Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12

AUTHORS

Sílvia Bonàs-Guarch, Marta Guindo-Martínez, Irene Miguel-Escalada, Niels Grarup, David Sebastian, Elias Rodriguez-Fos, Friman Sánchez, Mercè Planas-Fèlix, Paula Cortes-Sánchez, Santi González, Pascal Timshel, Tune H. Pers, Claire C. Morgan, Ignasi Moran, Goutham Atla, Juan R. González, Montserrat Puiggros, Jonathan Martí, Ehm A. Andersson, Carlos Díaz, Rosa M. Badia, Miriam Udler, Aaron Leong, Varindepal Kaur, Jason Flannick, Torben Jørgensen, Allan Linneberg, Marit E. Jørgensen, Daniel R. Witte, Cramer Christensen, Ivan Brandslund, Emil V. Appel, Robert A. Scott, Jian’an Luan, Claudia Langenberg, Nicholas J. Wareham, Oluf Pedersen, Antonio Zorzano, Jose C Florez, Torben Hansen, Jorge Ferrer, Josep Maria Mercader, David Torrents

ABSTRACT

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. More... »

PAGES

321

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41467-017-02380-9

DOI

http://dx.doi.org/10.1038/s41467-017-02380-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100426965

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29358691


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