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The Journal of Clinical Endocrinology & Metabolism Vol. 85, No. 9 3183-3190
Copyright © 2000 by The Endocrine Society

Original Studies

Genome-Wide Scan of Obesity in Finnish Sibpairs Reveals Linkage to Chromosome Xq241

Miina Öhman, Laura Oksanen, Jaakko Kaprio, Markku Koskenvuo, Pertti Mustajoki, Aila Rissanen, Jorma Salmi, Kimmo Kontula and Leena Peltonen

Department of Human Molecular Genetics, National Public Health Institute (M.Ö., L.P.), FIN-00300 Helsinki; Departments of Medicine (L.O., K.K.), Medical Genetics (L.P.), and Public Health (J.K.), University of Helsinki, FIN-00290 Helsinki; Department of Public Health and General Practice, University of Oulu (J.K.), FIN-90014 Oulu; Department of Public Health, University of Turku (M.K.), FIN-20520 Turku; Peijas Hospital (P.M.), FIN-01400 Vantaa; The Obesity Research Center, Helsinki University Central Hospital (A.R.), FIN-00290 Helsinki; and Department of Internal Medicine, University Hospital of Tampere (J.S.), FIN-33520 Tampere, Finland

Address all correspondence and requests for reprints to: Leena Peltonen, M.D., Ph.D., Department of Human Genetics, Gonda Neuroscience and Genetics Research Center, University of California, Room 6506, 695 Charles E. Young Drive South, Box 708822, Los Angeles, California 90095-7088. E-mail: lpeltonen{at}mednet.ucla.edu


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Obesity is a multifactorial trait with evidence of a genetic component. Obesity is very common in all westernized countries, including Finland, where 10% of the adult population has a body mass index of 32 kg/m2 or more. Here we report results from a three-stage genome-wide scan of obesity in 188 affected subjects (body mass index, >=32 kg/m2) from 87 Finnish families. Initially, 374 markers with an average density of 10 centimorgans were genotyped. The strongest evidence for linkage to obesity was detected on chromosome Xq24, with the marker DXS6804 providing a maximum likelihood score (MLS) 3.14 in a model-free 2-point sibpair analysis. Fine-mapping in an extended sample set of 367 affected subjects from 166 families yielded a multipoint MLS of 3.48 over this X-chromosomal region. The Xq24 region contains a plausible candidate gene, serotonin 2C receptor, variants of which have been shown to predispose to obesity and type II diabetes in mice. Another chromosomal region also provided suggestive evidence of linkage, an area on 18q21, flanking the melanocortin-4 receptor, where a 2-point MLS of 2.42 with marker D18S1155 was obtained with a set of 367 affected subjects. In conclusion, our results in this Finnish study sample suggest that a locus on chromosome Xq24 influences the risk of obesity.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
OBESITY INCREASES the risk for hypertension, cardiovascular diseases, osteoarthritis, and noninsulindependent diabetes mellitus. It is well recognized by family, twin, and adoption studies that obesity has an important genetic component (1, 2, 3), yet the mode of inheritance of obesity is unclear and poorly understood.

Several major genes influencing obesity have been identified in mice (4, 5, 6, 7, 8). In humans, the results are somewhat controversial. Excluding some rare cases (9, 10, 11, 12, 13, 14), to date no obvious relationships have been found between particular genotypes of any loci and obesity. To date, five genome-wide screens for loci of obesity and related phenotypes have been published from four separate study samples from four different populations (15, 16, 17, 18, 19). Replication of findings in the genome-wide context has not been conclusive among these studies. This might be explained by simple random sample variability (20) and may also be influenced by differences in the definition of the phenotypes, inheritance model, environmental factors, and/or genetic backgrounds. In studies of Finnish mono- and dizygotic twin pairs, it has been estimated that genetic effects account for 72% and 68% of the total variance in body mass index (BMI) in men and women, respectively (21), thus indicating a substantial genetic component in BMI in Finnish population.

