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Journal of Clinical Endocrinology & Metabolism, doi:10.1210/jc.2006-2657
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The Journal of Clinical Endocrinology & Metabolism Vol. 92, No. 6 2201-2204
Copyright © 2007 by The Endocrine Society

BRIEF REPORT

Examining the Candidacy of Ghrelin as a Gene Responsible for Variation in Adult Stature in a United Kingdom Population with Type 2 Diabetes

Maria Gueorguiev1, Steven Wiltshire1, Edwin A. Garcia, Charles Mein, Cecile Lecoeur, Brigitte Kristen, Rebecca Allotey, Andrew T. Hattersley, Mark Walker, Stephen O’Rahilly, Philippe Froguel, Ashley B. Grossman, Mark I. McCarthy, Graham A. Hitman and Márta Korbonits

Department of Endocrinology (M.G., E.A.G., A.B.G., M.K.), Genome Centre (C.M., B.K.), William Harvey Research Institute and Centre of Diabetes and Metabolic Medicine, Institute of Cell and Molecular Sciences (R.A., G.A.H.), Barts and the London Queen Mary’s School of Medicine and Dentistry, University of London, London, E1 2AD, United Kingdom; Wellcome Trust Centre for Human Genetics (S.W., M.I.M.), University of Oxford, Oxford, OX3 7BN, United Kingdom; Centre National de la Recherche Scientifique 8900 (C.L., P.F.), Institute of Biology, Pasteur Institute, 59000 Lille, France; Institute of Clinical and Biomedical Research (A.T.H.), Peninsula Medical School, Exeter, EX2 4NT, United Kingdom; Department of Medicine (M.W.), School of Medicine, University of Newcastle, Newcastle-upon-Tyne, NE1 7RU, United Kingdom; Departments of Medicine and Clinical Biochemistry (S.O.), Addenbrooke’s Hospital, University of Cambridge, Cambridge, CB2 2QQ, United Kingdom; Imperial College Genome Centre and Genomic Medicine (P.F.), Hammersmith Hospital, Imperial College London, London, W12 0NN, United Kingdom; and Oxford Centre for Diabetes, Endocrinology and Metabolism (M.I.M.), Churchill Hospital, Oxford, OX3 7LJ, United Kingdom

Address all correspondence and requests for reprints to: Márta Korbonits, M.D., Ph.D., Reader in Endocrine Research, Department of Endocrinology, Room 114C, John Vane Science Centre, Barts and the London Medical School, Charterhouse Square, London EC1M 6BQ, United Kingdom. E-mail: m.korbonits{at}qmul.ac.uk.


   Abstract
Top
 Abstract
Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Context: Recently, a quantitative trait locus for stature was reported on chromosome 3p26 in patients with type 2 diabetes.

Objective: Given that ghrelin is a peptide involved in GH release and located on 3p26, we hypothesized that variation within its gene (GHRL) may be responsible for the quantitative trait locus on 3p26.

Design: The evidence for linkage around GHRL was refined with the genotyping of an additional four microsatellites (D3S4545, D3S1537, D3S1597, and D3S3611), giving a total of 27 markers, followed by multipoint variance components linkage analysis. Probands from the linkage families were typed for five common single nucleotide polymorphisms (SNPs) within GHRL and tested for association with adult stature using haplotype trend regression.

Results: The maximum multipoint evidence for linkage between adult stature and the 27 microsatellites yielded an LOD score of 2.58 (P = 0.0003) between D3S1297 and D3S1304. Five common (frequency of ≥5%) SNPs were typed in the probands [two promoter SNPs (rs27647 and rs26802), two exonic (rs696217 and rs4684677), and one intronic (rs35683)] capturing 80% of the total common variation in GHRL. No association was found between any SNP (or haplotypes thereof) and adult stature.

Conclusion: Common genetic variation within GHRL is not responsible for variation in adult stature in this population.


   Introduction
Top
 Abstract
 Introduction
Subjects and Methods
 Results
 Discussion
 References
 
ADULT STATURE IS a tractable, highly heritable, complex trait ideally suited to genetic dissection. In a comparative study of twin cohorts in eight countries, heritability estimates ranged from 0.87 to 0.93 in men and from 0.66 to 0.84 in women (1). Although heritability estimates do not of themselves allow inferences about the genetic architecture of height (that is, distinguishing polygenic from oligogenic models), many genome-wide linkage studies have identified a number of potential quantitative trait loci (QTLs) influencing adult stature (2, 3, 4, 5, 6, 7, 8, 9, 10). However, replication of signals between studies has been limited.

In a set of United Kingdom families originally ascertained for type 2 diabetes (T2D) (10), reanalysis of genome-wide microsatellite data provided strong support (LOD of 3.17; empirical genome-wide, P = 0.11) for a gene influencing stature mapping to chromosome 3p26 (5). One compelling positional candidate gene of several that lay within this region of linkage is GHRL, which encodes the GH-releasing peptide ghrelin. GHRL (OMIM, 605353; Entrez, NM_016362; Ensembl, ENSG00000157017) maps within the 1 LOD unit support interval of this linkage evidence, 3.5 Mb downstream from the reported maximum LOD score. Given the relevance of GH secretion in the determination of adult height, GHRL represents an attractive positional and biological candidate for variation in stature.

