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1H NMR Metabonomics
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Genomics, transcriptomics and proteomics, represent the genomistic main discipline in life sciences. The genetic approaches are powerful in the rare cases in which the disease states are controlled by single genetic defects. However, their general applicability is limited in the case of complex multi-genetic diseases such as diabetes and coronary heart disease. In general, the phenotype of normality (health) as well as the phenotype of a multi-genetic disease is not well characterised. It is, however, reflected by the systemic metabolite composition and the metabolic interactions. Thus, a key 'omics in understanding of biomolecular function is metabonomics.
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Within these collaborative clinical and biochemical studies we will put particular effort towards a comprehensive systems biology approach in which we will be integrating complementary metabolic data, including lipoprotein subclass profile, from NMR spectroscopy with all available other data of clinical significance (including various clinically utilised biochemical markers, diagnostic data, other spectroscopic data as well as genetic information). We believe that this kind of multimodal and multidimensional data pool will prove especially useful in giving means to understand the molecular basis of atherothrombosis and other related diseases as type 1 and type 2 diabetes.
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It is our strong intention to develop methodologies towards increased biomolecular understanding and thereby towards individual risk assessment and diagnostics of vascular diseases. One of the potential key outcomes from the proposed research here are personalised approaches reflecting the natural complexity of human pathophysiology and the intrinsically indistinct borderline between health and disease. We strongly believe that our efforts to take the advantage of different 'omics sciences and the digitalisation of information to develop innovative socio-economical approaches will eventually save money from the society and also reduce human suffering.
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Metabonomiikkatutkimukseen rahoitusta Suomen Akatemialta
Laskennallisen lääketieteen ryhmälle on myönnetty Suomen Akatemiasta, kansanterveyden haasteet -tutkimusohjelmasta (SALVE) tutkimusrahoitusta yhteistyössä Prof. Markku Savolaisen johtaman tutkimusryhmän kanssa (Oulun yliopisto ja Biocenter Oulu). Tutkimus keskittyy uusien menetelmien kehittämiseen metabolisten riskien havaitsemiseen ja hoitamiseen.
Prof. Mika Ala-Korpelan johtama osaprojekti "1H NMR -metabonomiikka - molekylaarinen menetelmä henkilökohtaisen tautiriskin arvioimiseksi" keskittyy ko. uuden metodologian kehittämiseen ja soveltamiseen vaskulaaristen kansantautien riskien arviointiin.
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Biotieteissä genetiikan näkökulma on perinteisesti korostunut. Genetiikan voima tulee kuitenkin parhaiten esiin niissä harvinaisissa tapauksissa, joissa yksittäiset geenivirheet kontrolloivat tautiprosessia. Genetiikan yleinen käytännöllinen sovellettavuus on kuitenkin varsin rajallista tapauksissa, joissa tautin etiologia on useiden geenien säätelemää. Näin on kaikissa kansantaudeissa, kuten diabeteksessa ja sydän- ja verisuonitaudeissa. Yleisesti, niin fysiologisen normaalitilan kuin erilaisten tautitilojenkin metabolinen fenotyyppi on vaikeasti määriteltävissä. Näistä voidaan kuitenkin saada hyvä yleiskuva tarkastelemalla systeemistä metaboliaa ja metabolisia profiileita, esim. veren seerumissa. Yhdeksi biotieteiden merkittävistä sovelluskentistä onkin viime aikoina noussut metabonomiikka; ihmisen kehon nesteiden 1H NMR -spektroskopia on yksi keskeisimpiä alueen tutkimuskohteista.
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Tässä yhteistyössä on tarkoitus tehdä laajaa kliinistä ja biokemiallista yhteistyötä ja pyrkiä tautitilojen riskin kokonaisvaltaiseen arviointiin ja ymmärtämiseen systeemibiologisesta näkökulmasta. Seerumin monipuolisten metabolisten profiilien, mukaanlukien lipoproteiinien alaluokat, määrittäminen 1H NMR -spektroskopialla on yhteistyössä keskeisessä roolissa. Yhtenä keskeisenä tavoitteena on geneettisen ja metabolisen informaation yhdistäminen molekylaaristen tautiprosessien ymmärtämiseksi ja riskien ennustamiseksi.
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Uskomme tällaisen monitieteisen ja holistisen näkökulman hyödyttävän erityisesti multigeenisten kansantautien tapauksessa, missä terveyden ja sairauden raja on erittäin vaikeasti määriteltävissä. Selkeä tavoitteemme on parantaa vaskulaaritautien riskin ennustamista siten, että voitaisiin saavuttaa yhteiskunnan terveyden huollon kustannussäästöjä ja samalla yksilöiden parempaa terveyden ylläpitoa ja tauteihin liittyvien ongelmien ja tuskan minimointia. Uskomme tähän päästävän terveyttä ylläpitävillä menetelmillä ja riittävän aikaisella puuttumisella metabolisiin ongelmiin – ei perinteisesti sairauksia hoitamalla.