In small homogenous populations such as the Finns, the genetic variability may be reduced, and cultural (diet and exercise) habits are much more similar than in more heterogeneous populations (22). Due to the small number of founder populations, isolation, and recent expansion (23), the population of Finland has been a useful population for the identification of rare Mendelian disease genes (24). However, for the identification of common disease alleles, the number of founders might still be relatively high, resulting in multiple ancestral disease alleles and very small genomic regions of shared identical by descent (25). A very high density genome scan [~1-centimorgan (cM) marker interval] would be required, even if disease allele frequency was low and allelic diversity limited (25). However, genetically simplified isolates are likely to be more useful in mapping studies of complex diseases than diverse genetically heterogeneous populations under most assumptions. To support this statement, several examples of loci predisposing to complex diseases such as multiple sclerosis (26), hypertension (27), osteoarthritis (28), and familial combined hyperlipidemia (29) have been identified in Finnish study samples. Here, we report results from a three-stage genome-wide screen (Fig. 1Go) of obese siblings collected from Finland.



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  		Figure 1. A flow sheet summarizing the three stages of the genome scan and the following approach to analyze positional candidate genes by association and sequencing analyses.

 

   Subjects and Methods
Top
 Abstract
 Introduction
 Subjects and Methods
Results
 Discussion
 References
 
Study subjects

Genome-scan study sample. In Finland, 10% of the population, aged 25–64 yr, has BMI of 32 kg/m2 or more, and less than 1% of the population has BMI of 40 kg/m2 or more (30). For our study, a total of 188 individuals (100 sibpairs) with obesity (BMI, >=32 kg/m2) from 87 families were ascertained through the weight reduction program of the Helsinki University Central Hospital (53 families) and the Finnish Twin Cohort (34 families). In the weight reduction group, all of the probands were morbidly obese (BMI, >=40 kg/m2), and their recruited sibling(s) had BMI of 32 kg/m2 or more. From the Finnish Twin Cohort, all of the ascertained dizygotic twin pairs and their recruited sibling(s) had BMI of 32 kg/m2 or more. The zygosity of twins was determined primarily by a deterministic questionnaire method (31) and secondly by genotyping polymorphic markers. All of the study subjects were aged 18–64 yr, and their parents’ DNA samples were collected if available. In 10 of the 87 families there were 3 obese siblings in a sibship, and in 2 families there were 4 obese siblings. Both parents were available for phase determination in 14 families (16%), 1 parent was available in 22 families (25%), and additional siblings were ascertained in 11 families (13%), leaving 45 sibpairs with no additional phase information. Data collection was described in detail in our previous study (32). The weight and height of study subjects were measured, and only those individuals that fulfilled the required BMI criteria were chosen to the study. The study protocol was approved by the ethical review committee of the Department of Medicine, University of Helsinki. The characteristics of the study material are given in Table 1Go.


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  		Table 1. The characteristics of the two study groups, the primary and the replication sample sets

 
Replication study sample. One hundred and seventy-one additional affected individuals (93 sibpairs) from 79 Finnish families were collected through 3 new weight reduction groups at Helsinki University Central Hospital, Tampere University Hospital, and Peijas Hospital in Vantaa. All of the selected probands as well as their recruited siblings had BMI of 30 kg/m2 or more. In 70 of these families, there were 2 affected siblings in a sibship, in 6 families there were 3 affected subjects, in 2 families there were 4 affected subjects, and in 1 family there were 5 affected siblings. A parent(s) was available in 3 of those families that had only 2 affected siblings. A detailed questionnaire was mailed to all selected subjects, and they were asked to give a blood sample for DNA analysis at their local health center, where their heights and weights were recorded. A BMI of 30 kg/m2 or more could be ascertained for each of the replication study subjects and thus was used in the analysis. The characteristics of the study sample are given in Table 1Go.

Association study sample. Subjects used for determination of serotonin 2C receptor (5-HT2CR) allele frequencies consisted of 254 morbidly obese subjects (BMI, >=40 kg/m2) and 134 apparently healthy thin controls (BMI, <=25 kg/m2) from the same geographical area of Helsinki (33). None of the control subjects was diagnosed with any disease, nor did they have any medication as assessed by questionnaire. Their mean BMIs (±SE) were 42.9 ± 0.4 and 22.3 ± 0.2 kg/m2, respectively. All of the subjects were unrelated and of Finnish origin.

