Extensive molecular profiling of systemic metabolism to understand and prevent cardiometabolic diseases - Mika Ala-Korpela and Johannes Kettunen

Project description

Cardiometabolic diseases are the leading cause of death and disability worldwide. We tackle these common diseases by applying novel molecular methods, metabolomics and lipidomics, in a large-scale epidemiology study setting, to identify new biomarkers and to obtain improved understanding of molecular pathways involved. Our Team has long-term experience in utilising quantitative serum NMR metabolomics in systems epidemiology. Now we are accompanying the serum NMR data with novel mass spectrometry lipidomics data (>800 individual lipid species quantified from circulation) from population-based cohorts (n>10,000) with genetics and extensive clinical data available. The molecular outputs of these platforms are complementary, constituting some 1,000 biomarkers per serum sample, thus providing an unprecedented characterisation of individuals’ systemic metabolism. Integrated data from these technologies in epidemiology do not currently exist. We are performing large-scale genetic analyses of the lipidome to increase understanding of the genetic background of circulating lipids. We are also utilising the genetic information to elucidate interlinks between lipoprotein and lipid metabolism, and to assess the causal chains between biomarkers, wide range of traditional risk factors and cardiometabolic disease outcomes. We anticipate that this research will lead to identification of new causal molecular pathways and biomarkers, amenable to intervention and presenting new translational opportunities for disease prevention.

Selected publications:

Ekholm J, Ohukainen P, Kangas AJ, Kettunen J, Wang Q, Karsikas M, Khan AA, Kingwell BA, Kähönen M, Lehtimäki T, Raitakari OT, Järvelin MR, Meikle PJ, Ala-Korpela M. EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics. Int J Epidemiol. 2020 Jan 
16. pii: dyz244. doi: 10.1093/ije/dyz244. [Epub ahead of print] PubMed PMID:31943015.

Ohukainen P, Kuusisto S, Kettunen J, Perola M, Järvelin MR, Mäkinen VP, Ala-Korpela M. Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease. Atherosclerosis. 2019 Dec 13;294:10-15. doi:10.1016/j.atherosclerosis.2019.12.009. [Epub ahead of print] PubMed PMID: 31931463.

Kettunen J, Holmes MV, Allara E, Anufrieva O, Ohukainen P, Oliver-Williams C, Wang Q, Tillin T, Hughes AD, Kähönen M, Lehtimäki T, Viikari J, Raitakari OT, Salomaa V, Järvelin MR, Perola M, Davey Smith G, Chaturvedi N, Danesh J, Di Angelantonio E, Butterworth AS, Ala-Korpela M. Lipoprotein signatures of cholesteryl ester transfer protein and HMG-CoA reductase inhibition. PLoS Biol. 2019 Dec 20;17(12):e3000572. doi: 10.1371/journal.pbio.3000572. PubMed PMID: 31860674.

Kuusisto S, Holmes MV, Ohukainen P, Kangas AJ, Karsikas M, Tiainen M, Perola M, Salomaa V, Kettunen J, Ala-Korpela M. Direct Estimation of HDL-Mediated Cholesterol Efflux Capacity from Serum. Clin Chem. 2019 Aug;65(8):1042-1050. doi:10.1373/clinchem.2018.299222. PubMed PMID: 30996052.

Tynkkynen T, Wang Q, Ekholm J, Anufrieva O, Ohukainen P, Vepsäläinen J, Männikkö M, Keinänen-Kiukaanniemi S, Holmes MV, Goodwin M, Ring S, Chambers JC, Kooner J, Järvelin MR, Kettunen J, Hill M, Davey Smith G, Ala-Korpela M. Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics. Int J Epidemiol. 2019 Jun 1;48(3):978-993. doi: 10.1093/ije/dyy287. PubMed PMID: 30689875.

Wang Q, Jokelainen J, Auvinen J, Puukka K, Keinänen-Kiukaanniemi S, Järvelin MR, Kettunen J, Mäkinen VP, Ala-Korpela M. Insulin resistance and systemic metabolic changes in oral glucose tolerance test in 5340 individuals: an
interventional study. BMC Med. 2019 Nov 29;17(1):217. doi: 10.1186/s12916-019-1440-4. PubMed PMID: 31779625.

Sliz E, Sebert S, Würtz P, Kangas AJ, Soininen P, Lehtimäki T, Kähönen M, Viikari J, Männikkö M, Ala-Korpela M, Raitakari OT, Kettunen J. NAFLD risk alleles in PNPLA3, TM6SF2, GCKR and LYPLAL1 show divergent metabolic effects. Hum
Mol Genet. 2018 Jun 15;27(12):2214-2223. doi: 10.1093/hmg/ddy124. PubMed PMID: 29648650.

Kettunen J, Ritchie SC, Anufrieva O, Lyytikäinen LP, Hernesniemi J, Karhunen PJ, Kuukasjärvi P, Laurikka J, Kähönen M, Lehtimäki T, Havulinna AS, Salomaa V, Männistö S, Ala-Korpela M, Perola M, Inouye M, Würtz P. Biomarker Glycoprotein Acetyls Is Associated With the Risk of a Wide Spectrum of Incident Diseases and Stratifies Mortality Risk in Angiography Patients. Circ Genom Precis Med. 2018 Nov;11(11):e002234. doi: 10.1161/CIRCGEN.118.002234. PubMed PMID: 30571186.

Kettunen J, Demirkan A, Würtz P, Draisma HH, Haller T, Rawal R, Vaarhorst A, Kangas AJ, Lyytikäinen LP, Pirinen M, Pool R, Sarin AP, Soininen P, Tukiainen T, Wang Q, Tiainen M, Tynkkynen T, Amin N, Zeller T, Beekman M, Deelen J, van Dijk KW, Esko T, Hottenga JJ, van Leeuwen EM, Lehtimäki T, Mihailov E, Rose RJ, de Craen AJ, Gieger C, Kähönen M, Perola M, Blankenberg S, Savolainen MJ, Verhoeven  A, Viikari J, Willemsen G, Boomsma DI, van Duijn CM, Eriksson J, Jula A, Järvelin MR, Kaprio J, Metspalu A, Raitakari O, Salomaa V, Slagboom PE, Waldenberger M, Ripatti S, Ala-Korpela M. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA. Nat Commun. 2016 Mar 23;7:11122. doi: 0.1038/ncomms11122. PubMed PMID: 27005778.

Würtz P, Wang Q, Soininen P, Kangas AJ, Fatemifar G, Tynkkynen T, Tiainen M, Perola M, Tillin T, Hughes AD, Mäntyselkä P, Kähönen M, Lehtimäki T, Sattar N, Hingorani AD, Casas JP, Salomaa V, Kivimäki M, Järvelin MR, Davey Smith G, Vanhala M, Lawlor DA, Raitakari OT, Chaturvedi N, Kettunen J, Ala-Korpela M. Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase.  J Am Coll Cardiol. 2016 Mar 15;67(10):1200-1210. doi: 10.1016/j.jacc.2015.12.060. PubMed PMID: 26965542.

People

Johannes Kettunen

Johannes Kettunen

Professor