Bonàs Guarch, Sílvia
Guindo Martínez, Marta
Miguel-Escalada, Irene
Grarup, Niels
Sebastián Muñoz, David
Rodriguez-Fos, Elias
Sánchez, Friman
Planas-Fèlix, Mercè
Cortes-Sánchez, Paula
González, Santi
Timshel, Pascal
Pers, Tune H.
Morgan, Claire C.
Moran, Ignasi
Atla, Goutham
González, Juan Ramón
Puiggròs, Montserrat
Martí, Jonathan
Andersson, Ehm A.
Díaz, Carlos
Badia, Rosa M.
Udler, Miriam
Leong, Aaron
Kaur, Varindepal
Flannick, Jason
Jørgensen, Torben
Linneberg, Allan
Jørgensen, Marit E.
Witte, Daniel R.
Christensen, Cramer
Brandslund, Ivan
Appel, Emil V.
Scott, Robert A.
Luan, Jian'an
Langenberg, Claudia
Wareham, Nicholas J.
Pedersen, Oluf
Zorzano Olarte, Antonio
Florez, Jose C.
Hansen, Torben
2018-03-21T12:44:33Z
2018-03-21T12:44:33Z
2018-01-22
2018-03-21T12:44:33Z
The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.
Anglès
Diabetis; Genètica humana; Diabetes; Human genetics
Nature Publishing Group
Reproducció del document publicat a: https://doi.org/10.1038/s41467-017-02380-9
Nature Communications, 2018, vol. 9, num. 321
https://doi.org/10.1038/s41467-017-02380-9
info:eu-repo/grantAgreement/EC/H2020/658145/EU//3D-ADAPT
cc-by (c) Bonàs Guarch, Sílvia et al., 2018
http://creativecommons.org/licenses/by/3.0/es