Variation of the McKusick-Kaufman Gene and Studies of Relationships ...

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The Journal of Clinical Endocrinology & Metabolism 90(1):225–230 Copyright © 2005 by The Endocrine Society doi: 10.1210/jc.2004-0465

Variation of the McKusick-Kaufman Gene and Studies of Relationships with Common Forms of Obesity Kirstine L. Andersen,* Søren M. Echwald,* Lesli H. Larsen, Yasmin H. Hamid, Charlotte Glu¨mer, Torben Jørgensen, Knut Borch-Johnsen, Teis Andersen, Thorkild I. A. Sørensen, Torben Hansen, and Oluf Pedersen Steno Diabetes Center and Hagedorn Research Institute (K.L.A., S.M.E., L.H.L., Y.H.H., C.G., K.B.-J., T.H., O.P.), DK-2820 Gentofte, Denmark; Danish Epidemiology Science Center at the Institute of Preventive Medicine (L.H.L., T.I.A.S.), DK-1357 Copenhagen, Denmark; Research Center for Prevention and Health (C.G., T.J.), DK-2600 Glostrup, Denmark; Copenhagen City Heart Study, Bispebjerg University Hospital (T.A., T.I.A.S.), DK-2400 Copenhagen, Denmark; Roskilde County Hospital, University of Copenhagen (T.A.), DK-4000 Roskilde, Denmark; and Faculty of Health Science, University of Aarhus (K.L.A., O.P.), Aarhus, Denmark Arg517Cys variants are in complete linkage disequilibrium and defined a prevalent haplotype. In a case-control study, the Arg517Cys polymorphism allele prevalence was 11.4% [95% confidence interval (CI), 9.7–13.0] among 744 men with juvenile-onset obesity and 9.3% (CI, 7.9 –10.7) among 867 control subjects (P ⴝ 0.048). However, among middle-aged men the allelic prevalence was 9.7% (CI, 7.9 –11.4) among 523 obese men and 12.2% (CI, 10.8 –13.6) among 1051 lean men (P ⴝ 0.037). In conclusion, it is unlikely that MKKS variants play a major role in the pathogenesis of nonsyndromic obesity, although in rare cases the A242S allele may contribute to obesity. (J Clin Endocrinol Metab 90: 225–230, 2005)

Obesity is a prominent feature of the Bardet-Biedl syndrome (BBS), one subset of which, BBS6, is due to mutations in the chaperonin-like gene termed the McKusick-Kaufman syndrome (MKKS) gene. We tested whether variation in MKKS contributes to common and probably polygenic forms of obesity by performing mutation analysis of the coding region in 60 Danish white men with juvenile-onset obesity. Five variants were identified, including two synonymous mutations (Pro39Pro and Ile178Ile) and three nonsynonymous variants (Ala242Ser, Arg517Cys, and Gly532Val). Furthermore, the rare Ala242Ser was identified in two families and showed partial cosegregation with obesity. The Pro39Pro, Ile178Ile, and

T

HE GLOBAL EPIDEMIC of obesity requires much better prevention than is now available (1), and achievement of this goal is dependent on a more comprehensive understanding of the etiology of obesity. Studies of twins, adoptees, and families show that both environmental and genetic factors are important in predisposing to obesity (2– 6). The Bardet-Biedl syndrome (BBS) is a rare syndrome with a primarily autosomal recessive inheritance, although complex inheritance has been demonstrated in some families (7, 8). The syndrome has been linked to eight different chromosomal regions, and recently, the gene underlying the BBS syndrome linked to chromosome 20p12 was identified and shown to encode a group II chaperonin-like protein with a wide tissue distribution (9 –11). Variations in this gene are also the cause of the closely related McKusick-Kaufman syndrome (MKKS), and the gene has been termed MKKS (12). The BBS syndrome is primarily characterized by several severe clinical manifestations, including retinal dystrophy, polydactyly, hypogenitalism, and renal malformations, but at the same time, obesity is a recurrent finding among BBS

