Search tips
Search criteria 


Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
Int J Obes (Lond). Author manuscript; available in PMC 2009 May 18.
Published in final edited form as:
PMCID: PMC2683751

The V103I polymorphism of the MC4R gene and obesity: population based studies and meta-analysis of 29 563 individuals



Previous studies have suggested that a variant in the melanocortin-4 receptor (MC4R) gene is important in protecting against common obesity. Larger studies are needed, however, to confirm this relation.


We assessed the association between the V103I polymorphism in the MC4R gene and obesity in three UK population based cohort studies, totalling 8,304 individuals. We also did a meta-analysis of relevant studies, involving 10,975 cases and 18,588 controls, to place our findings in context.


In an analysis of all studies, individuals carrying the isoleucine allele had an 18% (95% CI 4-30%, p=0·015) lower risk of obesity compared with noncarriers. There was no heterogeneity among studies and no apparent publication bias.


This study confirms that the V103I polymorphism protects against human obesity at a population level. As such it provides proof of principle that specific gene variants may, at least in part, explain susceptibility and resistance to common forms of human obesity. A better understanding of the mechanisms underlying this association will help determine whether changes in MC4R activity have therapeutic potential.


The melanocortin-4 receptor (MC4R) is part of the central melanocortin system, which is known to regulate food intake and energy homeostasis. Disruption of the MC4R gene in mice and humans results in hyperphagia and obesity. Loss of function mutations in the MC4R are the commonest known form of monogenic obesity and are found in 4-5% of subjects with severe obesity of onset in childhood.1 2

By contrast, the role of MC4R variants in common, polygenic obesity is uncertain. With a carrier frequency of around 2-4%, the V103I missense variant is the most common coding MC4R polymorphism. A recent pooled analysis based on 3,631 cases and 4,082 controls suggested that, compared to noncarriers, individuals with the I103 allele might have a 31% reduced risk of obesity; however, this association had only marginal statistical significance.3 Large scale studies are required to reliably confirm or refute gene-disease associations.4 5 We therefore assessed the association between the MC4R V103I polymorphism and obesity in a series of population based studies, comprising 1,053 cases and 7,251 controls. These studies were included in a meta-analysis, providing total data on 10,975 cases and 18,588 controls.


Study populations

We used data from the Norfolk cohort of the European Prospective Investigation into Cancer (EPIC) and the MRC Ely Study. Ethics committees have approved both studies and all participants gave informed consent. EPIC is an ongoing prospective cohort study of chronic diseases comprising approximately 25,000 Norfolk residents aged 45-75 who were recruited from general practice registers between 1993 and 1997.6 It is an ethnically homogeneous Caucasian population. These participants completed a baseline health examination. From January 1998, we invited the cohort for a second health examination and 15,786 people had attended by October 2000. Details of recruitment, anthropometric measurements, health examinations and questionnaires following standardised protocols have been published.6 DNA was extracted from the 15,786 whole blood/EDTA samples (Whatman Biosciences, Ely, UK) taken at the second health examination.

For the purposes of this analysis, we examined data from two subcohorts of the 15,786 EPIC study participants who attended the second health examination. EPIC1 is a random sample of 5,000 participants who were free of baseline disease (cancer, coronary heart disease and diabetes), and that had fully arrayed DNA available, completed food frequency questionnaire data, and blood HbA1c and BMI measured at the two clinical assessments. EPIC2 comprises 3,345 participants with fully arrayed DNA available for genotyping. We excluded 692 participants from EPIC2 as they were also present in the EPIC1 sample set. However, we used this duplicate set to assess the concordance of our genotype results.

We also used data from the MRC Ely Study, a prospective population-based cohort study of the aetiology and pathogenesis of type 2 diabetes and related metabolic disorders.7 8 Again, the study population consists of an ethnically homogeneous Caucasian population in which phenotypic data have been recorded at clinical assessments using standardised protocols for anthropometric measurements. All participants were between 40 and 65 years of age at baseline. This cohort was recruited from a population-sampling frame with a high response rate (74%), making it representative of the general population for this area of eastern England. For the purposes of this analysis, we used data collected at the second health check, approximately four-and-a-half years from baseline.

