The genetics of metabolic and endocrine disease
Funding: Latvian Council of Science collaborration project "Genetic investigation of disease aetiology, pathogenesis and ageing processes in the Latvian population"
Subproject manager: Dr. biol. Jānis KLoviņš
With availability of novel molecular technologies the understanding of genetic mechanisms as well as their interaction between endogenous and environmental factors underlying development of multifactorial diseases has rapidly increased. Genetic variation, including single nucleotide polymorphisms (SNP) and copy number variations (CNV), of multiple loci as well as their changes on the level of epigenetics have been reported to be associated with increased risk of disease. Yet, genetic factors discovered so far explain only small proportion of disease heritability and still many questions remain.
The aim of this project is to explore under definite criteria selected single nucleotide polymorphisms (SNP) or copy number variations (CNV) in association with metabolic diseases with the main focus on study of genetic factors for type 2 diabetes. To provide more detailed assessment of implication of candidate genes and genome structures in the disease development, genetic variations will be analysed in context with well characterized phenotype including different metabolic markers.
Create the SNP genotyping panel based on genome wide association results, including polymorphisms representing several T2D candidate genes, like IGF2BP2, TCF7L2, FTO and others. Analyse selected SNPs in individuals with detailed phenotypic characterization from Endocrinology centre and Latvian Genome Data Base (LGDB).
To evaluate implementation of the copy number variations in T2D development. It is planned to choose few CNV selected based on available information on glucose homeostasis regulation processes in organism and/or genome loci related to increased T2D risk.
Possibility to include other metabolism related diseases like adiposity, cardiovascular diseases and acromegaly is also anticipated as well as additional genetic analysis for novel candidate genes adjusting obtained results with target SNP and gene-gene interaction data.
The evaluation of role of selected candidate genes and genome structure in T2D progression, by approach of selected complex markers and interactions will allow to successfully predict disease development.
The association have been demonstrated between SNPs in TCF7L2 locus and T2D development in Latvian population, also preliminary results for FTO and TMEM18 SNP alleles have been obtained.