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* Clinical Research Group, Department of Child and Adolescent Psychiatry, Philipps-University of Marburg, Germany;
Genome Analysis, Institute of Molecular Biotechnology (IMB), Jena, Germany;
** Clinic and Department of Outpatients for Radiology and Nuclear Medicine, Campus, Benjamin Franklin, Charité University Medicine, Berlin, Germany;
Institute of Medical Biometry and Epidemiology, Philipps-University of Marburg, Germany;
Obesity Treatment Center Insula, Berchtesgaden, Germany;
Spessart Klinik, Bad Orb, Germany;
# Institute of Psychological Sciences, University of Leeds, Leeds, UK;
¶ The Rowett Research Institute, Bucksburn, Aberdeen, Scotland, UK;
|| Rheinische Kliniken Essen, Child and Adolescent Psychiatry, University of Duisburg-Essen, Essen, Germany
3To whom correspondence should be addressed. E-mail: Anke.Hinney{at}uni-duisburg-essen.de.
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ABSTRACT |
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 TOP ABSTRACT SUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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C, g.–244GA; missense: g.47CT: Ala16Val) and one infrequent missense variation (c.253AG: Asn85Asp), and in GALR1 2 novel SNPs (silent: c.150CT, missense: c.793AT: Ile265Phe). To test for an association with obesity, we genotyped 7 SNPs (GAL: g.–244GA, g.47CT, rs7101947, rs1042577, rs3136540; GALR1: c.150CT, c.793AT) in up to 322 obese children and adolescents compared with up to 277 healthy underweight and normal weight young adults. Furthermore, we analyzed these SNPs with respect to potential effects on the percentage of energy consumed as fat in obese children and adolescents. Allele and genotype frequencies did not differ among the groups tested. In addition, we performed a pedigree transmission disequilibrium test (PDT) for one SNP (GAL: g.–244GA) in 610 (518 independent) obesity-trios (obese child or adolescent and both of its parents). However, the PDT for SNP GAL g.–244GA revealed no transmission disequilibrium. We conclude that the analyzed SNPs in GAL and GALR1 do not play a major role in early onset obesity or dietary fat intake in the obese children and adolescents of our study groups.
KEY WORDS: • percentage fat intake • body weight • adolescents • association
There is a large body of evidence indicating that galanin (GAL)4 has a role in appetite and body weight regulation. Examples for involvement in centrally regulated mechanisms include the following: 1) GAL causes an increase in dietary fat intake (1); 2) there is an interplay between GAL and leptin in the hypothalamic control of feeding (2); and 3) GAL neurons project from the anterior parvocellular region of the paraventricular nucleus to the median eminence (3). The paraventricular nucleus, which is important in the control of food intake, is positively related to the natural preference for high-fat diets in rats. Thus it is conceivable that hypothalamic GAL signaling can mediate the development of obesity induced by overconsumption of fat. Peripherally, GAL reduces energy expenditure and sympathetic activation of brown adipose tissue (4), modulates intestinal motility (5), and affects food consumption (6).
Transgenic mice overexpressing GAL are obese and have increased abdominal fat pads and cholesterol levels compared with wild-type mice (7), or have feeding patterns and body weights indistinguishable from wild-type controls (8). However, Npy–/– and Gal–/– mice (double knockout) develop obesity and endocrine dysfunction, whereas both phenotypes are not present in single knockouts (9).
The mature human galanin peptide consists of 30 amino acids and is proteolytically processed from a precursor (preprogalanin) (10). The effect of GAL is mediated through G-protein–coupled receptors (GALR1, GALR2, GALR3) (11); however, the specific role of each receptor subtype in mediating the physiologic or pathologic effects of GAL remains to be elucidated (7). Nonetheless, the widespread expression of GALR1 in brain, spinal cord, gut, and pancreas suggests that GALR1 might be broadly implicated in neurotransmitter release with potential effects on feeding, emotion, memory, nociception, glucose homeostasis, and gut secretion/motility (12). In Galr1–/– mice, no effect on body weight was found; however, a role of Galr1 in feeding behavior and body weight regulation has not been excluded (13).
In humans, intake of high-fat diets can result in obesity (14,15). Heritability of fat mass, body weight (16), as well as food preferences (17) was demonstrated in twin studies, e.g., a higher correlation for the percentage of energy consumed as fat was observed in monozygotic compared with dizygotic twins (18). It was also suggested that high-fat (HF) and low-fat (LF) phenotypes can be used as a conceptual tool to investigate the relation between genetic and environmental (diet) factors in the control of body weight (19).