The participants in each cohort were defined as obese cases and nonobese controls according to a baseline BMI of at least 30 kg/m2 or BMI less than 30kg/m2, respectively.


We genotyped the EPIC1, EPIC2 and Ely study sets for the G→A (valine to isoleucine) substitution at codon 103 of the MC4R gene (rs2229616), obtained with TaqMan chemistry (Applied Biosystems, Warrington, UK). The percentage of each cohort successfully genotyped was 98·0%, 86·5% and 97·3% respectively for EPIC1, EPIC2 and Ely.

Statistical analysis

We tested for Hardy-Weinberg equilibrium using the χ2 test. Based on previous reports we used a dominant genetic model, comparing common homozygotes (G/G) with carriers of the A allele (G/A or A/A). Stata version 8·0 was used for all analyses (Stata Corporation, Texas, USA).

Systematic review and meta-analysis

Case-control and cohort studies published before June 2005 in which the MC4R gene V103I polymorphism had been related to BMI were identified by electronic searches of PubMed, scanning of relevant reference lists, and by contacting authors of studies for any unpublished or additional tabulated data. We used MeSH and free text terms relating to the melanocortin-4 receptor (eg, “receptor, melanocortin, type 4”, “melanocortin 4 receptor”, “MC4R”) in combination with obesity (eg, “obesity”, “obesity, morbid”, “body weight”, “body mass index”, “thinness”, “weight”, “overweight”) and with polymorphism (eg, “polymorphism, single nucleotide”, “genes”, “mutation”, “genotype”, “variant”).

We only included studies in which obesity case-control status by genotype was available. Information was collected on other prespecified study-level covariates to explore possible sources of heterogeneity: case-control definition; whether studies included adults, children or both; ethnicity; relatedness between cases and controls; population based or selected individuals. To calculate a pooled estimate of the relation between genotype and obesity we used fixed and random effects models. Heterogeneity among studies was assessed by the heterogeneity Q statistic. Funnel plots and the Egger test were used to assess evidence of possible publication bias.

Role of the funding source

No funding source had any role in study design; collection, analysis, or interpretation of data; or the writing of the report.


Effect of the V103I polymorphism on BMI in three studies of British Caucasians

Full BMI and genotype data were available for 8,304 participants. The genotypic distributions in the control populations were in agreement with those expected under Hardy-Weinberg equilibrium (p>0·05). In a subgroup of 692 samples, concordance between genotyping methods was 99·9%. Table 1 shows demographic and anthropometric characteristics of study participants by V103I genotype for the three studies. We found that the mean age of participants varied by genotype (p=0·025) in the Ely study set; however, this observation was not evident in the other cohorts and is likely to be a chance finding. There was no association between V103I genotype and BMI. Similarly, we found no statistically significant association between genotype and obesity (table 2). Adjustment for age did not materially alter the results. However, because of our limited sample size we then combined these results in a meta-analysis of all available data.

Table 1
Demographic and anthropometric characteristics of study participants by MC4R V103I genotype
Table 2
Association of MC4R V103I genotype with obesity


A total of 25 datasets, including three from the present study, with 30,300 individuals met the inclusion criteria for the meta-analysis (figure 1).239-23 However, we could only calculate an odds ratio for 22 datasets (n=29,563). This total included unpublished additional data provided by two groups (Farooqi et al and Hebebrand et al) which supersedes previous publications (see figure 1 footnotes for details). Of the 22 datasets, 21 represented Caucasian populations; one contained data from Black Americans.15 Amongst the control populations, the isoleucine allele frequency ranged between 0.5-3.4% (figure 1). Using a fixed effects model we found that overall the V103I genotype was inversely associated with obesity (odds ratio 0·82; 95% confidence interval 0·70-0·96; p=0·015). There was no heterogeneity among studies (Q=13·99 (21 df); p=0·87); consequently, results under a random effects model were identical. A funnel plot of the association between V103I and obesity plotted against sample size showed a symmetrical distribution (p = 0·326), suggesting there was no apparent publication bias.

Figure 1
Meta-analysis of studies of MC4R V103I polymorphism and obesity


These data from 10,975 cases and 18,588 controls confirm that individuals carrying the isoleucine allele have a lower risk of obesity compared with noncarriers. However, whereas a previous pooled analysis reported a 31% risk reduction,3 our data based on nearly four times as many individuals show this reduced risk may be around 18%, suggesting the original association was overestimated. Our study reinforces the need for large scale studies to reliably assess gene-disease associations.

