Diabetes
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ma, L.
Right arrow Articles by Baier, L. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ma, L.
Right arrow Articles by Baier, L. J.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Diabetes 53:2696-2699, 2004
© 2004 by the American Diabetes Association, Inc.

Brief Genetics Report

Melanocortin 4 Receptor Gene Variation Is Associated With Severe Obesity in Pima Indians

Lijun Ma, P. Antonio Tataranni, Clifton Bogardus, and Leslie J. Baier

From the Clinical Diabetes and Nutrition Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Department of Health and Human Services, Phoenix, Arizona


   ABSTRACT
TOP
 ABSTRACT
RESEARCH DESIGN AND METHODS
 REFERENCES
 
Heterozygous coding mutations in the melanocortin 4 receptor gene (MC4R) are the most common genetic causes of severe human obesity identified to date. To determine whether MC4R has a role in causing severe obesity in Pima Indians, we sequenced the coding region of this gene in 426 full-heritage, non–first-degree related, adult Pima Indians (300 severely obese and 126 nondiabetic nonobese control subjects). Three coding variations were detected as heterozygotes only in severely obese subjects. One variation, detected in three obese subjects, was a novel single-base insertion (A) at nucleotide 100, and it predicted a frameshift and premature STOP at codon 37. The second variant, detected in 10 obese subjects, predicted a previously identified arginine-to-glutamine substitution at codon 165, and the third variant, detected in one obese subject, predicted a novel glycine-to-serine substitution at codon 231. Three polymorphisms were also identified in the 5' untranslated region, but these variants were detected in both obese and lean subjects and had similar allele frequencies. We conclude that variations in MC4R may account for a small portion of obesity in Pima Indians, but they do not explain the overall high prevalence of obesity in this Native American population.

The genetic basis of human obesity is largely unknown. A few genes, such as the melanocortin 4 receptor (MC4R) located on chromosome 18q22, have been identified as the cause of rare forms of monogenic obesity in both humans and rodents (1, 2). Heterozygous coding mutations in the MC4R gene are implicated in 1–6% of early onset or severe adult obesity, and they appear to exert a major gene effect in affected individuals (i.e., have a high penetrance and explain a high percentage of the phenotypic variance) (3, 4). To identify obesity susceptibility loci in Pima Indians, a population with high prevalence of severe obesity and type 2 diabetes (5), we screened MC4R as a candidate gene. The coding region of the single exon was sequenced in 426 full-heritage, non–first-degree related, adult Pima Indians (300 severely obese, as defined by maximum BMI >45 kg/m2, and 126 nonobese, as defined by maximum BMI <30 kg/m2 at age >35 years and nondiabetic) (Table 1). Three coding variations were identified. A novel single-base insertion (A) at nucleotide 100, which predicts a frameshift resulting in a premature STOP (TGA) at codon 37, was observed as a heterozygote in 3 of the 300 severely obese Pima subjects, but it was not observed in any of the 126 nonobese subjects. In addition, a previously described G-to-A substitution at nucleotide 494, which predicts an arginine (R)–to–glutamine (Q) substitution at codon 165 (R165Q), was observed as a heterozygote in 10 of the 300 obese Pima subjects but in none of the control subjects. Finally, a novel G-to-A substitution at nucleotide 691, predicting a glycine (G)–to–serine (S) substitution at codon 231 (G231S), was identified as a heterozygote in 1 of the 300 severely obese subjects but in none of the control subjects (Table 2). All of these coding variations occurred in different subjects of this sample.


