Genetic risk profiling for prediction of type 2 diabetes | Zendy

Raluca Mihăescu | Zendy; James B. Meigs | Zendy; Eric J.G. Sijbrands | Zendy; A. Cecile J.W. Janssens | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Genetic risk profiling for prediction of type 2 diabetes

Author(s) -

Raluca Mihăescu,

James B. Meigs,

Eric J.G. Sijbrands,

A. Cecile J.W. Janssens

Publication year - 2011

Publication title -

plos currents

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.282

H-Index - 49

ISSN - 2157-3999

DOI - 10.1371/currents.rrn1208

Subject(s) - single nucleotide polymorphism , type 2 diabetes , medicine , disease , bioinformatics , candidate gene , computational biology , profiling (computer programming) , genetic association , genome wide association study , diabetes mellitus , genetics , gene , computer science , biology , genotype , endocrinology , operating system

Type 2 diabetes (T2D) is a common disease caused by a complex interplay between many genetic and environmental factors. Candidate gene studies and recent collaborative genome-wide association efforts revealed at least 38 common single nucleotide polymorphisms (SNPs) associated with increased risk of T2D. Genetic testing of multiple SNPs is considered a potentially useful tool for early detection of individuals at high diabetes risk leading to improved targeting of preventive interventions.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research