Several studies have suggested that the V103I variant may be non-functional. Indeed, the V103I has been shown to possess a normal endogenous agonist ligand profile and normal receptor expression levels at the cell surface.2 3 10 24 25 However, recent functional studies have revealed that, compared to the wild-type receptor, the infrequent I103 allele is less responsive to agouti-related protein (AGRP).26 AGRP is an endogenous antagonist of the MC4 receptor that stimulates energy intake and promotes weight gain.27-30 Thus the V103I-mediated attenuation in MC4R activation by AGRP might lead to a relatively weaker orexigenic signal; in turn, this may result in a comparatively lower risk of obesity in human populations. Collectively, these findings suggest that the V103I polymorphism may be causally associated with obesity risk. Alternatively, this variant may be in linkage disequilibrium with an unknown functional variant elsewhere in the MC4R gene or in regulatory regions.

Our analysis was potentially limited by a number of factors. We cannot assess the impact of unmeasured genetic or environmental modifiers on the size and direction of the association. However, there is no reported evidence of interdependency. Secondly, because of the infrequency of the V103I polymorphism and the magnitude of the association observed in the current study, we cannot exclude the possibility that this finding is a false positive; however, this explanation is unlikely given the size of our study and the role of this gene in monogenic obesity. Finally, differences in study designs and case definitions may also have distorted the magnitude of the association between the V103I genetic variant and obesity. Despite these differences, we found no statistical evidence of heterogeneity among studies.

In conclusion, in this meta-analysis of 29,563 individuals we confirm that the MC4R V103I genotype protects against common obesity. We estimate that 17% of obesity in the population is attributable to the common homozygous genotype. This polymorphism is the first to be consistently associated with alterations in human obesity at the population level. As such, it provides proof of principle that specific genetic variants may, at least in part, explain susceptibility and resistance to common forms of human obesity. A better understanding of the mechanisms underlying this association will help determine whether changes in MC4R activity have therapeutic potential.


The analyses in this paper were conducted as part of the Genes in Energy Balance and Metabolism (GEM) Consortium between the MRC Epidemiology Unit, the Sanger Institute and University of Cambridge. The Ely Study is supported by the MRC and the EPIC-Norfolk Study by programme grants from the MRC and CRUK with additional support from the European Union, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency and the Wellcome Trust.

We gratefully acknowledge the support of corresponding authors: Dr C Bouchard, Dr P Jacobson, Dr RJF Loos Human Genomics Laboratory, Pennington Biomedical Research Center, USA; Dr IM Heid, Dr T Illig GSF National Research Center for Environment and Health, Institute of Epidemiology, Neuherberg, Germany; Prof Winfried Rief Department of Psychology, Philipps-University of Marburg, Germany; Prof S Herpertz Department for Psychosomatic Medicine and Psychotherapy, Westfälisches Zentrum for Psychiatry, Psychotherapy and Psychosomatics, Dortmund, Germany; Dr M Laakso, Dr J Pihlajamäki Department of Medicine, University of Kuopio, Finland; Dr F Santini Department of Endocrinology and Metabolism, University of Pisa, Italy.

Deborah Smyth and John Todd with Juvenile Diabetes Research Foundation and Wellcome Trust funding are thanked for genotyping some of the EPIC samples. Genotyping of additional German samples was funded by the German National Genome Net-2.

IB is funded by The Wellcome Trust. SO’R, IB and JH acknowledge support from EU FP6 funding (contract no LSHM-CT-2003-503041).

EHY is an MRC Career Development Fellow.


Conflict of interest statement

The authors declare no conflicts of interest.


