GCKR gene functional variants in type 2 diabetes and metabolic syndrome: do the rare variants associate with increased carotid intima-media thickness?
BACKGROUND
Recent studies revealed that glucokinase regulatory protein (GCKR) variants (rs780094 and rs1260326) are associated with serum triglycerides and plasma glucose levels. Here we analyzed primarily the association of these two variants with the lipid profile and plasma glucose levels in Hungarian subjects with type 2 diabetes mellitus and metabolic syndrome; and also correlated the genotypes with the carotid intima-media thickness records.


METHODS
A total of 321 type 2 diabetic patients, 455 metabolic syndrome patients, and 172 healthy controls were genotyped by PCR-RFLP.


RESULTS
Both GCKR variants were found to associate with serum triglycerides and with fasting plasma glucose. However, significant association with the development of type 2 diabetes mellitus and metabolic syndrome could not be observed. Analyzing the records of the patients, a positive association of prevalence the GCKR homozygous functional variants and carotid intima-media thickness was found in the metabolic syndrome patients.


CONCLUSIONS
Our results support that rs780094 and rs1260326 functional variants of the GCKR gene are inversely associated with serum triglycerides and fasting plasma glucose levels, as it was already reported for diabetic and metabolic syndrome patients in some other populations. Besides this positive replication, as a novel feature, our preliminary findings also suggest a cardiovascular risk role of the GCKR minor allele carriage based on the carotid intima-media thickness association.
2nd Department of Medicine and Nephrological Center, University of Pécs, Pécs, Hungary. mohasmarton@gmail.com
Márton
M
Mohás
Péter
P
Kisfali
Luca
L
Járomi
Anita
A
Maász
Eszter
E
Fehér
Veronika
V
Csöngei
Noémi
N
Polgár
Eniko
E
Sáfrány
Judit
J
Cseh
Katalin
K
Sümegi
Katalin
K
Hetyésy
István
I
Wittmann
Béla
B
Melegh
D048868:Adaptor Proteins, Signal Transducing / Q000235:genetics*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D002339:Carotid Arteries / Q000000981:diagnostic imaging*; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000000981:diagnostic imaging / Q000235:genetics*; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D006720:Homozygote; D006801:Humans; D006814:Hungary; D016015:Logistic Models; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000000981:diagnostic imaging / Q000235:genetics*; D008875:Middle Aged; D010641:Phenotype; D011110:Polymorphism, Genetic; D018570:Risk Assessment; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood; D017539:Tunica Intima / Q000000981:diagnostic imaging*; D017540:Tunica Media / Q000000981:diagnostic imaging*; D014463:Ultrasonography
D048868:Adaptor Proteins, Signal Transducing; D015415:Biomarkers; D001786:Blood Glucose; C485100:GCKR protein, human; D014280:Triglycerides