European Food Research and Technology

, Volume 240, Issue 3, pp 583–594 | Cite as

Impact of a 6-week very low-calorie diet and weight reduction on the serum and fecal metabolome of overweight subjects

  • Mette S. Schmedes
  • Christian C. Yde
  • Ulla Svensson
  • Janet Håkansson
  • Sanmohan Baby
  • Hanne C. BertramEmail author
Original Paper


The aim of this study was to elucidate the effects of a very low-calorie diet and weight loss on the serum and fecal metabolome and the potential of the metabolome to predict inter-individual differences in body weight loss. NMR-based metabolomics was carried out on serum and fecal samples obtained from healthy female subjects (n = 56; Age: 46.33 ± 10.39 years; BMI 28.32 ± 1.55 kg/m2) pre- and post-weight reduction. An elevated level of 3-hydroxybutyric acid (3-HBA) and acetoacetate and decreased levels of lipoproteins, cholines and glucose were identified in serum after the weight reduction. In the fecal metabolome, a decreased level of short-chain fatty acids was observed after the weight reduction. The body weight for each individual at pre- and post-intervention was linked to the level of lipoproteins in serum (VLDL, p = 0.039; LDL, p = 0.023) and serum 3-HBA (p < 0.001), and a tendency for a similar relation was found for the fecal concentration of acetate (p = 0.06) and propionate (p = 0.075). The study demonstrates that the serum and fecal metabolome is affected by weight loss and that it includes information about inter-individual differences at the post-genomic level that may be of importance for the ability to undergo a weight loss.


Calorie restriction Metabolic phenotype Nuclear magnetic resonance Very low-calorie diet Weight loss 



Arla Foods Nordic Innovation is thanked for the collaborative work behind this study. Also, Good Food Practice® is thanked for handling sample collection and clinical measurements of subjects. The Danish Research Council is thanked for financial support through the project ‘Advances in food quality and nutrition research through implementation of metabolomics technologies’ (#274-09-107).

Conflict of interest

The authors declare that they have no conflict of interest.

Compliance with Ethics Requirements

All procedures followed were in accordance with the EU Clinical Directive 2001/20/EC and ICH Guideline for Good Clinical Practice. Informed consent was obtained from the subjects included in the study.

Supplementary material

217_2014_2359_MOESM1_ESM.docx (65 kb)
Supplementary material 1 (DOCX 65 kb)


