Jürgen König, Department of Nutritional Sciences, University of Vienna

Transkript

1 Jürgen König, Department of Nutritional Sciences, University of Vienna

2 Was ist Nutrigenomics? ti i Nutrigenomics is the science that examines the response of individuals to food compounds using post genomic and related technologies (e.g. genomics, transcriptomics, proteomics, metabol/nomic etc.). The long term aim of nutrigenomics is to understand how the whole body responds to real foods using an integrated approach termed 'systems biology'. The huge advantage in this approach is that the studies can examine people (i.e. populations, sub populations based on genes or disease and individuals), food, life stage and life style tl without t preconceived ideas. NuGo The European Nutrigenomics Organisation,

3 Die "omics" Kaskade " Genome What can happen The genome of an organism is a complete DNA sequence of one set of chromosomes; for example, one of the two sets that t a diploid id individual id carries in every somatic cell. The term genome can be applied specifically to mean the complete set of nuclear DNA (i.e., the "nuclear genome") but can also be applied to organelles that contain their own DNA, as with the mitochondrial genome or the chloroplast genome. organisms is usually referred to as genomics, which distinguishes it from genetics which generally studies the properties of single genes or groups of genes.

4 Die "omics" Kaskade " Genome What can happen Transcriptome Whatappearsto be happening The transcriptome is the set of all messenger RNA (mrna), or "transcripts", produced in one or a population of cells. Unlike the genome, which is roughly fixed for a given cell line, the transcriptome can vary with ih external environmental conditions. Because it includes all mrna transcripts in the cell, the transcriptome reflects the genes that t are being actively expressed at any given time.

5 Die "omics" Kaskade " Genome What can happen Transcriptome What appears to be happening Proteome What makes it happen The proteome is the entire complement of proteins in a given biological organism or system at a given time, i.e. the protein products of the genome. The proteome is larger than the genome in the sense that there are more proteins than genes. This is due to alternative splicing of genes and post translational ti l modifications like glycosylation l or phosphorylation.

6 Die "omics" Kaskade " Genome Transcriptome What appears to be happening Proteome What makes it happen Metabolome What has happened and is happening

7 Die "omics" Kaskade " Genome What can happen Transcriptome What appears to be happening Proteome Metabolome What makes it happen What has happened and is happening Phenotype?

8 Single Nucleotide Polymorphisms SNPs A Single Nucleotide Polymorphism or SNP (pronounced snip) is a DNA sequence variation occurring when a single nucleotide A, T, C, or G in the genome (or other shared sequence) differs between members of a species (or between paired chromosomes in an individual). For example, two sequenced DNA fragments from different individuals, AAGCCTA to AAGCTTA, contain a difference in a single nucleotide. In this case we say that there are two alleles: C and T.

9 Si Single Nucleotide Polymorphisms Single Nucleotide Polymorphisms SNPs l N l tid P l hi SNP SNP SNPs GCC to GCT (at position 677 of the bp sequence) Ala Val GCC GCT Th G The Genetic Code i C d

10 Si Single Nucleotide Polymorphisms Single Nucleotide Polymorphisms SNPs l N l tid P l hi SNP SNP SNPs Translation of the modified genetic code of the MTHFR gene leads to insertion of a valin residual instead of an alanin residual into the enzyme peptide.

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12 Nutrigenomics Nti i und Gesundheit

13 Nutrigenomics Nti i und Gesundheit Protein Modification Function Apolipoprotein A1 G75 A cholesterol transport in HDL Apolipoprotein E Cys112 Arg lipid metabolism CETP C629 A cholesterol transfer SREBP Gly595 Ala cholesterol homeostasis enos T786 C endothelial NO synthesis PON1 Gln192 Arg anti LDL oxidation NPY Leu7 Pro energy metabolism ADRB3 Trp64 Arg fat storage VDR G283 A cell proliferation CYP1B1 T3801 C activation of procarcinogens COL1A1 G1546 T bone metabolism MTHFR C677 T folate metabolism

14 Nutrigenomics Nti i und Gesundheit Genotyping of individuals and population groups on polymorphisms related to nutrition and nutrient metabolism

15 Nutrigenomics Nti i und Gesundheit Intervention studies to test the effects of foods and food components on metabolic changes of the human organism

16 Nutrigenomics Nti i und Gesundheit Evaluation of the metabolic profile on possible effects on human health, to ultimately improve human health by nutrition.

