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2012 © Institute for Molecular Medicine Finland FIMM

Genetic variation, disease genes, risk prediction

Aims

• Cataloging genetic variation in Finland and the Nordic countries
• Discovery of genetic modifiers of metabolic and metabolomic traits
• Development of statistical methods for genetic risk estimation and prediction in cardiovascular disease

Background

Unprecedented amount of new knowledge about the genetic architecture of common complex diseases has been accumulated over the past five years. Cataloguing common genetic variation in large well-phenotyped and population-based biobanks around the world has been the key factor for the success, and Finnish cohorts and case-control samples have often been instrumental in these studies. Currently, the biobank samples are going to provide much more precise description of our genomic, transcriptomic, metabolomics, proteomic and other high throughput variation.

The Ripatti research group studies these sources of variation and their relation to complex traits and diseases. With particular focus on cardiovascular diseases and metabolism, the aim is to identify genes modifying trait variation in populations, to estimate the effect sizes of and joint effects of genes, biomarkers and lifestyle and to predict the risk of future cases of clinical endpoints. To gain sufficient statistical power, the work often calls for national and international collaborations.

Over the past two years the group has described Finnish genetic variability using a special Finnish Hapmap 3 reference sample of common genetic variants (Surakka et al 2010). The Finnish Hapmap panel was also shown to add power when tagging common SNPs and copy number variants and imputing Finnish GWAS datasets for dense genetic marker resolution. It also demonstrates the power of having a local imputation panel, particularly when imputing lower frequency variants.

Together with members of the Nordic Center of Excellence in Complex Diseases, a Nordic common GWAS control database was established and the Nordic genetic population structure described (Leu et al 2010).

The group also participates in Global Lipid Genetics Consortium and ENGAGE to find genes modifying circulating lipid levels (Aulchenko et al 2009, Teslovich et al 2010; Surakka et al 2011). This work has recently been extended to the genetic architecture of a broad spectrum of serum metabolites where many new loci associated with metabolite levels were identified and shown to be associated with a range of metabolites way beyond conventional lipid measures (Kettunen et al 2012, Tukiainen et al 2012).

Recently, the group created a genetic risk score to help predicting coronary heart disease. The multilocus risk score was evaluated in six prospective cohorts from Finland and Sweden and shown to be strongly associated with increased risk of heart disease (Ripatti et al 2010).

Selected publications

• Aulchenko YS, Ripatti S, Lindqvist I et al: Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts, Nat Genet. 2009 Jan;41(1):47-55. Epub 2008 Dec 7.
• Leu M, Humphreys K, Surakka I et al. NordicDB: A Nordic pool and portal for genome-wide control data, European Journal of Human Genetics, advance online publication 28 July 2010; doi: 10.1038/ejhg.2010.112, 2010.
• Ripatti S, Tikkanen E, Orho-Melander M et al. A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses The Lancet 2010; 376: 1393–400.
• Surakka I, Kristiansson K, Anttila V et al. Founder Population-Specific HapMap Panel Improves Imputation Accuracy and CNV Tagging in GWA Studies, Genome Res., doi:10.1101/gr.106534.110. Published in Advance September 1, 2010.
• Teslovich TM, Musunuru K, Smith AV et al. Biological, Clinical, and Population Relevance of 95 Loci Mapped for Serum Lipid Concentrations Nature, Aug 5;466(7307):707-13, 2010.
• Tukiainen T, Kettunen J, Kangas AJ et al. Detailed Metabolic and Genetic Characterization Reveals New Associations for 30 Known Lipid Loci, Hum. Mol. Genet. first published online December 9, 2011 doi:10.1093/hmg/ddr581.
• Kettunen J, Tukiainen T, Sarin AP et al.Genome-wide association study identifies multiple loci influencing human serum metabolite levels, Nat. Genet. 2012, Jan 29. doi: 10.1038/ng.1073.

Group members

Funding