A broad overview of genotype imputation:Standard guidelines,approaches,and future investigations in genomic association studies

The advent of genomic big data and the statistical need for reaching significant results have led genome-wide association studies to be ravenous of a huge number of genetic markers scattered along the whole genome.Since its very beginning,the so-called genotype imputation served this purpose;this statistical and inferential procedure based on a known reference panel opened the theoretical possibility to extend association analyses to a greater number of polymorphic sites which have not been previously assayed by the used technology.In this review,we present a broad overview of the genotype imputation process,showing the most known methods and presenting the main areas of interest,with a closer look to the most up-to-date approaches and a deeper understanding of its usage in the presentday genomic landscape,shedding a light on its future developments and investigation areas.

Common Variants Associated to Type 2 Diabetes in the Italian Population

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.