Metabolomics identifies increases in the acylcarnitine profiles in the plasma of overweight subjects in response to mild weight loss: a randomized, controlled design study

Miso Kang, Hye Jin Yoo, Minjoo Kim, Minkyung Kim, Jong Ho Lee, Miso Kang, Hye Jin Yoo, Minjoo Kim, Minkyung Kim, Jong Ho Lee

Abstract

Background: Using metabolomics technique to analyze the response to a dietary intervention generates valuable information concerning the effects of the prescribed diet on metabolic regulation. To determine whether low calorie diet (LCD)-induced weight reduction causes changes in plasma metabolites and metabolic characteristics.

Methods: Overweight subjects consumed a LCD (n = 47) or a weight maintenance diet (control, n = 50) in a randomized, controlled design study with a 12-week clinical intervention period. Plasma samples were analyzed using an UPLC-LTQ-Orbitrap MS.

Results: The 12-week LCD intervention resulted in significant mild weight loss, with an 8.3% and 10.6% reduction observed in the visceral fat area (VFA) at the level of the lumbar vertebrae L1 and L4, respectively. The LCD group showed a significant increase in the mean change of serum free fatty acids compared to the control group. In the LCD group, we observed a significant increase in the acylcarnitine (AC) levels, including hexanoylcarnitine, L-octanoylcarnitine, 9-decenoylcarnitine, trans-2-dodecenoylcanitine, dodecanoylcarnitine, 3,5-tetradecadiencarnitine, cis-5-tetradecenoylcarnitine, 9,12-hexadecadienoylcarnitine, and 9-hexadecenoylcarnitne at the 12-week follow-up assessment. When the plasma metabolite changes from baseline were compared between the control and LCD groups, the LCD group showed significant increases in hexanoylcarnitine, L-octanoylcarnitine, trans-2-dodecenoylcanitine, and 3,5-tetradecadiencarnitine than the control group. Additionally, the changes in these ACs in the LCD group strongly negatively correlated with the changes in the VFA at L1 and/or L4.

Conclusion: Mild weight loss from 12-week calorie restriction increased the plasma levels of medium- and long-chain ACs. These changes were coupled with a decrease in VFA and an increase in free fatty acids.

Trial registration: NCT03135132 ; April 26, 2017.

Keywords: Acylcarnitine; Low calorie diet; Metabolomics; Mild weight loss; Visceral fat area.

Conflict of interest statement

Ethics approval and consent to participate

We gave all subjects a careful explanation of the purpose of the study and received written consent prior to their participation. The protocol used in the study was approved by the the Institutional Review Boards of Yonsei University and the Yonsei University Severance Hospital approved the study protocol, which complied with the Declaration of Helsinki.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Identification of plasma metabolites with significantly altered levels. a Score plots from the OPLS-DA models in the control group (n = 50); comparison between baseline (yellow) and follow-up (blue). b Score plots from the OPLS-DA models in the low calorie diet (LCD) group (n = 47); comparison between baseline (green) and follow-up (red). c Score plots from the OPLS-DA models at follow-up; comparison between follow-up in the control (n = 50, blue) and LCD (n = 47, red) groups
Fig. 2
Fig. 2
Correlation matrix among the changes (Δ) from baseline in clinical parameters and major metabolites in the control and low calorie diet (LCD) groups. Correlations were obtained by deriving a Pearson correlation coefficient. Red indicates a positive correlation, and blue indicates a negative correlation
Fig. 3
Fig. 3
Correlation scatter plots of changes (Δ) from baseline in the major acylcarnitines and visceral fat areas at L1 and L4 in the low calorie diet (LCD) group. a, b, c, d Correlations between Δ hexanoylcarnitine, Δ L-octanoylcarnitine, Δ trans-2-dodecenoylcarnitine, Δ 3,5-tetradecadiencarnitine and Δ visceral fat area at L1, respectively. e, f, g, h Correlations between Δ hexanoylcarnitine, Δ L-octanoylcarnitine, Δ trans-2-dodecenoylcarnitine, Δ 3,5-tetradecadiencarnitine and Δ visceral fat area at L4, respectively

