published:

Eating behaviour in obese patients with melanocortin-4 receptor mutations: a literature review

International Journal of Obesity volume 37, pages 10271035 (2013) | Download Citation


Melanocortin-4 receptor (MC4R) mutations are the most common known cause of monogenic obesity and an important contributor to polygenic obesity. MC4R mutations with partial or total loss of function, as well as the variant rs17782313 mapped near MC4R, are positively associated with obesity. MC4R is involved in the leptin–melanocortin signalling system, located in hypothalamic nuclei, that controls food intake via both anorexigenic or orexigenic signals. Impairment in this receptor might affect eating behaviours. Thus, in the case of MC4R mutation carriers, obesity could be related, at least partly, to inadequate control over eating behaviours. Many published studies address eating behaviours in MC4R mutation carriers. Most studies focus on binge eating disorder, whereas others examine various aspects of intake and motivation. Up to now, no evaluation of this literature has been performed. In this review, we examine the available literature on eating behaviours in carriers of MC4R mutations and variant rs17782313 near MC4R gene. We address binge eating disorder, bulimia nervosa, mealtime hyperphagia, snacking, psychological factors, satiety responsiveness and intake of energy and macro/micronutrient. In a small number of studies, MC4R mutations seem to impair eating behaviours or motivation, but no clear causal effects can be found in the balance of the evidence presented. Improvements in methodologies will be necessary to clarify the behavioural effects of MC4R mutations.


Obesity is a rapidly growing global public health challenge with 400 million obese adults in 2005 worldwide and 700 million forecasted for 2015.1 Obesity is a complex disorder caused most often by the interaction of environmental and genetic factors. However, rare cases of monogenic obesity due to single gene mutations have been described.

Melanocortin-4 receptor (MC4R) deficiency is the most common known cause of monogenic obesity and an important contributor to polygenic obesity.2 About 150 naturally occurring MC4R gene mutations have been identified among patient cohorts,3 in which different gene function impairments occur, such as null mutation, intracellular-retained mutants, binding-defective mutants and signalling-defective mutants. In some cases, an apparently normal function is kept in spite of a mutation.4 The prevalence of MC4R mutations with impaired function ranges from 0.5 to 5.8%5, 6, 7, 8, 9 in childhood-onset obesity and is around 2.3% in obese adults.7

In contrast, two single-nucleotide polymorphisms (SNPs) of the MC4R gene, Ile251Leu and Val103Ile, are negatively correlated with obesity.10, 11, 12, 13 These SNPs occur with a frequency of 0.8–6%, both in obese and normal weight subjects from different ethnic backgrounds.14, 15, 16, 17 Moreover, a variant mapped 188 kb downstream MC4R gene (rs17782313) may affect gene function by participating in MC4R expression and translation regulation. It is associated with an increased body mass index (BMI) and has recently been shown to induce childhood-onset obesity.18

MC4R is expressed in the brain in the regions of the thalamus, hypothalamus, hippocampus and probably in human epidermal melanocytes.19, 20 MC4R mRNA is also present in the dentate gyros, cortex and amygdala.21 It is largely expressed in several brain sites involved in autonomic and endocrine functions. MC4R expressed on the surface of target neurons of the paraventricular nucleus has a role in the mechanisms of appetite.22 It affects the leptin–melanocortin signalling system, an important neuronal circuitry involved in the regulation of sympathetic neural function.23 The leptin–melanocortin signalling system is activated by leptin produced in the adipose tissue, which crosses the blood–brain barrier, binds to its receptors in two subsets of first-order neurons and stimulates proopiomelanocortin expression. In the arcuate nucleus, proopiomelanocortin is cleaved to produce alpha-melanocyte-stimulating hormone.24 The binding of these peptides to MC4R inhibits food intake. The binding of leptin also inhibits the expression of agouti-related peptide, an orexigenic protein that acts as an antagonist for MC4R.25 MC4R activates both satiety and hunger signals by integrating an anorexigenic (satiety) signal provided by the alpha-melanocyte-stimulating hormone and an orexigenic signal provided by the agouti-related peptide.26