In the present study, we have taken a three-stage approach to assess the role of variation in GHRL in adult stature. First, we reassessed the evidence for linkage around GHRL by typing additional microsatellites in the United Kingdom families displaying the 3p linkage signal (5). Second, we selected common single nucleotide polymorphisms (SNPs) in GHRL for analysis from in-house resequencing, complemented by data from the International HapMap Consortium. Third, we examined these common SNPs in GHRL for association with adult stature in the probands from the set of United Kingdom families.


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

Linkage study. The present study included the 573 families previously analyzed for loci influencing T2D susceptibility within the Diabetes UK Warren 2 study (11) and subsequently for QTLs influencing stature (5). Briefly, families were ascertained on the basis that they included a full sibpair with T2D diagnosed between 35 and 70 yr: all sibships were of British/Irish descent. Measurements of stature, taken during clinical examination at ascertainment, were available for 1377 siblings (665 women, 712 men), 1214 of whom had diabetes. These were transformed to normality and adjusted for the effects of age, gender, and diabetic status, before linkage analysis, as described previously (5).

SNP discovery. Because ghrelin has effect on both appetite and GH, we originally studied 70 French tall obese children from a cohort of 97 Caucasian nuclear families with at least two overweight probands (body mass index of >95th percentile for their age) with early onset of obesity (before the age of 8 yr).

Association study. There were 561 probands (from a total of 573, derived from the linkage pedigrees) with valid phenotypic measurements available at time of ascertainment for analysis. Clinical characteristics of these probands are provided in Table 1Go. Written informed consent was gained from all of the participants, and the study was approved by the local ethics committees.


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  		TABLE 1. Clinical characteristics of the 561 United Kingdom probands examined in the association study

 
Genotyping

Microsatellite genotyping. Four additional microsatellite markers (D3S4545, D3S1537, D3S1597, and D3S3611) mapping close to GHRL, but not typed in the original Warren 2 study, were selected from the Database of Sequence Tagged Sites. These markers were amplified using standard PCR conditions with fluorescently labeled primers, pooled, and separated on an ABI Prism 3700 DNA Analyzer (Applied Biosystems, Foster City, CA). Semiautomated and manual allele scoring was performed by two independent operators, and discrepancies were resolved by a third operator. Positive (Centre d’Etude du Polymorphisme Humain) and negative controls were included in the genotyping as part of the quality control. We used MERLIN (12) to check for Mendelian inconsistencies and latent genotyping errors that could give rise to the possibility of double recombinants.

SNP discovery. Seven sets of PCR primers were designed (available on request) to allow sequencing of approximately 1000 bp of the GHRL promoter and all exons (together with >100 bp of flanking intronic DNA to each side). Bidirectional sequencing reactions were performed in the 70 French children using the BigDye Terminator version 3.1 Cycle Sequencing kit according to the protocols of the manufacturer and analyzed in the ABI Prism 3700 DNA Analyzer. We compared our in-house SNP discovery with data available from HapMap Phase II (www.hapmap.org) and determined the extent to which these SNPs captured the total common variation in GHRL using HAPLOVIEW version 3.32 (13) and TAGGER (14).

SNP genotyping. Five hundred sixty-one probands from the Warren 2 families examined in the linkage analysis were genotyped for the set of tagSNPs by Kbiosciences (Hoddesdon, UK), using Taqman assays. No inconsistencies were seen in the 10% of samples that were genotyped in duplicate. All data were examined for deviation from Hardy Weinberg equilibrium, and the linkage disequilibrium relationships between the SNPs genotyped in the probands were examined using GOLD (15).

Statistical analyses

Linkage analysis. We reexamined the evidence for linkage to stature in the 573 British families using a total of 27 microsatellites across chromosome 3: the 23 analyzed in the original study (5) together with the four extra markers chosen to enhance the inheritance information extracted around GHRL. We used multipoint variance components linkage analysis, implemented in MERLIN, together with the Rutgers marker map (16, 17). We simulated (using MERLIN) 1000 replicates of chromosome 3 to determine the empirical distribution of the error-checking scores generated by MERLIN in these data.

Statistical power. The power of our pedigree dataset to detect linkage has been demonstrated previously to be good [for example, 76% power to detect a QTL accounting for 20% of the heritability with an LOD of ≥1.18 (5)]. We estimated the power of the present association study by simulation. We simulated 561 two-sib pedigrees segregating a single additive QTL, with a range of frequencies (5, 30, and 50%) similar those seen in our data and a range of heritabilities (5, 15, and 30%). We specified a genotyping success rate (88%) and an overall trait heritability (89%) seen in our empirical data. A QTL responsible for at least 5% of the total trait variance could be detected by haplotype trend regression with at least 99% power at P ≤ 0.05 and at least 94% power at P ≤ 0.001, given an allele frequency of at least 5%.

Association analyses. The associations between height and each individual SNP, together with haplotypes of all five SNPs, were examined using haplotype trend regression (18).


