Genome-wide association study identifies three novel loci for type 2 diabetes

Autor: Hara, K., Fujita, H., Johnson, T.A., Yamauchi, T., Yasuda, K., Horikoshi, M., Peng, C., Hu, C., Ma, R.C., Imamura, M., Iwata, M., Tsunoda, T., Morizono, T., Shojima, N., So, W.Y., Leung, T.F., Kwan, P., Zhang, R., Wang, J., Yu, W., Maegawa, H., Hirose, H., DIAGRAM Consortium (Huth, C., Gieger, C., Klopp, N., Meitinger, T., Illig, T., Grallert, H., Thorand, B., Wichmann, H.-E., Petersen, A.-K.), Kaku, K., Ito, C., Watada, H., Tanaka, Y., Tobe, K., Kashiwagi, A., Kawamori, R., Jia, W., Chan, J.C., Teo, Y.Y., Shyong, T.E., Kamatani, N., Kubo, M., Maeda, S., Kadowaki, T.
Přispěvatelé: Internal Medicine
Rok vydání: 2014
Předmět:
Zdroj: Hum. Mol. Genet. 23, 239-246 (2014)
Human Molecular Genetics, 23(1), 239-246. Oxford University Press
ISSN: 0964-6906
DOI: 10.1093/hmg/ddt399
Popis: Although over 60 loci for type 2 diabetes (T2D) have been identified, there still remains a large genetic component to be clarified. To explore unidentified loci for T2D, we performed a genome-wide association study (GWAS) of 6 209 637 single-nucleotide polymorphisms (SNPs), which were directly genotyped or imputed using East Asian references from the 1000 Genomes Project (June 2011 release) in 5976 Japanese patients with T2D and 20 829 nondiabetic individuals. Nineteen unreported loci were selected and taken forward to follow-up analyses. Combined discovery and follow-up analyses (30 392 cases and 34 814 controls) identified three new loci with genome-wide significance, which were MIR129-LEP [rs791595; risk allele = A; risk allele frequency (RAF) = 0.080; P = 2.55 × 10(-13); odds ratio (OR) = 1.17], GPSM1 [rs11787792; risk allele = A; RAF = 0.874; P = 1.74 × 10(-10); OR = 1.15] and SLC16A13 (rs312457; risk allele = G; RAF = 0.078; P = 7.69 × 10(-13); OR = 1.20). This study demonstrates that GWASs based on the imputation of genotypes using modern reference haplotypes such as that from the 1000 Genomes Project data can assist in identification of new loci for common diseases.
Databáze: OpenAIRE