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Human Molecular Genetics Advance Access originally published online on May 21, 2007
Human Molecular Genetics 2007 16(15):1837-1844; doi:10.1093/hmg/ddm132
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Non-synonymous polymorphisms in melanocortin-4 receptor protect against obesity: the two facets of a Janus obesity gene

Fanny Stutzmann1, Vincent Vatin1, Stéphane Cauchi1, Anita Morandi2, Béatrice Jouret3, Olfert Landt4, Patrick Tounian5, Claire Levy-Marchal6, Raffaella Buzzetti7, Leonardo Pinelli2, Beverley Balkau8, Fritz Horber9, Pierre Bougnères10, Philippe Froguel1,11,* and David Meyre1

1 CNRS-8090-Institute of Biology, Pasteur Institute, Lille, France, 2 Department of Pediatrics, Regional Center for Juvenile Diabetes, University of Verona, Italy, 3 INSERM U563, Children's Hospital, Toulouse, France, 4 TIB MOLBIOL GmbH, Berlin, Germany, 5 Department of Pediatric Gastroenterology and Nutrition, Trousseau Hospital, Paris, France, 6 INSERM U457, Robert Debré Hospital, Paris, France, 7 Endocrinology, Department of Clinical science, La Sapienza University, Roma, Italy, 8 INSERM U780-IFR69, University Paris Sud, Villejuif, France, 9 Klinik Lindberg, Winterthur, Switzerland, 10 INSERM Pediatrics Endocrinology and U561, Saint Vincent de Paul Hospital, Paris V University, Paris, France and 11 Department of Genomic Medicine, Hammersmith Hospital, Imperial College London, London, UK

* To whom correspondence should be addressed at: Department of Genomic Medicine, Hammersmith Hospital, Imperial College London, Du Cane Road, London W12 0NN, UK. Tel: +44 02083833989; Email: p.froguel{at}imperial.ac.uk

Received April 2, 2007; Revised May 3, 2007; Accepted May 10, 2007


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 REFERENCES
 
The melanocortin-4 receptor (MC4R) gene pathogenic mutations are the most prevalent forms of monogenic obesity, responsible for ~2% of obesity cases, but its role in common obesity is still elusive. We analyzed the contribution of non-synonymous mutations V103I (rs2229616, c.307G > A) and I251L (no rs, c.751A > C) to obesity in 16 797 individuals of European origin from nine independent case–control, population-based and familial cohorts. We observed a consistent negative association of I251L variant (prevalence ranging 0.41–1.21%) with both childhood and adult class III obesity [odds ratio (OR) ranging from 0.25 to 0.76, 0.001 < P-value < 0.05] and with modulation of body mass index (BMI) in general populations, in eight out of nine studies, whereas only one study showed an association between V103I and BMI. Meta-analyses of previous published data with the current ones provided strong evidence of the protective effect of I251L toward obesity (OR = 0.52, P = 3.58 10-5), together with a modest negative association between V103I and obesity (OR = 0.80, P = 0.002). Taken together, gain-of-function mutations I251L and V103I may be responsible for a preventive fraction of obesity of 2%, which mirrors the prevalence of monogenic obesity due to MC4R haploinsufficiency. These results also emphasize the importance of the MC4R signalling tonus to prevent obesity, even in the context of our current obesogenic environment.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 REFERENCES
 
Three rather infrequent, potentially functional single nucleotide polymorphisms (SNPs) have been reported in MC4R (1–3) but their physiological role on the energy balance is unknown. A meta-analysis of 14 case–control studies suggested that V103I may confer a protective effect against obesity [odds ratio (OR) = 0.69, P = 0.03] (4). These findings were recently confirmed in a meta-analysis of 29 563 individuals (OR = 0.82, P = 0.01) (5), but remain controversial in several cohorts (5–7). Several in vitro studies failed to show that this isoleucine at position 103 makes any functional difference in basal MC4R signaling compared with the wild-type (8–11). However, V103I mutation decreases 2-fold the potency of the MC4R antagonist hAGRP(87–132) (11). Another missense mutation, I251L SNP (3), was first considered as potentially ‘neutral’ (9,12) but recently this I251L substitution was shown to increase MC4R basal activity (11), by alteration of downstream intracellular events associated with GPCR cAMP signal transduction. In addition, an infrequent 5' c.-178 A > C SNP did not associate with obesity in small-sized European populations (1,13). Therefore we decided a staged approach to assess the effects of these variants on obesity in 16 797 European Caucasian individuals.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIAL AND METHODS
 REFERENCES
 