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FT Mika Ala-Korpela nimitetty laskennallisen lääketieteen professoriksi
Dosentti, FT Mika Ala-Korpela on 1. maaliskuuta 2009 alkaen nimitetty laskennallisen lääketieteen professoriksi Oulun yliopiston lääketieteellisessä tiedekunnassa, kliinisen lääketieteen laitoksella. Professuuri on yksi ensimmäisistä maailmassa tällä uudella tieteenalalla.
Laskennallinen lääketiede yhdistää ja kehittää matematiikan, biokemian ja laskennallisen tekniikan ja tieteen menetelmiä ja monitieteisiä lähestymistapoja eri tautien kvantitatiiviseen ja molekylaariseen ymmärtämiseen, riskianalyysiin ja diagnostiikkaan. Keskeisenä osatekijänä on systeemibiologinen näkemys ihmisen toiminnasta ja tämän kompleksisuuden käsittelyyn soveltuvat uudet kokeelliset ja laskennalliset menetelmät. Yhteiskunnallisena tavoitteena on sosioekonomisten lähestymistapojen integrointi tautien riskianalytiikkaan ja hoidon suunnitteluun; näin on mahdollista saada merkittäviä säästöjä terveydenhuollossa ja samalla ennalta ehkäistä yksilötasolla kärsimystä tuovien tautien eteneminen ja tautitapahtumat.
Lisätietoja: / 050 35 35 457
Dr Mika Ala-Korpela has been appointed to a Chair in Computational Medicine in the University of Oulu, Faculty of Medicine, Institute of Clinical Medicine. University of Oulu is thus among the pioneers in the world to recognise this new scientific field.
FT Mika Ala-Korpela nimitetty laskennallisen lääketieteen professoriksi
Metabonomiikkatutkimukseen rahoitusta Suomen Akatemiasta
Estimation of VLDL, IDL, LDL, HDL2, apoA-I and apoB from the Friedewald inputs – apoB and IDL, but not LDL, are associated with mortality in type 1 diabetes.
Annals of Medicine, in press, 2009.
A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer's disease.
Biochemical and Biophysical Research Communications 375, 356-361, 2008.
1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death a featured article in
Molecular Systems Biology 4, 167 (1-12), 2008.
M. Ala-Korpela at
Metabomeeting 2009
in Norwich, UK on July 5-8, 2009
M. Ala-Korpela & A. J. Kangas at
The Netherlands Metabolomics Centre (NMC)
in Utrecht, The Netherlands on July 10, 2009
M. Ala-Korpela at
The 26th Annual Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB 2009)
in Antalya, Turkey on October 1-3, 2009
M. Ala-Korpela at
A seminar day at the Central South University
in Changsha, China on October 26, 2009
Computational Medicine Research Group - multidisciplinary organisation
The Computational Medicine Research Group is homed by the University of Oulu and Biocenter Oulu, Faculty of Medicine, Institute of Clinical Medicine, Oulu, Finland. The Group is lead by Prof. Mika Ala-Korpela.
Computational Medicine is a new multidisciplinary field of research to understand the biological mechanisms and to improve the diagnosis, prediction and treatment of human diseases through applications of computational science. Our scientific focus is in the area of metabonomics and systems biology applications in the early risk assessment, prediction and molecular understanding of vascular diseases and their complications. Our mission can be specified as:
- To develop holistic methodologies to understand the molecular aetiology, risk assessment, prevention, diagnostics and treatment of common human diseases via systems biology perspective and with multidisciplinary data, multimodal imaging and bioinformatics;
- To develop personalised approaches reflecting the natural complexity of human (patho)physiology and the intrinsically indistinct borderline between health and disease;
- To take advantage of various ‘omics sciences and the digitalisation of information to develop innovative socio-economical approaches to save money from the society and to reduce human suffering.
The Group is now part of the Academy of Finland Responding to Public Health Challenges Research Programme (SALVE) 2009-2012 in collaboration with Prof. Markku Savolainen (University of Oulu and Biocenter Oulu) who is leading the metabolic consortium entitled Improved methods of lifestyle modification for patients at high risk for metabolic syndrome. Additional funding for the subproject lead by Prof. Marjo-Riitta Järvelin was awarded from the Imperial College, London. The subproject lead by Prof. Mika Ala-Korpela is entitled 1H NMR metabonomics - a holistic molecular approach on individual disease risk assessment and focuses on the development and applications of this new technology to the risk assessment of common vascular diseases.