References

    1. Chopra M, Galbraith S, Darnton-Hill I. A global response to a global problem: the epidemic of overnutrition. Bull World Health Organ. 2002;80:952–958.
    1. Ministry of Health and Welfare, Korea Centers for Disease Control and Prevention. Korea Health Statistics 2014 . Korea National Health and nutrition examination survey (KNHANES VI-2) Cheongju: Korea Centers for Disease Control and Prevention; 2015.
    1. Hu FB. Globalization of diabetes. Diabetes Care. 2011;34:1249–1257. doi: 10.2337/dc11-0442.
    1. Eckel RH, York DA, Rössner S, Hubbard V, Caterson I, St Jeor ST, et al. American Heart Association: prevention conference VII. Circulation. 2004;110:2968–2975. doi: 10.1161/01.CIR.0000140086.88453.9A.
    1. Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, Greenberg I, et al. Dietary intervention randomized controlled trial (DIRECT) group: weight loss with a low-carbohydrate, Mediterranean, or low-fat diet. N Engl J Med. 2008;359:229–241. doi: 10.1056/NEJMoa0708681.
    1. Sacks FM, Bray GA, Carey VJ, Smith SR, Ryan DH, Anton SD, et al. Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates. N Engl J Med. 2009;360:859–873. doi: 10.1056/NEJMoa0804748.
    1. Weckwerth W, Morgenthal K. Metabolomics: from pattern recognition to biological interpretation. Drug Discov Today. 2005;10:1551–1558. doi: 10.1016/S1359-6446(05)03609-3.
    1. Griffiths WJ, Koal T, Wang Y, Kohl M, Enot DP, Deigner HP. Targeted metabolomics for biomarker discovery. Angew Chem Int Ed Engl. 2010;49:5426–5445. doi: 10.1002/anie.200905579.
    1. Brennan L. Metabolomics in nutrition research: current status and perspectives. Biochem Soc Trans. 2013;41:670–673. doi: 10.1042/BST20120350.
    1. Gibney MJ, Walsh M, Brennan L, Roche HM, German B, Van Ommen B. Metabolomics in human nutrition: opportunities and challenges. Am J Clin Nutr. 2005;82:497–503. doi: 10.1093/ajcn/82.3.497.
    1. Rezzi S, Ramadan Z, Fay LB, Kochhar S. Nutritional metabonomics: applications and perspectives. J Proteome Res. 2007;6:513–525. doi: 10.1021/pr060522z.
    1. Smilowitz JT, Wiest MM, Watkins SM, Teegarden D, Zemel MB, German JB. Lipid metabolism predicts changes in body composition during energy restriction in overweight humans. J Nutr. 2009;139:222–229. doi: 10.3945/jn.108.095364.
    1. Kim M, Jung S, Lee SH, Lee JH. Association between arterial stiffness and serum L-octanoylcarnitine and lactosylceramide in overweight middle-aged subjects: 3-year follow-up study. PLoS One. 2015;10:e0119519. doi: 10.1371/journal.pone.0119519.
    1. Choi HJ, Song JM, Kim EK. Assessment of daily steps, activity coefficient, body composition, resting energy expenditure and daily energy expenditure in female university students. J Korean Diet Assoc. 2005;11:159–169.
    1. Kim M, Song G, Kang M, Yoo HJ, Jeong T-S, Lee S-H, et al. Replacing carbohydrate with protein and fat in prediabetes or type-2 diabetes: greater effect on metabolites in PBMC than plasma. Nutr Metab. 2016;13:3. doi: 10.1186/s12986-016-0063-4.
    1. Lee SH, Park S, Kim HS, Jung BH. Metabolomic approaches to the normal aging process. Metabolomics. 2014;10:1268–1292. doi: 10.1007/s11306-014-0663-9.
    1. Bylesjö M, Eriksson D, Sjödin A, Jansson S, Moritz T, Trygg J. Orthogonal projections to latent structures as a strategy for microarray data normalization. BMC Bioinformatics. 2007;8:207. doi: 10.1186/1471-2105-8-207.
    1. Reuter SE, Evans AM. Carnitine and acylcarnitines. Clin Pharmacokinet. 2012;51:553–572. doi: 10.1007/BF03261931.
    1. Rinaldo P, Matern D, Bennett MJ. Fatty acid oxidation disorders. Annu Rev Physiol. 2002;64:477–502. doi: 10.1146/annurev.physiol.64.082201.154705.
    1. Baek SH, Kim M, Kim M, Kang M, Yoo HJ, Lee NH. Metabolites distinguishing visceral fat obesity and atherogenic traits in individuals with overweight. Obesity. 2017;25:323–331. doi: 10.1002/oby.21724.
    1. Schooneman MG, Napolitano A, Houten SM, Ambler GK, Murgatroyd PR, Miller SR. Assessment of plasma acylcarnitines before and after weight loss in obese subjects. Arch Biochem Biophys. 2016;606:73–80. doi: 10.1016/j.abb.2016.07.013.
    1. Ibrahim MM. Subcutaneous and visceral adipose tissue: structural and functional differences. Obes Rev. 2010;11:11–18. doi: 10.1111/j.1467-789X.2009.00623.x.
    1. Graessler J, Schwudke D, Schwarz PE, Herzog R, Shevchenko A, Bornstein SR. Top-down lipidomics reveals ether lipid deficiency in blood plasma of hypertensive patients. PLoS One. 2009;4:e6261. doi: 10.1371/journal.pone.0006261.
    1. Murugesan G, Fox PL. Role of lysophosphatidylcholine in the inhibition of endothelial cell motility by oxidized low density lipoprotein. J Clin Invest. 1996;97:2736. doi: 10.1172/JCI118728.
    1. Van Wijk DF, Boekholdt SM, Arsenault BJ, Ahmadi-Abhari S, Wareham NJ, Stroes ES. C-reactive protein identifies low-risk metabolically healthy obese persons: the European prospective investigation of cancer–Norfolk prospective population study. J Am Heart Assoc. 2016;5:e002823. doi: 10.1161/JAHA.115.002823.
    1. De Lorenzo A, Soldati L, Sarlo F, Calvani M, Di Lorenzo N, Di Renzo L. New obesity classification criteria as a tool for bariatric surgery indication. World J Gastroenterol. 2016;22:681. doi: 10.3748/wjg.v22.i2.681.
    1. Katzmarzyk PT, Mire E, Bouchard C. Abdominal obesity and mortality: the Pennington Center longitudinal study. Nutr Diabetes. 2012;2:e42. doi: 10.1038/nutd.2012.15.
    1. Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol. 1992;135:1114–1126. doi: 10.1093/oxfordjournals.aje.a116211.
    1. Hu FB, Rimm E, Smith-Warner SA, Feskanich D, Stampfer MJ, Ascherio A. Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. Am J Clin Nutr. 1999;69:243–249. doi: 10.1093/ajcn/69.2.243.
    1. Dai W, Yin P, Zeng Z, Kong H, Tong H, Xu Z. Nontargeted modification-specific metabolomics study based on liquid chromatography–high-resolution mass spectrometry. Anal Chem. 2014;86:9146–9153. doi: 10.1021/ac502045j.

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