MITIN is proposing to elucidate the interplay between the insulin signaling pathway and the mitochondrial function

Dr. Matej Oresic

Matej Oresic

Contact e-mail

matej.oresicarrobavtt.fi

Background

Metabolomics systematically studies the metabolome, i.e., the small molecules in cells, tissues and biofluids. New analytical methods combined with bioinformatics provide a way to measure the extended metabolome. The metabolic phenotype is sensitive to subtle but pathogenically relevant factors such as age, lifestyle, nutrition and the microbe environment of the gut. Changes in the concentrations of metabolites may thus reflect both genetic and environmental factors influencing later susceptibility to chronic diseases.

We are investigating:

  • how are the genetic and environmental factors imprinted in the metabolome;
  • the mechanisms by which alterations of metabolome lead to (patho)physiological changes at the systems level;
  • discovery and functional characterization of metabolic markers for multiple diseases or responses to interventions and environmental challenges.

We are relying on metabolomics techniques to characterize the metabolome, combined with systems biology strategies to investigate, e.g., how changes in gene expression or in gut microbial composition alter the metabolic phenotypes.

Selected publications

  1. M. Orešič, V. Hänninen, A. Vidal-Puig, Lipidomics: a new window to biomedical frontiers, Trends Biotechnol. (2008). doi:10.1016/j.tibtech.2008.09.001
  2. J. Nikkilä, M. Sysi-Aho, A. Ermolov, T. Seppänen-Laakso, O. Simell, S. Kaski, M. Orešič, Gender dependent progression of systemic metabolic states in early childhood, Mol. Syst. Biol. 4, e197 (2008).
  3. M. Sysi-Aho, A. Vehtari, V. Velagapudi, J. Westerbacka, L. Yetukuri, R. Bergholm, M.-R. Taskinen, H. Yki-Järvinen, M. Orešič, Exploring the lipoprotein composition using Bayesian regression on serum lipidomic profiles, Bioinformatics 23, i519-i528 (2007).
  4. L. Yetukuri, M. Katajamaa, G. Medina-Gomez, T. Seppänen-Laakso, A. Vidal Puig, and M. Orešič, Bioinformatics strategies for lipidomics analysis: characterization of obesity related hepatic steatosis, BMC Syst. Biol. 1, e12 (2007).
  5. K. H. Pietiläinen, M. Sysi-Aho, A. Rissanen, T. Seppänen-Laakso, H. Yki-Järvinen, J. Kaprio, and M. Orešič, Acquired obesity is associated with changes in the serum lipidomic profile independent of genetic effects – a monozygotic twin study, PLoS ONE 2(2), e218 (2007).

Research Group Website

http://sysbio.vtt.fi