The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Polymorphisms within Novel Risk Loci for Type 2 Diabetes Determine β-Cell Function
Open accessAbstract
BACKGROUND: Type 2 diabetes arises when insulin resistance-induced compensatory insulin secretion exhausts. Insulin resistance and/or beta-cell dysfunction result from the interaction of environmental factors (high-caloric diet and reduced physical activity) with a predisposing polygenic background. Very recently, genetic variations within four novel genetic loci (SLC30A8, HHEX, EXT2, and LOC387761) were reported to be more frequent in subjects with type 2 diabetes than in healthy controls. However, associations of these variations with insulin resistance and/or beta-cell dysfunction were not assessed. METHODOLOGY/PRINCIPAL FINDINGS: By genotyping of 921 metabolically characterized German subjects for the reported candidate single nucleotide polymorphisms (SNPs), we show that the major alleles of the SLC30A8 SNP rs13266634 and the HHEX SNP rs7923837 associate with reduced insulin secretion stimulated by orally or intravenously administered glucose, but not with insulin resistance. In contrast, the other reported type 2 diabetes candidate SNPs within the EXT2 and LOC387761 loci did not associate with insulin resistance or beta-cell dysfunction, respectively. CONCLUSIONS/SIGNIFICANCE: The HHEX and SLC30A8 genes encode for proteins that were shown to be required for organogenesis of the ventral pancreas and for insulin maturation/storage, respectively. Therefore, the major alleles of type 2 diabetes candidate SNPs within these genetic loci represent crucial alleles for beta-cell dysfunction and, thus, might confer increased susceptibility of beta-cells towards adverse environmental factors.
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Citations
Cites
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
Genome-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
Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes
Grant, S. F. A., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., Helgason, A., Stefansson, H., Emilsson, V., Helgadottir, A., et al. (2006) · Nature Genetics · doi:10.1038/ng1732 · Cited by 2,287
Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes
Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science · doi:10.1126/science.1142364 · Cited by 2,194
Weyer, C., Bogardus, C., Mott, D. M., & Pratley, R. E. (1999) · Journal of Clinical Investigation · doi:10.1172/jci7231 · Cited by 1,940
A variant in CDKAL1 influences insulin response and risk of type 2 diabetes
Steinthorsdottir, V., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Jonsdottir, T., Walters, G. B., Styrkarsdottir, U., Gretarsdottir, S., Emilsson, V., Ghosh, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2043 · Cited by 1,072
Gloyn, A. L., Weedon, M. N., Owen, K. R., Turner, M. J., Knight, B. A., Hitman, G., Walker, M., Levy, J. C., Sampson, M., Halford, S., et al. (2003) · Diabetes · doi:10.2337/diabetes.52.2.568 · Cited by 754
Chimienti, F., Devergnas, S., Pattou, F., Schuit, F., Garcia-Cuenca, R., Vandewalle, B., Kerr-Conte, J., Van Lommel, L., Grunwald, D., Favier, A., et al. (2006) · Journal of Cell Science · doi:10.1242/jcs.03164 · Cited by 349
Hex homeobox gene-dependent tissue positioning is required for organogenesis of the ventral pancreas
Bort, R., Martinez-Barbera, J. P., Beddington, R. S. P., & Zaret, K. S. (2004) · Development · doi:10.1242/dev.00965 · Cited by 267 · cited 1×
“[14], HHEX’s role in the predispostion to T2DM could be attributed to this gene’s function during organogenesis of the ventral pancreas [21,22].”
Background
Cited by
Genetic Mapping in Human Disease
Altshuler, D., Daly, M. J., & Lander, E. S. (2008) · Science · doi:10.1126/science.1156409 · Cited by 1,452
Wijesekara, N., Dai, F. F., Hardy, A. B., Giglou, P. R., Bhattacharjee, A., Koshkin, V., Chimienti, F., Gaisano, H. Y., Rutter, G. A., & Wheeler, M. B. (2010) · Diabetologia · doi:10.1007/s00125-010-1733-9 · Cited by 305
Kirchhoff, K., Machicao, F., Haupt, A., Schäfer, S. A., Tschritter, O., Staiger, H., Stefan, N., Häring, H.-U., & Fritsche, A. (2008) · Diabetologia · doi:10.1007/s00125-008-0926-y · Cited by 265
Self-citationLatent Autoimmune Diabetes in Adults
Naik, R. G., Brooks-Worrell, B. M., & Palmer, J. P. (2009) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2009-1120 · Cited by 249
Wu, Y., Li, H., Loos, R. J. F., Yu, Z., Ye, X., Chen, L., Pan, A., Hu, F. B., & Lin, X. (2008) · Diabetes · doi:10.2337/db08-0047 · Cited by 240
Metadata
- Authors
- Staiger, H., Machicao, F., Stefan, N., Tschritter, O., Thamer, C., Kantartzis, K., Schäfer, S. A., Kirchhoff, K., Fritsche, A., & Häring, H.-U.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2007-09-05
- Volume
- 2
- Issue
- 9
- Pages
- e832
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2032734258
- Cited by
- 162
- References
- 10
- FWCI
- 22.32
- Type
- journal article
- Language
- en
- Open access
- gold
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- Staiger, H., Machicao, F., Stefan, N., Tschritter, O., Thamer, C., Kantartzis, K., Schäfer, S. A., Kirchhoff, K., Fritsche, A., & Häring, H.-U. (2007). Polymorphisms within Novel Risk Loci for Type 2 Diabetes Determine β-Cell Function. PLoS ONE. https://doi.org/10.1371/journal.pone.0000832
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