View this table:
[in this window]
[in a new window]
  		TABLE 1 Characteristics of subjects in case/control sample for severe obesity

 

View this table:
[in this window]
[in a new window]
  		TABLE 2 Frequency of heterozygous coding mutations in 426 case/control subjects

 
To search for variants that could affect gene expression, ~2 kb of the upstream untranslated (putative promoter) region of MC4R was additionally sequenced in 84 of the extremely obese subjects (BMI 50.5–73.8 kg/m2). The DNA sequences from these obese Pima Indian subjects were compared with each other and also with the published human MC4R sequence. Three polymorphisms were detected. The untranslated polymorphisms were all C-to-T substitutions, at positions –1,538, –1,005, and –896 relative to the transcriptional start site, where the minor allele (T) had frequencies of 0.02, 0.05, and 0.49, respectively. These three upstream polymorphisms were further genotyped in the 300 severely obese and 126 nonobese subjects, and their allelic frequencies were similar between the obese and nonobese groups (data not shown). Genotypes of these three upstream single nucleotide polymorphisms (SNPs) were in Hardy-Weinberg equilibrium when analyzed in the obese group, the nonobese group, and the combined group. In our linkage disequilibrium analysis, we noted that many of the pairwise estimates of D' are high, which is common for low-frequency polymorphisms because these are often recently introduced into the population and are typically carried on a single haplotype. However, {Delta}2 values are in general fairly low, indicating that there is little redundance for the information provided by each SNP (data not shown).

All of the coding mutations were detected only in severely obese subjects. As shown in Table 2, the nucleotide A insertion, resulting in the premature STOP codon, was detected as a heterozygous mutation in three severely obese subjects and was not observed in any of the control subjects, but its frequency (1%) was too rare to be statistically associated with obesity in this sample. Similarly, G231S was too rare (0.3%) to be statistically associated with severe obesity in this case-control sample. In contrast, the coding R165Q was detected in heterozygous form in 10 severely obese subjects (6 female and 4 male subjects), was monomorphic in all of the control subjects, and was statistically associated with severe obesity (P = 0.04, {chi}2 test) in the case-control sample. Among the 300 severely obese subjects, the 10 individuals heterozygous for R165Q had a similar maximum BMI as compared with individuals who did not carry the Q allele (Table 3). However, the R165Q subjects tended to be younger when they reached their maximum BMI as compared with the other obese subjects (30 ± 7 vs. 37 ± 11 years, P = 0.04) (Table 3).


View this table:
[in this window]
[in a new window]
  		TABLE 3 Characteristics of severely obese subjects based on R165Q genotype

 
Among the 3 subjects who were heterozygous for the novel insertion at nucleotide 100, 1 subject had extended pedigree information and DNA to allow genotyping of 16 additional family members (Fig. 1A). Seven family members in this pedigree were confirmed to be heterozygous for the nucleotide insertion. These seven subjects had a maximum BMI that ranged from 33 to 54 kg/m2, and some subjects reached their maximum BMI at a very young age (e.g., subject II8 and III15 had a BMI of 43 and 49 kg/m2 at age 19 and 7, respectively) (Fig. 1A). Based on previous functional studies of MC4R mutations, an insertion resulting in a premature STOP at codon 37 should produce a truncated receptor with no activity (3). Critical ligand-binding and transmembrane domains lie COOH-terminal to this region (3, 6–9). Complete loss of function of one MC4R allele is predicted to result in obesity because the gene appears to function in a codominant manner (2, 3). However, we are unable to clearly demonstrate a link between severe obesity and the inheritance of this single nucleotide insertion in our Pima Indian pedigree because there are at least two siblings in generation IV (Fig. 1A) who are severely obese (BMI of 50 and 45 kg/m2) but do not carry the nucleotide insertion. Therefore, we propose that there are additional genetic and/or environmental factors that have major effects on determining obesity in this pedigree.



View larger version (25K):
[in this window]
[in a new window]
  		FIG. 1. A: Pedigree for subject with insertion A at nucleotide 100. B: Pedigree for subject with heterozygous Gly231Ser. The arrow indicates the proband. Only subjects with symbols outlined in bold had DNA samples available for sequencing. Shaded symbols represent subjects carrying the heterozygous insertion A at nucleotide 100 (A) or Gly231Ser (B). Maximum BMI and age at maximum BMI are shown for each subject, if known.