patients (7). A study by Croft et al. (13) has shown that obligate carriers of BBS heterozygous mutations are more obese than noncarriers, without displaying other phenotypes associated with BBS or MKKS. We therefore hypothesized that less severe or heterozygous mutations in the recently identified MKKS might underlie more common forms of obesity. To test this hypothesis we performed a mutation analysis of the coding region of MKKS in a cohort of obese [body mass index (BMI), 33.3 ⫾ 2.3 kg/m2] Danish white men by combined single-strand conformational polymorphism (SSCP) and heteroduplex analysis. The identified variants for association with both juvenile-onset obesity and common obesity in middle-aged men, respectively. Subjects and Methods Subjects The de novo mutation analysis was performed on genomic DNA from a random selection of 60 subjects from a sample of 744 obese young Danish men, with a mean age 19.8 yr (range, 18 –28 yr) who were examined at the draft board and, in addition, were examined at the Copenhagen City Heart Study Program between 1981–1983 (14) and again during 1992–1994 after 23.2 ⫾ 6.0 yr (⫾sd) of follow-up (15). The Ala242Ser and Arg517Cys variants of MKKS were genotyped in the total cohort of young men encompassing two groups of subjects; one obese group (n ⫽ 744) with juvenile-onset obesity and a BMI of 31 kg/m2 or more and one control group (n ⫽ 867) of the randomly selected half percentage of the young men with a BMI less than 31 kg/m2 at the draft board examination. The clinical characteristics of the two study groups are given in Table 1 (16). The Arg517Cys polymorphism was also genotyped in middle-aged subjects in the population-based Inter99 cohort involving 6164 Danish

First Published Online October 13, 2004 * K.L.A. and S.M.E. contributed equally to this study. Abbreviations: BBS, Bardet-Biedl syndrome; BMI, body mass index; CI, confidence interval; MKKS, McKusick-Kaufman syndrome; RFLP, restriction fragment length polymorphism; SSCP, single-strand conformational polymorphism. JCEM is published monthly by The Endocrine Society (http://www. endo-society.org), the foremost professional society serving the endocrine community.

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147 20 ⫾ 2 33.4 ⫾ 2.8 179 ⫾ 7 107 ⫾ 11 43 ⫾ 6 35.9 ⫾ 5.8 179 ⫾ 7 115 ⫾ 20 118 ⫾ 13 116 ⫾ 109 1.02 ⫾ 0.07 107.0 ⫾ 20.2 20.0 ⫾ 5.8 126.1 ⫾ 57.6 0.40 ⫾ 0.88 147 11.4

586 20 ⫾ 2 33.2 ⫾ 2.2 177 ⫾ 6 104 ⫾ 10 43 ⫾ 6 35.7 ⫾ 5.7 178 ⫾ 6 113 ⫾ 19 117 ⫾ 14 115 ⫾ 11 1.02 ⫾ 0.09 108.4 ⫾ 25.0 20.7 ⫾ 6.3 126.1 ⫾ 66.7 0.39 ⫾ 0.83 586

Heterozygous

42 ⫾ 6 35.1 ⫾ 3.4 181 ⫾ 6 114 ⫾ 10 117 ⫾ 98 115 ⫾ 71 1.01 ⫾ 0.06 104.5 ⫾ 21.4 18.6 ⫾ 6.1 126.1 ⫾ 64.9 0.18 ⫾ 0.06 11

11 21 ⫾ 3 34.1 ⫾ 3.1 180 ⫾ 7 110 ⫾ 8

Homozygous

Obese subjects (n ⫽ 744)

0.048e

0.64 0.85 0.052 0.45 0.91 0.58 0.67 0.30 0.90 0.75 0.61

0.16 0.30 0.36 0.76

P

0.66b

0.66a

48 ⫾ 9 26.2 ⫾ 3.6 178 ⫾ 7 83 ⫾ 12 94 ⫾ 10 101 ⫾ 7 0.93 ⫾ 0.07 111.2 ⫾ 23.2 25.4 ⫾ 7.4 106.3 ⫾ 27.0 0.56 ⫾ 0.38 715

715 20 ⫾ 2 21.7 ⫾ 2.3 177 ⫾ 6 68 ⫾ 8

Wild type

47 ⫾ 8 25.7 ⫾ 3.5 176 ⫾ 7 80 ⫾ 12 93 ⫾ 10 99 ⫾ 8 0.94 ⫾ 0.07 109.2 ⫾ 21.3 26.8 ⫾ 8.3 104.5 ⫾ 27.0 0.51 ⫾ 0.37 143 9.3