By affecting the leptin–melanocortin signalling system, functional MC4R mutations, variants near MC4R gene, and SNPs may have a key role in central appetite control and affect eating behaviours.27 Among the other four known melanocortin receptors, significant linkages with adiposity-related variables were found for MC5R28 and a potential association with obesity has been suggested for MC3R, but data are available only in rats.25, 29

Eating behaviours can be considered in numerous qualitative and quantitative aspects. They fulfil nutritional as well as hedonic and social functions. Energy intake and amounts of food ingested are under the control of the physiological mechanisms of hunger, appetite and satiety, whereas food likes and dislikes orient food choices.30 Altered brain mechanisms of appetite control might induce eating disorders and/or nutrition-related pathologies.31 In the case of MC4R mutation carriers, obesity could be related, at least partly, to inadequate control over eating behaviours.32 In the published literature about MC4R mutations, eating disorders classified in the Diagnostic and Statistical Manual of Mental Disorders – Fourth edition (DSM-IV)33 as well as many other aspects of eating behaviours have been examined. Up to now, no systematic evaluation of the literature has been performed.

In this review, we address eating behaviours and eating-related psychological aspects observed in subjects with MC4R mutations and variant rs17782313. First, we examine the reports of eating disorders, including the binge eating disorder (BED) and bulimia nervosa (BN). According to the DSM-IV-Text Revised, BED is defined as episodes of rapid consumption of an unusually large amount of food in the absence of hunger, without purging behaviour, occurring at least twice a week for a period of 6 months.33 BED elicits feelings of embarrassment, depression, guilt and loss of control. BN is characterized by repeated episodes of binge eating, followed by inappropriate compensatory behaviours, such as self-induced vomiting, use of laxative or diuretics, fasting or engaging in excessive exercise, occurring at least twice a week for 3 months.33, 34 Second, we address behaviours that are likely to induce excessive intake, such as mealtime hyperphagia and snacking. Finally, we examine qualitative and/or quantitative aspects of food intake and motivation to eat, including factors of the Three-Factor Eating Questionnaire (TFEQ), satiety responsiveness and energy and macro/micronutrient intake.

Materials and methods

A PubMed database search was performed. Relevant studies published between 2000 and 2011 were identified with the following search terms: Obesity and Melanocortin-4 Receptor OR MC4R mutations OR rs17782313 AND Eating Disorders OR Eating Behaviours OR Food Intake OR Binge Eating Disorder OR Bulimia Nervosa OR Mealtime Hyperphagia OR Snacking OR Satiety OR Energy Intake OR Nutrient Intake. This generated 222 articles, which were then limited to human works published in English. Reference lists of full-length articles were hand searched to identify additional studies relevant for inclusion. Sixteen observational studies on MC4R mutation carriers’ eating behaviour were identified and reviewed. The studies were classified according to the type of behaviour studied.

Eating disorders: BN and BED

Two reference manuals, the International Classification Disease (ICD-10)35 and the DSM-IV-Text Revised33 define several eating disorders, such as anorexia nervosa, BN, BED and eating disorders not otherwise specified. Two of them, BN and BED, were reported in studies of MC4R mutations and variant rs17782313 effects.

Bulimia nervosa (BN)

Hebebrand et al. hypothesized that genetic factors predisposing to obesity, such as MC4R mutations, might be commonly detected in patient with BN. However, in a population of 81 patients with clinically assessed BN, only 1 extremely obese woman, with a current BMI of 48 kg m2, aged 32 years, had a functionally relevant mutation in the MC4R gene.36 Stutzmann et al.37 cited the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study38 of French adults in whom the variant rs17782313, near MC4R, was not associated with self-reported ‘bulimia’. No validated method was used in this study to confirm the presence of clinical BN. The studied population had 4877 obese and non-obese subjects, with a mean BMI of 24.7 (range from 15.4 to 53.6 kg m2), aged 30 to 66 years, and with a minor allele frequency (MAF) of 23.7% for rs17782313-C allele. Statistical analyses were performed with a logistic regression model without any adjustment on age, sex and BMI.

