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Genetical genomics of type 2 diabetes and cardiovascular phenotypes in experimental systems (IRGENOMICS)
Start date: Jan 1, 2009, End date: Dec 31, 2010 PROJECT  FINISHED 

"The objectives of this proposal are to establish causal relationships between altered gene expression regulation and diabetes metabolic changes in a rat model of spontaneous insulin resistance, the Goto-Kakizaki (GK) strain, and define disease-associated biomarkers. This multidisciplinary research addresses fundamental questions concerning the impact of naturally-occurring genetic variants on metabolic regulations contributing to diabetes and obesity, which have become dominant causes of reduced life expectancy in westernized societies. The proposed research builds on knowledge of genetic loci linked to variables relevant to insulin resistance and quantitative changes in metabolites derived by metabonomics, as well as advances in functional genomic technologies and expanding rat genomic resources (genome sequence, single nucleotide polymorphism - SNP). This research takes advantage of the availability of congenic strains of the GK rat, which are powerful tools for validating results from genetic and genetical genomic experiments and testing hypotheses regarding the involvement of SNPs in disease features. In this programme gene transcription profiling, bioinformatic tools and metabolic and biochemical studies will be applied in existing congenic strains of the GK rat carrying chromosomal regions of a locus associated with insulin resistance, transferred onto the genetic background of a control strain. Gene pathways and networks associated with altered metabolic variables will be correlated with SNP-derived haplotypes of the parental strains across the congenic intervals in order to fine map the causative genetic variant(s). This strategy, which integrates different mechanistic levels of gene expression (transcriptome and metabonome), will define biomarkers associated with or predicting disease onset and progression and provide key information for identifying the underlying genes. Results will provide improved knowledge for therapeutic targets and disease prevention."
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