143 20 ⫾ 2 21.5 ⫾ 2.3 176 ⫾ 7 66 ⫾ 8

Heterozygous

50 ⫾ 9 24.3 ⫾ 2.1 178 ⫾ 6 77 ⫾ 7 91 ⫾ 6 97 ⫾ 5 0.93 ⫾ 0.06 115.3 ⫾ 22.5 24.9 ⫾ 6.8 102.7 ⫾ 18.0 0.45 ⫾ 0.24 9

9 21 ⫾ 2 20.8 ⫾ 2.1 177 ⫾ 6 65 ⫾ 6

Homozygous

Control subjects (n ⫽ 867)

0.53 0.10 0.20 0.31 0.20 0.039 0.75 0.131 0.90 0.23 0.22

0.02 0.37 0.39 0.65

0.69b

0.35a

P

J Clin Endocrinol Metab, January 2005, 90(1):225–230

Data from two examination dates: at the draft board examination and at the latest examination. Values for quantitative variables are the mean ⫾ SD. P values were obtained by regression analysis within each of the control and obese groups, respectively, using genotype as the dependent factor, and BMI and age as covariates. a P value of BMI when corrected for waist circumference. b P value of waist circumference when corrected for BMI. c To convert to Systeme International units (millimoles per liter), multiply by 0.05551. d Average follow-up time for weight change is 23.2 yr. e P values were determined by ␹2 test of allele distribution between obese and control groups.

Measured at draft board examination N Age (yr) BMI (kg/m2) Height (cm) Weight (kg) Measured at last examination Age (yr) BMI (kg/m2) Height (cm) Weight (kg) Waist circumference (cm) Hip circumference (cm) Waist/hip ratio Serum total cholesterol (mg/dl)c Serum high-density cholesterol (mg/dl)c Plasma glucose (mg/dl)c Average weight gain/yr (kg)d Genotype distribution of the haplotypes Allele prevalence (%)

Wild type

TABLE 1. Clinical and biochemical characteristics of study participants stratified according to genotypes Arg517Cys of MKKS within the respective groups of 744 men with juvenile-onset obesity and 867 control men

226 Andersen et al. • Genetic Variation of MKKS in Obesity

In the initial study, a ␹2 test was applied to test for significance of differences in allele frequencies. All tests were two-sided, and P ⬍ 0.05 was considered significant. Regression analysis for the codon 517 MKKS variant was performed with SPSS 11.1 software (SPSS, Inc., Chicago, IL), using age and BMI as cofactors in the analysis. In the population-based study of middle-aged subjects, P values were calculated using Fisher’s exact test, and P ⬍ 0.05 was considered significant.

0.74a 0.44b 1317 (78.9) 325 (19.4) 28 (1.7) 11.4 (10.3–12.5) 0.11a 0.048b

425 (81.2) 95 (18.2) 3 (0.6) 9.7 (7.9 –11.4)

48 ⫾ 10 51 ⫾ 9

815 (77.5) 216 (20.6) 20 (1.9) 12.2 (10.8 –13.6)

0.048a 0.037b

51 ⫾ 10

436 (80.4) 98 (18.1) 8 (1.5) 10.5 (8.7–12.3)

47 ⫾ 10

P Lean subjects (n ⫽ 1670) Women Obese subjects (n ⫽ 542) P Lean subjects (n ⫽ 1051) Men Obese subjects (n ⫽ 523)

47 ⫾ 8

2132 (78.3) 541 (19.9) 48 (1.8) 11.7 (10.9 –12.6) 861 (80.9) 193 (18.1) 11 (1.0) 10.1 (8.8 –11.4)

P

Data are the number of subjects with each genotype (the percentage of each group is given in parentheses). P values were calculated using Fisher’s exact test. The percent minor allele frequency (MAF) is shown (95% CI is in parentheses). The P values compare allele frequencies (a) and genotype distributions (b) between obese and lean subjects. All genotype groups obeyed Hardy-Weinberg equilibrium.

Statistics

51 ⫾ 10

In subjects with juvenile-onset obesity and in matched lean control subjects, the Ala242Ser and Arg517Cys variants were genotyped by PCRRFLP, Ala242Ser was genotyped by primers MKKS3 forward and reverse and digested with Bsl1 and MaeIII (New England Biolabs, Inc., Beverly, MA), and Arg517Cys was genotyped by primers MKKS9 forward and reverse and digested with Nsp1 (New England Biolabs, Inc.). All PCRRFLP studies included a control site for the restriction enzyme as a control for false negative assays. The restriction enzyme digests were separated on 3.5% agarose gels and stained with ethidium bromide. In the group of middle-aged subjects, the Arg517Cys polymorphism was genotyped by a chip-based, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (DNA MassARRAY; Sequonome, San Diego, CA) of PCR-generated primer extension products as previously described (19). The genotyping success rate was 94%, and among 89 replicate samples there were no mismatches.