These two articles used clearly different methodological approaches.36, 37 In the case report study, BN was assessed by a specialist on the basis of validated diagnostic criteria, whereas in the other study, it is unclear that the self-reported instances of ‘bulimia’ actually reflected the clinical status of the respondents. Many patients in the latter study may have been misclassified (with cases of both false positives and false negatives). Neither of these two very different studies supports a clear association between BN and MC4R mutations.

Binge eating disorder (BED)

In some studies (Table 1), BED appears as a major phenotype of patients with MC4R mutations. Branson et al.39 compared phenotypic data between 20 carriers and 120 non-carriers of MC4R mutations, matched for age (43.7±2.8 years), sex and BMI (43.1±1.3 kg m2). BED was identified with the validated eating disorder questionnaire of Spitzer et al.41 based on the DSM-IV, and diagnosis was validated by interviews with a dietician, a psychologist and a physician. BED was detected in 100% (20/20) of carriers and only 14.2% (17/120) of non-carriers. Carriers of non-functional mutations and carriers of SNPs Val103Ile and Ile251Leu were not excluded from the studied population.42 These SNPs occur in non-obese subjects17, 43 and negative associations with obesity have been reported,10, 11, 12, 13 which makes the interpretation of these results rather challenging as discussed elsewhere.42, 44, 45 Potoczna et al.40 used the same population sample as the Branson et al.39 study to demonstrate that carriers of MC4R gene variants exhibit a more aggressive form of BED than non-carriers.

Table 1: Characteristics of studies addressing the association between MC4R mutations and binge eating disorder

Other studies did not report any association between BED and MC4R mutations.7, 46 Lubrano-Berthelier et al.7 assessed BED based on DSM-IV criteria in a sample of 19 severely obese adults and reported that BED was not more prevalent in the five functional MC4R mutation carriers compared with controls. Hebebrand et al.46 compared a larger sample of 199 non-carrier obese children and adolescents with nine carriers of MC4R mutations. Diagnostic assessment of BED was based on the Munich Composite Diagnostic Interview question: ‘Have you ever had a time when you would eat abnormally large amounts of food within a few hours—that is, eat in binges?’ For those with a positive response on the Munich Composite Diagnostic Interview question, the interview was continued by assessing the DSM-IV A and C criteria for BN: ‘A1 criterion: Eating in a discrete period of time an amount of food that is definitely larger than most people would eat during a similar period of time and under similar circumstance, A2 criterion: A sense of lack of control over eating during the period. C criterion: The binge eating and inappropriate compensatory behaviours both occur, on average, at least twice a week for 3 months’.33 After adjusting for age, sex and BMI and without function impairment investigation, no association appeared between BED and MC4R status (22.2% binge eaters in carriers of pathogenic MC4R mutations vs 19.6% in non-carriers, P=0.93).46 A study in 10-year old obese and overweight children compared 16 heterozygous carriers of functional mutations and their 8 non-carrier relatives with significantly different BMI (24.7 kg m−2 for carriers vs 19 for non-carriers, P=0.005). Based on a question asked by a trained physician and assessing BED as a binary phenotype, no case of BED was detected in these two groups.47 Other studies using different methodological approaches did not report any association between the BED phenotype and MC4R mutations. For example, Herpertz et al.45 found only one heterozygous carrier of a functionally relevant MC4R mutation, without binge eating, in a group of 239 severely obese adults seeking conventional treatment. Tao and Segaloff48 found variants with apparently normal function in all of the eleven obese binge eaters while one obese patient with a functional mutation had no BED.

In summary, two studies using a similar method, that is, diagnosis based on DSM-IV criteria in severely obese adults interviewed in a medical centre by a specialist, report contradictory results.7, 39 No association between MC4R mutations and BED was reported in other studies in children and adolescents, in which BMI status, assessment methods, population recruitment, families ties and statistical adjustments on BMI were different.46, 47 Overall, the existing data remain largely negative and the most demanding studies for the clinical assessment of BED are the only positive ones.39, 40 These last studies, however, did not control for polymorphisms that may confound the results.

