Mika Ala-Korpela
BSc, MSc, PhLic, PhD in Physics, Docent in Biological NMR
Professor of Computational Medicine
Systems Epidemiology
Dr Ala-Korpela is a Professor of Computational Medicine at the Faculty of Medicine, University of Oulu, and a Research Director at the School of Pharmacy, University of Eastern Finland. He is an honorary Professor of Computational Medicine at the University of Bristol, UK, after working there for over 6 years.
Professor Ala-Korpela has been one of the principal investigators at the Biocenter Oulu since 2016. His newest project at BCO for 2024-2027 is titled Innovative multi-domain metabolomics paradigm to disrupt metabolic health profiling and to improve cardiometabolic disease prevention.
Since 2017 he has been an Associate Editor for the International Journal of Epidemiology (IF 7.7, JUFO 3) and he has published 25 papers in the journal.
Professor Ala-Korpela was recently awarded a 4-year 0.5 M€ research grant (2023-2027) from the Academy of Finland, the Research Council for Biosciences, Health and Environment for a project titled New open access platform of quantitative high-throughput urine metabolomics to uncover molecular risk factors and drug effects on cardiometabolic diseases. He also recently got research grants (2023 & 2024) from the Finnish Foundation for Cardiovascular Research for his research in the area of urinary metabolomics in relation to cardiometabolic diseases.
Prof Ala-Korpela is listed among the top medical scientists in the world: https://research.com/scientists-rankings/medicine. His ranking is 178 in Finland out of the 219 Finnish medical scientists that reached the list (i.e., the Discipline H-index is at least 70). From the University of Oulu only a handful of currently active scientists reached the list.
His research focuses on the applications of ‘omics technologies in clinical and systems epidemiology to understand the molecular and genetic characteristics of metabolic health and disease development and to utilise these data in advancing disease risk assessment and prevention.
In a recent bibliometric analysis on metabolomics in coronary artery disease research, Prof Ala-Korpela was classified as the most productive author (Front. Cardiovasc. Med. 9, 804463, 2022): https://www.frontiersin.org/articles/10.3389/fcvm.2022.804463/full.
Prof Ala-Korpela has published ~270 articles in international peer-reviewed journals, and is in a leading position in 40% of them. A marked portion of his papers has been published in the most appreciated scientific journals in various medical fields, encapsulating his multidisciplinary expertise in the area or molecular and medical biosciences.
His H-index is 84 and he has 74 papers with more than or equal to 100 citations and 12 papers with more than 500 citations; his total number of citations is close to 29,000 with a steep increase in annual citations in recent years, i.e., around 3,000 citations a year since 2021. These are obvious signs of broad scientific relevance of his publications in biomedicine.
Three recent representative papers:
Genome-wide characterization of circulating metabolic biomarkers. Nature 2024;628(8006):130-138. https://www.nature.com/articles/s41586-024-07148-y
Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers. International Journal of Epidemiology 2024; 53(1): dyad162. https://doi.org/10.1093/ije/dyad162
Apt interpretation of comprehensive lipoprotein data in large-scale epidemiology: disclosure of fundamental structural and metabolic relationships. International Journal of Epidemiology 2022;51(3):996–1011. https://doi.org/10.1093/ije/dyab156
Research interests
- Systems & molecular epidemiology
- Multiple 'omics - metabolomics, lipidomics and genetics
- Metabolic phenotyping and biomarkers
- Cardiometabolic health and diseases
- Disease risk assessment and prevention
- Large-scale population studies and biobanks
- Causality and Mendelian randomization
- Artificial intelligence and machine learning
- NMR spectroscopy and mass spec lipidomics
- Scientific robustness and reproducibility
- Resisting scientific hype
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