Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Short Communication
  • Published:

Epigenetic patterns in successful weight loss maintainers: a pilot study

Abstract

DNA methylation changes occur in animal models of calorie restriction, simulating human dieting, and in human subjects undergoing behavioral weight loss interventions. This suggests that obese (OB) individuals may possess unique epigenetic patterns that may vary with weight loss. Here, we examine whether methylation patterns in leukocytes differ in individuals who lost sufficient weight to go from OB to normal weight (NW; successful weight loss maintainers; SWLMs) vs currently OB or NW individuals. This study examined peripheral blood mononuclear cell (PBMC) methylation patterns in NW (n=16, current/lifetime BMI 18.5–24.9) and OB individuals (n=16, current body mass index (BMI)30), and SWLM (n=16, current BMI 18.5–24.9, lifetime maximum BMI 30, average weight loss 57.4 lbs) using an Illumina Infinium HumanMethylation450 BeadArray. No leukocyte population-adjusted epigenome-wide analyses were significant; however, potentially differentially methylated loci across the groups were observed in ryanodine receptor-1 (RYR1; P=1.54E−6), myelin protein zero-like 3 (MPZL3; P=4.70E−6) and alpha 3c tubulin (TUBA3C; P=4.78E−6). In 32 obesity-related candidate genes, differential methylation patterns were found in brain-derived neurotrophic factor (BDNF; gene-wide P=0.00018). In RYR1, TUBA3C and BDNF, SWLM differed from OB but not NW. In this preliminary investigation, leukocyte SWLM DNA methylation patterns more closely resembled NW than OB individuals in three gene regions. These results suggest that PBMC methylation is associated with weight status.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2

Similar content being viewed by others

References

  1. Bird A . Perceptions of epigenetics. Nature 2007; 447: 396–398.

    Article  CAS  Google Scholar 

  2. Barres R, Kirchner H, Rasmussen M, Yan J, Kantor FR, Krook A et al. Weight loss after gastric bypass surgery in human obesity remodels promoter methylation. Cell Rep 2013; 3: 1020.

    Article  CAS  Google Scholar 

  3. Wing RR, Phelan S . Long-term weight loss maintenance. Am J Clin Nutr 2005; 82: 222S–225S.

    Article  CAS  Google Scholar 

  4. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 2012; 13: 86.

    Article  Google Scholar 

  5. Phelan S, Hassenstab J, McCaffery JM, Sweet L, Raynor HA, Cohen RA et al. Cognitive interference from food cues in weight loss maintainers, normal weight, and obese individuals. Obesity (Silver Spring) 2011; 19: 69–73.

    Article  Google Scholar 

  6. Illumina. Illumina HumanMethylation450 BeadChip Kit. 2013 (updated 2013; cited on 7 March 2013); Available at http://www.illumina.com/products/methylation_450_beadchip_kits.ilmn.

  7. Johnson WE, Li C, Rabinovic A . Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 2007; 8: 118–127.

    Article  Google Scholar 

  8. Benjamini Y, Hochberg Y . Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B 1995; 57: 12.

    Google Scholar 

  9. Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 2010; 42: 937–948.

    Article  CAS  Google Scholar 

  10. Huang YT, Lin X . Gene set analysis using variance component tests. BMC Bioinformatics 2013; 14: 210.

    Article  Google Scholar 

  11. Paulino EC, Ferreira JC, Bechara LR, Tsutsui JM, Mathias W Jr, Lima FB et al. Exercise training and caloric restriction prevent reduction in cardiac Ca2+-handling protein profile in obese rats. Hypertension 2010; 56: 629–635.

    Article  CAS  Google Scholar 

  12. Mikelsaar R, Nelis M, Kurg A, Zilina O, Korrovits P, Ratsep R et al. Balanced reciprocal translocation t(5;13)(q33;q12) and 9q31.1 microduplication in a man suffering from infertility and pollinosis. J Appl Genet 2012; 53: 93–97.

    Article  Google Scholar 

  13. Gomez-Pinilla F, Zhuang Y, Feng J, Ying Z, Fan G . Exercise impacts brain-derived neurotrophic factor plasticity by engaging mechanisms of epigenetic regulation. Eur J Neurosci 2011; 33: 383–390.

    Article  CAS  Google Scholar 

  14. Czyzyk TA, Andrews JL, Coskun T, Wade MR, Hawkins ED, Lockwood JF et al. Genetic ablation of myelin protein zero-like 3 in mice increases energy expenditure, improves glycemic control, and reduces hepatic lipid synthesis. Am J Physiol Endocrinol Metab 2013; 305: E282–E292.

    Article  CAS  Google Scholar 

  15. Smith AG, Sheridan PA, Tseng RJ, Sheridan JF, Beck MA . Selective impairment in dendritic cell function and altered antigen-specific CD8+ T-cell responses in diet-induced obese mice infected with influenza virus. Immunology 2009; 126: 268–279.

    Article  CAS  Google Scholar 

  16. Morlino G, Barreiro O, Baixauli F, Robles-Valero J, González-Granado JM, Villa-Bellosta R et al. Miro-1 links mitochondria and microtubule Dynein motors to control lymphocyte migration and polarity. Mol Cell Biol 2014; 34: 1412–1426.

    Article  Google Scholar 

  17. Barouch R, Appel E, Kazimirsky G, Braun A, Renz H, Brodie C . Differential regulation of neurotrophin expression by mitogens and neurotransmitters in mouse lymphocytes. J Neuroimmunol 2000; 103: 112–121.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (grant DK066787 to JMM) and the National Heart, Lung, and Blood Institute (grant T32HL076134-04 to JZJM). JZJM is now at the Penn State College of Medicine Tobacco Center of Regulatory Science (TCORS) and is funded by grant P50-DA-036107-01 from the National Institutes of Health.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J M McCaffery.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on International Journal of Obesity website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, YT., Maccani, J., Hawley, N. et al. Epigenetic patterns in successful weight loss maintainers: a pilot study. Int J Obes 39, 865–868 (2015). https://doi.org/10.1038/ijo.2014.213

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ijo.2014.213

This article is cited by

Search

Quick links