Skupina integrativní a systémové biologie komplexních onemocnění

Vedoucí / Head: prof. MUDr. Ondřej Šeda, Ph.D.


Aktuální vybrané publikace (2016-2017) /

Recent selected publications (2016-2017):


ZBTB16 and metabolic syndrome: a network perspective.

Šeda O, Šedová L, Včelák J, Vaňková M, Liška F, Bendlová B. Physiol Res. 2017 Sep 26;66(Supplementum 3):S357-S365.

Downregulation of Plzf Gene Ameliorates Metabolic and Cardiac Traits in the Spontaneously Hypertensive Rat.

Liška F, Landa V, Zídek V, Mlejnek P, Šilhavý J, Šimáková M, Strnad H, Trnovská J, Škop V, Kazdová L, Starker CG, Voytas DF, Izsvák Z, Mancini M, Šeda O, Křen V, Pravenec M.Hypertension. 2017 Jun;69(6):1084-1091. doi: 10.1161/HYPERTENSIONAHA.116.08798.

Heterozygous connexin 50 mutation affects metabolic syndrome attributes in spontaneously hypertensive rat.

Šeda O, Křenová D, Oliyarnyk O, Šedová L, Krupková M, Liška F, Chylíková B, Kazdová L, Křen V. Lipids Health Dis. 2016 Nov 21;15(1):199.

Adipose tissue (P)RR regulates insulin sensitivity, fat mass and body weight. Shamansurova Z, Tan P, Ahmed B, Pepin E, Seda O, Lavoie JL. Mol Metab. 2016 Aug 23;5(10):959-69. doi: 10.1016/j.molmet.2016.08.009.

Splicing mutation in Sbf1 causes nonsyndromic male infertility in the rat.

Liška F, Chylíková B, Janků M, Šeda O, Vernerová Z, Pravenec M, Křen V. Reproduction. 2016 Sep;152(3):215-23. doi: 10.1530/REP-16-0042.

Isolation of a Genomic Region Affecting Most Components of Metabolic Syndrome in a Chromosome-16 Congenic Rat Model.

Šedová L, Pravenec M, Křenová D, Kazdová L, Zídek V, Krupková M, Liška F, Křen V, Šeda O. PLoS One. 2016 Mar 31;11(3):e0152708. doi: 10.1371/journal.pone.0152708.

Inhibition of Lipolysis Ameliorates Diabetic Phenotype in a Mouse Model of Obstructive Sleep Apnea.

Weiszenstein M, Shimoda LA, Koc M, Seda O, Polak J. Am J Respir Cell Mol Biol. 2016 Aug;55(2):299-307. doi: 10.1165/rcmb.2015-0315OC.

Genome-wide methylation analysis of tubulocystic and papillary renal cell carcinomas.

Korabecna M, Geryk J, Hora M, Steiner P, Seda O, Tesar V. Neoplasma. 2016;63(3):402-10. doi: 10.4149/309_151102N559.

 The overall aim of our project is the systematic deconstruction of eco-genomic architecture of metabolic syndrome. We are pursuing this goal using genetically designed rat models with modulated gene expression (single genes or metabolic/signaling pathways). We are particularly focusing on four major aspects of metabolic syndrome eco-genomic “landscape”.

Early environment and metabolic programming of metabolic syndrome.

Our initial studies showed that the metabolic and hemodynamic outcomes of early environment challenges are to a certain extent dependent on the genomic background. We are set to determine major metabolic (biomarkers), transcriptomic (transcripts, pathways) and epigenomic (methylation) features related to developmental drivers of particular subsets of metabolic syndrome as seen in clinical setting.

Genetical genomics of metabolic syndrome.

This approach involves identification of signaling and expression modules playing a role in pathogenesis of metabolic syndrome and its aspects. By combining the existing and newly generated –omics level data from designed rat models of metabolic syndrome we are seeking the sex, age and organ-specific expression and signaling networks and playing crucial roles in pathogenesis of the metabolic syndrome.

Nutrigenomics and pharmacogenomics of metabolic syndrome.

Reflecting the complex network of dietary and pharmacological influences that only together with the genomic background make up the clinical presentation of metabolic syndrome in real life, we are systematically dissecting the diet-modulated, pharmacogenetic interactions we have previously described e.g. for the antidiabetic drug rosiglitazone. We are testing the effects of westernized diets and commonly used drugs known to affect features of metabolic syndrome when acting on specific genomic backgrounds in the designed rat models.

Towards integrative eco-genomics of metabolic syndrome.

By integration of the results from the above project and the available date we aim to proceed beyond the identification of individual risk and protective variants using the tools of system biology (analysis and modeling of genetic and signaling networks). This effort should lead us towards identification of functional genomic signatures connected with manifestation of specific forms of metabolic syndrome.


počet zobrazení: 814 poslední aktualizace: oseda, 10.11.2017
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