  1. 1.
    WHO (2013) Obesity and overweight
  2. 2.
    Anderson JWK, Cyril WC, Jenkins DJA (2003) Importance of weight management in type 2 diabetes: review with meta-analysis of clinical studies. J Am Coll Nutr 22(5):331–339CrossRefGoogle Scholar
  3. 3.
    Wolin KY, Carson K, Colditz G (2010) Obesity and cancer. Oncologist 15:556–565CrossRefGoogle Scholar
  4. 4.
    Deslypere JP (1995) Obesity and cancer. Metabolism 44(9):24–27CrossRefGoogle Scholar
  5. 5.
    Ley RET, Peter J, Klein S, Gordon JI (2006) Human gut microbes associated with obesity. Nature 444(21/28):1022–1023CrossRefGoogle Scholar
  6. 6.
    Turnbaugh PJH, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon JI (2009) A core gut microbiome in obese and lean twins. Nature 457:480–485CrossRefGoogle Scholar
  7. 7.
    Dumas M-E, Maibaum EC, Teague C, Ueshima H, Zhou B, Lindon JC, Nicholson JK, Stamler J, Elliott P, Chan Q, Holmes E (2006) Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP study. Anal Chem 78:2199–2208CrossRefGoogle Scholar
  8. 8.
    Lenz EM, Wilson ID (2007) Analytical strategies in metabonomics. J Proteome Res 6:443–458CrossRefGoogle Scholar
  9. 9.
    Bertram CH, Malmendal A, Nielsen NC, Straadt IK, Larsen T, Bach Knudsen KE, Nygaard Lærke H (2009) NMR-based metabonomics reveals that plasma betaine increases upon intake of high-fiber rye buns in hypercholesterolemic pigs. Mol Nutr Food Res 53:1055–1062CrossRefGoogle Scholar
  10. 10.
    Bertram HC, Hoppe C, Petersen BO, Duus JØ, Mølgaard C, Michaelsen KF (2007) An NMR-based metabonomic investigation on effects of milk and meat protein diets given to 8-year-old boys. Br J Nutr 97:758–763CrossRefGoogle Scholar
  11. 11.
    Moazzami AA, Zhang J-X, Kamal-Eldin A, Åman P, Hallmans G, Johansson J-E, Andersson S-O (2011) Nuclear magnetic resonance-based metabolomics enable detection of the effects of a whole grain rye and rye bran diet on the metabolic profile of plasma in prostate cancer patients. J Nutr 141:2126–2136CrossRefGoogle Scholar
  12. 12.
    Maccaferri S, Klinder A, Cacciatore S, Chitarrari R, Honda H, Luchinat C, Bertini I, Carnevali P, Gibson GR, Brigidi P, Costabile A (2012) In vitro fermentation of potential prebiotic flours from natural sources: impact on the human colonic microbiota and metabolome. Mol Nutr Food Res 56:1342–1352CrossRefGoogle Scholar
  13. 13.
    De Preter V, Ghebretinsae AH, Abrahantes JC, Windey K, Rutgeerts P, Verbeke K (2011) Impact of the synbiotic combination of Lactobacillus casei shirota and oligofructose-enriched inulin on the fecal volatile metabolite profile in healthy subjects. Mol Nutr Food Res 55:714–722CrossRefGoogle Scholar
  14. 14.
    Claus SP, Ellero SL, Berger B, Krause L, Bruttin A, Molina J, Paris A, Want EJ, de Waziers I, Cloarec O, Richards SE, Wang Y, Dumas ME, Ross A, Rezzi S, Kochhar S, Van Bladeren P, Lindon JC, Holmes E, Nicholson JK (2011) Colonization-induced host-gut microbial metabolic interaction. mBio 2(2):e00271–00210. doi: 10.1128/mBio.00271-10
  15. 15.
    Martin F-PJ, Sprenger N, Montoliu I, Rezzi S, Kochhar S, Nicholson JK (2010) Dietary modulation of gut functional ecology studied by fecal metabonomics. J Proteome Res 9:5284–5295CrossRefGoogle Scholar
  16. 16.
    Martin F-PJ, Collino S, Rezzi S (2011) 1H NMR-based metabonomic applications to decipher gut microbial metabolic influence on mammalian health†. Magn Reson Chem 49:47–59CrossRefGoogle Scholar
  17. 17.
    German JB, Bauman DE, Burrin DG, Failla M, Failla ML, Freake HC, King JC, Klein S, Milner JA, Pelto GH, Rasmussen KM, Zeisel SH (2004) Metabolomics in the opening decade of the 21st century: building the roads to individualized health. J Nutr 134:2729–2732Google Scholar
  18. 18.
    O’Sullivan AG, Michael J, Connor AO, Mion B, Kaluskar S, Cashman KD, Flynn A, Shanahan F, Brennan L (2011) Biochemical and metabolomic phenotyping in the identification of a vitamin D responsive metabotype for markers of the metabolic syndrome. Mol Nutr Food Res 55:679–690CrossRefGoogle Scholar
