Mika Ala-Korpela
Ph.D. in Physics, Docent in Biological NMR
Professor in Computational Medicine
Consultant in Computational Medicine
Professor in Computational Medicine
Mobile: +358 40 1977 657
The reality we face in trying to understand metabolic disorders is the
nonexistence of single biomarkers, real cut-off values and even separate diseases.
Research Focus
The research focuses on lipoprotein biophysics and metabolism, development and applications of multi-parametric data analysis methods for metabolic phenotyping and risk assessment, and the use of various –omics technologies, particularly high-throughput serum NMR metabolomics, in clinical and epidemiological studies of metabolic disorders. Academic ActivityDr Ala-Korpela has published over 100 articles in international peer-reviewed journals, his h-index is 26 and his papers have been cited over 2,000 times. He has also published some 220 conference abstracts, proceedings or papers, one US-patent, and a Popular Science Book (in Finnish) on cybernetics and human-machine interaction. Dr Ala-Korpela is a regular peer reviewer for various scientific journals. He was also a Lead Guest Editor for a Special Issue on Clinical and Epidemiological Metabonomics in the Journal of Biomedicine and Biotechnology (2011). Dr Ala-Korpela has chaired several sessions in scientific meetings and given almost 50 invited talks in international meetings and seminars. The most recent and forthcoming talks can be seen on the side bar on the right. He is currently holding grants from the Academy of Finland in the Responding to Public Health Challenges Research Programme, from the Finnish Diabetes Research Foundation, and from the Finnish Foundation for Cardiovascular Research to study the role of combined genetics and metabolomics in the risk assessment and prediction of vascular and metabolic diseases and their complications. He is also having funding from TEKES, the Finnish National Technology Agency, to elaborate the role of serum NMR metabolomics in individual healthcare. Various funding for serum NMR metabolomics is also arising from national & international collaboration, for example, with the University of Turku, University of Tampere, University of Eastern Finland, Estonian Genome Center, Instituto Nacional de Ciencias Médicas y Nutrición México, University of Bristol, University of Glasgow, Imperial College London and University College London. Dr Ala-Korpela has previously been a leader of the Computational Systems Biology section of the Finnish Academy Centre of Excellence in Computational Complex Systems Research. Dr Ala-Korpela is currently holding a visiting professorship at Central South University, College of Chemistry and Chemical Engineering, Changsha, China (2010-2013). During February - July 2012 Dr Ala-Korpela was a visiting professor at Imperial College London, School of Public Health, Department of Epidemiology and Biostatistics, London, UK
Computational MedicineProfessor Ala-Korpela has more than two decades of experience in biomedical NMR spectroscopy and has pioneered high-throughput applications of NMR-based metabolomics in molecular epidemiology and functional genetics. Under his lead Computational Medicine was selected as one of the strategic scientific areas for development and funding at the University of Oulu for 2012-2016. The Metabolomics PlatformSince 2004 Professor Ala-Korpela's team has focused on developing an NMR-based metabolomics platform for human serum (and plasma). An operational platform using a 500 MHz instrument and a novel fully automated and quantitative methodology has been up and running since late 2008. Data from approximately 100,000 samples have been measured. The methodology provides information on >100 primary metabolic measures and >100 derived variables with clear biochemical interpretation and significance. The directly measured metabolites include lipoprotein subclass distribution with 14 subclasses quantified including particle concentrations and individual subclass lipids, low-molecular-weight metabolites such as amino acids, ketone bodies, and creatinine, and detailed molecular information on serum lipid extracts including free and esterified cholesterol, sphingomyelin, degree of saturation and ω-3 fatty acids. Derived variables include selected ratios of metabolites implicated in lipolysis, proteolysis, ketogenesis and glycolysis as well as reagents and products of enzymatic reactions and measures obtained with the extended Friedewald formula, eg., apolipoprotein A-I and B. This platform has recently been applied in various large-scale epidemiological and genetic studies the results of which have been published in the leading scientific journals. Genome-wide association study identifies multiple loci influencing human serum metabolite levels Nature Genetics 44, 269-276, 2012 Publication HighlightsA complete list of publications from the Computational Medicine Research Group 2005– can be found here. Click here for a list of publications before 2005. Long-term leisure-time physical activity and serum metabolome Circulation 127, 340-348, 2013 Triglyceride-cholesterol imbalance across lipoprotein subclasses predicts diabetic kidney disease and mortality in type 1 diabetes (the FinnDiane Study). Journal of Internal Medicine 2012, in press Metabolic Signatures of Insulin Resistance in 7,098 Young Adults Diabetes 61, 1372-1380, 2012 High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis European Heart Journal 33, 2307-2316, 2012 Genome-wide association study identifies multiple loci influencing human serum metabolite levels Nature Genetics 44, 269-276, 2012 Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci Human Molecular Genetics 21 (6), 1444-1455, 2012 Genome-wide association studies and systems biology: Together at last. Trends in Genetics 27, 493-498, 2011 Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nature Genetics 43, 1131-8, 2011 Metabonomic, transcriptomic, and genomic variation of a population cohort. Molecular Systems Biology 6, 441, 2010 Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing maps. Journal of Lipid Research 51, 431-9, 2010 High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism. Analyst 134, 1781-5, 2009 1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death Molecular Systems Biology 4, 167 (1-12), 2008 The potential role of body fluid 1H NMR metabonomics as a prognostic and diagnostic tool Expert Review of Molecular Diagnostics 7, 761-773, 2007 Application of self-organizing maps in conformational analysis of lipids. Journal of the American Chemical Society 123, 810-816, 2001 Structure of low density lipoprotein (LDL) particles. Basis for understanding molecular changes in modified LDL. Biochimica Biophysica Acta - Molecular and Cell Biology of Lipids 1488, 189-210, 2000 1H NMR spectroscopy of human blood plasma. Progress in Nuclear Magnetic Resonance Spectroscopy 27, 475-554, 1995 1H NMR based quantitation of human lipoproteins and their lipid contents directly from plasma. Journal of Lipid Research 35, 2292-2304, 1994 Effects of orientational order and particle size on the NMR line positions of lipoproteins. Physical Review Letters 72, 4049-4052, 1994 |
Contact
Mika Ala-Korpela, PhD
University of Oulu Consultant in Computational Medicine Professor of Computational Medicine
Mobile: +358 40 1977 657 |
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