The genotypic distributions of all three SNPs were in Hardy–Weinberg equilibrium (P > 0.01). The c.-178 A > C, V103I and I251L minor allele frequencies ranged, respectively, 1.49–2.24%, 1.37–1.49% and 0.41–1.21% in the cases and controls, in agreement with previously reported data from other European populations. Moreover, there was no linkage disequilibrium between -178 A > C, V103I and I251L (r2 = 0 for each of the three possible combinations, estimated from the whole sample set, n = 16 797). We found only six, seven and five compound heterozygous carriers for -178A > C/V103I, -178A > C/I251L and V103I/I251L, respectively. Our first case–control analysis of 1631 severely obese children and adults and 2378 controls showed that the I251L is a variant protective against severe obesity in the French population [allelic OR = 0.42 (95% CI 0.25–0.73), P = 0.001]. Interestingly, if the 748 unrelated obese children and the 883 unrelated class III obese adults are analyzed apart, a similar result is found [allelic OR = 0.33 (95% CI 0.14–0.76), P = 0.006 for children and OR = 0.51 (95% CI 0.27–0.97), P = 0.037 for adults]. Neither the c.-178A > C nor the V103I polymorphisms showed an association with obesity in our study populations (Table 1). To test the validity of our observation, we performed the Bonferroni correction, taking into account the three SNPs and the three tests (nine tests). We obtained a corrected P-value of 0.009, which remains significant.


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  		Table 1. Association of the three SNPs in MC4R with childhood or late-onset obesity in our cohorts and in replication samples

 
We then genotyped the three SNPs in 1109 French Caucasian pedigrees with obese children or adults (5326 individuals). We used the 90th and 97th BMI percentiles as thresholds for childhood overweight and obesity, respectively, according to the recommendations of the European Childhood Obesity Group study (14) in a French reference population (15), and the BMI Z-score as a quantitative measure of corpulence in both children and adults. Because of a partial overlap of individuals in case–control and family studies, the TDT and QTDT tests cannot be considered as an independent replication of association, but rather as a procedure to rule out the risk of stratification bias. The variant I251L was undertransmitted to overweight and obese subjects, defined by the 90th and 97th percentiles (% allele I251L transmitted: 23.5 and 23.3, P = 0.001 and 0.003, respectively), and the variant I251L was associated with a 0.76 SD decrease in the BMI Z-score (P = 0.01) (Table 2). No significant familial association (0.38 < P < 0.64) of either c.-178C or V103I alleles were observed for the same traits (Table 2).


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  		Table 2. Transmission disequilibrium test

 
We also tested for familial association of MC4R SNPs with body corpulence (using the BMI Z-score) in families from the general population of Northern France (294 pedigrees, 1175 individuals). We observed that children who were carriers of the I251L allele showed a reduction of 0.35 SD of their BMI Z-score (P = 0.05). Again, c.-178 A > C and V103I polymorphisms did not show any significant association with the BMI Z-score (0.46 < P < 0.97).

To further support the effect of the I251L allele in other studies of individuals of European origin, we then genotyped the three SNPs in an independently ascertained cohort of 484 obese French children who were compared with 590 young adult French controls (Table 1). We replicated the negative association between the I251L allele and childhood obesity [allelic OR = 0.35 (95% CI 0.13–0.95), P = 0.03], although we again did not find any association between –c.-178 A > C or V103I and childhood obesity. We also genotyped a small cohort of 179 obese and 670 lean Italian children. Case–control analyses showed the same trend toward a protective effect of the I251L allele against obesity [OR = 0.36 (95% CI 0.05–2.94), P = 0.5], although non-significant, owing to the modest sample size of obese children. No association was observed with V103I, nor with c.-178A > C (Table 1).

Finally, we studied 551 class III obese Swiss adults and compared them with 509 Swiss adults unselected on BMI. We observed once more the association between the I251L and class III adult obesity [allelic OR = 0.25 (95% CI 0.08–0.77), P = 0.009]. No association was observed with V103I, nor with c.-178A > C (Table 1).