 
The single subject with G231S had four more family members for whom clinical information and DNA were available. Genotyping of these four additional family members identified two members to be G231S heterozygotes, with maximum BMIs of 44 and 47 kg/m2 at age 44 and 47 years, respectively (II2 and II5) (Fig. 1B). The lean sibling (I3) (Fig. 1B) of the proband (I2) (Fig. 1B) did not carry the mutation, and the only available subject of the third generation, whose maximum BMI was 44 kg/m2 at age 22 years, did not carry G231S. Based on our current data, we are not able to determine whether the novel heterozygous amino acid substitution G231S is the cause of morbid obesity in this family.

The R165Q substitution has been previously reported as a rare mutation causing severe obesity (3, 9), and this variant is statistically associated with severe obesity in Pima Indians. This heterozygous mutation was observed in 3% of severely obese Pima Indians (maximum BMI >45 kg/m2), which is the highest frequency reported for any single functional MC4R variant. Subjects with the Q allele were also younger when they reached maximum BMI as compared with equally obese subjects homozygous for the R allele (Table 3). The finding that heterozygous R165Q Pima subjects had an earlier onset to their obesity is supported by other studies in humans (3, 9–11). Amino acid 165 is located in a transmembrane domain, and functional studies have shown that the R165Q mutation dramatically reduces the binding activity of MC4R by 70% (3, 12). In addition, another recent study demonstrated that the R165Q mutant receptor is poorly expressed on the cell surface (13). Therefore, R165Q should decrease MC4R signaling.

Haploinsufficiency at the MC4R locus, which is thought to be sufficient to cause obesity, typically results from translated nonfunctional MC4R protein rather than aberrant gene transcription. We specifically sought mutations that could reduce MC4R gene transcription in Pima Indians by sequencing a 2-kb region that included the minimal promoter region (14). Although three upstream variants were identified, none were associated with obesity, which is consistent with a recent report of MC4R promoter variants in 266 children and 165 adults (14).

We have previously published a report that failed to identify variation in the MC4R coding sequence in Pima Indians (15). Our inability to detect allelic variation in this previous study was likely caused by the smaller number of samples that were sequenced (10 lean and 10 obese subjects), which would allow detection of variant alleles with a frequency ≥2.5% in the general Pima population, or ≥5.0% if a variant occurred only in obese subjects. In the current study, 426 subjects were sequenced, which should allow detection of coding variants with an allele frequency of ≥0.12%.

Identification of two rare functional variants in MC4R suggests that this gene has an important role in contributing to severe obesity in some Pima Indian families, but these two variants do not account for the high prevalence of obesity in this Native American tribe. However, identifying individuals and pedigrees whose BMI is influenced by rare mutations may lessen the complexity of population-based studies to search for genes that cause common, multigenic obesity.


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 RESEARCH DESIGN AND METHODS
REFERENCES
 
All of the subjects are part of our ongoing longitudinal study of the etiology of obesity and type 2 diabetes among the Gila River Indian Community in central Arizona (16). Sequencing of the coding region was performed in DNA from 300 severely obese subjects, as defined by a maximum BMI >45 kg/m2, and 126 nondiabetic and nonobese control subjects, as defined by BMI <30 at age >35 years. Additional sequencing of 2 kb of the 5' upstream untranslated region was performed in 84 extremely obese subjects (38 men and 46 women aged 35 ± 10 years [means ± SD]; BMI 60.2 ± 5.6 kg/m2, range 51.2–73.8 kg/m2) selected from 300 severely obese subjects mentioned above whose maximum BMI was >50 kg/m2. The 5' untranslated variants initially identified in the 84 extremely obese subjects were analyzed in a case-control association study by genotyping the remaining 216 obese subjects (for a total of 300 obese subjects) and 126 nonobese subjects. Diabetic status was determined by the criteria of the World Health Organization (17). All subjects in the case-control set were from different nuclear families.

The pedigree analyzed for the insertion A at nucleotide 100 had clinical data available for five generations and DNA for 17 subjects, from generation II to IV, for genotypic analysis (Fig. 1A), whereas pedigree analyzed for G231S had only three generations’ clinical data and 5 subjects’ DNA available (Fig. 1B).