Samples for sequencing. The 18 male subjects chosen for the sequencing study were all included in the original sibpair material, and only 1 male/family was chosen. Nineteen thin (BMI <=25.0 kg/m2) male controls were selected through the Finnish Twin Cohort. They were matched for age (±5 yr) and county of birthplace to corresponding case.

Genotyping and sequencing

DNA was extracted from ethylenediamine tetraacetate-anticoagulated whole blood according to standard procedures. The PCR reactions were performed by means of an MJ Research, Inc. (Cambridge, MA) thermocycler in a reaction volume of 15 µl. The forward primer of each pair was labeled with one of three fluorescent dyes (FAM, HEX, or TET) to enable detection. PCR products were separated on an ABI 377XL automated DNA sequencer (Perkin-Elmer Corp., Foster City, CA) using denaturing 6% polyacrylamide gel, with analysis by PE Applied Biosystems Genescan 2.1 software (Perkin-Elmer Corp.). Analysis and assignment of the marker alleles were performed using Genotyper 2.0 (Perkin-Elmer Corp.) by two individuals independently.

In stage 1, we initially typed 188 affected individuals without parents using 374 microsatellite markers included in the Weber screening set version 6 (34), spaced, on the average, 10.0 cM apart and covering all 22 autosomes and the X-chromosome. The estimated average heterozygosity for the 374 markers was 0.76.

For saturation mapping in the stage 2, we first selected 16 screening set markers from chromosomes 1, 4, 5, 9, 10, 12, 16, 18, and X that revealed a maximum likelihood score (MLS) of more than 0.8 in 2-point analysis and genotyped all available parents with them to confirm the results and eliminate the negative influence of marker genotyping errors (35). Furthermore, we selected 6 areas with MLS more than 1.0 in 2-point analysis (on chromosomes 1, 4, 5, 12, 18, and X) and saturated these areas with 24 new microsatellite markers. On chromosome 18q, we used markers that we had previously selected for obesity candidate gene regions (32).

In stage 3, a replication study was carried out using 171 additional affected individuals in 79 families collected from 3 new weight-reducing groups. We focused on 2 chromosomes that gave the most significant results from the stage 2 analyses: 18q and Xq. With the replication material, we genotyped 5 markers that had yielded the best linkage results in these regions.

The potential candidate gene on Xq24 encoding the 5-HT2CR (36, 37) was examined more carefully by association analysis for a known polymorphism, a Cys23Ser amino acid variant (38, 39), and by sequencing. For assaying the 5-HT2CR polymorphism, PCR amplification was carried out using the 5' mismatch PCR primer 5'-TTGGCCTATTGG-TTTGGGAAT-3' and the 3' primer 5'-GTCTGGGAATTTGAAGCGTCCAC-3'. After initial denaturation for 5 min at 95 C, 30 PCR cycles (for 1 min each) at 95, 50, and 72 C were used. After PCR, aliquots (15 µl) of the samples were digested with the restriction enzyme HinfI (1 U/sample) overnight at 37 C, followed by electrophoresis on a 10% polyacrylamide gel, and visualization of the cleavage products by ethidium bromide staining.

