TITLE:
Common Variants Associated to Type 2 Diabetes in the Italian Population
AUTHORS:
Sara Bonetti, Chiara Zusi, Elisabetta Rinaldi, Maria Linda Boselli, Cristina Patuzzo, Elisabetta Trabetti, Giovanni Malerba, Cristina Bianchi, Gianmarco Lombardi, Gianluigi Zaza, Stefano Del Prato, Giovanni Gambaro, Enzo Bonora, Riccardo C. Bonadonna, Maddalena Trombetta
KEYWORDS:
T2D, Genetics, Susceptibility, SNPs, Variants
JOURNAL NAME:
Open Journal of Endocrine and Metabolic Diseases,
Vol.11 No.1,
January
22,
2021
ABSTRACT:
Genome-wide association studies have identified numerous genetic variants for type 2 diabetes (T2D). Most genetic loci discovered to date were studied in Caucasians or Asian ancestry, however, there are no data regarding a quite large Italian sample. Therefore, we investigated T2D genetic susceptibility of 143 single nucleotide polymorphisms (SNPs) within 30 genes involved in glucose metabolism in a large Italian case-control study. For the study, 1875 Caucasian patients were selected from three Italian cohorts. Age, gender, BMI and fasting plasma glucose (FPG) values were collected. Population was split in cases and controls based on FPG values or T2D diagnosis. T2D subjects and whom with FPG higher that 126 mg/dL were recruited as cases whereas subjects with normal values of FPG were considered controls. In each subject 143 SNPs were genotyped. To evaluate the association between genetic variations and diabetes status, a logistic regression analysis, adjusted for age, sex and BMI, was performed. Overall, 948 (50.6%) had T2D. Twenty out of 143 variants within 11 different genes resulted significantly associated to T2D. Four of them were located into TCF7L2 gene and presented the highest odd ratio (from 1.42 to 1.57). At least two SNPs were located within KCNJ11, WFS1, ABCC8, JAZF1 and HNF1B genes and one SNP each was identified in ADAMTS9, IGF2BP2, FTO, G6PC2 and GCK genes. Our findings support the role of 11 genes involved in glucose homeostasis in T2D risk development in a large Italian population. We found that such genetic information may be advantageous for predicting T2D.