Allele scoring of genetic risk in previous gestational diabetes mellitus (pGDM)

Abstract

This research was intended to assess the association of two panels of candidate genes (HI and IV) in Maltese probands with a past history of severe Gestational Diabetes Mellitus (pGDM; 2hrBG>11.0mmol/l) GDM affects ~_7% of all pregnancies and is defined as carbohydrate intolerance with onset or first recognition during pregnancy. Twenty-Six pto bands with pGDM aged 19 - 42 years were recruited to this study. All were overweight or obese with a BMI in excess of 25 Kg I m2. The frequency of Panel IV SNPs was determined in the pGDM group and the Maltese Neonatal Reference DNA Pool (Malta BioBank) by quantitative real time PCR (qPCR). Genotype distribution and allelic frequencies were compared between patients and control group. Odds ratios (ORs) and relative risk (RR) with 95% confidence intervals (Cl) were calculated for both panels using SPSS software version17.0. All selected genes of Panel IH were significantly correlated (RR of 1.7 to 2.5) with pGDM except resistin (nt1326 G-7C). Panel IV SNPs showed an association to pGDM namely, positive (4 SNPs) and protective (5 SNPs). The patients with pGDM had accumulated allele scores (SNIPLOTYPEST M) between 4 and 8. The higher Sniplotype scores were associated with considerably higher RR values (R2= 0.96). Ethnic influence is suggested by the significant association of B1B2 and B1B1 genotypes of IL4 VNTR with pGDM. IL-1RN VNTR genotyping showed that the BA genotype frequency was more common in the pGDM (23%) than in controls (0 %). The General Linear Model analysis suggested that the best genetic predictor/s of all glucose biomarkers was MTHFRC677T in Panel HI and IL-6(rs1800795 CIG) in Panel IV. Moreover, FTO (rs9939609 A/T) was the best genetic predictor of multiple anthropometric measurements including (BMI and waist circumference). The two step cluster analysis showed that the Absolute HbA1c (=Hb A 1c % X Hb g I dL) was the most powerful factor in the clustering process, but short of being statistically significant. It can be seen that the summation of a few alleles from the inflammatory and metabolic pathways may be sufficient to determine genetic risk for GDM as in T2DM. Robust associations with phenotypic markers with quantitative biomarkers such as anthropometry and the absolute Hb A 1c require further exploration.