Nutrigenetic variants and cardio-metabolic risk in women with or without gestational diabetes. (March 2018)

• Record Type: Journal Article
• Authors: Franzago, Marica; Fraticelli, Federica; Marchetti, Daniela; Celentano, Claudio; Liberati, Marco; Stuppia, Liborio; Vitacolonna, Ester
• Is Part Of: Diabetes research and clinical practice. Volume 137(2018)
• Page Start: 64
• Page End: 71
• Publication Date: 2018-03
• Subjects: GDM gestational diabetes mellitus -- CVD cardiovascular diseases -- MetS metabolic syndrome -- GWAS genome-wide association studies -- BMI body mass index -- TC total cholesterol -- HDL-C high-density lipoprotein cholesterol -- LDL-C low-density lipoprotein cholesterol -- TG triglycerides -- CAD coronary artery disease -- CHD coronary heart disease; Gestational diabetes mellitus -- Cardio-metabolic risk -- Genetic variants -- Nutrigenetics; Diabetes -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462
• DOI: 10.1016/j.diabres.2018.01.001
• Languages: English
• ISSNs: 0168-8227

Abstract

Abstract: Aim: Gestational diabetes mellitus (GDM) is the most frequent metabolic disorder in pregnancy and it can be considered a silent risk associated to T2DM and CVD later in life. The aim of this study was to investigate the association of clinical parameters with nine single nucleotide polymorphisms (SNPs) involved with nutrients and metabolism in women with or without GDM in order to identify potential routine clinical markers for early prevention. Methods: Nine gene variants associated with nutrients and metabolism, namely PPARG2 rs1801282 (C > G); PPARGC1A rs8192678 (C > T); TCF7L2 rs7903146 (C > T); LDLR rs2228671 (C > T); MTHFR rs1801133 (C > T); APOA5 rs662799 (T > C); GCKR rs1260326 (C > T); FTO rs9939609 (T > A); MC4R rs17782313 (T > C) were genotyped in 104 GDM cases and 124 controls using High Resolution Melting (HRM) analysis. Results: The genetic variant rs7903146 (C > T) in TCF7L2 gene showed a strong association with GDM risk (OR: 2.56; 95% CI: [1.24–5.29]). Moreover, a significant correlation was observed between lipid parameters and polymorphisms in other genes, namely PPARG2 [p = 0, 03], APOA5 [p = 0, 02], MC4R [p = 0, 03], LDLR [p = 0, 04] and FTO [p = 0, 03]. In addition, rs17782313 variant, mapped close to MC4R gene, was associated to BMI in pre-pregnancy [p = 0, 02] and at the end of pregnancy [p = 0, 03] in GDM group. Conclusion: In our study, we found significant associations between routine clinical parameters and some gene variants connected with nutrients and metabolism in women with GDM. These results can provide useful information to develop effective tools and possible personalized intervention strategies in a timely manner.