Age (yr) Arg517Cys genotype Arg/Arg Arg/Cys Cys/Cys MAF (%)

PCR-restriction fragment length polymorphism (PCR-RFLP)

Lean subjects (n ⫽ 2721)

Genomic DNA was isolated from human leukocytes using standard methods. PCR amplification was carried out in a reaction volume of 25 ␮l containing 100 ng genomic DNA, 1⫻ PCR buffer, 3603 mg/dl (200 mmol/liter) of each primer, 3.60 mg/dl (0.2 mmol/liter) dNTP, 15 mm MgCl2, and 0.35 U AmpliTaq DNA polymerase (PerkinElmer, Foster City, CA). The cycle program was an initial denaturation at 95 C for 5 min, followed by 35 cycles of denaturation at 95 C for 30 sec, annealing at 55 C for 30 sec, and elongation at 72 C for 30 sec, with a final elongation step at 72 C for 10 min, using a GeneAmp PCR System 9700 (PerkinElmer). Primers were selected from the published GenBank sequence of the MKKS gene (accession no. gi:27501067) to cover the coding region of the gene. Primers and PCR conditions are available from the authors upon request. The SSCP and heteroduplex analyses were performed at two different experimental settings as described previously (18), and aberrantly migrating samples were sequenced (MWG-Biotech AG, Ebersberg, Germany).

All

Mutation analysis of the coding region of MKKS

Obese subjects (n ⫽ 1065)

white individuals who participated in a randomized nonpharmacological intervention study for the prevention of cardiovascular disease undertaken at the Research Center for Prevention and Health (Glostrup, Copenhagen) (17). From this cohort we recruited subjects with a BMI greater than 30 kg/m2, constituting the obese group (n ⫽ 1065; according to World Health Organization criteria), and subjects with a BMI of 25 kg/m2 or less, constituting the lean group (n ⫽ 2721). More details are given in Table 2. Furthermore, in a separate study all available members (n ⫽ 378) from 62 obese families recruited from the Danish Family Resource Bank at University of Copenhagen, Denmark (16 families), or from the outpatient clinic at Steno Diabetes Center (Gentofte, Denmark; 46 families) were screened for the Ala242Ser variant of MKKS. Probands from the 62 families had a mean ⫾ sd age of 53 ⫾ 14 yr, a BMI of 39.4 ⫾ 3.3 kg/m2, and a waist/hip ratio of 0.94 ⫾ 0.10. All study participants were Danish Caucasians by self-report. All studies were approved by the ethical committee of Copenhagen and were conducted in accordance with Helsinki Declaration II. Height was measured without shoes, to the nearest half-centimeter, and body weight was measured to the nearest decimal in kilograms in light indoor clothing without shoes. BMI was calculated as the weight (kilograms) per height (meters) squared. Waist and hip circumferences were measured in the standing position to the nearest half-centimeter. Biochemical values were measured in the nonfasting state.


TABLE 2. Genotype distribution and allele frequencies of the Arg517Cys variant of MKKS in the Inter99 study population of middle-aged subjects

Andersen et al. • Genetic Variation of MKKS in Obesity

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228



FIG. 1. Location of the identified variants in the MKKS protein. The three variants in bold are in complete linkage disequilibrium.

In silico data analysis Protein and nucleotide sequence alignments among species were performed using ClustalW version 1.8 (http://clustalw.genome.jp/) and were confirmed using Ensembl (www.ensembl.org). Accession numbers for studies of MKKS nucleotide homology were: human, NM_018848; mouse, NM_021527; rat, XM_230628; and chicken, XM_415033. Primers for PCR were designed using Primer3 (www-genome.wi.mit. edu/cgi-bin/ primer /primer3_www.cgi).