The 5-HT2CR coding region spans from part of exon III to exon VI and is interrupted by three introns (40, 41). We amplified the coding region in five PCRs with the following sizes, primers, and annealing temperatures: 114 bp, primers 5'-AAAGGATGAT-ATGATGAACCT-3' and 5'-AGGAATGAATGCACCGCATTC-3', at 55 C; 314 bp, primers 5'-TGTGCACCTAAT-TGGCCTATT-3' and 5'-CATAAAGGATTGCCAGGAGAG-3', at 56 C; 201 bp, primers 5'-ATTATGTCTGGCCACTACCTA-3' and 5'-CTATAGAAATT-GCCCAAACAA-3', at 55 C; 582 bp, primers 5'-TCCATTAGGTGTATCAGTTCC-3' and 5'-GTTACAGGACTT-CTCACAAAG-3', at 56 C; and 459 bp, primers 5'-TTCTTTGTGT-TTCTGATCATG-3' and 5'-TACCGTAGGAAAAGACTGTGC-3', at 56 C. The promoter region was amplified in two PCRs with the following sizes, primers and annealing temperatures: 364 bp, primers 5'-C'TGAAGGGAGTTTCAAAGC-3' and 5'-AGGAGCCAAGAGCAG-CCAA-3', at 59 C; and 405 bp, primers 5'-TTCCCCCAACTCTCTAGGCC-3' and 5'-TCGCGACGACTC-CGACGACA-3', at 58 C. The PCR products were sequenced by cycle sequencing using the BigDye Terminator Cycle Sequencing Ready Reaction Kit with AmpliTaq DNA Polymerase FS (Perkin-Elmer Corp., Foster City, CA) on a model 377 automated DNA sequencer (PE Applied Biosystems). To confirm the sequencing results of three subjects, we also used Thermo Sequenase II dye terminator cycle sequencing premix kit (Amersham Pharmacia Biotech, Arlington Heights, IL).

Statistical analysis

Linkage analysis. Genotyped markers were checked for incompatibilities using the PedCheck program (42). All of the obvious Mendelian errors were either resolved unambiguously or the offending families were discarded from linkage analysis for all markers. A sibpair-based analysis method, MAPMAKER/SIBS (43), was used to test for linkage using two-point and multipoint analyses. To use all independent pairs of siblings in multiplex families, we chose the option pairs used in our analyses. We also performed a pseudomarker linkage analysis, with the program SIBPAIR from the ANALYZE package (26, 44, 45). In sibships of more than two siblings, this algorithm does not break them into pairs, but, rather, analyzes them as sibships, which is generally more efficient. The statistic employed in the SIBPAIR program is computed as a lod score in which all parents are assumed to be informative for the disease, with all affected siblings inheriting the disease-predisposing allele from each parent. The recombination fraction parameter in the linkage analysis is a combination of the real disease marker recombination fraction and the percentage of the total number of meioses, which are actually informative for the disease. The use of this lod score statistic ensures that the distribution of the test statistic converges rapidly to a 50–50 mix of a {chi}2 distribution with 1 df, and a point mass at 0 (46). Allele frequencies were estimated from all individuals using DOWNFREQ (47). One percent penetrance for nongene carriers was allowed.

The replication material was analyzed separate from as well as together with the original study sample. The replication material of 171 individuals was stratified into 3 subgroups, which were analyzed individually: male-male pairs, female-female pairs, and nondiabetic pairs (the male-female pairs were included in this subgroup). This dissection was made to clarify the effect of sex on our linkage result and also to observe whether the diabetic status of patients would affect the results.

Association analysis. A {chi}2 test was used to compare the frequencies of the different genotypes of the 5-HT2CR gene in the association analysis (44). Values for BMI and maximal BMI were adjusted by linear regression on age before testing. Equality of BMI means by genotype in the lean control and obese subjects was tested by the nonparametric Kruskal-Wallis method due to some heterogeneity of variances of BMI. Computations were performed in SYSTAT software (SPSS, Inc., Chicago, IL). P < 0.05 was considered statistically significant.


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
In the genome-wide scan for the obesity defined as a BMI of 32 kg/m2 or more, the most significant two-point MLS was found on chromosome Xq, with the marker DXS8064 producing the value of 3.14. All of the two-point and multipoint ML scores obtained in the first stage of the scan, and two-point MLS of fine-mapping regions are available on our public web page (http://ktlwww.ktl.fi/molbio/wwwpub/index.htm). In stage 1, two-point analyses of the 374 scan markers revealed nine regions with marginal evidence for linkage (MLS, >0.8) on chromosomes 1q, 4q, 5p, 9p, 10q, 12q, 16q, 18q, and Xq (Table 2Go and Fig. 2Go). Generally, the multipoint MLSs tended to be lower than the values for two-point MLS, although whether this is the result of marker errors or the absence of a gene is impossible to distinguish (35, 47). The highest multipoint values were established on chromosomes 18q and Xq, where the MLS reached 2.16 (Fig. 3Go) and 2.10 (Fig. 4Go), respectively. In addition, multipoint MLS greater than 1.0 were found on chromosomes 1, 5, 10, 11, and 12 (data shown at our web page: http://ktlwww.ktl.fi/molbio/wwwpub/index.htm).