Sequence variant identification and genotyping.
Genomic DNA for sequencing and genotyping was obtained from peripheral lymphocytes. Sequencing was performed using Big Dye terminator (Applied Biosystems) on an automated DNA capillary sequencer (model 3700; Applied Biosystems). The DNA region encompassing the insertion A at nucleotide 100 was sequenced using primers MC4R-insA100 forward 5'-TGAGACGACTCCCTGACCCA-3' and reverse 5'-CCCAACCCGCTTAACTGTCA-3'. The DNA region encompassing R165Q was sequenced using primers MC4R-R165Q forward 5'-TACGGATGCACAGAGTTTCA-3' and reverse 5'-CCCAGCAGACAACAAAGACG-3'. The DNA region encompassing G231S was sequenced using primers MC4R-G231S forward 5'-GGGTTGGGATCATCATAAGT-3' and reverse 5'-CCAGTACCCTACACGGAAGA-3'. The DNA region encompassing the MC4R-896, -1,005, and -1,538 positions upstream of transcriptional start site was sequenced using primers MC4R-896 forward 5'-TCTTCCAGCCATACCATGTC-3' and reverse 5'-CTGAAGTCGAGAAGCAAGCC-3', primers MC4R-1005 forward 5'-CCATCTTTCAAACCACCTTA-3' and reverse 5'-TAAGAACCCAGCCAGTAGTG-3', and primers MC4R-1,538 forward 5'-GGAGTTGGAGGTGTGAGTTC-3' and reverse 5'-CGTAAGTTGAACCGACAAAT-3', respectively. Genotyping of MC4R-896, -1,005, and -1,538 was performed using TaqMan allelic discrimination assay (Applied Biosystems) for case-control association study. The TaqMan genotyping reaction was amplified on a GeneAmp PCR system 9700 (95°C for 10 min, followed by 40 cycles of 95°C for 30 s and 60°C for 1 min 30 s), and fluorescence was detected on an ABI Prism 7700 sequencer detector (Applied BioSystems). Sequence information for all oligonucleotide primers and probes is available upon request.

Statistical analysis.
Statistical analyses were performed using the statistical analysis system of the SAS Institute (Cary, NC). Age and BMI are expressed as means ± SD. Differences between means were compared by unpaired Student’s t test or general linear model (GLM) when adjusted for age and sex, and differences of frequencies were compared by {chi}2 test. All reported P values were two sided. P values <0.05 were considered to be of statistical significance.


   ACKNOWLEDGMENTS
 
The authors are grateful to Dr. Michal Prochazka for his critical reading of this manuscript and Dr. Robert L. Hanson for his analysis of linkage disequilibrium.

Address correspondence and reprint requests to Leslie J. Baier, PhD, Clinical Diabetes and Nutrition Section, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 4212 N. 16th St., Phoenix, AZ 85016. E-mail: lbaier{at}phx.niddk.nih.gov

Received for publication February 26, 2004 and accepted in revised form July 16, 2004