A genome-wide linkage scan (genome scan) is used to identify chromosomal regions that are linked to the phenotype under study. Combined with functional or fine mapping evidence, the information is integrated to determine candidate genes. We recently performed a genome scan for obesity, based on 89 families comprising 
2 obese siblings and both of their biological parents ("obesity families"; n = 369; criteria: one offspring BMI 95th and at least one sibling BMI 90th percentile), and a confirmatory sample of 76 "obesity families" with 2 obese siblings (n = 315; same criteria as above). In both samples, we observed a peak signal for the chromosomal region 11q11 in the vicinity of the GAL locus (20), which was mapped to human chromosome 11q13.3–13.5 (10).
The rationale of this study was to assess the following: 1) whether variations in GAL and GALR1 are involved in body weight regulation and the percentage of energy consumed as fat; and 2) whether GAL is the positional candidate gene underlying the observed peak on chromosome 11q11.
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SUBJECTS AND METHODS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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90th percentile, all healthy underweight young adults (students) had a BMI < 15th percentile, and all normal weight young adults (students) had a BMI between the 40th and 60th percentiles. Written informed consent was given by all participants and in case of minors, their parents. The study was approved by the Ethics Committee of the University of Marburg. Detailed methods and material including primer sequences are provided as online supplemental material.
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Genotyping.
Five GAL single nucleotide polymorphism (SNPs; g.–244GA, g.47CT, rs7101947, rs3136540, rs1042577) were genotyped by PCR-based restriction fragment length polymorphism analyses (PCR-RFLP). For GALR1, 2 SNPs (c.150CT, c.793AT) were genotyped by tetra-amplification refractory mutation system (ARMS)-PCR or ARMS-PCR. For validity of the genotypes, alleles were determined independently by at least 2 experienced individuals. Discrepancies were resolved unambiguously either by reaching consensus or by retyping.
Genotype analysis was performed in study group 4 for GALR1 and in study group 1 for GAL. Of study group 1 (GAL), 49 (18 men) index patients of the obese individuals (mean age 13.7 ± 2.9 y, mean BMI 32.0 ± 5.6 kg/m2) were included in our original linkage study (20). These individuals had the highest "Identity By Descent" (IBD) sharing at the linkage region on chromosome 11q11 (marker D11S1313, Maximum Likelihood Binomial LOD Score = 1.65) (20). Because the linkage signal emerged largely from these individuals, we hypothesized that they would be enriched with relevant mutations in a candidate gene for obesity at the chromosome 11q11 locus.
SNP g.–244GA was resequenced for pedigree transmission disequilibrium test (PDT) analysis in 610 families (518 independent), presented as study group 2 (independent of study group 1). For resequencing, a genomic fragment of 2139 bp (encompassing g.–244GA) was generated and used as template for a 2nd PCR. Sequencing reactions were electrophoresed on ABI 3700 automated sequencers. Trace files were inspected visually in gap.4 (23). Resequencing by pyrosequencing was performed with the PSQ 96 SNP Reagent Kit (Pyrosequencing) according to the manufacturer on a PSQ96MA machine.
In study group 3, a subgroup of the obese individuals in study group 1, we genotyped both GAL and GALR1 SNPs in obese adolescents within LF (i.e., consuming 21–36% of total energy as fat) or HF (i.e., consuming 43–50% of total energy as fat) quartiles for the percentage of energy.
FFQ. The percentage of energy consumed as fat was assessed using the "Leeds Food Frequency Questionnaire" [Leeds FFQ, Leeds Food and Nutrition Survey (24)], which was adapted for German nutritional habits. Consistency of the adapted FFQ was evaluated using a short FFQ validated in Germany (25). Evidence for a substantial construct overlap of the questionnaires was indicated by Pearson’s correlation coefficient for the scale "fat intake" (r = 0.693, P < 0.001, 2-sided). Adolescents were asked to indicate intake frequency for every food item and to record whether the FFQ was filled in by themselves, with the help of their parents, or entirely by the parents. Eleven of 169 returned FFQs were disregarded because more than 5 food items were missing.
Statistics.
Between-group differences in genotype frequencies were investigated by 2-sided asymptotic or, in the case of reduced cell counts, exact Cochran-Armitage trend tests. Two-sided asymptotic Pearson’s 
2 or Fisher’s Exact Test was used to analyze between-group differences in allele frequencies. Note that the number of patients in different quartiles for the percentage of energy consumed as fat varied because quartile cutoff values were set to percentage values that were available in integers only.
