Innovative multi-domain metabolomics paradigm to disrupt metabolic health profiling and to improve cardiometabolic disease prevention
Project information
Project duration
-
Project funder
Project coordinator
University of Oulu
Unit and faculty
Contact information
Project leader
- Professor of Computational Medicine
Researchers
Project description
Project leaders: Mika Ala-Korpela and Ville-Petteri Mäkinen
We have long-term experience in utilising blood-based quantitative NMR metabolomics in systems epidemiology. Currently we are developing a new open-access urine NMR metabolomics platform at the Research Unit of Population Health, in collaboration with the School of Pharmacy & the NMR Metabolomics Laboratory at the University of Eastern Finland. In this unique project we will study over 100,000 individuals with multiple ethnic backgrounds combining data from their urine samples, systemic metabolism, and genetics. Urine metabolomics at epidemiological scale is in its infancy and thus the unprecedented molecular information is likely to provide new insight on kidney function and related biomarkers on the renal-cardiometabolic system. We are also in the process to translate the new knowledge and methodologies into a leading-edge paradigm facilitating cost-effective use of metabolomics in local laboratories and clinics to maximise public health impact. Together these efforts make concrete steps towards the transition of metabolomics from bench to bedside.
Key publications
Karjalainen MK, Karthikeyan S, Oliver-Williams C, Sliz E, Allara E, . . . , Danesh J, Ala-Korpela M, Butterworth AS, Kettunen J. Genome-wide characterization of circulating metabolic biomarkers. Nature. 2024, in press.
Li T, Ihanus A, Ohukainen P, Järvelin MR, Kähönen M, Kettunen J, Raitakari OT, Lehtimäki T, Mäkinen VP, Tynkkynen T, Ala-Korpela M. Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers. Int J Epidemiol. 2024 Feb 1;53(1):dyad162. doi: 10.1093/ije/dyad162.
Mäkinen VP, Kettunen J, Lehtimäki T, Kähönen M, Viikari J, Perola M, Salomaa V, Järvelin MR, Raitakari OT, Ala-Korpela M. Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic. Int J Obes (Lond). 2023 Jun;47(6):453-462. doi: 10.1038/s41366-023-01281-w.
Ala-Korpela M, Lehtimäki T, Kähönen M, Viikari J, Perola M, Salomaa V, Kettunen J, Raitakari OT, Mäkinen VP. Cross-sectionally Calculated Metabolic Aging Does Not Relate to Longitudinal Metabolic Changes-Support for Stratified Aging Models. J Clin Endocrinol Metab. 2023 Jul 14;108(8):2099-2104. doi: 10.1210/clinem/dgad032.
Mäkinen VP, Karsikas M, Kettunen J, Lehtimäki T, Kähönen M, Viikari J, Perola M, Salomaa V, Järvelin MR, Raitakari OT, Ala-Korpela M. Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults. Int J Epidemiol. 2022 Dec 13;51(6):1970-1983. doi: 10.1093/ije/dyac062.
Ala-Korpela M, Zhao S, Järvelin MR, Mäkinen VP, Ohukainen P. Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology: disclosure of fundamental structural and metabolic relationships. Int J Epidemiol. 2022 Jun 13;51(3):996-1011. doi: 10.1093/ije/dyab156.
Wang Q, Oliver-Williams C, Raitakari OT, Viikari J, Lehtimäki T, Kähönen M, Järvelin MR, Salomaa V, Perola M, Danesh J, Kettunen J, Butterworth AS, Holmes MV, Ala-Korpela M. Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis. Eur Heart J. 2021 Mar 21;42(12):1160-1169. doi: 10.1093/eurheartj/ehaa972.
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. 2020 Feb;294:10-15. doi: 10.1016/j.atherosclerosis.2019.12.009.
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.
Mäkinen VP, Soininen P, Forsblom C, Parkkonen M, Ingman P, Kaski K, Groop PH; FinnDiane Study Group; Ala-Korpela M. 1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death. Mol Syst Biol. 2008;4:167. doi: 10.1038/msb4100205.