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  		Table 2. Single point, maximum likelihood scores (MLS) of markers revealing marginal evidence for linkage, MLS of markers after genotyping the parents, parametric LOD scores, and markers chosen for saturation mapping are indicated

 


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  		Figure 2. Single point MLSs of all chromosomes in the stage 1 of the genome scan. Presented on the y-axis are the MLS values and on the x-axis individual chromosomes.

 


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  		Figure 3. MLSs on chromosome 18 in the stage 1 of the scan. Presented on the y-axis are the MLS values and on the x-axis centimorgans from the p-ter of the chromosome.

 


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  		Figure 4. Multipoint MLSs on the X-chromosome in the stage 1 of the scan. Presented on the y-axis are the MLS values, and on the x-axis are centimorgans from the p-ter of the chromosome.

 
In stage 2, 16 screening set markers on those 9 positive chromosomal regions showing 2-point MLS greater than 0.8 were genotyped in all available parents to increase the phase information. This resulted in an increase in ML scores on chromosomes 1q, 4q, 12q, and 16q, whereas the ML scores decreased or did not change for markers on chromosomes 5p, 9p, 10q, and Xq (presented in Table 2Go). No major differences were detected in results obtained using parametric or nonparametric linkage analysis as expected (44), but in two-point linkage analysis all of the LOD scores were generally slightly reduced (Table 2Go). For the fine-mapping, we selected 6 regions showing MLS greater than 1.0 in 2-point analysis on chromosomes 1q, 4q, 5p, 12q, 18q, and Xq (Fig. 2Go). For these regions, we performed genotyping using 24 additional markers in our initial study material of 188 individuals (100 sibpairs). This provided a marker map with the average 2-cM density on these selected regions. The saturation mapping supported evidence for linkage only on chromosomes 18q and Xq (Table 3Go). On the other regions, all of the ML scores obtained were less than 1.0 when additional markers were added.


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  		Table 3. Single point, maximum likelihood scores obtained with the markers on chromosomes 18q21 and Xq24 providing the strongest evidence for linkage: data from three stages of the genome scan

 
For the third stage of the genome scan, we used a replication material of 171 obese (BMI, >=30 kg/m2) individuals (93 sibling pairs) from 79 families. Selecting the markers showing the best evidence for linkage, we genotyped 5 markers on chromosome 18q21 covering a region of 9 cM, and 5 markers on Xq24 covering a region of 12 cM. We analyzed genotypes of the replication sample set separately and also carried out pooled analyses with the original study material. Two-point and multipoint analyses of replication material were also completed in 3 subsets: male-male pairs (n = 15), female-female pairs (n = 21), and nondiabetic pairs (n = 66).

The replication material analyzed alone provided additional evidence for linkage with the Xq24 region markers: the two-point MLS of DXS8067 was increased to 2.5 from the primary material’s two-point MLS of 0.6. The two-point MLS for DXS1001 was 1.0 in both the replication and primary materials. The other three markers did not give significant results. The diabetic status of patients did not seem to significantly affect the results; when the diabetic sibpairs were discarded from analyses, the tendency of all MLS stayed the same as in the total replication material, but altogether values were lower.

In the pooled analysis of 367 affected individuals (193 sibpairs) from 166 families, 2-point ML scores further increased on the Xq24 region; the ML score of DXS8067 increased to 2.7, and that of DXS1001 increased to 2.2 (Table 3Go). The 2-point MLS of DXS6804 and DXS6799 stayed the same as in the original sample set, i.e. 3.0 and 1.1 respectively (Table 3Go). With the extended material, the multipoint MLS reached 3.5 over the Xq24 region (Fig. 5Go).