17 Nutrigenomics Nti i und Gesundheit Metabolic profiling of human samples by LC-MS n /TOF in response to nutrition intervention Identification of molecular and biochemical key pathways of individual health problems (metabolic syndrome, obesity, cardiovascular diseases, aging) and Identification of strategies for individual intervention

18 Nutrigenomics Nti i und Gesundheit MTHFR (methylene tetrahydrofolate reductase) gene is located on chromosome 1 (1p36.3). 3) It is a C677 T polymorphism, with a change of the triplet GCC to GCT (at position 677 of the bp sequence)

19 Nutrigenomics Nti i und Gesundheit MTHFR (methylene tetrahydrofolate reductase) gene is located on chromosome 1 (1p36.3). It is a C677 T polymorphism, with a change of the triplet GCC to GCT (at position 677 of the bp sequence) Specific versus residual MTHFR activity from individuals with MTHFR polymorphism Van der Put et al. Lancet 1995; 346 (8982):

20 Nutrigenomics Nti i und Gesundheit MTHFR (methylene tetrahydrofolate reductase) gene is located on chromosome 1 (1p36.3). It is a C677 T polymorphism, with a change of the triplet GCC to GCT (at position 677 of the bp sequence)

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22 Nti Nutrigenomics i und Ernährungsforschung h Leptin und Leptinrezeptor Proopiomelanocortin (POMC) und Melanocortinrezeptoren Agouti Protein, Agouti related Peptide (AgRP) β 2 und β 3 adrenerge Rezeptoren Hormonsensitive Lipase (HSL) Uncoupling Proteins (UCP1, UCP2?, UCP3?) TNF α Peroxisomenproliferatoraktivierter Rezeptor (PPARγ) Glycoprotein PC 1 Insulinrezeptorsubstrat IRS 1 Glykogensynthase Genome wide scans

23 Nti Nutrigenomics i und Ernährungsforschung h Bouchard L, Tremblay A, Bouchard C, Pérusse L. International Journal of Obesity advance online publication 13 February 2007 In the whole sample, the variance in age related adiposity changes explained by the candidate gene polymorphisms ranged from 3.1% (BMI, P<0.05) to 8.5% (fat mass (FM), P ). The genes retained in the prediction model for changes in FM were leptin (P 0.05), guanine nucleotide binding protein 3 (P 0.05), adrenergic receptor 3 (P 0.05), neuromedin (P 0.05) and peroxisome proliferator activated receptor 2 (P 0.10). The effects of the genes were significant in both age groups, but the genes contributing to adiposity changes were different and their effects were stronger in the younger than in the older age group.

24 Nti Nutrigenomics i und Ernährungsforschung h Sladek et al. A genome wide association study identifies novel risk loci for type 2 diabetes. Nature 2007; 445: A genome wide association study is an approach that involves rapidly scanning markers across the complete sets of DNA, or genomes, of many people to find genetic variations associated with a particular disease. Once new genetic associations are identified, researchers can use the information i to develop better strategies to detect, treat and prevent the disease. Such studies are particularly useful in finding genetic variations that contribute to common, complex diseases, such as asthma, cancer, diabetes, heart disease and mental illnesses.

25 Nti Nutrigenomics i und Ernährungsforschung h SLC30A8: zinc transporter in insulin producing β cells Pairwise linkage disequilibrium diagrams for novel T2DM associated loci. D9 was calculated from the stage 1 genotyping data as a fraction of observed linkage disequilibrium over the maximal possible. The bar graph indicates the negative logarithm of the stage 1 P value for each SNP. Transcriptional units are indicated by green lines, with exons highlighted in orange. Blue asterisks mark the SNPs chosen for confirmatory studies.

26 Nti Nutrigenomics i und Ernährungsforschung h Thus, although our findings can be the source of valuable physiological insights, their contribution to the familial clustering and individual risk prediction of T2DM is relatively small. Of note, for seven of the eight SNPs in Table 1, the risk allele is the ancestral allele, which may be consistent with ih the hypothesis h 41 that the ancestral alleles were adapted to the environment of a: SLC30A8 ancient human populations but today, b: IDE KIF11 HHEX in a different environment, c: EXT2 ALX4 they increase disease risk. Further d: LOC population genetics analyses of these loci will allow direct testing of Sladek et al. A genome wide association this hypothesis. study identifies novel risk loci for type 2 diabetes. Nature 2007; 445:

27 Nti Nutrigenomics i und Ernährungsforschung h Protein Methionine adenosyltransferase Tetrahydrofolate Methionine ATP S-Adenosylmethionine Methylgroup 5,10-Methylene tetrahydrofolate Methionine synthase Methylgroup S-Adenosylhomocysteine NADPH Methylene tetrahydrofolate reductase NADP 5Methyl 5-Methyltetrahydrofolate Homocysteine Adenosine > 100 reactions, e.g.: RNA methylation, proteins, phospholipids

28 Nti Nutrigenomics i und Ernährungsforschung h Protein Methionine adenosyltransferase Tetrahydrofolate Methionine ATP Purine Synthesis Methylgroup S-Adenosylmethionine 5,10-Methylene tetrahydrofolate 10-Formyl tetrahydrofolate Methionine synthase Methylgroup S-Adenosylhomocysteine NADPH Methylene tetrahydrofolate reductase NADP 5Methyl 5-Methyltetrahydrofolate Homocysteine Adenosine > 100 reactions, e.g.: RNA methylation, proteins, phospholipids

29 Nti Nutrigenomics i und Ernährungsforschung h DNA-Synthesis Dihydrofolate Protein dtmp Methionine adenosyltransferase Tetrahydrofolate Methionine ATP dump Glycine Serine Purine Synthesis Methylgroup S-Adenosylmethionine 5,10-Methylene tetrahydrofolate 10-Formyl tetrahydrofolate Methionine synthase Methylgroup S-Adenosylhomocysteine NADPH Methylene tetrahydrofolate reductase NADP 5Methyl 5-Methyltetrahydrofolate Homocysteine Adenosine > 100 reactions, e.g.: RNA methylation, proteins, phospholipids

30 Nti Nutrigenomics i und Ernährungsforschung h Blood sampling from individuals of different genetic background (CC/CT/TT) Solid phase extraction for purification LC MS/MS analysis of metabolites

31 Nti Nutrigenomics i und Ernährungsforschung h Generation of metabolite dtb databases Mass specs of different samples for metabolic profiling

32 Nti Nutrigenomics i und Ernährungsforschung h Data consolidation and statistical analysis by PCA to identify profiles

33 Nti Nutrigenomics i und Ernährungsforschung h

34 Nti Nutrigenomics i und Ernährungsforschung h bioinformatics

35 Nti Nutrigenomics i und Ernährungsforschung h It is a long and rocky path to combine all data from genomics, transcriptomics, proteomics, and metabolomics, into practical nutriton concepts. And the question still remains, whether all this effort will result in a healthier population.

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37 Eine neue Ära? Derzeit lassen sich nur in einzelnen Fällen (z.b. MTHFR SNP) konkrete Maßnahmen für individuelle Ernährungskonzepte formulieren. Für komplexe, multigenetische und multifaktorielle Krankheiten befindet sich die Nutrigenomics im Grundlagenstadium und es sind weitreichende und langwierige Studien erforderlich, um die Stufen der omics Kaskade auch nur ansatzweise zu verstehen.

38 Eine neue Ära? Erst multidisziplinäre Ansätze von Molekularbiologen, Nutrigenomikern, Molekularmedizinern, Epigenetikern und Bioinformatikern sowie eine Konsolidierung aller vorhandenen und in Zukunft generierter Information zur omics Kaskade werden unser Verständnis der genetischen, metabolischen und phänotypischen Zusammenhänge verbessern und konkrete Anwendungen ermöglichen.

39 Eine neue Ära? Erst multidisziplinäre Ansätze von Molekularbiologen, Nutrigenomikern, Molekularmedizinern, Epigenetikern und Bioinformatikern sowie eine Konsolidierung aller vorhandenen und in Zukunft generierter Information zur omics Kaskade werden unser Verständnis der genetischen, metabolischen und phänotypischen Zusammenhänge verbessern und konkrete Anwendungen ermöglichen.

40 Eine neue Ära? Viele Fragen sind und bleiben offen, wobei in einigen Bereichen eine wissenschaftsethische und philosophische Diskussion erforderlich sein wird.

41 Jürgen König Emerging Focus Nutrigenomics University of Vienna Althanstr. 14, 1090 Vienna

42 Jürgen König Emerging Focus Nutrigenomics University of Vienna Althanstr. 14, 1090 Vienna