  19. 19.
    Heinzmann SSM, Claire A, Rezzi S, Kochhar S, Lindon JC, Holmes E, Nicholson JK (2012) Stability and robustness of human metabolic phenotypes in response to sequential food challenges. J Proteome Res 11:643–655CrossRefGoogle Scholar
  20. 20.
    Saris WHM (2001) Very-low-calorie diets and sustained weight loss. Obes Res 9:295–301CrossRefGoogle Scholar
  21. 21.
    Meckling KA, Gauthier M, Grubb R, Sanford J (2002) Effects of a hypocaloric, low-carbohydrate diet on weight loss, blood lipids, blood pressure, glucose tolerance, and body composition in free-living overweight women. Can J Physiol Pharmacol 80:1095–1105CrossRefGoogle Scholar
  22. 22.
    Dattilo AM, Kris-Etherton PM (1992) Effects of weight reduction on blood lipids and lipoproteins: a metaanalysis. Am J Clin Nutr 56:320–328Google Scholar
  23. 23.
    Malandrucco I, Pasqualetti P, Giordani I, Manfellotto D, De Marco F, De Alegiani F, Sidoti AM, Picconi F, Di Flaviani A, Frajese G, Bonadonna RC, Frontoni S (2012) Very-low-calorie diet: a quick therapeutic tool to improve b cell function in morbidly obese patients with type 2 diabetes. Am J Clin Nutr 95:609–613CrossRefGoogle Scholar
  24. 24.
    Svendsen PF, Jensen FK, Holst JJ, Haugaard SB, Nilas L, Madsbad S (2012) The effect of a very low calorie diet on insulin sensitivity, beta cell function, insulin clearance, incretin hormone secretion, androgen levels and body composition in obese young women. Scand J Clin Lab Invest 72:410–419CrossRefGoogle Scholar
  25. 25.
    Yea Gu (2013) Beneficial effects of an 8-week, very low carbohydrate diet intervention on obese subjects. Evid Based Complement Alternat Med 2013:1–8CrossRefGoogle Scholar
  26. 26.
    Dengel DRK, Aaron S, Olsona TP, Kaiser DR, Dengele JL, Bank AJ (2006) Effects of weight loss on insulin sensitivity and arterial stiffness in overweight adults. Metab Clin Exp 55:907–911CrossRefGoogle Scholar
  27. 27.
    Mason C (2013) History of weight cycling does not impede future weight loss or metabolic improvements in postmenopausal women. Metab Clin Exp 62:127–136CrossRefGoogle Scholar
  28. 28.
    Meiboo S, Gill D (1958) Modified spin-echo method for measuring nuclear relaxation times. Rev Sci Instrum 29(8):688–691CrossRefGoogle Scholar
  29. 29.
    Jacobs DM, Deltimple N, van Velzen E, van Dorsten FA, Bingham M, Vaughan EE, van Duynhoven J (2008) 1H NMR metabolite profiling of feces as a tool to assess the impact of nutrition on the human microbiome. NMR Biomed 21:615–626CrossRefGoogle Scholar
  30. 30.
    Saric J (2008) Species variation in the fecal metabolome gives insight into differential gastrointestinal function. J Proteome Res 7:352–360CrossRefGoogle Scholar
  31. 31.
    Lindon JC, Nicholson JK, Everett JR (1999) NMR spectroscopy of biofluids. Annu Rep NMR Spectrosc 38:1–88CrossRefGoogle Scholar
  32. 32.
    Wishart DS (2007) HMDB: the human metabolome database. Nucleic Acids Res 35:521–526CrossRefGoogle Scholar
  33. 33.
    Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD (2009) Analytical and statistical approaches to metabolomics research. J Sep Sci 32:2183–2199CrossRefGoogle Scholar
  34. 34.
    Nakagawa SS, Schielzeth H (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4:133–142CrossRefGoogle Scholar
  35. 35.
    Ala-Korpela M, Korhonen A, Keisala J, Hörkkö S, Korpi P, Ingman LP, Jokisaari J, Savolainen MJ, Kesäniemi YA (1994) 1H NMR-based absolute quantification of humans lipoproteins and their lipid contents directly from plasma. J Lipid Res 35(12):2292–2304Google Scholar
  36. 36.
    Otvos JD, Jeyarajah EJ, Bennett DW (1991) Quantification of plasma lipoproteins by proton nuclear magnetic resonance spectroscopy. Clin Chem 37(3):377–386Google Scholar
  37. 37.
    Chearskul S, Delbridge E, Shulkes A, Proietto J, Kriketos A (2008) Effect of weight loss and ketosis on postprandial cholecystokinin and free fatty acid concentrations. Am J Clin Nutr 87:1238–1246Google Scholar
  38. 38.
    Brehm BJ, Spang SE, Lattin BL, Seeley RJ, Daniels SR, D’Alessio DA (2004) The role of energy expenditure in the differential weight loss in obese women on low-fat and low-carbohydrate diets. J Clin Endocrinol Metab 90(3):1475–1482CrossRefGoogle Scholar
  39. 39.
    Vicea E, Privette JD, Hicknerb RC, Barakat HA (2005) Ketone body metabolism in lean and obese women. Metab Clin Exp 54:1542–1545CrossRefGoogle Scholar
  40. 40.
    Volek JSS, Matthew J, Forsythe CE (2005) Modification of lipoproteins by very low-carbohydrate diets 1. J Nutr 135:1339–1342Google Scholar
  41. 41.
    Vaanholt LM, Magee V, Speakman JR (2011) Factors predicting individual variability in diet-induced weight loss in MF1 mice. Obesity 20:285–294CrossRefGoogle Scholar
  42. 42.
    Gibney MJ, Walsh M, Brennan L, Roche HM, German B, van Ommen B (2005) Metabolomics in human nutrition: opportunities and challenges. Am J Clin Nutr 82:497–503Google Scholar
  43. 43.
    Smilowitz JT, Wiest MM, Watkins SM, Teegarden D, Zemel MB, German JB, Van Loan MD (2008) Lipid metabolism predicts changes in body composition during energy restriction in overweight humans. J Nutr 139(2):222–229CrossRefGoogle Scholar
  44. 44.
    Astrup A, Buemann B, Gluud C, Bennett P, Tjur T, Christensen N (1995) Prognostic markers for diet-induced weight-loss in obese women. Int J Obes 19(4):275–278Google Scholar
  45. 45.
    Cook SI, Sellin JH (1998) Short chain fatty acids in health and disease. Aliment Pharmacol Ther 12:499–507CrossRefGoogle Scholar
  46. 46.
    Mortensen PB, Clausen MR (1996) Short-chain fatty acids in the human colon: relation to gastrointestinal health and disease. Scand J Gastroenterol 31(s216):132–148. doi: 10.3109/00365529609094568 CrossRefGoogle Scholar
  47. 47.
    Duncan SH, Belenguer A, Holtrop G, Johnstone AM, Flint HJ, Lobley GE (2007) reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces. Appl Environ Microbiol 73(4):1073–1078CrossRefGoogle Scholar
  48. 48.
    Macfarlane G, Gibson G (1997) Carbohydrate fermentation, energy transduction and gas metabolism in the human large intestine. In: Mackie R, White B (eds) Gastrointestinal microbiology. Chapman & Hall Microbiology Series. Springer, USA, pp 269–318. doi: 10.1007/978-1-4615-4111-0_9
  49. 49.
    De Preter V, Falony G, Windey K, Hamer HM, De Vuyst L, Verbeke K (2010) The prebiotic, oligofructose-enriched inulin modulates the faecal metabolite profile: an in vitro analysis. Mol Nutr Food Res 54:1791–1801CrossRefGoogle Scholar
  50. 50.
    Wong JMW (2010) The effect on the blood lipid profile of soy foods combined with a prebiotic: a randomized controlled trial. Metab Clin Exp 59:1331–1340CrossRefGoogle Scholar
  51. 51.
    Lin HV (2012) Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms. PLoS ONE 7(4):e35240CrossRefGoogle Scholar
  52. 52.
    Al-Lahham SH, Roelofsen H, Priebe M, Weening D, Dijkstra M, Hoek A, Rezaee F, Venema K, Vonk RJ (2010) Regulation of adipokine production in human adipose tissue by propionic acid. Eur J Clin Invest 40(5):401–407Google Scholar
  53. 53.
    Al-Lahham SAH, Peppelenbosch MP, Roelofsen H, Vonk RJ, Venema K (2010) Biological effects of propionic acid in humans; metabolism, potential applications and underlying mechanisms. Biochim Biophys Acta 1801:1175–1183CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mette S. Schmedes
    • 1
  • Christian C. Yde
    • 1
  • Ulla Svensson
    • 2
  • Janet Håkansson
    • 2
  • Sanmohan Baby
    • 3
  • Hanne C. Bertram
    • 1
    Email author
  1. 1.Department of Food ScienceAarhus UniversityAarslevDenmark
  2. 2.Arla FoodsArla Strategic Innovation CenterStockholmSweden
  3. 3.Department of AgroecologyAarhus UniversityTjeleDenmark

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