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  		Figure 5. Single point (represented as bands) and multipoint (represented as line) MLSs over the Xq24 region in the extended material in the stage 3 of the scan. Presented on the y-axis are the MLS values, and on the x-axis the analyzed fine-mapping markers, their heterozygosity, and their chromosomal location from the p-ter.

 
None of the 18q region markers showed significant evidence of linkage in the replication material. The highest two-point MLS was 0.9 with marker D18S487: practically all the power of this MLS came from the subgroup containing only female-female pairs (n = 21). However, the pooled analysis, including the original and replication subjects (193 sibpairs), strengthened the linkage to 18q21 region; the two-point MLS of D18S1155 increased from 1.8 to 2.4, and that of D18S64 increased from 1.6 to 2.3 (Table 3Go). The marker D18S487 provided a MLS of 1.8. The multipoint MLS values did not exceed 1.2 on this genomic region.

On the Xq24 region, we chose one of the most potential candidate genes, 5-HT2CR (6, 39, 48), to be examined more carefully by association analysis and DNA sequencing. A previously reported polymorphism of this gene, a Cys23Ser amino acid variant (38, 49), was examined to test for differences in allelic frequencies conditional on phenotype. This polymorphism was genotyped in an association material consisting of 254 morbidly obese subjects and 134 lean controls; their mean BMIs (±SE) were 42.9 ± 0.4 and 22.3 ± 0.2 kg/m2, respectively. As the gene is X-chromosomal and as women, on the average, tend to be more obese than men, the allelic frequencies were examined separately in the two sexes. The genotype and allelic frequencies did not differ between the study subjects and controls (P = 0.42 for females and P = 0.96 for males). When the BMIs were analyzed according to genotype, no significant correlations with genotypes of the polymorphism were seen (Table 4Go).


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  		Table 4. Body mass indexes in the morbidly obese subjects (n = 254) according to 5-HT2CR Cys23Ser genotype

 
We also screened 18 obese, unrelated male subjects included in our sibpair material and 19 lean male controls for sequence changes in the 5-HT2CR gene. We sequenced the coding region and also the known promoter region of 7.3 kb (41), but no DNA variants correlated with obesity were found. In exon 3, we detected one single nucleotide polymorphism (C->A) -42 bp upstream of the 5'-end of the coding region in one of the cases. Additionally, we detected the previously published (G->C) polymorphism in codon 23 (Cys23Ser) in another case. In the promoter region, we found two polymorphisms that were present in three cases and six controls; a C->T variation in position -757 and a G->C variation in position -690. In addition, we found two single nucleotide insertions in all cases and all controls; compared to the published sequence, there was 1 additional guanine (G) in position -815, and another G in the position -870 upstream of the 5'-end of exon 1. These variations most likely represent errors in the published sequence (41).


   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
In genome-wide searches completed in other populations, evidence of linkage to obesity phenotype has been reported for several genetic loci. These include loci on chromosomes 2p, 11q, 10p, and 20q (15, 16, 17, 18, 19). However, none of the earlier screens has reported a significant linkage to the X-chromosome or provided even suggestive evidence for linkage to 18q. Yet, in a recently published scan of French obese sibpairs (17), some evidence of linkage was reported to the same chromosomal region Xq24; for marker DXS1001 the multipoint MLS equaled 1.42. Additionally, there was suggestive evidence of linkage with DXS1226 on Xp with a multipoint MLS of 2.42. Our study does not replicate earlier significant findings on chromosome 2p, corresponding to the POMC gene region, or on chromosomes 10p, 11q, or 20q. However, it should be emphasized that the phenotype we tested was BMI of 32 kg/m2 or more, not, for instance, serum leptin level or fat mass, as in other studies (15, 50), and that our results do not have the potential to exclude any earlier findings of other obesity genome scans.

