Type 2 diabetes (T2D) is a common metabolic disease where complex interactions between genetics and environment take place. The aim of this thesis is to apply an integrative analysis of genetic and epigenetic data in order to identify new possible molecular interactions at the basis of T2D in the Italian population. First we performed a genome-wide association study (GWAS) on 1,352 individuals (~ 550,000 SNPs) comparing patients with at least one complication (T2D-pts) with healthy controls (CTRL) and with centenarians (CENT), who never developed the disease (“extreme phenotype” approach). The comparison TD2-pts vs CTRL showed for the first time an association for SNPs in MS4A14 and THSD4 genes and confirmed SNPs in DNHD1, ELMOD1 DLC1 genes (pval <10-4). The comparison CENT vs T2D-pts showed association (pval <10-4) with FAM13A, TCF7L2, APBB2 and MGLL genes, the last two have never been associated to T2D. Loci in TMEM108, UPP2 and TCF7L2 genes showed significant association in both comparisons. Considering 229 diabetic patients and 219 controls we analysed the interactions between TCF7L2-rs7903146 and DNA methylation (DNAm) of 5 CpG-sites of TCF7L2 gene. DNAm of few genes highly correlated with age ("little epigenetic clock") and prediction models have been performed. The results showed: i) an association between 2 CpG-sites and T2D; ii) a correlation between DNAm (4 CpGs) and rs7903146; iii) absence of acceleration of epigenetic age in T2D (calculated with the little epigenetic clock); iv) based on these results, a prediction model was developed (based on rs7903146 genotype, DNAm, phenotypic traits) able to classify 63% of subjects. In conclusion we identified new genetic variants associated to T2D thanks to the “extreme phenotype” approach and the relationship between DNAm and genotype of TCF7L2-rs7903146. The potential effect of environmental factors on epigenetic age of T2D patients has been observed for the first time.

An Integrated Genetic and Epigenetic Analysis of Type 2 Diabetes in the Italian population

2018

Abstract

Type 2 diabetes (T2D) is a common metabolic disease where complex interactions between genetics and environment take place. The aim of this thesis is to apply an integrative analysis of genetic and epigenetic data in order to identify new possible molecular interactions at the basis of T2D in the Italian population. First we performed a genome-wide association study (GWAS) on 1,352 individuals (~ 550,000 SNPs) comparing patients with at least one complication (T2D-pts) with healthy controls (CTRL) and with centenarians (CENT), who never developed the disease (“extreme phenotype” approach). The comparison TD2-pts vs CTRL showed for the first time an association for SNPs in MS4A14 and THSD4 genes and confirmed SNPs in DNHD1, ELMOD1 DLC1 genes (pval <10-4). The comparison CENT vs T2D-pts showed association (pval <10-4) with FAM13A, TCF7L2, APBB2 and MGLL genes, the last two have never been associated to T2D. Loci in TMEM108, UPP2 and TCF7L2 genes showed significant association in both comparisons. Considering 229 diabetic patients and 219 controls we analysed the interactions between TCF7L2-rs7903146 and DNA methylation (DNAm) of 5 CpG-sites of TCF7L2 gene. DNAm of few genes highly correlated with age ("little epigenetic clock") and prediction models have been performed. The results showed: i) an association between 2 CpG-sites and T2D; ii) a correlation between DNAm (4 CpGs) and rs7903146; iii) absence of acceleration of epigenetic age in T2D (calculated with the little epigenetic clock); iv) based on these results, a prediction model was developed (based on rs7903146 genotype, DNAm, phenotypic traits) able to classify 63% of subjects. In conclusion we identified new genetic variants associated to T2D thanks to the “extreme phenotype” approach and the relationship between DNAm and genotype of TCF7L2-rs7903146. The potential effect of environmental factors on epigenetic age of T2D patients has been observed for the first time.
9-mag-2018
Università degli Studi di Bologna
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/144330
Il codice NBN di questa tesi è URN:NBN:IT:UNIBO-144330