   Results
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
Discussion
 References
 
Multipoint variance components linkage analysis of the 27 chromosome 3 microsatellites yielded an LOD score of 2.58 (asymptotic pointwise, P = 0.0003) between D3S1297 and D3S1304 at position 11.8cM (Haldane) on 3p26. This represented a reduction in the LOD score of 3.28 (P = 0.00005) obtained at the same position when the 23 microsatellites previously typed were reanalyzed using the Rutgers map. The error-checking function of MERLIN identified seven individual genotypes (of a total of ~37,000) that yielded error-checking scores more extreme than those expected by chance (at the 5% level) in our data; deleting these from the dataset yielded a maximum LOD score of 2.59 between D3S1297 and D3S1304. We can be confident, therefore, that the observed reduction in LOD score (from 3.28 to 2.58) is not a result of undetected genotype errors.

We identified five common SNPs from our resequencing efforts in the French cohort, all of which were subsequently found to be present in HapMap Phase II (build 21); no novel common SNPs were identified. [Additionally, we identified seven very rare (single copy) mutations.] Two of these common SNPs were located in the promoter (rs27647 and rs26802), two were exonic (rs696217, L72M and rs4684677, Q90L), and one was intronic (rs35683). All five were obligatory tags of themselves because of the low linkage disequilibrium (r2) between them and additionally captured four of the remaining six common HapMap Phase II SNPs with r2 > 0.8 (and mean maximum r2 = 0.972). The remaining two intronic HapMap Phase II SNPs could only be tagged at an r2 threshold of 0.3; there were no gains to be made with multimarker (i.e. haplotype-based) tags.

All five common SNPs were typed in the United Kingdom proband sample and examined for association with stature in the 561 probands for which there were valid measurements of adult stature; one SNP (rs696217) was marginally out of Hardy-Weinberg disequilibrium (exact P = 0.045) (Table 2Go). No significant associations with stature were seen for any SNP (all P > 0.281). Furthermore, there was no association between stature and haplotypes of all five SNPs (P = 0.752).


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  		TABLE 2. Genotype and allele frequencies for the five common SNPs examined in the United Kingdom probands

 

   Discussion
Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
References
 
Despite the large number of genome scans seeking QTLs for adult stature in a variety of populations and the detection of multiple chromosomal regions showing evidence for linkage, no genetic variants have yet been identified that both are associated with adult stature and explain the linkage evidence. In the present study, we examined in detail the candidacy of GHRL, which falls within the region of linkage to adult stature seen on 3p26 in a set of British pedigrees previously analyzed for linkage to stature and T2D (5, 11). Although the biological candidacy of GHRL (and its product ghrelin) is strong, there have been no published studies to date of any association between the variation in GHRL and variation in stature.

We first reexamined the evidence for linkage to stature in these pedigrees by typing additional microsatellites around GHRL. This increased the inheritance information extracted from the families from 40–45% in the original analysis to approximately 60%, providing better estimates of allele sharing. Nonetheless, the modest drop in LOD score seen in the present study (compared with that obtained in the original study) suggests nothing more than a slight reduction in the probability that the primary linkage signal represents a genuine genetic effect rather than stochastic variation (19).

We subsequently examined the relationship between common variation in GHRL and adult stature in the probands from our linkage pedigrees in a study highly powered to detect even modest additive gene effects. We found no statistically significant evidence for such an association. We conclude that the variation within GHRL is not responsible for variation in adult stature and, consequently, cannot account for the evidence for linkage to stature seen on chromosome 3p26 in our sample of British pedigrees. Our study examined the overwhelming majority (80%) of the common variation in GHRL; however, we cannot exclude any possible effects of the two unexamined common intronic SNPs or of any rarer genetic variants.

The linkage signal observed on chromosome 3p has not been widely replicated (2, 3, 4, 6, 7, 8, 9, 10). The possibility remains that this observation represents only stochastic variation in the allele-sharing statistic. This possibility notwithstanding, additional strong positional candidates within the 3p26 region that merit additional study include BHLHB2 (a basic helix-loop-helix domain), which encodes a transcription factor involved in the regulation of chondrocyte differentiation via the cAMP pathway (20). Given the frequency with which height phenotypes are recorded in many large-scale genetic samples, it is likely that the genome-wide association studies currently underway for a wide range of diseases (including T2D) will provide the opportunity for detailed analysis of the chromosome 3p26 region for stature-influencing variants in some tens of thousands of subjects in the near future.


   Acknowledgments
 
We are grateful to Diabetes UK for the sample collection and funding of the original genome scan.


   Footnotes
 
This work was supported by the Joint Research Board of Saint Bartholomew’s Hospital (to M.G.), Diabetes UK (to E.A.G.), a Medical Research Council Clinician Scientist Fellowship (to M.K.), and a Wellcome Trust Career Development Fellowship (to S.W.).

Disclosure Information: The authors have nothing to declare.

First Published Online March 27, 2007

1 M.G. and S.W. contributed equally to this work Back

Abbreviations: QTL, Quantitative trait locus; SNP, single nucleotide polymorphism; T2D, type 2 diabetes.

Received December 4, 2006.

Accepted March 21, 2007.


   References
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 Discussion
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