Nutrigenomics in human intervention studies: Current status, lessons learned and future perspectives

Molecular Nutrition and Food Research

Volumn 55, Issue 3, 2011, Pages 341-358

  Wittwer, Jonas ^a   Rubio Aliaga, Isabel ^b   Hoeft, Birgit ^a   Bendik, Igor ^a   Weber, Peter ^a   Daniel, Hannelore ^b  

^a DSM NUTRITIONAL PRODUCTS LTD   (Switzerland)

^b TECHNICAL UNIVERSITY OF MUNICH   (Germany)

Author keywords

Intervention studies; Metabolomics; Nutrigenetics; Proteomics; Transcriptomics

Indexed keywords

CLINICAL TRIAL (TOPIC); DIET; FEEDING BEHAVIOR; FOOD HANDLING; GENE EXPRESSION PROFILING; HUMAN; INTERVENTION STUDY; METABOLOMICS; METHODOLOGY; NUTRIGENOMICS; PROTEOMICS; REVIEW;

CLINICAL TRIALS AS TOPIC; DIET; FOOD HABITS; FOOD TECHNOLOGY; GENE EXPRESSION PROFILING; HUMANS; INTERVENTION STUDIES; METABOLOMICS; NUTRIGENOMICS; PROTEOMICS;

EID: 79952129174     PISSN: 16134125     EISSN: 16134133     Source Type: Journal    
DOI: 10.1002/mnfr.201000512     Document Type: Review

References (102)