Other aspects of eating behaviours

Potentially obesogenic behaviours, such as snacking and mealtime hyperphagia, have been studied in MC4R mutations carriers, as well as other qualitative and quantitative aspects of intake and motivation to eat. Measures of intake include dietary survey methods such as 24-h recalls, Food Frequency Questionnaires (FFQ) and experimental test meals. They record the amount and/or types of foods ingested and address the daily energy and nutrient intake. The motivation to eat can be assessed by validated instruments, such as the Three Factors Eating Questionnaire (TFEQ)49 and the Children’s Eating Behaviour Questionnaire50 that score various psychological traits, for example, restraint, disinhibition or emotional eating. Many studies of intake and motivation use a variety of in-house methods that can be as simple as a question asked by a trained or untrained experimenter.

Mealtime hyperphagia

A feeding experiment reported that, during an ad libitum experimental meal, obese children aged 5 to 10 years, including two heterozygous and three homozygous carriers of functional MC4R mutations, had greater energy intake, expressed as per kilogram of lean body mass, than two non-obese non-carriers aged 15 years (t-test, P-values<0.05). This result was consistent with the reported food-seeking behaviour of the affected children in their free-living environment.51 In another experiment, energy consumed at an ad libitum meal was examined in severely obese English children below 16 years of age, including 23 heterozygous and 6 homozygous carriers. MC4R deficiency was significantly associated with hyperphagia. Three older children (11–16 years old) showed a less hyperphagic phenotype than younger ones (<10 years). Moreover the hyperphagic phenotype was more severe in carriers with complete loss, as opposed to partial loss of MC4R function, and this finding appeared to be exacerbated in homozygous vs heterozygous children.5 In the Stutzmann et al.47 study involving 25 obese and overweight children, aged 10 years, hyperphagia was identified by a physician asking a question about eating large amounts of food during meals. Twice as many heterozygous carriers of functional MC4R mutations (61.1%) declared eating large amounts of food at meal times compared with their unaffected relatives (37.5%), but this was not statistically significant.

A study of 1004 obese French children, aged 11 years, assessed the effect of the variant rs17782313 near the MC4R gene. An in-house questionnaire administered by a trained physician suggested a trend towards a higher prevalence of mealtime hyperphagia in carriers of the variant (P=0.036) with a MAF of 27.9%.37 In the same report, in another sample of 1274 severely obese Swiss subjects, aged 16–73 years, no difference in hyperphagia was found between carriers and non-carriers, with an rs17782313 MAF of 29.7%. Hyperphagia was assessed using the validated eating behaviour questionnaire of Spitzer et al.41 plus semi-structured and structured interviews with specialists. Data revealing the intake of large amounts of food were extracted from this questionnaire but the time of this hyperphagia (at meals or between meals) was not specified.

In summary, these results suggest more frequent mealtime hyperphagia in overweight/obese children carriers of functional MC4R mutations and rs17782313 variant. The two studies with direct measurement of mealtime intake reveal a clear effect,5, 51 and observations extracted from questionnaires point in the same direction.37 The consistent but non-significant results in the Stutzmann et al. study could be due to the insufficient statistical power.47 The severity of the hyperphagia seems to decline with age and to be higher in homozygous than heterozygous cases. In adults, only one study used a questionnaire to investigate ‘eating large amounts of foods’ at any time of day.37 Its non-significant results may reflect either the decline of the effect with age, or the imprecision of the assessment method.