To evaluate the contribution of the three MC4R polymorphisms to BMI variation in a general population, we genotyped the middle-aged general French population D.E.S.I.R. cohort (16) (n = 5195). Taking into account the low allele frequency of the studied polymorphisms, we focused on the analysis of BMI in the whole population set at baseline (n = 5195) rather than doing prospective analyses with low statistical power. Indeed, after 9 years of follow-up, only 74% of subjects were documented for BMI (n = 3861). We found a trend toward an association between I251L and BMI (P = 0.05) leading to a decrease in BMI of 0.7 kg/m2. The V103I variant was also associated with a decrease in BMI 0.8 kg/m2 (P = 0.03, Table 2). The c.-178C allele showed no association with BMI (P = 0.73).

We combined our current results with all the available information in a meta-analysis. We used only published case–control data from 29 (n = 39 879) and 12 studies (n = 11 435) for V103I and I251L, respectively. No heterogeneity between studies was detected for any of the two meta-analyses (P-value for {chi}2 test = 0.77 and 0.35 for V103I and I251L, respectively). We confirmed the modest effect of the V103I allele after pooling the 29 studies, with an OR of 0.80 (0.70–0.92) and a P-value of 0.002. In contrast, we found much stronger evidence for an association between the I251L allele and obesity (OR = 0.52, 95% CI 0.38–0.71, P-value = 3.58 10–5) (Fig. 1) (17). The consistency of these results is underlined by the fact that all 95% CI values overlap and contain the OR estimate of the meta-analysis. Moreover, we used QUANTO software, as described in the Materials and Methods section, to calculate the statistical power of this test. Calculations indicated a power of 95 and 99% to observe the mentioned effects (OR = 0.80 and 0.52) for V103I and I251L, respectively. Because the variants are protective, we did not calculate the population-attributable risk but rather the preventive fraction (18). It predicts the additional frequency of affected people in the same population, in the absence of the protective variant. We observed a preventive fraction of 0.84 and 1.05% for V103I and I251L, respectively, in the population of the meta-analyses.


Figure 1
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  		Figure 1. Meta-analysis of I251L polymorphism. The meta-analysis has been performed with 5972 controls and 5463 cases. Summary illustrates the final OR; 95% CI is included in the pictogram. Swiss adults, our study and Peterli et al. (17), 2006; Jacobson et al. (1), white cohort only; Miraglia del Giudice and Ohshiro, personal data communication.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIAL AND METHODS
 REFERENCES
 
The frequent disease, frequent allele theory postulates that the genetic risk for common diseases should be mainly driven by prevalent DNA polymorphism. Even if data confirm this hypothesis (19–21), our data show that infrequent coding functional SNPs in MC4R, the only gene frequently involved in monogenic early onset severe obesity, also contribute to common obesity phenotypes. Similar effects, although weaker, were previously found for POMC rare variation (22). Apart from decreasing the risk for obesity to nearly 50%, the I251L amino acid substitution decreases BMI in both obese/general and childhood/middle-aged adult populations of European descent. In eight studies out of nine, this MC4R I251L polymorphism is reproducibly associated with protection against obesity. The recently reported increased basal activity of the I251L mutant receptor (11) is consistent with a food intake reduction, leading to protection against obesity. The V103I variant showed a less reproducible pattern of association, although our updated meta-analysis still detects a modest protective effect against obesity (OR = 0.80, P = 0.002, n = 39 879).

Recently, we and others identified a major obesity gene: FTO reproducibly accounts for 22% of the attributable risk of obesity in both populations (23,24). However, despite lower population-attributable risk of MC4R I251L compared with FTO variant, we feel that this result presents two major interests. First, we found a rare variant with an important effect (OR = 2) implicated in genetic determination of obesity. To our knowledge, except for a POMC variant (22), this has not been clearly evidenced so far. Moreover, our discovery highlights all the more the importance of MC4R in the homeostasis of body corpulence because we found an obesity-protective variant in a gene well-known for rare pathogenic mutations causing obesity.

False-positive associations can be observed because of population stratification. However, the weak and homogeneous frequency of the protective alleles within the different cohorts is a first reason to exclude that stratification could explain our result. Moreover, the effect of the variant I251L is homogeneous among all case–control designs (OR ranging from 0.25 to 0.51), and replication populations come from small region recruitment area, decreasing also the potential bias. Finally, both independent familial analyses confirmed the association and we observed an even stronger effect with this test (OR = 0.34 in 1109 pedigrees with obesity). This suggests that potential stratification, if there is one, would decrease the effect instead of overestimating it. Multiple case–control studies alone have successfully identified the association with FTO, which we confirmed by TDT in two independent obesity-selected pedigrees (24), meaning that this method is powerful enough (23,24).