1. Steinmetz, L. M., Davis, R. W., Maximizing the potential of functional genomics. Nat. Rev. Genet. 2004, 5, 190-201.
2. van Ommen, B., Nutrigenomics: exploiting systems biology in the nutrition and health arenas. Nutrition 2004, 20, 4-8.
3. Kulesh, D. A., Clive, D. R., Zarlenga, D. S., Greene, J. J., Identification of interferon-modulated proliferation-related cDNA sequences. Proc. Natl. Acad. Sci. USA 1987, 84, 8453-8457.
4. Schena, M., Shalon, D., Davis, R. W., Brown, P. O., Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995, 270, 467-470.
5. Taylor, C. F., Field, D., Sansone, S. A., Aerts, J. et al., Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat. Biotechnol. 2008, 26, 889-896.
6. Brazma, A., Minimum Information About a Microarray Experiment (MIAME) - successes, failures, challenges. The ScientificWorld J. 2009, 29, 420-423.
7. Shi, L., Perkins, R. G., Fang, H., Tong, W., Reproducible and reliable microarray results through quality control: good laboratory proficiency and appropriate data analysis practices are essential. Curr. Opin. Biotechnol. 2008, 19, 10-18.
8. Kim, Y., Park, T., DNA microarrays to define and search for genes associated with obesity. Biotechnol. J. 2010, 5, 99-112.
9. Bouwens, M., Van De Rest, O., Dellschaft, N., Bromhaar, M. G. et al., Fish-oil supplementation induces antiinflammatory gene expression profiles in human blood mononuclear cells. Am. J. Clin. Nutr. 2009, 90, 415-424.
10. Bouwens, M., Grootte Bromhaar, M., Jansen, J., Muller, M., Afman, L. A., Postprandial dietary lipid-specific effects on human peripheral blood mononuclear cell gene expression profiles. Am. J. Clin. Nutr. 2010, 91, 208-217.
11. van Dijk, S. J., Feskens, E. J., Bos, M. B., Hoelen, D. W. et al., A saturated fatty acid-rich diet induces an obesity-linked proinflammatory gene expression profile in adipose tissue of subjects at risk of metabolic syndrome. Am. J. Clin. Nutr. 2009, 90, 1656-1664.
12. Kabir, M., Skurnik, G., Naour, N., Pechtner, V. et al., Treatment for 2 mo with n 3 polyunsaturated fatty acids reduces adiposity and some atherogenic factors but does not improve insulin sensitivity in women with type 2 diabetes: a randomized controlled study. Am. J. Clin. Nutr. 2007, 86, 1670-1679.
13. Gorjao, R., Verlengia, R., Lima, T. M., Soriano, F. G. et al., Effect of docosahexaenoic acid-rich fish oil supplementation on human leukocyte function. Clin. Nutr. 2006, 25, 923-938.
14. van Oostrom, O., de Kleijn, D. P. V., Fledderus, J. O., Pescatori, M. et al., Folic acid supplementation normalizes the endothelial progenitor cell transcriptome of patients with type 1 diabetes: a case-control pilot study. Cardiovasc. Diabetol. 2009, 8, 47.
15. Camargo, A., Ruano, J., Fernandez, J. M., Parnell, L. D. et al., Gene expression changes in mononuclear cells in patients with metabolic syndrome after acute intake of phenol-rich virgin olive oil. BMC Genomics 2010, 11, 253.
16. Konstantinidou, V., Khymenets, O., Fito, M., De La Torre, R. et al., Characterization of human gene expression changes after olive oil ingestion: an exploratory approach. Folia Biol. (Praha) 2009, 55, 85-91.
17. Khymenets, O., Fito, M., Covas, M. I., Farre, M. et al., Mononuclear cell transcriptome response after sustained virgin olive oil consumption in humans: an exploratory nutrigenomics study. Omics 2009, 13, 7-19.
18. Dahlman, I., Linder, K., Arvidsson Nordstrom, E., Andersson, I. et al., Changes in adipose tissue gene expression with energy-restricted diets in obese women. Am. J. Clin. Nutr. 2005, 81, 1275-1285.
19. Ong, K. R., Sims, A. H., Harvie, M., Chapman, M. et al., Biomarkers of dietary energy restriction in women at increased risk of breast cancer. Cancer Prev. Res. (Philadelphia PA) 2009, 2, 720-731.
20. Capel, F., Viguerie, N., Vega, N., Dejean, S. et al., Contribution of energy restriction and macronutrient composition to changes in adipose tissue gene expression during dietary weight-loss programs in obese women. J. Clin. Endocrinol. Metabol. 2008, 93, 4315-4322.