The transmission disequilibrium test uses family trios composed of affected persons and both of their parents, comparing the total number of transmissions and nontransmissions of a specific allele over all heterozygous parents (26). If the allele in question is neither linked nor associated with disease risk (here, obesity risk), the expected ratio of allele transmissions compared with nontransmissions is 1. In addition, the PDT used in this study (for SNP g.–244GA in GAL) allows correction for dependencies due to multiple children within nuclear families (27).
Because homozygous 793-T carriers were not observed for the missense SNP (c.793AT) in GALR1 in the 2 groups with different fat intake, Fisher’s Exact Test was performed to investigate differences in allele and genotype frequencies. Linkage disequilibrium between these 2 GALR1 SNPs was investigated with the program EH, version 1.11 (28).
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RESULTS |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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C in the putative promoter, 2) g.–244GA in the untranslated first exon, located in a GC-box [CCCGCC] (29), 3) g.47CT in exon 2 leading to a conservative amino acid exchange (Ala16Val) and 4) c.253AG in exon 5 leading to a nonconservative amino acid exchange (Asn85Asp). Three known SNPs were confirmed: 1) rs7101947 (exon 1, 5'UTR), 2) rs1042577 (intron 5), and 3) rs3136540 (exon 6, 3'UTR). By resequencing 518 independent obesity trios (study group 2), 4 infrequent sequence variations were identified: g.–460CA, g.–363CT, g.–344CT, g.–22CT, which were not analyzed further.
Two novel (silent: g.–244GA; missense: g.47CT: Ala16Val) and 3 known SNPs (rs7101947, rs1042577, rs3136540) of GAL were genotyped by PCR-RFLP in up to 322 obese children and adolescents and up to 182 healthy underweight and 95 normal weight controls (study group 1). Genotype and allele frequencies of obese children and adolescents and controls did not differ for any of these SNPs (all P > 0.05; Table 2). Furthermore, genotype and allele frequencies did not differ for the analyzed SNPs in obese patients of the low and high quartile of the percentage of energy consumed as fat (study group 3; Table 2). Nonconservative missense variation Asn85Asp (c.253AG) was infrequent and therefore excluded from further analyses.
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A, which is in complete linkage disequilibrium (LD, D' = 1) with Ala16Val (g.47CT), a PDT in 610 trios (518 independent; study group 2) was performed because we observed a slightly increased frequency of the g.–244 A-allele in the obese sample (3.4%) compared with normal weight and underweight individuals (1.1%, nominal P = 0.10, Table 2). This trend was not substantiated in the family-based association study (PDT); the A-allele was not preferentially transmitted to obese index patients (nominal P = 0.7). In those individuals who substantially contributed to the peak on chromosome 11q11 (study group 1) in our genome scan (20), we did not detect increased frequencies of any of the analyzed alleles, nor was there an increased rate of homozygotes (data not shown). Hence, we found no evidence that GAL might be the positional candidate gene underlying the peak observed in the genome scan.
Galanin receptor 1.
Two novel SNPs, which were in linkage disequilibrium (nominal P < 0.05), were identified by SSCP in the coding region of GALR1: 1) silent c.150CT; Gly50 in exon 1 and 2) missense g.793AT; Ile265Phe in exon 3. The genotype and allele frequencies of the 2 SNPs did not differ in obese children and adolescents and underweight controls (study group 4; Table 3). Missense SNP Ile265Phe (g.793AT) was found in 3 of 45 individuals (6.67%) of the low quartile and 8 of 50 individuals (16.0%) of the high quartile for the percentage of energy consumed as fat (study group 3; Table 3); however, association tests (Fisher’s Exact Test) were not significant (P > 0.05).
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DISCUSSION |
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TOPABSTRACTSUBJECTS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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A, g.47CT: Ala16Val) and 3 known SNPs (rs7101947, rs1042577, rs3136540) of GAL with obesity. Subsequently, we analyzed these SNPs for association with the percentage of energy consumed as fat in obese individuals because certain patterns of eating behavior, such as fat preference, contribute to the development of obesity (14,15). None of the tests revealed a positive finding. Additionally, there is no evidence that GAL might be the positional candidate gene explaining the peak on chromosome 11q11 observed in our genome scan (20).