1. Farooqi IS, Keogh JM, Yeo GSH, Lank EJ, Cheetham T, O’Rahilly S. Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med. 2003;348:1085–1095. [PubMed]
2. Vaisse C, Clement K, Durand E, Hercberg S, Guy-Grand B, Froguel P. Melanocortin-4 receptor mutations are a frequent and heterogeneous cause of morbid obesity. J Clin Invest. 2000;106:253–262. [PMC free article] [PubMed]
3. Geller F, Reichwald K, Dempfle A, Illig T, Vollmert C, Herpertz S, et al. Melanocortin-4 receptor gene variant I103 is negatively associated with obesity. Am J Hum Genet. 2004;74:572–581. [PubMed]
4. Lohmueller KE, Pearce CL, Pike M, Lander ES, Hirschhorn JN. Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat Genet. 2003;33:177–182. [PubMed]
5. Ioannidis JPA, Trikalinos TA, Ntzani EE, Contopoulos-Ioannidis DG. Genetic associations in large versus small studies: an empirical assessment. Lancet. 2003;361:567–571. [PubMed]
6. Day N, Oakes S, Luben R, Khaw KT, Bingham S, Welch A, et al. EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. Br J Cancer. 1999;80(Suppl 1):95–103. [PubMed]
7. Williams DRR, Wareham NJ, Brown DC, Byrne CD, Clark PMS, Cox BD, et al. Undiagnosed glucose intolerance in the community: the Isle of Ely Diabetes Project. Diabet Med. 1995;12:30–35. [PubMed]
8. Wareham NJ, Byrne CD, Williams R, Day NE, Hales CN. Fasting proinsulin concentrations predict the development of type 2 diabetes. Diabetes Care. 1999;22:262–270. [PubMed]
9. Gotoda T, Scott J, Aitman TJ. Molecular screening of the human melanocortin-4 receptor gene: identification of a missense variant showing no association with obesity, plasma glucose, or insulin. Diabetologia. 1997;40:976–979. [PubMed]
10. Gu W, Tu Z, Kleyn PW, Kissebah A, Duprat L, Lee J, et al. Identification and functional analysis of novel human melanocortin-4 receptor variants. Diabetes. 1999;48:635–639. [PubMed]
11. Ohshiro Y, Sanke T, Ueda K, Shimajiri Y, Nakagawa T, Tsunoda K, et al. Molecular scanning for mutations in the melanocortin-4 receptor gene in obese/diabetic Japanese. Ann Hum Genet. 1999;63:483–487. [PubMed]
12. Dubern B, Clement K, Pelloux V, Froguel P, Girardet J-P, Guy-Grand B, et al. Mutational analysis of melanocortin-4 receptor, agouti-related protein, and alpha-melanocyte-stimulating hormone genes in severely obese children. J Pediatr. 2001;139:204–209. [PubMed]
13. Rosmond R, Chagnon M, Bouchard C, Bjorntorp P. A missense mutation in the human melanocortin-4 receptor gene in relation to abdominal obesity and salivary cortisol. Diabetologia. 2001;44:1335–1338. [PubMed]
14. Miraglia del Giudice E, Cirillo G, Nigro V, Santoro N, D’Urso L, Raimondo P, et al. Low frequency of melanocortin-4 receptor (MC4R) mutations in a Mediterranean population with early-onset obesity. Int J Obes. 2002;26:647–651. [PubMed]
15. Jacobson P, Ukkola O, Rankinen T, Snyder EE, Leon AS, Rao DC, et al. Melanocortin 4 receptor sequence variations are seldom a cause of human obesity: the Swedish Obese Subjects, the HERITAGE Family Study, and a Memphis Cohort. J Clin Endocrinol Metab. 2002;87:4442–4446. [PubMed]
16. Branson R, Potoczna N, Kral JG, Lentes K-U, Hoehe MR, Horber FF. Binge eating as a major phenotype of melanocortin 4 receptor gene mutations. N Engl J Med. 2003;348:1096–1103. [PubMed]
17. Marti A, Corbalan MS, Forga L, Martinez JA, Hinney A, Hebebrand J. A novel nonsense mutation in the melanocortin-4 receptor associated with obesity in a Spanish population. Int J Obes. 2003;27:385–388. [PubMed]
18. Valli-Jaakola K, Lipsanen-Nyman M, Oksanen L, Hollenberg AN, Kontula K, Bjorbaek C, et al. Identification and characterization of melanocortin-4 receptor gene mutations in morbidly obese Finnish children and adults. J Clin Endocrinol Metab. 2004;89:940–945. [PubMed]