Results Mutation analysis

SSCP and heteroduplex analyses and subsequent sequencing of the coding region of MKKS identified two synonymous variants (Pro39Pro and Ile178Ile) and three nonsynonymous variants (Ala242Ser, Arg517Cys, and Gly532Val, respectively). The Arg517Cys variant was found in 16 of the 60 obese subjects. Ala242Ser and Gly532Val were rare variants identified in only two and one of the 60 obese subjects, respectively. Pro39Pro, Ile178Ile, and Arg517Cys were in complete linkage disequilibrium in the cohort examined. The synonymous variants (Pro39 and Ile178 alleles) and two of the nonsynonymous variants (Arg517 and Gly532 alleles) are all conserved among three different species (human, chicken, and mice). The A242 allele is conserved among human, mouse, and chicken. Figure 1 depicts the localization of variants in the MKKS protein. Screening of obese families

All available members from 62 obese families were screened for the previously identified Ala242Ser variant, because this variant has been reported as a potential BBS susceptibility factor (20). Two obese probands (F85-51 and F1159-5) representing pedigrees carrying the codon 242 variant were identified. Family F85 (Fig. 2A) consists of six sib-

FIG. 2. Pedigrees of families carrying the Ala242Ser variant of MKKS. A, Family F-85. F85-51 is the family member carrying the variant in the heterozygous form. f, Obese (BMI, ⬎30.0 kg/ m2); , overweight (BMI, 27.0 –30.0 kg/ m2); 䡺, normal weight. B, Family F-1159. The parents, F1159-2 and F1159-1, are carrying the variant in the heterozygous form. F1159-5 is the family member carrying the variant in the homozygous form. f, Obese (BMI, ⬎30.0 kg/m2); , overweight (BMI, ⬎27.0 kg/m2); 䡺, normal weight. Square, Man; circle, woman.

;

;

lings, aged 55– 68 yr at the time of examination. No data were available for the parents. Screening of the pedigree revealed that only the obese proband (F85-51; BMI, 40.2 kg/m2) was a carrier of one 242Ser allele, whereas the remaining siblings carried the wild-type genotype. Family F1159 (Fig. 2B) consists of parents and two siblings, the latter aged 24 –27 yr at the time of examination. Only limited data for this family were available. The parents were both obese (F1159-2: BMI, 40.8 kg/m2; F1159-1: BMI, 39.3 kg/m2) and were heterozygous carriers of the 242Ser variant. The overweight sibling (F1159-5: BMI, 29.2 kg/m2) was a homozygous carrier (Ser242Ser) of the variant, whereas the normal weight sibling was wild type at this locus. Association studies

A case-control study of the impact of the Arg517Cys variant (Taq single nucleotide polymorphism for the Pro39Pro, Ile178Ile, and Arg517Cys haplotypes) and the risk of juvenileonset obesity in 744 obese and 867 control subjects showed an allele prevalence of 11.9% [95% confidence interval (CI), 9.7–13.0] among obese subjects and 9.5% (CI, 7.9 –10.7) among control subjects (P ⫽ 0.048; Table 1). In genotypequantitative trait analyses, there were no significant relationships in either obese or lean men between codon 517 genotypes and measured anthropometric or biochemical values (Table 1). The case-control study of the impact of the same haplotype on the risk of obesity in middle-aged men in the Inter99 cohort showed allele prevalences of 9.7% (CI, 7.9 –11.4) among 523 obese men and 12.2% (CI, 10.8 –13.6) among 1051 lean men (P ⫽ 0.037; Table 2). Similar studies were performed in 542 middle-aged obese women who showed allele prevalence of 10.5% (CI, 8.7–12.3) compared with 11.4% (CI, 10.3–


12.5) among 1670 lean women (P ⫽ 0.044; Table 2). To test whether the codon 517 polymorphism was associated with estimates of central adiposity or peripheral adiposity in the middle-aged subjects of the Inter99 cohort, we performed quantitative trait studies between the genotype and waist circumference adjusted for BMI and BMI adjusted for waist circumference, respectively. However, no significant relationships between genotypes and adiposity estimates could be found (data not shown). Also, we were unable to demonstrate any convincing association between the codon 517 variant and obesity in women (Table 2). All variants were in Hardy-Weinberg equilibrium. Discussion

