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Finding Genetic Risk Factors of Gestational Diabetes
Genomics & Informatics ; : 239-243, 2012.
Article in English | WPRIM | ID: wpr-11758
ABSTRACT
Gestational diabetes mellitus (GDM) is a complex metabolic disorder of pregnancy that is suspected to have a strong genetic predisposition. It is associated with poor perinatal outcome, and both GDM women and their offspring are at increased risk of future development of type 2 diabetes mellitus (T2DM). During the past several years, there has been progress in finding the genetic risk factors of GDM in relation to T2DM. Some of the genetic variants that were proven to be significantly associated with T2DM are also genetic risk factors of GDM. Recently, a genome-wide association study of GDM was performed and reported that genetic variants in CDKAL1 and MTNR1B were associated with GDM at a genome-wide significance level. Current investigations using next-generation sequencing will improve our insight into the pathophysiology of GDM. It would be important to know whether genetic information revealed from these studies could improve our prediction of GDM and the future development of T2DM. We hope further research on the genetics of GDM would ultimately lead us to personalized genomic medicine and improved patient care.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Risk Factors / Diabetes, Gestational / Genetic Predisposition to Disease / Diabetes Mellitus, Type 2 / Genome-Wide Association Study / Patient Care Type of study: Diagnostic study / Etiology study / Prognostic study / Risk factors Limits: Female / Humans / Pregnancy Language: English Journal: Genomics & Informatics Year: 2012 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Risk Factors / Diabetes, Gestational / Genetic Predisposition to Disease / Diabetes Mellitus, Type 2 / Genome-Wide Association Study / Patient Care Type of study: Diagnostic study / Etiology study / Prognostic study / Risk factors Limits: Female / Humans / Pregnancy Language: English Journal: Genomics & Informatics Year: 2012 Type: Article