19. Santini F, Maffei M, Ceccarini G, Pelosini C, Scartabelli G, Rosellini V, et al. Genetic screening for melanocortin-4 receptor mutations in a cohort of Italian obese patients: description and functional characterization of a novel mutation. J Clin Endocrinol Metab. 2004;89:904–908. [PubMed]
20. Rutanen J, Pihlajamaki J, Karhapaa P, Vauhkonen I, Kuusisto J, Moilanen Mykkanen L, et al. The Val103Ile polymorphism of melanocortin-4 receptor regulates energy expenditure and weight gain. Obes Res. 2004;12:1060–1066. [PubMed]
21. Larsen LH, Echwald SM, Sorensen TI, Andersen T, Wulff BS, Pedersen O. Prevalence of mutations and functional analyses of melanocortin 4 receptor variants identified among 750 men with juvenile-onset obesity. J Clin Endocrinol Metab. 2005;90:219–224. [PubMed]
22. Loos RJF, Rankinen T, Tremblay A, Pérusse L, Chagnon Y, Bouchard C. Melanocortin-4 receptor gene and physical activity in the Québec Family Study. Int J Obes. 2005;29:420–428. [PubMed]
23. Heid IM, Vollmert C, Hinney A, Doring A, Geller F, Lowel H, et al. Association of the 103I MC4R allele with decreased body mass in 7937 participants of two population based surveys. J Med Genet. 2005;42:e21. [PMC free article] [PubMed]
24. Hinney A, Hohmann S, Geller F, Vogel C, Hess C, Wermter A-K, et al. Melanocortin-4 receptor gene: case-control study and transmission disequilibrium test confirm that functionally relevant mutations are compatible with a major gene effect for extreme obesity. J Clin Endocrinol Metab. 2003;88:4258–4267. [PubMed]
25. Ho G, MacKenzie RG. Functional characterization of mutations in melanocortin-4 receptor associated with human obesity. J Biol Chem. 1999;274:35816–35822. [PubMed]
26. Xiang Z, Litherland SA, Sorensen NB, Wood MS, Shaw AM, Millard WJ, et al. Pharmacological characterization of 40 human melanocortin-4 receptor polymorphisms with the endogenous proopiomelanocortin-derived agonists and the agouti-related protein (AGRP) antagonist. Biochemistry. 2006;45:7277–7288. [PubMed]
27. Bewick GA, Gardiner JV, Dhillo WS, Kent AS, White NE, Webster Z, et al. Postembryonic ablation of AgRP neurons in mice leads to a lean, hypophagic phenotype. FASEB J. 2005;19:1680–1682. [PubMed]
28. Graham M, Shutter JR, Sarmiento U, Sarosi I, Stark KL. Overexpression of Agrt leads to obesity in transgenic mice. Nat Genet. 1997;17:273–274. [PubMed]
29. Ollmann MM, Wilson BD, Yang Y-K, Kerns JA, Chen Y, Gantz I, et al. Antagonism of central melanocortin receptors in vitro and in vivo by agouti-related protein. Science. 1997;278:135–138. [PubMed]
30. Schwartz MW, Woods SC, Porte D, Jr, Seeley RJ, Baskin DG. Central nervous system control of food intake. Nature. 2000;404:661–671. [PubMed]
31. Farooqi IS, Yeo GSH, Keogh JM, Aminian S, Jebb SA, Butler G, et al. Dominant and recessive inheritance of morbid obesity associated with melanocortin 4 receptor deficiency. J Clin Invest. 2000;106:271–279. [PMC free article] [PubMed]
32. Hinney A, Schmidt A, Nottebom K, Heibult O, Becker I, Ziegler A, et al. Several mutations in the melanocortin-4 receptor gene including a nonsense and a frameshift mutation associated with dominantly inherited obesity in humans. J Clin Endocrinol Metab. 1999;84:1483–1486. [PubMed]
33. Herpertz S, Siffert W, Hebebrand J. Binge eating as a phenotype of melanocortin 4 receptor gene mutations. N Engl J Med. 2003;349:606–607. [PubMed]
34. Hebebrand J, Geller F, Dempfle A, Heinzel-Gutenbrunner M, Raab M, Gerber G, et al. Binge-eating episodes are not characteristic of carriers of melanocortin-4 receptor gene mutations. Mol Psychiatry. 2004;9:796–800. [PubMed]