Furthermore, a PDT for g.–244GA in 610 obesity trios revealed no transmission disequilibrium. We chose this SNP for PDT analysis for the following reasons: 1) it might have a functional effect itself; 2) it is in complete LD with Ala16Val (g.47CT), which might also be functionally relevant; and 3) we observed a slightly increased frequency of the g.–244 A-allele in the obese sample compared with controls. In detail, 1) g.–244GA is located in a GC-Box in the untranslated first exon where the g.–244 A-allele might result in the loss of a SP1 binding site (29). However, the regulatory relevance of this variation must be analyzed in functional studies. 2) The conservative missense variation Ala16Val (g.47CT) is located in the hydrophobic signal peptide of preprogalanin. However, at amino acid position 16, there is Ala in rats and cows, Val in mice and Ser in pigs (10). Hence, this position is not conserved, deeming an effect of the missense variation rather unlikely.
Because we did not find an association (in either the case-control or family-based approach) with obesity, it seems unlikely that novel SNPs g.–244GA and Ala16Val (g.47CT) are relevant for body weight regulation in the obese children and adolescents of our study groups.
Galanin 1 receptor.
In the coding region of GALR1 2 novel SNPs were identified. Whereas g.150CT in exon 1 is silent, c.793AT in exon 3 causes the conservative missense variation Ile265Phe. Although it is presently unknown whether one of these SNPs might alter GALR1 function, we initially analyzed the SNPs for association in study groups of different body weight. The comparison of obese children and adolescents with underweight controls revealed no association for the 2 SNPs. Subsequently, we tested for association in obese patients whose reported fat intake was in the lowest and highest quartile for the percentage of energy consumed as fat. We found a slightly higher, although not significant occurrence (P = 0.2 for genotypes and P = 0.22 for alleles) of the less frequent allele of SNP Ile265Phe (c.793AT) in those obese patients in the highest quartile for the percentage of energy consumed as fat. Assuming that the allele frequencies of this polymorphism are in fact in the reported magnitude in our overweight groups for the highest and lowest quartile of the percentage of energy consumed as fat, a 2-sided test at a significance level of 5% with the present sample size has a power of 28%. To investigate this further, a total of 150 individuals per group would be necessary to perform a one-sided test at a significance level of 5% with 80% power.
Sensitivity of the FFQ.
Only very few studies have included dietary fat intake as a phenotype in a candidate gene study (30,31). Recently, a FFQ was used to measure the ratio of dietary polyunsaturated to saturated fatty acids (P:S ratio); an association of the P:S ratio with a PPAR
polymorphism was described (31). Hence, the FFQ might be considered a sensitive tool with which to measure dietary macronutrient composition. We have to emphasize that the definition of the upper and lower quartile for energy intake from fat is based solely on the results of the Leeds FFQ. In our study, the Leeds FFQs were completed by obese adolescents, partially with the help of or entirely by their parents. One has to keep in mind that estimating absolute values (kJ) for habitual fat consumption is difficult. Nevertheless, the Leeds FFQ can be reliably used to classify individuals on the basis of energy or nutrient intakes within a sample. We found a significant difference in BMI (2.4 kg/m2, P < 0.001) between the lowest and highest quartiles of the percentage of energy intake from fat. A positive relation between relative fat intake and body weight has been described in various studies (32,33), thus indirectly confirming our measurement of the percentage of energy consumed as fat.
In a recent study, we identified negative association of an infrequent variation in the MC4R gene with obesity (34) proving that a SNP-based approach for analyzing the association with complex phenotypes was successful. At the GAL and GALR1 loci, we identified a total of 10 novel sequence variations. However, we did not obtain evidence for an involvement of GAL or GALR1 in body weight regulation or the percentage of energy consumed as fat in our study groups. Also, we did not find evidence that GAL is the positional candidate gene underlying the peak on chromosome 11q11. Therefore, we conclude that the analyzed SNPs in GAL and GALR1 do not play a major role in early onset obesity or dietary fat intake.
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FOOTNOTES |
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2 Supported by the European Union (EU framework V, ‘Diet and obesity’ QLK1-CT-2000-00515) and the German Bundesministerium für Bildung und Forschung (BMBF; 01GS0118, 01KW0006, 01GS0482, 01GS0483, and 01GR0460).
4 Abbreviations used: ARMS, amplification refractory mutation system; dHPLC, denaturing HPLC; GAL, galanin; GALR 1, 2 or 3, galanin receptors 1, 2 or 3; HF, high-fat; IBD, identity by descent; LD, linkage disequilibrium; LF, low-fat; PDT, pedigree transmission disequilibrium test; RFLP, restriction fragment length polymorphism analyses; SNP, single nucleotide polymorphism; SSCP, single-strand conformation polymorphism.
Manuscript received 5 January 2005. Initial review completed 1 February 2005. Revision accepted 26 March 2005.
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