Several syndromic forms of obesity have been reported, including the obese phenotype of the BBS (21). The syndrome may encompass at least eight disease-causing genetic loci with various etiologies (7). The disease-causing genetic locus of BBS causing both this syndrome and the MKKS is due to mutations in MKKS (9, 10, 12). The encoded protein has sequence similarity to the group II chaperonin family of proteins and is therefore assumed to be involved in the folding and structural modification of numerous proteins (12). The discovery of MKKS as a gene underlying BBS led to our hypothesis that less severe variation of MKKS might also be involved in the pathogenesis of subsets of common and probably polygenic forms of obesity. In this study we report the finding of a conserved amino acid polymorphism at codon 517 of MKKS, which in a casecontrol study shows a borderline significant association (P ⫽ 0.048) with juvenile-onset obesity among Danish white men. In an attempt to extend these findings to obesity among middle-aged men in a population-based sample, we failed, however, to replicate an association between the variant and obesity. In fact, among middle-aged men, the codon 517 MKKS variant was more prevalent among lean than among obese men. We have no obvious explanation for this discrepancy, except that there potentially could be differences in etiology between juvenile-onset obesity and obesity among middle-aged men for whom we have no information about the time of obesity onset. Given that there potentially might be differences in etiology between juvenile-onset obesity (often a more peripheral form of obesity) and obesity among middle-aged men (often a central form of obesity) it was hypothesized that the 517 polymorphism could be associated with peripheral obesity. However, this idea was not supported in studies of the middleaged subjects. In studies of the BBS, the codon 242 variant of MKKS has been implicated as a putative disease-contributing variant in combination with variants in other BBS genes and as part of a triallelic inheritance of the disease (8, 21). Because the codon 242 variant is rare, we tested our available obese family resources for carriers of this variant. We identified two families carrying the 242Ser variant. In the first mentioned family (F85), the only heterozygous carrier of the codon 242 mutation among five siblings is also the only obese subject in the family accessible. In the other family (F1159), the two heterozygous parents are obese, whereas a young, physically


229

active (self-reported questionnaire) offspring who is homozygous for the variant has a phenotype of overweight. Although these pedigrees are small, our preliminary findings might suggest a role for the codon 242 variant of MKKS in increasing susceptibility to obesity, possibly in an agedependent manner and in combination with other obesitypredisposing gene variants. In conclusion, it is unlikely that MKKS mutations play a major role in the pathogenesis of nonsyndromic obesity although in rare cases the A242S allele may influence disease manifestation. However, more studies are needed to elucidate whether the rare Ala242Ser variant may contribute to the pathogenesis of subsets of obesity. Acknowledgments We thank Annemette Forman, Lene Aabo, Helle Fjordvang, and Christina B. P. Hansen for technical assistance, and Grete Lademann for secretarial support. Received March 9, 2004. Accepted September 28, 2004. Address all correspondence and requests for reprints to: Dr. Oluf Pedersen, Steno Diabetes Center, DK-2820 Gentofte, Denmark. E-mail: [email protected]. This study is part of the NUGENOB Project (Nutrient-Gene Interactions in Human Obesity) and was supported by the University of Copenhagen, the Danish Heart Foundation, and European Union Grants QLRT-199-00546 and QLKT-CT-2000-00618, and Danish Medical Research Council Grant 09902592. The NUGENOB Project and its partners are described on the project website; see www.nugenob.com for additional information. The Danish Epidemiology Science Center is supported by the Danish National Research Foundation.