Nevertheless, there is a certain overlap in some chromosomal regions providing suggestive LOD scores in an earlier genome-scan by Lee et al. (18): on chromosome 1, our marker D1S518 (location 204 cM from p-ter) giving two-point MLS 1.4 corresponds to their D1S194 (206 cM) that gives a nominal P value of 0.0126 for percentage of fat. This region on 1q21–23 is homologous with pig and mouse obesity quantitative trait loci (51, 52). On chromosome 9, our D9S158 (158 cM) with two-point MLS 1.0 is near their D9S1863 (151 cM) with a P value of 0.185 for BMI. On chromosome 10, our D10S1223 (160 cM) and D10S169 (171 cM) with two-point MLS of 0.9 and 1.3, respectively, are in concordance with their D10S587 (170 cM) with a P value of 0.0113 to percent fat (18). To date, several studies have implicated the melanocortin-4 receptor in human obesity (13, 14, 53, 54). On the 18q region containing MC4-R, our results in the genome-wide scan support the previous positive findings on this chromosomal region and replicate our previously published data (32). This should stimulate further analyses of this and nearby genes in the complex phenotype of obesity.

As the principal finding of this study, our results suggest that a major locus affecting obesity phenotype in Finnish sibpairs would lie on chromosome Xq24. Sex differences exist between obesity phenotypes; for instance, abdominal obesity is more prevalent in males (55, 56), and it has been indicated in twin studies that genes contributing to the variation in BMI are not identical for men and women (57, 58). Thus, an X-chromosomal obesity gene would be consistent with sex-specific effects on BMI. The Xq24 chromosomal region harbors a number of relevant candidate genes, e.g. the serotonin receptor 2C, which has probably accumulated the widest evidence for being involved in body weight regulation. The adenine nucleotide translocator 2 catalyzes the exchange of ADP and ATP across the mitochondrial inner membrane, the NADH dehydrogenase ubiquinone-1{alpha} subcomplex is also involved in the mitochondrial respiratory chain, and the brain mitochondrial carrier protein-1 is a novel homologue of the mitochondrial carriers predominantly expressed in the central nervous system. Further, the long chain fatty acid coenzyme A ligase plays an essential role in lipid biosynthesis and fatty acid degradation.

Serotonin and serotonergic receptor mechanisms have been implicated in the control of eating behavior and body weight (39, 59). In animal models, 5-HT2C receptors play an important role in the regulation of food intake (60), and a recently published study (6) shows that mice with a mutated 5-HT2C receptor are hyperphagic and develop middle-age-onset obesity. Furthermore, as these mice age, they develop insulin resistance and impaired glucose tolerance. To clarify the possible role of this particular gene in Finnish obese subjects, we performed an association analysis with a previously published amino acid substitution (38, 49) and also sequenced the coding and promoter regions in several obese males from different families (41). The association study did not reveal significant differences in allele frequencies of this polymorphism between cases and controls. The results are in agreement with another study (61) that found no evidence for association of this Cys23Ser mutant allele with obesity. In the sequence analyses of 19 obese male subjects and 18 lean male controls, no trait-associated DNA variants were identified, but all of the nucleotide variants disclosed were also equally present in cases and controls. However, the 5-HT2C receptor gene and other genes on this X-chromosomal region should be targets for further studies in other populations.


   Acknowledgments
 
We thank Dr. Joseph Terwilliger for his statistical advice and valuable critical comments during the preparation of the manuscript. Dr. Markus Perola is thanked for his valuable advice, help, and support during the study. Mr. Tero Hiekkalinna and Mr. Teemu Perheentupa are thanked for their help with biocomputing. Mr. Kauko Heikkilä is thanked for database management. Ms. Elli Kempas, Ms. Jaana Hartiala, Ms. Mira Kyttälä, and Mr. Pekka Ellonen are thanked for their excellent technical assistance.


   Footnotes
 
1 This work was supported by the Finnish Heart Foundation, the Hjelt Foundation, the Academy of Finland, the Farmos Research Foundation, the Aarne Koskelo Foundation, the Paulo Foundation, the Duodecim Foundation, and the Sigrid Juselius Foundation. Back

Received February 29, 2000.

Revised May 18, 2000.

Accepted May 30, 2000.


   References
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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