Non-replication of an association of CTNNBL1polymorphisms and obesity in a population of Central European ancestry
© Vogel et al; licensee BioMed Central Ltd. 2009
Received: 14 October 2008
Accepted: 19 February 2009
Published: 19 February 2009
A recent genome-wide association (GWA) study of U.S. Caucasians suggested that eight single nucleotide polymorphisms (SNPs) in CTNNBL1 are associated with obesity and increased fat mass. We analysed the respective SNPs in data from our previously published GWA for early onset obesity (case-control design), in GWA data from a population-based cohort of adults, and in an independent family-based obesity study. We investigated whether variants in CTNNBL1 (including rs6013029) and in three other genes (SH3PXD2B, SLIT3 and FLJ42133,) were associated with obesity.
The GWA studies were carried out using Affymetrix® SNP Chips with approximately 500,000 markers each. In the families, SNP rs6013029 was genotyped using the TaqMan® allelic discrimination assay. The German case-control GWA included 487 extremely obese children and adolescents and 442 healthy lean individuals. The adult GWA included 1,644 individuals from a German population-based study (KORA). The 775 independent German families consisted of extremely obese children and adolescents and their parents.
We found no evidence for an association of the reported variants in CTNNBL1 with early onset obesity or increased BMI. Further, in our family-based study we found no evidence for over-transmission of the rs6013029 risk-allele T to obese children. Additionally, we found no evidence for an association of SH3PXD2B, SLIT3 and FLJ42133 variants in our two GWA samples.
We detected no confirmation of the recent association of variants in CTNNBL1 with obesity in a population of Central European ancestry.
Obesity is a major health problem worldwide and results from an interplay of social, environmental and genetic factors . Genome-wide association (GWA) studies have contributed to the identification of new polygenic variants contributing to inter-individual body mass index (BMI) differences [2–5]. Recently, Liu et al.  reported that variants in the beta catenin-like 1 gene (CTNNBL1) were associated with increased fat mass and obesity in a GWA conducted with 1,000 adult U.S. Caucasians. In the same report, this observation was validated in a French case-control sample (896 class III obese adults; BMI ≥ 40 kg/m2 and 2,916 normal weight controls; BMI < 25 kg/m2).
Our study had two objectives. First, we aimed to replicate the association of the obesity risk alleles (rs6013029 T-allele, rs16986921 T-allele, rs6020712 A-allele, rs6020846 G-allele, rs6020395 C-allele, rs16986890 G-allele, rs6096781 C-allele, and rs6020339 C-allele) of CTNNBL1 in two GWA data sets. Second, we explored three other genes SH3PXD2B (rs13356223, rs10077897 and rs13436547), SLIT3 (rs17734503 and rs12654448) and FLJ42133 (rs7363432 and rs6095722), also mentioned by Liu et al.  in our GWAs. We analysed three samples: (1) GWA data from 487 cases with early onset extreme obesity and 442 controls; (2) GWA data of 1,644 individuals from a population-based adult cohort and (3) genotyping data of the best CTNNBL1 SNP rs6013029 previously reported in  in a sample of 775 independent nuclear families each comprising one or more extremely obese offspring and both parents.
Participants and Genotyping
487 extremely obese children and adolescents (cases: mean age 14.38 ± 3.74; BMI = 33.40 ± 6.81; BMI Z-score = 4.63 ± 2.27; 42.9% male) and 442 healthy lean individuals (controls: mean age 26.07 ± 5.79; BMI = 18.31 ± 1.10; BMI Z-score = -1.38 ± 0.35; 38.7% male) from Germany. The use of lean adults who were never overweight or obese during childhood (assessed by interview ) as control group reduces the chances of misclassification compared to the use of lean children as controls that might become overweight in adulthood. This sample was genotyped using the Affymetrix® Genome-Wide Human SNP Array 5.0 with 440,794 markers. Details on this GWA have been reported elsewhere . The study was approved by the local ethics committee.
KORA (Kooperative Gesundheitsforschung im Raum Augsburg, follow up of Survey 3 (F3); 'Cooperative Health Research in the Region of Augsburg') comprises 3,126 German adults representative of the population within the age range 25–74 years in Augsburg and surrounding areas (Bavaria, Germany). 1,644 probands (mean age 52.52 ± 10.09; BMI = 27.33 ± 4.12; 48.9% male) were genotyped using the Affymetrix® GeneChip® Human Mapping 500K Array Set (for details on the sample see ). The ethics committee of the Länderärztekammer for Bavaria approved the study.
775 German families comprising 1,058 extremely obese children and adolescents (775 index patients, 283 siblings; mean age 13.88 ± 3.69; BMI 31.12 ± 6.06 kg/m2; BMI Z-score = 3.91 ± 2.02, 45.8% male) and 1,550 parents (mean age 42.56 ± 5.95; BMI 30.37 ± 6.29 kg/m2; BMI Z-score = 1.68 ± 1.83) were recruited at the University of Marburg and the University Duisburg-Essen. Participants were genotyped for the SNP rs6013029 using the TaqMan® allelic discrimination assay (C_29958195_10 assay, Applied Biosystems, Germany); the call rate was 99.7%, with 100% concordance of duplicates. All individuals studied are Caucasians from Central Europe, with German ancestry. All studies were conducted in accordance with the guidelines of The Declaration of Helsinki.