Key Words: MC4R, melanocortin 4 receptor • SNP, single nucleotide polymorphism


   REFERENCES
TOP
 ABSTRACT
 RESEARCH DESIGN AND METHODS
 REFERENCES
 

  1. Ste Marie L, Miura GI, Marsh DJ, Yagaloff K, Palmiter RD: A metabolic defect promotes obesity in mice lacking melanocortin-4 receptors. Proc Natl Acad Sci U S A97 :12339 –12344,2000[Abstract/Free Full Text]
  2. Farooqi IS, Yeo GS, Keogh JM, Aminian S, Jebb SA, Butler G, Cheetham T, O’Rahilly S: Dominant and recessive inheritance of morbid obesity associated with melanocortin 4 receptor deficiency. J Clin Invest106 :271 –279,2000[Medline]
  3. Farooqi IS, Keogh JM, Yeo GS, Lank EJ, Cheetham T, O’Rahilly S: Clinical spectrum of obesity and mutations in the melanocortin 4 receptor gene. N Engl J Med348 :1085 –1095,2003[Abstract/Free Full Text]
  4. Hinney A, Hohmann S, Geller F, Vogel C, Hess C, Wermter AK, Brokamp B, Goldschmidt H, Siegfried W, Remschmidt H, Schafer H, Gudermann T, Hebebrand J: 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 Metab88 :4258 –4267,2003[Abstract/Free Full Text]
  5. Krosnick A: The diabetes and obesity epidemic among the Pima Indians. N J Med97 :31 –37,2000
  6. Schioth HB, Petersson S, Muceniece R, Szardenings M, Wikberg JE: Deletions of the N-terminal regions of the human melanocortin receptors. FEBS Lett410 :223 –228,1997[Medline]
  7. Kobayashi H, Ogawa Y, Shintani M, Ebihara K, Shimodahira M, Iwakura T, Hino M, Ishihara T, Ikekubo K, Kurahachi H, Nakao K: A novel homozygous missense mutation of melanocortin-4 receptor (MC4R) in a Japanese woman with severe obesity. Diabetes51 :243 –246,2002[Abstract/Free Full Text]
  8. Biebermann H, Krude H, Elsner A, Chubanov V, Gudermann T, Gruters A: Autosomal-dominant mode of inheritance of a melanocortin-4 receptor mutation in a patient with severe early-onset obesity is due to a dominant-negative effect caused by receptor dimerization. Diabetes52 :2984 –2988,2003[Abstract/Free Full Text]
  9. Branson R, Potoczna N, Kral JG, Lentes KU, Hoehe MR, Horber FF: Binge eating as a major phenotype of melanocortin 4 receptor gene mutations. N Engl J Med348 :1096 –1103,2003[Abstract/Free Full Text]
  10. Lubrano-Berthelier C, Durand E, Dubern B, Shapiro A, Dazin P, Weill J, Ferron C, Froguel P, Vaisse C: Intracellular retention is a common characteristic of childhood obesity-associated MC4R mutations. Hum Mol Genet12 :145 –153,2003[Abstract/Free Full Text]
  11. Tao YX, Segaloff DL: Functional characterization of melanocortin-4 receptor mutations associated with childhood obesity. Endocrinology144 :4544 –4551,2003[Abstract/Free Full Text]
  12. Yeo GS, Lank EJ, Farooqi IS, Keogh J, Challis BG, O’Rahilly S: Mutations in the human melanocortin-4 receptor gene associated with severe familial obesity disrupts receptor function through multiple molecular mechanisms. Hum Mol Genet12 :561 –574,2003[Abstract/Free Full Text]
  13. Nijenhuis WA, Garner KM, van Rozen RJ, Adan RA: Poor cell surface expression of human melanocortin-4 receptor mutations associated with obesity. J Biol Chem278 :22939 –22945,2003[Abstract/Free Full Text]
  14. Lubrano-Berthelier C, Cavazos M, Le Stunff C, Haas K, Shapiro A, Zhang S, Bougneres P, Vaisse C: The human MC4R promoter: characterization and role in obesity. Diabetes52 :2996 –3000,2003[Abstract/Free Full Text]
  15. Norman RA, Permana P, Tanizawa Y, Ravussin E: Absence of genetic variation in some obesity candidate genes (GLP1R, ASIP, MC4R, MC5R) among Pima Indians. Int J Obes Relat Metab Disord23 :163 –165,1999[Medline]
  16. Knowler WC, Bennett PH, Hamman RF, Miller M: Diabetes incidence and prevalence in Pima Indians: a 19-fold greater incidence than in Rochester, Minnesota. Am J Epidemiology108 :497 –505,1978[Abstract/Free Full Text]
  17. World Health Organization: Diabetes Mellitus: Report of a WHO Study Group. Geneva, World Health Org.,1985 (Tech. Rep. Ser., no. 727)

Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?



This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Ma, L.
Right arrow Articles by Baier, L. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Ma, L.
Right arrow Articles by Baier, L. J.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum