Measuring efficacy of dietary fatty acid intake using a proteomics approach. Baukje de Roos
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1 Measuring efficacy of dietary fatty acid intake using a proteomics approach Baukje de Roos
2 Dietary fat and mammary tumors rodent models Strong tumor-enhancing effect for n-6 fatty acids Weaker tumor-enhancing effect for saturated fatty acids Small protective effect for n-3 PUFAs (not statistically signficant)
3 Fatty acids and and breast cancer risk in humans Total and very long chain n-3 PUFA have a protective effect, while total SFA, total MUFA, palmitic and oleic acid are associated with an increased risk of breast cancer.
4 Linoleic acid intake and cancer risk in humans Although current evidence cannot exclude a small increase in risk, it seems unlikely that a high intake of linoleic acid substantially raises the risks of breast, colorectal, or prostate cancer in humans.
5 -Linolenic acid intake and prostate cancer Relative risk of prostate cancer with high versus low ALA intake or blood concentrations in prospective (8,20-22) and case-control studies (23-27) Brouwer, I. A. et al. J. Nutr. 2004;134:
6 -Linolenic acid intake and prostate cancer Simon, J. A et al. Am J Clin Nutr 2009;89:1558S-1564S
7 This review highlights the inconsistent way in which total dietary fat and specific fatty acids have been measured and reported across epidemiologic studies of prostate cancer. The heterogeneity between studies was large, possibly because of the variation in the dietary instruments used and the corresponding databases (non-differential misclassification), recall bias, differing case definitions, residual confounding, or potential selection bias in different studies.
8 Biomarkers of dietary fat intake diet synthesis pool liver transport pool plasma / lipoproteins storage pool adipoyctes buccal functional pool cells / phospholipids linoleic acid -linolenic acid omega-3 fatty acids C15:0 C17:0 Hodson L, et al. Prog Lipid Res. 2008;47:348-80
9 From intake to efficacy biomarker Harris WS.Curr Atheroscler Rep. 2009;11:411-7
10 Availability of fatty acids for cell functioning
11 Receptor-mediated uptake of fatty acids Oh DY et al, Cell 2010; 142: Saltiel AR, Cell 2010;142:672-4 Shi et al., J Clin Invest 2006;116:
12 Dihydroxyeicosatrienoic acids inactive seh n-6 fatty acids n-3 fatty acids 5-HETE 4-series Leukotrienes pro-inflammatory Lipoxin A 4 5-series Leukotrienes inactive anti-inflammatory 15-LOX and 5-LOX or 5 LOX and 12-LOX E-series Resolvins anti-inflammatory 3-series Prostaglandins COX-2 and 5-LOX vasodilators 3-series Thromboxanes inactive Epoxyeicosatrieonic acids 5-LOX anti-inflammatory CYP450 COX-1 or -2 COX-1 or 2 AA Diacylglycerol EPA DHA 5-LOX COX-1 or -2 COX-1 or -2 PL-C or DAGL PL-C or DAGL CYP450 COX-2 and 5-LOX FAAH 2-series Thromboxanes vasoconstrictors 2-series Prostaglandins vasodilators 5-LOX anti-inflammatory Anandamide NAPE-PL-D N-arachidonoyl-phosphatidylethanolamine PE NAT Phospholipid remodelling D-series Resolvins Neuroprotectin D1 anti-inflammatory 17(R),18(S)-Epoxyeicosaquatraenoic acid Epoxydocosapentaenoic acid anti-inflammatory De Roos et al. Br J Pharmacol 2009;158:413-28
13 Proteomics in nutrition research Proteome analysis can identify efficacy biomarkers that can: Provide new biomarkers for health and disease diagnosis Enable discovery of mechanisms of effects of food components de Roos B and McArdle H. Br J Nutr. 2008;99 Suppl 3:S66-71; de Roos B, Exp Rev Prot 2008 and 2009
14 Prognostic biomarkers of disease Gerszten RE. Circulation 2008; 451:
15 Will biomarkers take off at last? Difficult to find those proteins that are biomarkers - and which are affected by dietary intervention! Blood is challenging to work with - huge variety in protein abundance Danger of false positives - candidate biomarkers must be validated through clinical trials Mass spectrometry has not been sensitive enough to spot clinically relevant biomarkers in the ng/ml range Service RF. Science 2008; 321: 1760
16 Proteomics in nutrition research Proteome analysis can identify proteins that can: Provide new biomarkers for health and disease diagnosis Enable discovery of mechanisms of effects of food components Non-targeted Targeted
17 Plasma proteomics and controlled dietary trials PERIOD 1 (3 weeks) PERIOD 2 (3 weeks) PERIOD 3 (3 weeks) CLA Oleic acid Industrial trans n=2 CLA Industrial trans Oleic acid n=2 Industrial trans CLA Oleic acid n=2 Industrial trans Oleic acid CLA n=2 Oleic acid Industrial trans CLA n=2 Oleic acid CLA Industrial trans n=2 Blood sampling n=12 Three complete diets in which 7% of energy was exchanged Total fat intake: 40 energy%
18 Plasma proteomics and controlled dietary trials 275 proteins treatment effect period effect subject effect
19 Systemic markers of cellular processes We need biomarkers of inflammatory and/or oxidative stress to assess efficacy of a dietary fatty acids (and not necessarily dietary fats!) Larsson SC, et al. Am J Clin Nutr. 2004;79:935-45
20 Olive oils and anti-oxidant enzymes mm * * 0 Picual olive oil Arbequina olive oil Palm oil Arbones-Mainar JM et al, J Proteom Res 2007;10:
21 Anti-oxidant enzymes in human platelets Platelet Nrf2 protein levels (A.U.) meal 1 t=0 meal 1 t=3 meal 2 t=0 meal 2 t=3 Nguyen et al, J Biol Chem 2009; 246:
22 Fish oil and eicosanoid metabolism arachidonic acid (AA) CYP450 COOH EPA, not DHA - O 14,15 epoxyeicosatrienoic acid (EET) soluble epoxide hydrolase (seh) COOH HO OH 14,15 dihydroxyeicosatrienoic acid (DHET) Mavrommatis Y et al, Br J Nutr 2010;103:16-24
23 Omega-3 fatty acids and platelet function
24 EPA lowers seh in human platelets Platelet aggregation Platelet seh protein levels
25 Biomarker discovery CELLULAR EFFECTS SYSTEMIC EFFECTS ANIMAL MODELS HUMAN STUDIES Target organs Lower variability Blood cells Lower variability Plasma Higher variability de Roos B, Exp Rev Prot 2008 and 2009
26 Use of proteomics in dietary studies 25 reviews research papers Number of publications / year Year of publication de Roos B and McArdle H. Br J Nutr. 2008;99 Suppl 3:S66-71 de Roos. Exp Rev Proteom 2008;5:
27 Targeted approaches CHEMICAL PROTEOMICS MULTIANALYTE PROFILING MULTIPLE REACTION MONITORING
28 In silico approaches In silico network interaction analysis Activated pathways Regulatory hubs In silico computational modelling of compound-protein interactions Proteins with high affinity for food compound
29 Acknowledgements Sharon Wood Karen Ross Yiannis Mavrommatis Luisa Ostertag Eva-Maria Bachmair Emma Massie Katie Crosley Garry Rucklidge Martin Reid Gary Duncan Louisa Cantley Niamh O Kennedy Wendy Russel Susan Duthie Harry McArdle Lynda Williams Garry Duthie Hannelore Daniel Isabel Rubio-Aliaga Carolin Heim Ruan Elliott Abigael Polley Francis Mulholland Ian Johnson Edwin Mariman Freek Bouwman Graham Horgan Claus Mayer Jose Miguel Arbones-Mainar Jesus Osada Ingeborg Brouwer Anouk Geelen Anne Wanders Chris Evelo Thomas Kelder Funding by the Scottish Government Rural and Environment Research and Analysis Directorate (RERAD), NuGO, Spanish Government and Dutch Heart Foundation
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