Prior to analysis, the genotype distributions of all three samples (case-control GWA sample, population based GWA sample, and the family sample) were tested for deviations from Hardy-Weinberg equilibrium using an exact two-sided test . The association between increased BMI and CTNNBL1 polymorphisms in the KORA cohort was analysed using linear regression analysis adjusted for age and sex while logistic regression was used for data from the case-control GWA. In both cases we used an additive model for the risk allele as described in . In our family-based study we tested for overtransmission of the rs6013029 "T" allele – reported in the original study as being the risk allele – to affected offspring with the Pedigree Disequilibrium Test (PDT-sum)  and generated a genotype relative risk estimates using conditional logistic regression.
Power calculations based on the effect of genetic variants in rs6013029 were performed for the case-control and the cohort using the program QUANTO Version 1.2.3 http://hydra.usc.edu/gxe and for the family-based sample using TDT Power Calculator 1.2.1 http://www.biostat.jhsph.edu/~wmchen/pc.html. For these calculations we assumed a minor allele frequency = 0.05 and genetic effect size of OR = 1.42 as estimated in  for the tests which used the case-control and family setting, while a true genetic effect of β = 0.1 (increase in mean BMI with each additional risk allele) was chosen for the cohort. In either case α = 0.05 (one-sided) was chosen.
Results and discussion
Results of the best SNPs in CTNNBL1 as previously described  in two independent GWAs.
Genotype distribution cases (%)/controls (%)
Odds ratio (95% CI)
β (95% CI)
(0.603 – 1.296)
(-0.522 – 0.724)
(0.611 – 1.324)
(-0.463 – 0.780)
(0.591 – 1.273)
(-0.515 – 0.725)
(0.649 – 1.340)
(-0.529 – 0.635)
(0.650 – 1.320)
(-0.444 – 0.700)
(-0.682 – 0.436)
(0.773 – 1.670)
(-0.517 – 0.708)
(0.651 – 1.346)
(-0.447 – 0.715)
Results of the best SNPs in SH3PXD2B, SLIT3 and FLJ42133 as previously described  in two independent GWAs.
Genotype distribution cases (%)/controls (%)
Odds ratio (95% CI)
β (95% CI)
(0.614 – 1.722)
(-1.235 – 0.136)
(0.690 – 1.799)
(-1.086 – 0.225)
(0.620 – 1.739)
(-1.172 – 0.201)
(0.814 – 1.626)
(-0.109 – 0.825)
(0.791 – 1.602)
(-0.352 – 0.601)
(0.649 – 1.340)
(-0.369 – 0.837)
(0.651 – 1.346)
(-0.447 – 0.715)
In sum, our results underline the importance of replication of GWA results in independent samples even though independent validations may have been reported within the same initial study. While replication of association with obesity of intron 1 variants in FTO has been demonstrated robustly in almost all subsequent studies comprising obese adults and children [7, 12–15], the study by Liu et al.  was an exception as none of the intron 1 FTO SNPs showed evidence for a body weight-related association. Interestingly, however, the study did find some evidence for an association of variants in INSIG2 with obesity [5, 16–19]. Both examples underline the difficulties that arise when trying to validate, confirm and replicate associations with such complex traits as obesity. Our failure to replicate the initial findings  also does not appear to be a result of population stratification. All recruitment was done in Germany for which population stratification effects have shown to be of minor importance .
Another possible explanation for a lack of replication is that our results are mainly based on data for children and adolescents which are different from  where only adults were investigated. Again the example of FTO  highlights how validated associations found in adults with obesity may also be present in children with extreme obesity [3, 21]. Recently, two independent studies comprising more than 32,000  and 14,000  individuals also did not find significant association of the CTNNBL1 variant rs6013029 and obesity. Our study is a replication and validation attempt with sufficient combined power to independently replicate an initial finding , while also providing some evidence to support the decision not to follow-up variants that did not "survive" a validation within the same initial report . Although we were not able to replicate the original findings, our data may be useful for a meta-analytical assessment of the association of CTNNBL1 variants and obesity. A retrospective look at the conflicting reports on INSIG2 and the recent reports on CTNNBL1 suggests that research on mediating and moderating variables to more comprehensively assess phenotype-genotype relationships is urgently needed.
We did not detect confirmation of association of variants in CTNNBL1 with obesity in a population of Central European ancestry. Further studies have to be performed to validate or not the initial findings about the association of CTNNBL1 variants and obesity.
We thank the probands for their participation. We thank the technical assistance of Jitka Andrä and Sieglinde Düerkop. This work was supported by grants from the German Ministry of Education & Research (BMBF, NGFN2 and NGFNplus: 01GS0820, 01GS0830 and 01GS0823), the German Research Foundation (DFG: HE 1446/4-1,2) and the European Union (FP6 LSHMCT-2003-503041).
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