Association between Single Nucleotide Polymorphisms of the Fibrinogen Alpha Chain (FGA) Gene and Type 2 Diabetes Mellitus in the Korean Population
Genomics & Informatics
;
: 57-64, 2009.
Article
in English
| WPRIM
| ID: wpr-190153
ABSTRACT
Fibrinogen alpha chain (FGA), a subunit of fibrinogen, might be a potential player for type 2 diabetes mellitus (T2DM), since the plasma levels of fibrinogen is known to be related to the incidence of T2DM. To elucidate the potential role of FGA in T2DM, we investigated whether FGA genetic variations are relevant in T2DM in the Korean population. Seven FGA single nucleotide polymorphisms (SNPs) were genotyped in Ansung and Ansan cohorts (474 T2DM subjects and 470 normal controls) in Korea. The association between SNPs and T2DM was determined by logistic regression analysis. Genetic relevance of SNPs to T2DM-related phenotypes was investigated by multiple linear regression analysis. Statistical analysis revealed that among seven FGA SNPs, significant associations with T2DM were observed in FGA rs2070011 (p=0.013-0.034, OR=0.72~ 0.79), rs6050 (p=0.026~0.048, OR=1.24~1.37), and rs2070022 (p=0.016~0.039, OR=0.70~0.72). Two SNPs, rs2070011 and rs6050, also showed significant association with T2DM-related phenotypes such as triglyceride (p=0.005~0.011 for rs2070011 and p=0.003~0.008 for rs6050), total cholesterol (p=0.01 for rs2070011 and p=0.024 for rs6050) and fasting glucose (p=0.035~ 0.036 for rs2070011 and p=0.048 for rs6050) in 470 normal controls. Our association study implies that FGA might be an important genetic factor in T2DM pathogenesis in the Korean population by affecting plasma lipid and glucose levels.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Phenotype
/
Plasma
/
Genetic Variation
/
Fibrinogen
/
Linear Models
/
Logistic Models
/
Cholesterol
/
Incidence
/
Cohort Studies
/
Fasting
Type of study:
Etiology study
/
Incidence study
/
Observational study
/
Prognostic study
/
Risk factors
Country/Region as subject:
Asia
Language:
English
Journal:
Genomics & Informatics
Year:
2009
Type:
Article
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