Together with our collaborators we now form an international computational medicine research consortium focusing on common vascular diseases and their interplay; currently ~60 scientists from ~25 laboratories in ~12 countries are involved.
The Group was launched from scratch in summer 2004 in the Laboratory of Computational Engineering (LCE) at the Helsinki University of Technology (HUT) in the context of Computational Systems Biology by Docent Mika Ala-Korpela. It grew to its shape and focus as a joint endeavour of the Department of Biomedical Engineering and Computational Science (BECS) at HUT and the Department of Diabetes Genetics at the Folkhälsan Research Center, Biomedicum, Helsinki, Finland. The collaboration with Prof. Kimmo Kaski (at HUT) and Docent Per-Henrik Groop (at Folkhälsan) was in a central position in the development phase. The Group was also part of the Academy of Finland Centre of Excellence in Computational Complex Systems Research (2006-2008).
Towards personalised medicine
This application of 1H NMR metabonomics of serum demonstrates the diffuse nature of complex vascular diseases and the limitations of single diagnostic biomarkers, but it also promises cost-effective solutions through high-throughput analytics and advanced computational methods, as illustrated here for patients with type 1 diabetes in a real clinical situation.
Mäkinen, Soininen, Forsblom, Parkkonen, Ingman, Kaski, Groop & Ala-Korpela
Molecular Systems Biology 4, 167 (1-12), 2008
Understanding the factors that influence human health and cause diseases has always been a driving force of research. With the exciting progress in high-throughput analytical techniques and the profound integration of experimental and computational approaches, medicine has newly got hold of new technological and conceptual tools for holistic investigations of living organisms at the system level. The still young discipline of systems biology has mostly been applied to study well-characterised model organisms. However, the first human studies also report on tremendous opportunities that combined molecular and computational technologies can have for the progress of personalised and predictive medicine.
Metabonomics – a new field of ‘omics’
In retrospect, we wonder why we spent millions on the genome.
Nature News, 1 March, 2007
1H NMR spectroscopy techniques are rather fast and straightforward to apply to all biofluids in vitro and also to various tissues ex vivo and in vivo – approaches combining data on various biofluids and/or tissues of the same individuals (integrated metabonomics) are thus increasingly used to study systems level biochemistry.
Ala-Korpela
Expert Review of Molecular Diagnostics 7, 761–773, 2007
Genomics, transcriptomics and proteomics, represent the ‘genomistic’ main discipline in life sciences. The phenotype of a biological system, however, is principally reflected by its metabolite composition and their interactions. Therefore, a key ‘omics’ in understanding of biomolecular function is metabonomics: the measurements of multi-metabolic responses to pathophysiological stimuli or genetic modifications. Mass spectrometry (MS) and 1H nuclear magnetic resonance (NMR) spectroscopy have become the two key technologies in this area. An appealing feature of NMR is its specific yet non-selective nature.
Measuring metabolites is not new. For decades, clinicians have charted chemistries in blood, urine, and other body fluids - using glucose to track diabetes and cholesterol to monitor heart disease, for example. What is new in the metabonomics approach is that we are now casting a wider net, attempting to gather an unbiased sample of metabolites that can serve as a snapshot of an organism's physiology. The ultimate goal of metabonomics is to be able to distinguish between an individual who is healthy and someone who has (the diagnostic dimension) - or might develop (the risk assessment dimension) - a disease.
Towards new technological platforms
The presented novel scheme utilising magnetic resonance methodologies in the risk assessment of long-term risk for atherothrombotic events might be operational in the near future saving both human suffering and societal health costs.
Ala-Korpela, Sipola & Kaski
Annals of Medicine 38, 322-336, 2006
One of the great challenges for 21st century medicine is to deliver effective therapies that are tailored to the biological state of an individual to enable personalised healthcare solutions. We have recently outlined the advantages of magnetic resonance (MR) technologies in detecting molecular and cellular processes related to developing coronary heart disease (CHD): lipoprotein subclass analytics by in vitro 1H NMR metabonomics of serum is used for risk assessment and in vivo MR imaging for direct detection of plaque composition and vulnerability. This would clinically facilitate early individual primary prevention and also give a personal rationale to comply with lifestyle modifications and potential drug therapies.
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Mika Ala-Korpela, PhD
Professor in Computational Medicine
University of Oulu & Biocenter Oulu
Faculty of Medicine
Institute of Clinical Medicine
FI-90014 University of Oulu
Finland
Mobile: + 358 50 35 35 457
E-mail: 
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