21. Ornish, D., Magbanua, M. J., Weidner, G., Weinberg, V. et al., Changes in prostate gene expression in men undergoing an intensive nutrition and lifestyle intervention. Proc. Natl. Acad. Sci. USA 2008, 105, 8369-8374.
22. Kolehmainen, M., Salopuro, T., Schwab, U. S., Kekalainen, J. et al., Weight reduction modulates expression of genes involved in extracellular matrix and cell death: the GENOBIN study. Int. J. Obes. (Lond) 2008, 32, 292-303.
23. Kallio, P., Kolehmainen, M., Laaksonen, D. E., Kekalainen, J. et al., Dietary carbohydrate modification induces alterations in gene expression in abdominal subcutaneous adipose tissue in persons with the metabolic syndrome: the FUNGENUT Study. Am. J. Clin. Nutr. 2007, 85, 1417-1427.
24. Lin, D. W., Neuhouser, M. L., Schenk, J. M., Coleman, I. M. et al., Low-fat, low-glycemic load diet and gene expression in human prostate epithelium: a feasibility study of using cDNA microarrays to assess the response to dietary intervention in target tissues. Cancer Epidemiol. Biomarkers Prev. 2007, 16, 2150-2154.
25. Mangravite, L. M., Dawson, K., Davis, R. R., Gregg, J. P., Krauss, R. M., Fatty acid desaturase regulation in adipose tissue by dietary composition is independent of weight loss and is correlated with the plasma triacylglycerol response. Am. J. Clin. Nutr. 2007, 86, 759-767.
26. Meugnier, E., Bossu, C., Oliel, M., Jeanne, S. et al., Changes in gene expression in skeletal muscle in response to fat overfeeding in lean men. Obesity (Silver Spring) 2007, 15, 2583-2594.
27. van Erk, M. J., Blom, W. A., van Ommen, B., Hendriks, H. F., High-protein and high-carbohydrate breakfasts differentially change the transcriptome of human blood cells. Am. J. Clin. Nutr. 2006, 84, 1233-1241.
28. Sparks, L. M., Xie, H., Koza, R. A., Mynatt, R. et al., High-fat/low-carbohydrate diets regulate glucose metabolism via a long-term transcriptional loop. Metabolism 2006, 55, 1457-1463.
29. Clement, K., Viguerie, N., Poitou, C., Carette, C. et al., Weight loss regulates inflammation-related genes in white adipose tissue of obese subjects. Faseb J. 2004, 18, 1657-1669.
30. Viguerie, N., Vidal, H., Arner, P., Holst, C. et al., Adipose tissue gene expression in obese subjects during low-fat and high-fat hypocaloric diets. Diabetologia 2005, 48, 123-131.
31. Mutch, D. M., Temanni, M. R., Henegar, C., Combes, F. et al., Adipose gene expression prior to weight loss can differentiate and weakly predict dietary responders. PLoS One 2007, 2, e1344.
32. Safdar, A., Yardley, N. J., Snow, R., Melov, S., Tarnopolsky, M. A., Global and targeted gene expression and protein content in skeletal muscle of young men following short-term creatine monohydrate supplementation. Physiol. Genomics 2008, 32, 219-228.
33. Tsavachidou, D., McDonnell, T. J., Wen, S., Wang, X. et al., Selenium and vitamin E: cell type- and intervention-specific tissue effects in prostate cancer. J. Natl. Cancer Inst. 2009, 101, 306-320.
34. Linnane, A. W., Kopsidas, G., Zhang, C., Yarovaya, N. et al., Cellular redox activity of coenzyme Q10: effect of CoQ10 supplementation on human skeletal muscle. Free Radic. Res. 2002, 36, 445-453.
35. Niculescu, M. D., Pop, E. A., Fischer, L. M., Zeisel, S. H., Dietary isoflavones differentially induce gene expression changes in lymphocytes from postmenopausal women who form equol as compared with those who do not. J. Nutr. Biochem. 2007, 18, 380-390.
36. Gasper, A. V., Traka, M., Bacon, J. R., Smith, J. A. et al., Consuming broccoli does not induce genes associated with xenobiotic metabolism and cell cycle control in human gastric mucosa. J. Nutr. 2007, 137, 1718-1724.
37. van Baarlen, P., Troost, F. J., van Hemert, S., van der Meer, C. et al., Differential NF-kappaB pathways induction by Lactobacillus plantarum in the duodenum of healthy humans correlating with immune tolerance. Proc. Natl. Acad. Sci. USA 2009, 106, 2371-2376.
38. Di Caro, S., Tao, H., Grillo, A., Elia, C. et al., Effects of Lactobacillus GG on genes expression pattern in small bowel mucosa. Dig. Liver Dis. 2005, 37, 320-329.
39. Elliott, R. M., Transcriptomics and micronutrient research. Br. J. Nutr. 2008, 99, S59-S65.
40. Eady, J. J., Wortley, G. M., Wormstone, Y. M., Hughes, J. C. et al., Variation in gene expression profiles of peripheral blood mononuclear cells from healthy volunteers. Physiol. Genomics 2005, 22, 402-411.
41. Mutch, D. M., Tordjman, J., Pelloux, V., Hanczar, B. et al., Needle and surgical biopsy techniques differentially affect adipose tissue gene expression profiles. Am. J. Clin. Nutr. 2009, 89, 51-57.
42. Lin, D. W., Coleman, I. M., Hawley, S., Huang, C. Y. et al., Influence of surgical manipulation on prostate gene expression: implications for molecular correlates of treatment effects and disease prognosis. J. Clin. Oncol. 2006, 24, 3763-3770.
43. Cravatt, B. F., Simon, G. M., Yates, J. R., 3rd, The biological impact of mass-spectrometry-based proteomics. Nature 2007, 450, 991-1000.
44. Walther, T. C., Mann, M., Mass spectrometry-based proteomics in cell biology. J. Cell Biol. 2010, 190, 491-500.
45. de Roos, B., McArdle, H. J., Proteomics as a tool for the modelling of biological processes and biomarker development in nutrition research. Br. J. Nutr. 2008, 99, S66-S71.
46. Weiss, M., Schrimpf, S., Hengartner, M. O., Lercher, M. J., von Mering, C., Shotgun proteomics data from multiple organisms reveals remarkable quantitative conservation of the eukaryotic core proteome. Proteomics 2010, 10, 1297-1306.
47. Panchaud, A., Affolter, M., Moreillon, P., Kussmann, M., Experimental and computational approaches to quantitative proteomics: status quo and outlook. J. Proteomics 2008, 71, 19-33.
48. Kussmann, M., Panchaud, A., Affolter, M., Proteomics in nutrition: status quo and outlook for biomarkers and bioactives. J. Proteome Res. 2010, 9, 4876-4887.
49. Fuchs, D., Piller, R., Linseisen, J., Daniel, H., Wenzel, U., The human peripheral blood mononuclear cell proteome responds to a dietary flaxseed-intervention and proteins identified suggest a protective effect in atherosclerosis. Proteomics 2007, 7, 3278-3288.
50. Duthie, S. J., Horgan, G., de Roos, B., Rucklidge, G. et al., Blood folate status and expression of proteins involved in immune function, inflammation, and coagulation: biochemical and proteomic changes in the plasma of humans in response to long-term synthetic folic acid supplementation. J. Proteome Res. 2010, 9, 1941-1950.
51. Aldred, S., Sozzi, T., Mudway, I., Grant, M. M. et al., Alpha tocopherol supplementation elevates plasma apolipoprotein A1 isoforms in normal healthy subjects. Proteomics 2006, 6, 1695-1703.
52. Hoelzl, C., Lorenz, O., Haudek, V., Gundacker, N. et al., Proteome alterations induced in human white blood cells by consumption of Brussels sprouts: results of a pilot intervention study. Proteomics Clin. Appl. 2008, 2, 108-117.
53. Fuchs, D., Vafeiadou, K., Hall, W. L., Daniel, H. et al., Proteomic biomarkers of peripheral blood mononuclear cells obtained from postmenopausal women undergoing an intervention with soy isoflavones. Am. J. Clin. Nutr. 2007, 86, 1369-1375.
54. De Roos, B., Geelen, A., Ross, K., Rucklidge, G. et al., Identification of potential serum biomarkers of inflammation and lipid modulation that are altered by fish oil supplementation in healthy volunteers. Proteomics 2008, 8, 1965-1974.
55. Griffiths, H. R., Willetts, R. S., Grant, M. M., Mistry, N. et al., In vivo vitamin C supplementation increases phosphoinositol transfer protein expression in peripheral blood mononuclear cells from healthy individuals. Br. J. Nutr. 2009, 101, 1432-1439.
56. Mitchell, B. L., Yasui, Y., Lampe, J. W., Gafken, P. R., Lampe, P. D., Evaluation of matrix-assisted laser desorption/ionization-time of flight mass spectrometry proteomic profiling: Identification of alpha 2-HS glycoprotein B-chain as a biomarker of diet. Proteomics 2005, 5, 2238-2246.
57. Kim, J., Sun, P., Lam, Y.-W., Troncoso, P. et al., Changes in serum proteomic patterns by presurgical α-tocopherol and L-selenomethionine supplementation in prostate cancer. Cancer Epidemiol. Biomarkers Prev. 2005, 14, 1697-1702.
58. Biron, D. G., Brun, C., Lefevre, T., Lebarbenchon, C. et al., The pitfalls of proteomics experiments without the correct use of bioinformatics tools. Proteomics 2006, 6, 5577-5596.
59. Nicholson, J. K., Lindon, J. C., Holmes, E., 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999, 29, 1181-1189.
60. Fiehn, O., Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics 2001, 2, 155-168.
61. Nicholson, J. K., Wilson, I. D., Opinion: understanding 'global' systems biology: metabonomics and the continuum of metabolism. Nat. Rev. Drug Discov. 2003, 2, 668-676.
62. Goodacre, R., Vaidyanathan, S., Dunn, W. B., Harrigan, G. G., Kell, D. B., Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol. 2004, 22, 245-252.
63. Nicholson, J. K., Lindon, J. C., Systems biology: metabonomics. Nature 2008, 455, 1054-1056.
64. Wishart, D. S., Tzur, D., Knox, C., Eisner, R. et al., HMDB: the human metabolome database. Nucleic Acids Res. 2007, 35, D521-D526.
65. Pearson, H., Meet the human metabolome. Nature 2007, 8, 446.
66. Rezzi, S., Ramadan, Z., Fay, L. B., Kochhar, S., Nutritional metabonomics: applications and perspectives. J. Proteome Res. 2007, 6, 513-525.
67. Rochfort, S., Metabolomics reviewed: a new "omics" platform technology for systems biology and implications for natural products research. J. Nat. Prod. 2005, 68, 1813-1820.
68. Beckonert, O., Keun, H. C., Ebbels, T. M., Bundy, J. et al., Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat. Protoc. 2007, 2, 2692-2703.
69. Scalbert, A., Brennan, L., Fiehn, O., Hankemeier, T. et al., Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics 2009, 5, 435-458.
70. Watson, A. D., Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Lipidomics: a global approach to lipid analysis in biological systems. J. Lipid Res. 2006, 47, 2101-2111.
71. Zeisel, S. H., Freake, H. C., Bauman, D. E., Bier, D. M. et al., The nutritional phenotype in the age of metabolomics. J. Nutr. 2005, 135, 1613-1616.
72. Goodacre, R., Broadhurst, D., Smilde, A., Kristal, B. et al., Metabolomics, Springer, Boston 2007, pp. 231-241.
73. Westerhuis, J., Hoefsloot, H., Smit, S., Vis, D. et al., Metabolomics, Springer, Boston 2008, pp. 81-89.
74. Solanky, K. S., Bailey, N. J., Beckwith-Hall, B. M., Bingham, S. et al., Biofluid 1H NMR-based metabonomic techniques in nutrition research - metabolic effects of dietary isoflavones in humans. J. Nutr. Biochem. 2005, 16, 236-244.
75. Stella, C., Beckwith-Hall, B., Cloarec, O., Holmes, E. et al., Susceptibility of human metabolic phenotypes to dietary modulation. J. Proteome Res. 2006, 5, 2780-2788.
76. Walsh, M. C., Brennan, L., Pujos-Guillot, E., Sebedio, J. L. et al., Influence of acute phytochemical intake on human urinary metabolomic profiles. Am. J. Clin. Nutr. 2007, 86, 1687-1693.
77. 1H-NMR and LC-MS lipid metabolomic data combined with phenotypic data. Chemomet. Intell. Lab. Syst. 2008, 93, 34-42.
78. Schwab, U., Seppanen-Laakso, T., Yetukuri, L., Agren, J. et al., Triacylglycerol fatty acid composition in diet-induced weight loss in subjects with abnormal glucose metabolism - the GENOBIN study. PLoS One 2008, 3, e2630.
79. Chorell, E., Moritz, T., Branth, S., Antti, H., Svensson, M. B., Predictive metabolomics evaluation of nutrition-modulated metabolic stress responses in human blood serum during the early recovery phase of strenuous physical exercise. J. Proteome Res. 2009, 8, 2966-2977.
80. Lankinen, M., Schwab, U., Erkkila, A., Seppanen-Laakso, T. et al., Fatty fish intake decreases lipids related to inflammation and insulin signaling - a lipidomics approach. PLoS One 2009, 4, e5258.
81. Daykin, C. A., Van Duynhoven, J. P., Groenewegen, A., Dachtler, M. et al., Nuclear magnetic resonance spectroscopic based studies of the metabolism of black tea polyphenols in humans. J. Agric. Food Chem. 2005, 53, 1428-1434.
82. Van Dorsten, F. A., Daykin, C. A., Mulder, T. P. J., Van Duynhoven, J. P. M., Metabonomics approach to determine metabolic differences between green tea and black tea consumption. J. Agric. Food Chem. 2006, 54, 6929-6938.
83. Miccheli, A., Marini, F., Capuani, G., Miccheli, A. T. et al., The influence of a sports drink on the postexercise metabolism of elite athletes as investigated by NMR-based metabolomics. J. Am. Coll. Nutr. 2009, 28, 553-564.
84. van Velzen, E. J., Westerhuis, J. A., van Duynhoven, J. P., van Dorsten, F. A. et al., Phenotyping tea consumers by nutrikinetic analysis of polyphenolic end-metabolites. J. Proteome Res. 2009, 8, 3317-3330.
85. Rezzi, S., Ramadan, Z., Martin, F. P., Fay, L. B. et al., Human metabolic phenotypes link directly to specific dietary preferences in healthy individuals. J. Proteome Res. 2007, 6, 4469-4477.
86. Llorach, R., Urpi-Sarda, M., Jauregui, O., Monagas, M., Andres-Lacueva, C., An LC-MS-based metabolomics approach for exploring urinary metabolome modifications after cocoa consumption. J. Proteome Res. 2009, 8, 5060-5068.
87. Martin, F. P., Rezzi, S., Pere-Trepat, E., Kamlage, B. et al., Metabolic effects of dark chocolate consumption on energy, gut microbiota, and stress-related metabolism in free-living subjects. J. Proteome Res. 2009, 8, 5568-5579.
88. Coolen, S. A., Daykin, C. A., van Duynhoven, J. P., van Dorsten, F. A. et al., Measurement of ischaemia-reperfusion in patients with intermittent claudication using NMR-based metabonomics. NMR Biomed. 2008, 21, 686-695.
89. McCombie, G., Browning, L. M., Titman, C. M., Song, M. et al., Omega-3 oil intake during weight loss in obese women results in remodelling of plasma triglyceride and fatty acids. Metabolomics 2009, 5, 363-374.
90. Bakker, G. C., van Erk, M. J., Pellis, L., Wopereis, S. et al., An antiinflammatory dietary mix modulates inflammation and oxidative and metabolic stress in overweight men: a nutrigenomics approach. Am. J. Clin. Nutr. 2010, 91, 1044-1059.
91. Lee, R., West, D., Phillips, S. M., Britz-McKibbin, P., Differential metabolomics for quantitative assessment of oxidative stress with strenuous exercise and nutritional intervention: thiol-specific regulation of cellular metabolism with N-acetyl-L-cysteine pretreatment. Anal. Chem. 2010, 82, 2959-2968.
92. Ordovas, J. M., Mooser, V., Nutrigenomics and nutrigenetics. Curr. Opin. Lipidol. 2004, 15, 101-108.
93. Brookes, A. J., The essence of SNPs. Gene 1999, 234, 177-186.
94. Abbey, M., Hirata, F., Chen, G. Z., Ross, R. et al., Restriction fragment length polymorphism of the apolipoprotein B gene and response to dietary fat and cholesterol. Can. J. Cardiol. 1995, 11, 79G-85G.
95. Drabek, J., A commented dictionary of techniques for genotyping. Electrophoresis 2001, 22, 1024-1045.
96. Kim, S., Misra, A., SNP genotyping: technologies and biomedical applications. Annu. Rev. Biomed. Eng. 2007, 9, 289-320.
97. Frosst, P., Blom, H. J., Milos, R., Goyette, P. et al., A candidate genetic risk factor for vascular disease: a common mutation in methylenetetrahydrofolate reductase. Nat. Genet. 1995, 10, 111-113.
98. Molloy, A. M., Daly, S., Mills, J. L., Kirke, P. N. et al., Thermolabile variant of 5, 10-methylenetetrahydrofolate reductase associated with low red-cell folates: implications for folate intake recommendations. Lancet 1997, 349, 1591-1593.
99. Miyaki, K., Genetic polymorphisms in homocysteine metabolism and response to folate intake: a comprehensive strategy to elucidate useful genetic information. J. Epidemiol. 20, 266-270.
100. Miyaki, K., Murata, M., Kikuchi, H., Takei, I. et al., Assessment of tailor-made prevention of atherosclerosis with folic acid supplementation: randomized, double-blind, placebo-controlled trials in each MTHFR C677T genotype. J. Hum. Genet. 2005, 50, 241-248.
101. Blum, S., Vardi, M., Brown, J. B., Russell, A. et al., Vitamin E reduces cardiovascular disease in individuals with diabetes mellitus and the haptoglobin 2-2 genotype. Pharmacogenomics 2010, 11, 675-684.
102. Kircher, M., Kelso, J., High-throughput DNA sequencing-concepts and limitations. Bioessays 2010, 32, 524-536.