It is to note that the conclusion of the meta-analysis is limited by the lack of homogeneity of ascertainment for obesity and even for leanness between the studies. Even if we tested the absence of publication bias, it remains possible that the effect of the variant can be modulated by the severity of obesity.

Interestingly, both associated variants are protective against obesity, meaning that the obesity susceptibility is carried by the ancestral alleles that are highly conserved in most mammals, including chimpanzee and macaque (24). The low allele frequency (MAF = 0.41–2.24%) of the two obesity-protective MC4R variants is in accordance with recent data, demonstrating that most of the rare missense variants are deleterious (26). This was likely to be the case for both MC4R variants during chronic starvation episodes and before the recent shift in human environment and lifestyle.

On the basis of previous and current results, we can evaluate the ‘weight’ of MC4R on the risk of obesity: whereas loss-of-function mutations have been shown to be associated with ~2% of the cases of severe obesity (27–29), gain-of-function I251L (and possibly V103I) may be responsible for 2% of population-preventive fraction against obesity. If true, it is the first time to our knowledge that a gene has such a balanced effect on a metabolic trait. Altogether, MC4R should be considered as a Janus (double-faced) key modulator of body corpulence. Moreover, this report suggests that the stimulation of the leptin–melanocortin tonus is beneficial in humans to limit weight gain. In this regard, MC4R agonists that are currently under development may be useful to fight obesity in the near future (30).


   MATERIAL AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
REFERENCES
 
The phenotypic characteristics of the studied cohorts are summarized in Tables 3.


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  		Table 3. Characteristics of the different cohorts

 
The study protocol was approved by all local ethic committees and an informed consent was obtained from each subject before participating in the study.

Study I: initial case–control design
Our sample included 2378 control subjects, 748 children ascertained for severe obesity and 883 class III (BMI > 40 kg/m2) obese adults, all unrelated and French Caucasians. Childhood overweight and obesity have been defined as BMI exceeding, respectively, the 90th and 97th percentile for gender and age in a French reference population (14) according to the recommendation of the ECOG study (15). Control subjects were participants of the D.E.S.I.R. prospective study in a general population (16). Selection criteria were BMI < 27 kg/m2 and normal glucose tolerance at baseline and during the 9 year study follow-up. Two hundred and seventy unrelated adult French Caucasians recruited at the CNRS UMR8090 were also used as control subjects (BMI < 27 kg/m2 and normal glucose tolerance). Obese children were selected through a multimedia campaign run by the CNRS UMR8090 (n = 580) as well as in the Toulouse Children's Hospital (n = 82) and in the Paris Trousseau Hospital (n = 86). Obese adults were recruited through a multimedia campaign run by the CNRS UMR8090 and the Department of Nutrition of the Paris Hotel Dieu Hospital.

Study II: familial population-based cohorts selected for childhood/adult obesity
We tested familial association with obesity using (i) 674 pedigrees with at least one obese child and one obese relative, including 3427 individuals: 971 obese children, 288 non-obese children, 1282 parents and 640 grandparents, and (ii) 435 pedigrees with severe adult obesity (at least one person with BMI ≥ 35 kg/m2 and a first degree related with BMI ≥ 30 kg/m2), including a total of 1899 individuals: 174 lean, 353 overweighed, 749 class I and class II obese and 623 class III obese.

We also tested familial association in population-based pedigrees, in participants from the Fleurbaix–Laventie Ville Santé II study. The purpose of the study was to investigate cross-sectional and longitudinal associations between weight and fat mass and genetic, metabolic, and environmental factors in children and adults. This community-based cohort was recruited in 1999 on a voluntary basis and included 1175 participants, aged 8 years and over, from families living in the towns of Fleurbaix and Laventie and surroundings. This cohort included 294 families: 431 children and adolescents, 206 fathers, 244 mothers.

Study III: childhood obesity: French and Italian replication cohorts
Two independent cohorts were genotyped to confirm the findings of studies I and II. We first genotyped 484 French children ascertained for childhood obesity, from St Vincent de Paul Hospital (31), and 590 young adult French control subjects (mean age = 21 years, BMI < 25 kg/m2) from the Haguenau study (32). We then genotyped 179 obese Italian children from Rome (33) and 670 lean children from Verona.

Study IV: class III obesity: swiss replication cohort
To confirm the association between class III obesity and MC4R genetic variation, we genotyped 551 Swiss adults from Zurich with class III obesity (BMI ≥ 40 kg/m2) unrelated (34), 94 Swiss lean (BMI < 25 kg/m2) from Zurich and 415 Swiss from anonymous healthy blood donors from CHUV of Lausanne (for which we do not have phenotypical data; Swiss obesity prevalence 7.7%).

