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An integrated transcriptomic and epigenomic analysis identifies CD44 gene as a potential biomarker for weight loss within an energy-restricted program

  • Mirian Samblas
  • Maria Luisa Mansego
  • Maria Angeles Zulet
  • Fermín I. Milagro
  • J. Alfredo Martinez
Original Contribution

Abstract

Purpose

The interindividual variable response to weight-loss treatments requires the search for new predictive biomarkers for improving the success of weight-loss programs. The aim of this study is to identify novel genes that distinguish individual responses to a weight-loss dietary treatment by using the integrative analysis of mRNA expression and DNA methylation arrays.

Methods

Subjects from Metabolic Syndrome Reduction in Navarra (RESMENA) project were classified as low (LR) or high (HR) responders depending on their weight loss. Transcriptomic (n = 24) and epigenomic (n = 47) patterns were determined by array-based genome-wide technologies in human white blood cells at the baseline of the treatment period. CD44 expression was validated by qRT-PCR and methylation degree of CpGs of the gene was validated by MassARRAY® EpiTYPER™ in a subsample of 47 subjects. CD44 protein levels were measured by ELISA in human plasma.

Results

Different expression and DNA methylation profiles were identified in LR in comparison to HR. The integrative analysis of both array data identified four genes: CD44, ITPR1, MTSS1 and FBXW5 that were differently methylated and expressed between groups. CD44 showed higher expression and lower DNA methylation levels in LR than in HR. Although differences in CD44 protein levels between LR and HR were not statistically significant, a positive association was observed between CD44 mRNA expression and protein levels.

Conclusions

In summary, the combination of a genome-wide methylation and expression array dataset can be a useful strategy to identify novel genes that might be considered as predictors of the dietary response. CD44 gene transcription and methylation may be a possible candidate biomarker for weight-loss prediction.

Keywords

mRNA Methylation Weight loss Obesity Metabolic syndrome 

Notes

Acknowledgements

We thank the participants of the RESMENA project and technical assistance of Enrique Buso (UCIM, University of Valencia) for the MassARRAY measurements. The technical assistance of Veronica Ciaurriz and Ana Lorente is gratefully acknowledged. We credit the financial support of Ministry of Economy, Industry and Competitiveness (Nutrigenio Project reference AGL2013-45554-R) and Spanish Biomedical Research Centre CIBER de Fisiopatología de la Obesidad y Nutrición (CIBERobn). Mirian Samblas holds a FPI Grant from the Ministry of Education, Culture and Sport (BES-2014-068409).

Compliance with ethical standards

Conflict of interest

The authors have nothing to declare.

Supplementary material

394_2018_1750_MOESM1_ESM.docx (42 kb)
Supplementary material 1 (DOCX 42 KB)
394_2018_1750_MOESM2_ESM.docx (485 kb)
Supplementary material 2 (DOCX 484 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Nutrition, Food Science and Physiology, Centre for Nutrition ResearchUniversity of NavarraPamplonaSpain
  2. 2.CIBERobn, CIBER Fisiopatología de la Obesidad y NutriciónInstituto de Salud Carlos IIIMadridSpain
  3. 3.Navarra Institute for Health Research (IdiSNA)PamplonaSpain

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