References 1. World Health Organization 1998 Obesity. Preventing and managing the global epidemic: report of a WHO consultation. Geneva: World Health Organization; WHO Tech Rep Ser 894 2. Stunkard AJ, Sørensen TIA, Hanis C, Teasdale TW, Chakraborty R, Schull WJ, Schulsinger F 1986 An adoption study of human obesity. N Engl J Med 314:193–198 3. Sørensen TI, Price RA, Stunkard AJ, Shulsinger F 1989 Genetics of obesity in adult adoptees and their biological siblings. BMJ 298:87–90 4. Stunkard AJ, Harris JR, Pedersen NL, McClearn GE 1990 The body-mass index of twins who have been reared apart. N Engl J Med 322:1483–1487 5. Maes HH, Neale MC, Eaves LJ 1997 Genetic and environmental factors in relative body weight and human adiposity. Behav Genet 27:325–351 6. Carey DG, Nguyen TV, Campbell LV, Chisholm DJ, Kelly P 1996 Genetic influences on central abdominal fat: a twin study. Int J Obes 20:722–726 7. Sheffield VC, Nishimura D, Stone EM 2001 The molecular genetics of BardetBiedl syndrome. Curr Opin Genet Dev 11:317–321 8. Katsanis N, Ansley SJ, Badano JL, Eichers ER, Lewis RA, Hoskins BE, Scambler PJ, Davidson WS, Beales PL, Lupski JR 2001 Triallelic inheritance in Bardet-Biedl syndrome, a Mendelian recessive disorder. Science 293:2256 – 2259 9. Katsanis N, Beales PL, Woods MO, Lewis RA, Green JS, Parfrey PS, Ansley SJ, Davidson WS, Lupski JR 2000 Mutations in MKKS cause obesity, retinal dystrophy and renal malformations associated with Bardet-Biedl syndrome. Nat Genet 26:67–70 10. Slavotinek AM, Stone EM, Mykytyn K, Heckenlively JR, Green JS, Heon E, Musarella MA, Parfrey PS, Sheffield VC, Biesecker LG 2000 Mutations in MKKS cause Bardet-Biedl syndrome. Nat Genet 26:15–16 11. Ansley SJ, Badano JL, Blacque OE, Hill J, Hoskins BE, Leitch CC, Kim JC, Ross AJ, Eichers ER, Teslovich TM, Mah AK, Johnsen RC, Cavender JC, Lewis RA, Leroux MR, Beales PL, Katsanis N 2003 Basal body dysfunction is a likely cause of pleiotropic Bardet-Biedl syndrome. Nature 425:628 – 633 12. Stone DL, Slavotinek A, Bouffard GG, Banerjee-Basu S, Baxevanis AD, Barr M, Biesecker LG 2000 Mutation of a gene encoding a putative chaperonin causes McKusick-Kaufman syndrome. Nat Genet 25:79 – 82 13. Croft JB, Morrell D, Chase CL, Swift M 1995 Obesity in heterozygous carriers of the gene for the Bardet-Biedl syndrome. Am J Med Genet 55:12–15 14. Sonne-Holm S, Sørensen TI, Jensen G, Schnohr P 1990 Long-term changes of body weight in adult obese and non-obese men. Int J Obes 14:319 –326 15. Sonne-Holm S, Sørensen TI, Jensen G, Schnohr P 1989 Independent effects

230

16. 17.

18. 19.


of weight change and attained body weight on prevalence of arterial hypertension in obese and non-obese men. BMJ 299:767–770 Schnohr P, Jensen G, Lange P, Scharling H, Appleyard M 2001 The Copenhagen City heart study: introduction. Eur Heart J 3:H1–H83 Jorgensen T, Borch-Johnsen K, Thomsen TF, Ibsen H, Glu¨mer C, Pisinger C 2003 A randomized non-pharmacological intervention study for prevention of ischaemic heart disease: baseline results Inter99 (1). Eur J Cardiovasc Prev Rehabil 10:377–386 Echwald SM, Sørensen TIA, Andersen T, Tybjærg-Hansen A, Clausen JO, Borch-Johnsen K, Pedersen O 1999 Mutational analysis of the proopiomelanocortin gene in Caucasians with early onset obesity. Int J Obes 23:293–298 Buetow KH, Edmonson M, MacDonald R, Clifford R, Yip P, Kelley J, Little DP, Strausberg R, Koester H, Cantor CR, Braun A 2001 High-throughput


development and characterization of a genomewide collection of gene-based single nucleotide polymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Proc Natl Acad Sci USA 98:581–584 20. Beales PL, Katsanis N, Lewis RA, Ansley SJ, Elcioglu N, Raza J, Woods MO, Green JS, Parfrey PS, Davidson WS, Lupski JR 2001 Genetic and mutational analyses of a large multiethnic Bardet-Biedl cohort reveal a minor involvement of BBS6 and delineate the critical intervals of other loci. Am J Hum Genet 68:606 – 616 21. Katsanis N, Eichers ER, Ansley SJ, Lewis RA, Kayserili H, Hoskins BE, Scambler PJ, Beales PL, Lupski JR 2002 BBS4 is a minor contributor to Bardet-Biedl syndrome and may also participate in triallelic inheritance. Am J Hum Genet 71:22–29

JCEM is published monthly by The Endocrine Society (http://www.endo-society.org), the foremost professional society serving the endocrine community.