Study V: population-based prospective cohort
The D.E.S.I.R. cohort is a population of volunteers (n = 5195) recruited from 10 health examination centers in the western-central part of France who were examined every 3 years, over 9 years, with the aim of clarifying the development of the insulin resistance syndrome.

Phenotypes
Weight, height and waist circumference were measured by trained personnel, and BMI was calculated. The BMI Z-score was determined according to the Cole's method (35).

Genotypes
Genomic DNA was extracted from peripheral blood cells using a Pure-Gene D50K isolation kit (Gentra Systems) according to the manufacturer's instructions.

Three pairs of primers were designed by Primer3 to amplify overlapping fragments covering 2.3 kb, including the entire MC4R gene and minimal promoter. (They were also used to perform direct sequencing.) Each fragment contains one SNP. Primers were the following:

  1. 1F GAACCTGGCTGCCTGAAGATA
  2. 1R CTGTAACTGCTGCGGTTCCA
  3. 2F ACTGAGACGACTCCCTGACCC
  4. 2R AATCGCTCCCTTCATATTGGC
  5. 3F TTGATAATGTCATTGACTCGGTGA
  6. 3R TCAACCAGTACCCTACACGGAAG

PCR condition was 94°C 4 min for HotStart, denaturing at 94°C 15 s, annealing at 60°C 15 s, extension at 72°C 30 s and incubation at 72°C 10 min.

SNPs were genotyped with the LightCycler480 (Roche Diagnostics) assay on the basis of hybridization probes and fluorescent resonance energy transfer between fluorescein and LCRed 640. Probes were synthesized by TIB Molbiol Syntheselabor. The conditions are available upon request.

Quality controls
Hardy–Weinberg equilibrium has been tested in each cohort (Table 1). Looking for rare mutations in MC4R, we sequenced 1079 individuals and compared the results with genotyping by LightCycler480: we observed concordance rates of 99.8, 100 and 100% for c.-178 A > C, V103I and I251L, respectively. Genotyping was also controlled in familial designs, using the PedCheck program (36). In pedigrees with adult obesity, we observed one incompatibility out of 435 pedigrees. The Pedcheck analysis of 674 pedigrees with childhood obesity showed 3, 3 and 0 incompatibilities for c.-178A > C, V103I and I251L, respectively.

Statistical analyses
Tests for deviation from Hardy–Weinberg equilibrium used the DeFinetti program (http://linkage.rockefeller.edu/soft/). Case–control analyses used the {chi}2 test, and P-values were empirically computed with the CLUMP program (37). Transmission disequilibrium test and QPDT (Quantitative trait Pedigree Disequilibrium Test) were implemented in UNPHASED software. Familial association of the SNPs with quantitative traits, such as the BMI Z-score, was tested using the QPDTphase subprogram of UNPHASED software. In this test, the covariance is estimated within each family and the estimates combined across the dataset by the central limit theorem (http://portal.litbio.org/Registered/Help/unphased/). The meta-analysis by Mantel–Haentzel used the R program. We then used reported and updated (as much as possible) raw genotype counts to calculate OR under the allelic model. The statistical power of this test has been calculated for each variant with QUANTO software, using the total number of cases and controls, prevalence of obesity of 20% in European population (as suggested by the International Obesity Task Force) and the allele frequency and OR of the variants, resulting from the meta-analysis. We used 29 studies including 15 820 controls and 24 797 cases for V103I and 12 studies including 5972 controls and 5463 cases for I251L.


   ACKNOWLEDGEMENTS
 
We thank the patients and families that participated in this study. This work was supported in part by Conseil Regional Nord-Pas de Calais and Association Française des Diabétiques funding and by Roche and ALFEDIAM/Roche Diagnostics research prizes. Genotyping was supported by TibMol Biol. We also thank S. Gaget, M. Deweirder and F. Allegaert for technical assistance. We are particularly grateful to Cécile Lecoeur and David Serre for analytical help, and Drs Barbara Heude, Catherine Le Stunff, Juan Ruiz, Natascha Potoczna, Jean Tichet, Michel Marre and Jacques Weill for providing DNA.

Conflict of Interest statement. The authors declare that they have no competing financial interests.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIAL AND METHODS
 REFERENCES
 

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