Snacking is characterized by the consumption of food outside of meals, accounting for more than 15% of total daily energy intake.52 A few studies (Table 2) have assessed snacking among functional MC4R mutations and variant rs17782313 carriers. In obese and overweight French children, aged 10 years, the frequency of snacking, assessed by a binary question asked in a physician-led examination, was similar for 17 heterozygous carriers and 8 non-carriers of functional MC4R mutations.47 By contrast, differences were observed when analysing mutations near MC4R for the variant rs17782313. For example, among 1274 severely obese Swiss adults (16–73 years old), variant rs17782313 carriers (MAF of 29.7%) had a higher prevalence of snacking (P=0.036),37 as assessed by a validated eating disorder questionnaire41 and confirmed by interviews. In addition, the rs17782313-C allele was associated with a higher prevalence of frequent snacking (P=0.01) in 1004 French obese children, aged 11 years, with a MAF of 27.9% and among 5612 non-obese Finnish adolescents, with a MAF of 17.7%.37

Table 2: Characteristics of observational studies addressing the association between functional MC4R mutations, variant rs17782313 and snacking

Overall, many reports confirm the effects of rs17782313-C allele on snacking in various populations (children, adolescents, adults; obese, overweight or normal weight). The failure to observe functional MC4R mutation effects in obese and overweight children might be due to the limits of the assessment method (binary question) and/or to the limited statistical power.47

Studying the motivation to eat: the TFEQ

To assess the cognitive and motivational dimensions of eating behaviours, Stunkard and Messick49 developed the Three Factors Eating Questionnaire. The TFEQ quantifies three behavioural traits that have been suggested to have a decisive influence in body weight control. This self-administered questionnaire, extensively used in the study of eating behaviours, contains 51 items and scores three factors ‘Restraint’, ‘Disinhibition’ and ‘Hunger’. Disinhibition is defined as the tendency to lose control over eating and to ingest excessively large quantities of foods in response to a variety of cues or circumstances;53 restraint refers to the cognitive, deliberate limitation of intake for body weight control purposes.54 A revised version of the TFEQ with 18 items was developed by Karlsson et al.55 The TFEQ-R18 also considers three factors: ‘Cognitive Restraint’, ‘Uncontrolled Eating’ and ‘Emotional Eating’. The effects of MC4R mutations and variant rs17782313 on these different dimensions were examined in a few studies (Table 3).

Table 3: Characteristics of observational studies addressing the association between MC4R mutations, variant rs17782313 and TFEQ factors

Disinhibition scores were higher among 38 obese functional MC4R mutation carriers than among their 33 non-carrier overweight relatives (Student’s t-test, P=0.007). In this study, mean hunger scores were not statistically different but the proportion of carriers with a hunger score above the mean was 31% vs 10% in carriers’ relatives (Student’s t-test, P=0.047). As disinhibition is a strong correlate of obesity level,56 the difference in weight status between cases and controls in this study might account for the difference in disinhibition scores regardless of genotype. No difference was found for dietary restraint.47

Another comparison of 731 severely obese non-carriers and 19 carriers of functional MC4R mutations, aged 44±12 and 41±12 years, respectively, with similar BMI, found no difference in any of the three factors of the TFEQ.7 Similarly, no difference was found in TFEQ scores in two studies that compared carriers and non-carriers among 187 obese adults from independent families, aged 42±12 years with a BMI of 51±7.5 kg m2 (ref. 17) and among 130 patients from 26 families adjusted for BMI s.d. score.46

Two studies addressed the potential role of the rs17782313 variant.37, 57 Stutzmann et al.37 administered the TFEQ to 2438 obese and severely obese French adults aged 18–89 years and found a hunger score of 4.45 for the TT (wild type), 4.67 for the CT (heterozygous), and 5.21 for the CC (homozygous) genotypes of the variant rs17782313. These data reveal a positive association between rs17782313-C allele and mean hunger scores (P=0.02). Valladares et al.57 examined the results of the TFEQ Chilean Parent Version (TFEQP-19), an adapted version of the TFEQ-R18 administered to subjects’ mothers, in a group of 195 obese children (23.7% heterozygous and 3.1% homozygous, aged 7–12 years). No association was found between rs17782313-C allele and TFEQP-19 scores in these children.

In summary, the TFEQ was used in several studies of obese and severely obese adults. Most results are negative, with two exceptions: higher hunger scores in carriers of variant rs17782313 and higher disinhibition score in functional MC4R mutation obese carriers vs overweight controls.37, 47 Overall, there is no consistent evidence that MC4R mutations or variant rs17782313 affect the behavioural dimensions scored by the TFEQ.

Satiety responsiveness

Satiety is a complex psycho-physiological state that follows the intake of foods and inhibits eating until the return of hunger.58 Its alteration may be associated with MC4R mutations, which could influence appetite and the nutritional status. Valladares et al.57 assessed satiety responsiveness scores of the Children’s Eating Behaviour Questionnaire, in a sample of 148 obese Chilean children, including 39 heterozygous and 4 homozygous carriers of the rs17782313-C allele. A negative association (P=0.01) was found between the rs17782313-C allele and satiety responsiveness scores, but this effect disappeared after adjustment for gender, age and Tanner stage.59, 60 A comprehensive examination of the four carriers of the homozygous CC genotype revealed that they had lower satiety responsiveness than heterozygous subjects. Although the results are not totally conclusive (no significant effect after adjustment), this study suggests that the variant rs17782313 could decrease satiety responsiveness in obese children, with a greater alteration in homozygous than heterozygous individuals.57

Energy intake

Food intake is under the influence of various neural and endocrine mechanisms that trigger, maintain, or inhibit eating,31 particularly those affected by MC4R function. Most intake assessment methods are based on self-declaration.

A dietary history assessment (addressing the habitual diet) performed by a trained dietician in severely obese adults showed similar energy intakes in a subgroup of 83 non-carriers compared with 8 carriers of MC4R mutations with equivalent BMI.17 Using the same method in severely obese adults aged 39–56 years, Lubrano-Berthelier et al.7 did not detect any difference in daily energy intake between 19 functional mutation carriers and 731 non-carriers.

Qi et al.61 used a standardised FFQ, including 116 food items in overweight women, and reported that the total daily energy intake was significantly higher in 284 carriers of the homozygous (CC) genotype compared with 2790 carriers of the wild-type (TT) genotype of the rs17782313 variant (P=0.028). Another study in 1700 healthy adult women with a rs17782313-C MAF of 26% did not confirm these findings.62 Moreover, in an observational study conducted in 1115 lean twins, including 34.7% heterozygous and 4.5% homozygous for the variant rs17782313, a FFQ with 247 food items revealed no difference in energy intake between the various genotypes.63

Table 4 summarizes studies addressing mealtime or total daily energy intake. Differences between these studies include energy intake assessment, sample size and nutritional status of the subjects (overweight vs normal weight). The only study suggesting higher intake in rs17782313-C mutation carriers used a FFQ (as opposed to dietary recall) and included the highest numbers of cases (284) and controls (2790).61 No dietary survey revealed any association of food or nutrient intake with MC4R mutations. The high level of under-reporting frequently observed in overweight and obese respondents might critically limit the validity of dietary reports in the present populations and blur any relationship with genotypes.

Table 4: Characteristics of studies addressing the association between MC4R mutations, variant rs17782313 and energy intake per day or at mealtime

Macro/micronutrient intake

Overweight and obese individuals show a tendency towards greater liking and selection of energy-dense foods, which may contribute to the development and maintenance of these conditions.64 Macronutrient composition of the diet is a major correlate of energy density.

Farooqi et al.51 found no difference in macronutrient intake in a test meal between five children carriers of functional MC4R mutations (65% carbohydrate, 15% protein, 20% fat) and two wild-type siblings (72% carbohydrate, 10% protein, 18% fat). Hebebrand et al.46 also failed to show any difference in fat intake between carriers and non-carriers among obese adolescents.

Diet assessment based on a FFQ including 116 food items showed a significantly higher protein (P=0.003) and fat (P=0.008) intake, and particularly a higher saturated fat intake (P=0.007) in 284 overweight women carriers of the CC genotype of the variant rs17782313 compared with 2790 wild type, aged 47–61 years.61 Two other FFQ studies did not confirm these findings and reported similar intakes of fat, protein and carbohydrate. One of these studies used a FFQ with 77 food items in a sample of 1700 healthy adult women with a rs17782313-C 26% MAF,62 whereas the other used a FFQ with 247 food items in a sample of 1115 lean twins.63 The only dietary study with significant results had the highest number of cases and controls and was conducted in overweight women. The two non-significant reports had lower N and were conducted in normal weight subjects.

Table 5 lists the articles studying the effects of MC4R mutations or variant rs17782313 on qualitative or quantitative dimensions of food intake.

Table 5: Summary of the different quantitative and qualitative aspects of intake and motivation studied in subjects with MC4R mutations and variant rs17782313a


In this review, we explore the relative contributions of the MC4R mutations and variant rs17782313 on eating behaviours. We identified studies conducted on various populations (age, sex, ethnicity, genotype) looking at different variables (among which eating disorders, psychological traits, energy and nutrient intakes) and using various methodologies. Overall, results are inconsistent about the presence of DSM-IV-defined eating disorders in MC4R mutation carriers. Inconclusive findings are also reported for most other behaviours except for mealtime hyperphagia and satiety responsiveness. Mealtime hyperphagia appears more frequent in overweight/obese children carriers of functional MC4R mutations and rs17782313 variant, and satiety responsiveness might be lowered by the presence of the variant rs17782313, both effects being larger in homozygous than heterozygous individuals.

A number of methodological issues may explain why the current evidence remains inconsistent or contradictory. First, the methodology of the epidemiological studies listed in Table 5 was often not rigorous enough to generate clear results. All studies were observational and assessed the prevalence of MC4R mutations and their phenotype relationship but none had a fully rigorous case–control design. A case–control study determines the relative importance of a predictor variable in relation to the presence or absence of a disease and may be the only feasible approach when the outcome is rare.65 The Branson et al.39, 40 study was well designed as a case–control but did not exclude confounding polymorphisms.38 Other studies were case series without appropriate selection of cases and controls. Cases and controls came from cohorts and were not matched for age, gender or BMI levels.5, 37, 51, 61 Most studies were based on small samples of MC4R mutation carriers, often less than 30 cases5, 39, 51 or less than 20 cases,7, 17, 40, 45, 46, 47 which limits statistical power.

Second, the mutation effects considered in the studies may have been inadequately characterized. Genotype and phenotype expression intensity depends on MC4R mutation characteristics but this information was rarely available in the published data. Information on partial or total loss of function, specific of each mutation, was not always available,17, 46 despite the consequences on mutation effects. Although some SNPs, including Val103Ile and Ile251Leu, are negatively correlated with obesity,10, 11, 12, 13 the effect of these SNPs was not acknowledged when interpreting the results.36, 39, 40, 46 Furthermore, although the phenotype appeared to be exacerbated among homozygous compared with heterozygous carriers,5 homozygous and heterozygous subjects were generally not analysed separately.7, 17, 39, 40, 45, 46, 47 Future studies should include the functional characteristics of MC4R mutations (in vitro experimentation or reference studies) and subjects’ genotype status, so that their different functional consequences can be sorted out.

Third, inconsistencies may be due to differences in measurement methods. Various methods such as ad libitum test meals,5, 51 semi quantitative interviews with specialists,17, 37, 39 questionnaires,7, 17, 37, 39, 46, 47, 61, 62, 63 or a single question37, 47 differed between studies and were used single or combined. Data based on standard questionnaires, validated or not, may not address the same dimensions of behaviours as actual eating tests or interviews with trained specialists. Dietary history may be inadequate to reveal an association because of the patients’ under-reporting or response bias. Different FFQs that include a variable number of food items make the comparison of data difficult across studies.61, 62, 63 The validity of FFQ or of dimensions, such as dietary restraint, as proxies of actual behaviours has been questioned.66, 67 Future studies should measure behaviours directly, whenever feasible. In other cases, validated questionnaires, rather than in-house methods, should be used and/or interviews should be conducted by well-trained professionals.

Fourth, other inconsistencies could be due to the heterogeneity of the populations. Population characteristics, such as ethnic origin, age, sex and family ties, differed between studies and sometimes within the same study. Different recruitment methods such as case and control recruitment in medical centres, cohorts in epidemiological studies, recruitment campaigns in research centres or schools, make inter-studies comparisons difficult.

Fifth, the stable or dynamic status of body adiposity should be acknowledged. It is generally recognized that obesity develops in successive phases of adiposity accumulation (dynamic phases) and stabilization (static phases).56 The static and dynamic phases of obesity constitution have different physiopathology and could be associated with different behaviours. Hyperphagia or eating disorders might be more obvious during dynamic phases than during static periods. This might explain why many significant results were observed in children who probably were developing their obese body mass, whereas inconsistent results were reported in adults in whom the dynamic or static obesity status was not assessed. In agreement with this hypothesis, four affected obese adults reported experiencing intense feeling of hunger during childhood, which became less pronounced in their late teens.51 It could also happen that effects of MC4R mutations are more salient during specific periods of life, for example during somatic growth.7 All the studies published so far were cross-sectional, preventing the accurate assessment of the time-course of the observed effects. Future studies should assess weight history since childhood and categorize subjects according to static and dynamic phases of obesity.

One recurrent limitation of studies of rare genotypes is their low statistical power, whatever their design or methodology. Given the large variability of ingestive behaviours in humans, the low level of consistency between the studies described in this review is hardly surprising. The low number of cases in studies of rare genetic mutations will always be particularly challenging.

In conclusion, the existing evidence does not allow clear conclusions to be drawn regarding eating behaviours in carriers of MC4R mutations and rs17782313 variant. Purposely designed case–control studies seem necessary to clarify the potential effects of MC4R mutations on the eating behaviours of obese patients. Optimally, they should specify key characteristics of the studied groups (children or adults, adiposity status and development, genotype, functionality of MC4R mutations) and construct valid control groups by matching for age, gender and BMI. Additionally, eating behaviour assessment requires validated methods, preferably actual measurement of behaviours (for example, during a test meal) and/or interviews with specialists. Given the rare frequency of these mutations and the large variability of human ingestive behaviours, the problem of statistical power is likely to make progress very difficult in this area.


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The study was supported by a research grant from the foundation NRJ- Institute de France. M Valette is supported by a fellowship from the University Paris 13. G Paradis holds a Canadian Institutes of Health Research Chair in Applied Public Health Research.

Author Contributions

MV, FB, SC, GP and CC wrote the manuscript. CP, BD, SH and KC, LM critically revised the manuscript for scientific content.

Author information


  1. Nutritional Epidemiology Research Unit-UMR U557 INSERM, U1125 INRA, CNAM, Paris 13 University, CRNH-IdF, Bobigny, France

    • M Valette
    • , F Bellisle
    •  & S Hercberg
  2. Department of Nutrition, Ambroise Paré Hospital (AP-HP), Boulogne-Billancourt, France

    • C Carette
    • , L Muzard
    •  & S Czernichow
  3. INSERM U1016, CNRS UMR 8104, University of Paris-Descartes, Cochin Institute, Paris, France

    • C Carette
  4. Department of Nutrition, Pitié Salpetrière Hospital (AP-HP), Paris, France

    • C Poitou
    •  & K Clément
  5. Institut National de la Santé et de la Recherche Médicale, U872 team7, Nutriomique, Cordelier Research Center, Paris, France

    • C Poitou
    • , B Dubern
    •  & K Clément
  6. Department of Gastroenterology and Pediatric Nutrition, Armand-Trousseau Hospital, Paris, France

    • B Dubern
  7. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

    • G Paradis
  8. McGill University Health Center Research Institute, Montreal, Quebec, Canada

    • G Paradis
  9. Department of Public Health, Avicenne Hospital (AP-HP), Bobigny, France

    • S Hercberg
  10. University of Versailles Saint Quentin en Yvelines, Boulogne-Billancourt, France

    • S Czernichow


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The authors declare no conflict of interest.

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Correspondence to S Czernichow.

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