The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Genome-wide association scans identified CTNNBL1 as a novel gene for obesity
Open accessAbstract
Obesity is a major public health problem with strong genetic determination; however, the genetic factors underlying obesity are largely unknown. In this study, we performed a genome-wide association scan for obesity by examining approximately 500 000 single-nucleotide polymorphisms (SNPs) in a sample of 1000 unrelated US Caucasians. We identified a novel gene, CTNNBL1, which has multiple SNPs associated with body mass index (BMI) and fat mass. The most significant SNP, rs6013029, achieved experiment-wise P-values of 2.69 x 10(-7) for BMI and of 4.99 x 10(-8) for fat mass, respectively. The SNP rs6013029 minor allele T confers an average increase in BMI and fat mass of 2.67 kg/m(2) and 5.96 kg, respectively, compared with the alternative allele G. We further genotyped the five most significant CTNNBL1 SNPs in a French case-control sample comprising 896 class III obese adults (BMI > or = 40 kg/m(2)) and 2916 lean adults (BMI < 25 kg/m(2)). All five SNPs showed consistent associations with obesity (8.83 x 10(-3) < P < 6.96 x 10(-4)). Those subjects who were homozygous for the rs6013029 T allele had 1.42-fold increased odds of obesity compared with those without the T allele. The protein structure of CTNNBL1 is homologous to beta-catenin, a family of proteins containing armadillo repeats, suggesting similar biological functions. beta-Catenin is involved in the Wnt/beta-catenin-signaling pathway which appears to contribute to maintaining the undifferentiated state of pre-adipocytes by inhibiting adipogenic gene expression. Our study hence suggests a novel mechanism for the development of obesity, where CTNNBL1 may play an important role. Our study also provided supportive evidence for previously identified associations between obesity and INSIG2 and PFKP, but not FTO.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057
The Structure of Haplotype Blocks in the Human Genome
Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., et al. (2002) · Science · doi:10.1126/science.1069424 · Cited by 5,863
Kopelman, P. G. (2000) · Nature · doi:10.1038/35007508 · Cited by 4,795
A second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438
A genome-wide association study identifies novel risk loci for type 2 diabetes
Sladek, R., Rocheleau, G., Rung, J., Dina, C., Shen, L., Serre, D., Boutin, P., Vincent, D., Belisle, A., Hadjadj, S., et al. (2007) · Nature · doi:10.1038/nature05616 · Cited by 2,993
Self-citationGenome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels
Saxena, R., Voight, B. F., Lyssenko, V., Burtt, N. P., de Bakker, P. I. W., Chen, H., Roix, J. J., Kathiresan, S., Hirschhorn, J. N., Daly, M. J., et al. (2007) · Science · doi:10.1126/science.1142358 · Cited by 2,843
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants
Scott, L. J., Mohlke, K. L., Bonnycastle, L. L., Willer, C. J., Li, Y., Duren, W. L., Erdos, M. R., Stringham, H. M., Chines, P. S., Jackson, A. U., et al. (2007) · Science · doi:10.1126/science.1142382 · Cited by 2,753
Cited by
Benefits and limitations of genome-wide association studies
Tam, V., Patel, N., Turcotte, M., Bossé, Y., Paré, G., & Meyre, D. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0127-1 · Cited by 2,092
Self-citationthe GIANT Consortium (2009) · Nature Genetics · doi:10.1038/ng.287 · Cited by 1,720
Cho, Y. S., Go, M. J., Kim, Y. J., Heo, J. Y., Oh, J. H., Ban, H.-J., Yoon, D., Lee, M. H., Kim, D.-J., Park, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.357 · Cited by 1,015
Li, Y., Willer, C., Sanna, S., & Abecasis, G. (2009) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.9.081307.164242 · Cited by 990
The effect of host genetics on the gut microbiome
Bonder, M. J., Kurilshikov, A., Tigchelaar, E. F., Mujagic, Z., Imhann, F., Vila, A. V., Deelen, P., Vatanen, T., Schirmer, M., Smeekens, S. P., et al. (2016) · Nature Genetics · doi:10.1038/ng.3663 · Cited by 819
Metadata
- Authors
- Liu, Y.-J., Liu, X.-G., Wang, L., Dina, C., Yan, H., Liu, J.-F., Levy, S., Papasian, C. J., Drees, B. M., Hamilton, J. J., Meyre, D., Delplanque, J., Pei, Y.-F., Zhang, L., Recker, R. R., Froguel, P., & Deng, H.-W.
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2008-03-05
- Volume
- 17
- Issue
- 12
- Pages
- 1803-1813
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- OpenAlex
- W2100083951
- Cited by
- 187
- References
- 16
- FWCI
- 15.64
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Genome-wide association scans identified CTNNBL1 as a novel gene for obesity. https://app.cochat.ai/papers/10.1093/hmg/ddn072
- The paper
- Liu, Y.-J., Liu, X.-G., Wang, L., Dina, C., Yan, H., Liu, J.-F., Levy, S., Papasian, C. J., Drees, B. M., Hamilton, J. J., Meyre, D., Delplanque, J., Pei, Y.-F., Zhang, L., Recker, R. R., Froguel, P., & Deng, H.-W. (2008). Genome-wide association scans identified CTNNBL1 as a novel gene for obesity. Human Molecular Genetics. https://doi.org/10.1093/hmg/ddn072
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.