Cited by 542Diabetes and associated disordersGenetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

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A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene

Hakonarson, Hakon, Grant, Struan F. A., Bradfield, Jonathan P., Marchand, Luc, Kim, Cecilia E., Glessner, Joseph T., Grabs, Rosemarie, Casalunovo, Tracy, Taback, Shayne P., Frackelton, Edward C., Lawson, Margaret L., Robinson, Luke J., Skraban, Robert, Lu, Yang, Chiavacci, Rosetta M., Stanley, Charles A., Kirsch, Susan E., Rappaport, Eric F., Orange, Jordan S., Monos, Dimitri S., Devoto, Marcella, Qu, Hui-Qi, Polychronakos, Constantin·2007·Nature

DOI 10.1038/nature06010

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Abstract

Type 1 diabetes (T1D) in children results from autoimmune destruction of pancreatic beta cells, leading to insufficient production of insulin. A number of genetic determinants of T1D have already been established through candidate gene studies, primarily within the major histocompatibility complex but also within other loci. To identify new genetic factors that increase the risk of T1D, we performed a genome-wide association study in a large paediatric cohort of European descent. In addition to confirming previously identified loci, we found that T1D was significantly associated with variation within a 233-kb linkage disequilibrium block on chromosome 16p13. This region contains KIAA0350, the gene product of which is predicted to be a sugar-binding, C-type lectin. Three common non-coding variants of the gene (rs2903692, rs725613 and rs17673553) in strong linkage disequilibrium reached genome-wide significance for association with T1D. A subsequent transmission disequilibrium test replication study in an independent cohort confirmed the association. These results indicate that KIAA0350 might be involved in the pathogenesis of T1D and demonstrate the utility of the genome-wide association approach in the identification of previously unsuspected genetic determinants of complex traits.

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PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Haploview: analysis and visualization of LD and haplotype maps
Barrett, J. C., Fry, B., Maller, J., & Daly, M. J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth457 · Cited by 14,551
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
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
Pfam: clans, web tools and services
Finn, R. D. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj149 · Cited by 2,291
Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease
Ueda, H., Howson, J. M. M., Esposito, L., Heward, J., Snook, Chamberlain, G., Rainbow, D. B., Hunter, K. M. D., Smith, A. N., Di Genova, G., et al. (2003) · Nature · doi:10.1038/nature01621 · Cited by 2,175
A comprehensive review of genetic association studies
Hirschhorn, J. N., Lohmueller, K., Byrne, E., & Hirschhorn, K. (2002) · Genetics in Medicine · doi:10.1097/00125817-200203000-00002 · Cited by 1,674
Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes
Finland, G. O. T. 1. D. I., Todd, J. A., the Wellcome Trust Case Control Consortium, Walker, N. M., Cooper, J. D., Smyth, D. J., Downes, K., Plagnol, V., Bailey, R., Nejentsev, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2068 · Cited by 1,456
A functional variant of lymphoid tyrosine phosphatase is associated with type I diabetes
Bottini, N., Musumeci, L., Alonso, A., Rahmouni, S., Nika, K., Rostamkhani, M., MacMurray, J. P., Meloni, T., Lucarelli, P., Pellecchia, M., et al. (2004) · Nature Genetics · doi:10.1038/ng1323 · Cited by 1,419
A genome-wide search for human type 1 diabetes susceptibility genes
Davies, J. L., Kawaguchi, Y., Bennett, S. T., Copeman, J. B., Cordell, H. J., Pritchard, L. E., Reed, P. W., Gough, S. C. L., Jenkins, S. C., Palmer, S. M., et al. (1994) · Nature · doi:10.1038/371130a0 · Cited by 1,276

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Authors: Hakonarson, H., Grant, S. F. A., Bradfield, J. P., Marchand, L., Kim, C. E., Glessner, J. T., Grabs, R., Casalunovo, T., Taback, S. P., Frackelton, E. C., Lawson, M. L., Robinson, L. J., Skraban, R., Lu, Y., Chiavacci, R. M., Stanley, C. A., Kirsch, S. E., Rappaport, E. F., Orange, J. S., Monos, D. S., Devoto, M., Qu, H.-Q., & Polychronakos, C.
Affiliations: Children's Hospital of Philadelphia (US)
Pediatrics and Genetics (US)
Centre for Applied Genomics (CA)
McGill University (CA)
University of Manitoba (CA)
University of Ottawa (CA)
Markham Stouffville Hospital (CA)
University of Pennsylvania (US)
Corresponding author: Hakonarson, Hakon
Polychronakos, Constantin
ORCID: Hakonarson, Hakon
Grant, Struan F. A.
Glessner, Joseph T.
Lawson, Margaret L.
Lu, Yang
Stanley, Charles A.
Kirsch, Susan E.
Orange, Jordan S.
Monos, Dimitri S.
Devoto, Marcella
Qu, Hui-Qi
Polychronakos, Constantin
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2007-07-15
Volume: 448
Issue: 7153
Pages: 591-594
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/nature06010
OpenAlex: W2031539362
Cited by: 542
References: 34
Citations by year: 2026: 8 · 2025: 9 · 2024: 14 · 2023: 7 · 2022: 16 · 2021: 26 · 2020: 13 · 2019: 16 · 2018: 14 · 2017: 18 · 2016: 22 · 2015: 22 · 2014: 28 · 2013: 40 · 2012: 25
FWCI: 39.45
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords: type 1 diabetes, C-type lectin, sugar-binding proteins, genetic susceptibility, chromosome 16p13, linkage disequilibrium, non-coding variants, transmission disequilibrium test, pediatric diabetes, major histocompatibility complex, islet autoimmunity
MeSH terms: Diabetes Mellitus, Type 1, Genetic Markers, Humans, Monosaccharide Transport Proteins, Nuclear Family, Cohort Studies, Linkage Disequilibrium, Genome, Human, Case-Control Studies, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Lectins, C-Type

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A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene

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